Weights and thresholds of ANN used to model the inverter in Fig. 5.
\r\n\t
",isbn:"978-1-80355-622-2",printIsbn:"978-1-80355-621-5",pdfIsbn:"978-1-80355-623-9",doi:null,price:0,priceEur:0,priceUsd:0,slug:null,numberOfPages:0,isOpenForSubmission:!1,isSalesforceBook:!1,hash:"db8b89225c5cf9bfef68e2e4e42a4d4a",bookSignature:"Dr. Fumiaki Uchiumi",publishedDate:null,coverURL:"https://cdn.intechopen.com/books/images_new/11349.jpg",keywords:"Transcription Factors, R-Loop, RNA Splicing, Epigenetic Regulation, circRNA, miRNA, lncRNA, ncRNA, Extrachromosomal Circular DNAs, Transposable Elements, Aging Related Diseases, Cancer",numberOfDownloads:225,numberOfWosCitations:0,numberOfCrossrefCitations:0,numberOfDimensionsCitations:0,numberOfTotalCitations:0,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"September 29th 2021",dateEndSecondStepPublish:"October 27th 2021",dateEndThirdStepPublish:"December 26th 2021",dateEndFourthStepPublish:"March 16th 2022",dateEndFifthStepPublish:"May 15th 2022",remainingDaysToSecondStep:"7 months",secondStepPassed:!0,currentStepOfPublishingProcess:5,editedByType:null,kuFlag:!1,biosketch:"Researcher and educator in molecular biology and biological chemistry, chairman of the genetic engineering safety committee of Tokyo University of Science.",coeditorOneBiosketch:null,coeditorTwoBiosketch:null,coeditorThreeBiosketch:null,coeditorFourBiosketch:null,coeditorFiveBiosketch:null,editors:[{id:"47235",title:"Dr.",name:"Fumiaki",middleName:null,surname:"Uchiumi",slug:"fumiaki-uchiumi",fullName:"Fumiaki Uchiumi",profilePictureURL:"https://mts.intechopen.com/storage/users/47235/images/system/47235.jpg",biography:"Fumiaki Uchiumi, Professor of Pharmaceutical Sciences, Tokyo University of Science, received his Bachelor\\'s degree (Chemistry) from Tokyo University of Science in 1987. In 1993, after obtaining his Ph.D. degree (Molecular Biology) from Tokyo University, he joined Professor S. Tanuma\\'s Laboratory at Tokyo University of Science as an Assistant Professor. He obtained his second Ph.D. (Pharmaceutical Science) from Tokyo University of Science in 1999 and in 2000 was promoted to the position of Lecturer at Tokyo University of Science. Professor Uchiumi then went abroad as a post-doctoral researcher for the United States-Japan Cooperative Cancer Research Program in Professor E. Fanning’s Laboratory at Vanderbilt University, 2000-2001. Professor Uchiumi was promoted to Associate Professor and then Full Professor at Tokyo University of Science in 2010 and 2016, respectively.",institutionString:"Tokyo University of Science",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"6",totalChapterViews:"0",totalEditedBooks:"3",institution:{name:"Tokyo University of Science",institutionURL:null,country:{name:"Japan"}}}],coeditorOne:null,coeditorTwo:null,coeditorThree:null,coeditorFour:null,coeditorFive:null,topics:[{id:"6",title:"Biochemistry, Genetics and Molecular Biology",slug:"biochemistry-genetics-and-molecular-biology"}],chapters:[{id:"80760",title:"Transcription Elongation Factors in Health and Disease",slug:"transcription-elongation-factors-in-health-and-disease",totalDownloads:56,totalCrossrefCites:0,authors:[null]},{id:"80609",title:"Circular DNA: How Circular DNA Assists Cancer Roll with Therapeutic 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The design of such systems requires simulation tools that are both fast and accurate at the same time.
\n\t\t\tThe main obstacle to this requirement is related to the difficulties in high-level modelling of the analog part, and sufficiently accurate modelling of the digital-analog (D/A) and analog-digital (A/D) interfaces which are frequently encountered in such systems (Trihy & Kundert, 1995; Kundert, 1999). We will consider here analog mixed-level behavioural modelling as a special case of the behavioural modelling of mixed-signal systems.
\n\t\t\tAccording to McAndrew: “It is difficult to develop complete, accurate, numerically robust models that work properly with numerical algorithms in simulators and with the CAD tools in an IC design system” (McAndrew et al., 1998). Modelling dynamic non-linear networks is practically the most difficult. One needs to solve not only the problem of the approximations to be used (modelling) and the method of evaluation of the coefficients within them (characterisation) but also to determine appropriate test signals able to activate the complete non-linear and dynamic properties of the circuit to be modelled.
\n\t\t\tConsidering Fig. 1., we may have two distinct situations. First, for the A/D interface, we need the voltage and the current at the interface so that the input impedance of the digital part can be modelled. Modelling of the input impedance of a CMOS circuit is, to our knowledge, usually considered simple: a capacitor is used as a model. However, this capacitance is highly non-linear so that there is need for more realistic modelling as we propose in the next. Second, at the D/A interface, we need an electrical circuit to model the digital output driving the analog load. That model should perform D/A signal conversion and maintain electrical compatibility. Among the solutions available in the literature are an approach where time-varying resistors have been used (Petković & Litovski, 1989; Petković & Litovski, 1991), and a macromodelling procedure which has difficulties in characterising the reactive part of the non-linear output impedance of the model (Nichols et al., 1992; Brown et al., 1994). Recently, while attempting to enable high-level behavioural simulation of complex combinational CMOS circuits, successful techniques have been developed for equivalent inverter or equivalent transistor synthesis represented as a non-linear voltage controlled current source (Chatzigeorgiou et al., 1999). Here an alternative, algorithmically simpler procedure, but robust and with broader scope of application, is proposed based on use of artificial neural networks (ANNs).
\n\t\t\tAfter the first application of ANNs for modelling electronic components, it became clear that this concept could be successfully used for modelling dynamics too (Litovski et al., 1992). The dynamics in a micro-electro-magneto-mechanical actuator were modelled first, taking advantage of the fact that the dynamic and the resistive properties may be expressed separately (Litovski et al., 1997a).
\n\t\t\tSchematic depiction of the interface to be modelled between analog and digital parts of the circuit.
Full non-linear dynamic modelling using ANNs was described later – the approximation being performed in the frequency domain using direct and inverse Fourier transforms repeatedly (Citterio et al., 1999). Here we propose, for the first time, ANNs to be used for behavioural modelling of the digital output with modelling performed in the time domain.
\n\t\t\tThe proceedings in the next will go in two directions. First we will describe the solution to the problem of A/D interface modelling. Since we assume that the digital (loading) part of the interface has no own feedback to its input, we will use its input impedance as the load to the analog part. In that way the problem of modelling of the A/D interface will be reduced to the problem of modelling the input impedance of the digital part. Second, the solution to the problem of the D/A interface will be proposed. In this case a complete new analog circuit will be proposed that will model the output behaviour of the digital driver at the interface. It will be shown by inspection that despite the fact that the model was developed for unloaded digital part, it behaves perfectly for every load used as a control.
\n\t\tThe simplest circuit representing input impedance of a MOS logic circuit is shown in Fig. 2. Here and on, for simplicity, the very conversion (analog to digital value) of the signal is not shown. The circuit is linear, with constant element values, what is not good enough approximation of the real MOS input impedance.
\n\t\t\tInput resistance and capacitance of bipolar circuits is nonlinear, so the simplest input TTL circuit is diode. Fig. 3. shows one solution with diodes (Corman & Wimborow, 1988).
\n\t\t\tThe problem of an analog circuit output can be generally solved by connecting nonlinear resistance and nonlinear capacitance in parallel controlled by the voltage of the analog part of A/D interface, Fig. 4., (Petković & Stojanović, 1992). A special procedure is proposed in order to get the characteristics of the nonlinear elements depicted.
\n\t\t\tRC input circuit.
Input circuit-one possible solution.
A/D interface model.
In the following (Litovski & Andrejević, 2002) we will show that MOS circuit input impedance is highly nonlinear, so more precise method of modelling is required. In order to get more information concerning our problem, as an example of two-terminal non-linear dynamic circuit, the input of an inverter is considered, as shown in Fig. 5. It is capacitive but highly non-linear, the non-linearity coming mostly from the Miller effect. As shown in Fig. 6., the inverter\'s gain is strongly non-linear, so that the Miller capacitances have to be too.
\n\t\t\tInverter has only one input, so we are modelling only one input impedance. When there are more inputs, we have to model as many impedances as there are circuit inputs.
\n\t\t\tWe attacked the problem of implementation of ANNs to analog modelling by first solving the simulation of an electro-magneto-mechanical actuator, as mentioned above. Thereafter, the problem of modelling linear dynamic networks was solved (Ilić et al., 2000). Two main ideas were implemented. First, to enable application of ANNs for implementation of the model the so-called recurrent time-delay structure was used. It is already proven (Chow & Li, 2000) “that any finite time trajectory of a given
CMOS inverter with non-linear capacitances.
The dependence of the inverter\'s gain on the input signal.
The structure of such a network is depicted in Fig. 7. The need for both time-delay and recurrence comes from the theory of dynamic system modelling (Bernieri et al., 1994). In our experience, however, time delay of the input signal facilitates modelling of the nonlinear properties while recurrence better accounts for the memory property of the system to be modelled. The core of the structure is a feed-forward ANN that, apart of the input layer, has one hidden layer having neurons with sigmoidal activation function, and output layer with a single linear output neuron. In the special case of modelling a two-terminal device, \n\t\t\t\t
Second, to capture the dynamic behaviour of the circuit to be modelled, a chirp signal (i.e., a frequency-modulated sinusoidal signal) was used as excitation. It has evenly-distributed spectral components across the “passband” of the circuit. If the change in frequency is sufficiently slow, one gets the proper time-domain response of the dynamic system that is being modelled. This response is then used for training the ANN described above. The generalisation property of the ANN was verified by testing the models obtained as above with new signals, such as square pulses (Ilić et al., 2000). In order to model non-linear circuits with the concept described above, one needs amplitude large enough of the chirp signal to encompass all non-linearities encountered during excitation.
\n\t\t\tThe topology of the proposed ANN.
Response (voltage) at the inverter\'s input obtained for sinusoidal excitation. Here “simulated” denotes the circuit simulation of the inverter of
The response observed was the input voltage of the inverter. The modelling results are shown in Fig. 8. where the difference between the simulated circuit and the model response is difficult to discern.
\n\t\t\tFor the example used here, five inputs (three direct input connections and two feed-backs from the output as shown in Fig. 7.), four hidden units, and one output neuron are incorporated in the ANN. Note that the input units are simply distributing signals to the hidden layer. The hidden units have sigmoidal activation functions, while the output neuron is linear. Table 1. shows the weights and the thresholds of the neurons. A modified steepest-descent learning algorithm was used to train the ANN (Zografski, 1991). Other details of the training procedure are practically the same as described elsewhere (Bernieri et al., 1994).
\n\t\t\tNo. | \n\t\t\t\t\t\tHidden-layer neurons (First figure stands for the input neuron) | \n\t\t\t\t\t\tOutput neuron (First figure stands for the hidden neuron) | \n\t\t\t\t\t
1 | \n\t\t\t\t\t\tw 1 (1,1) = –1.15618 w 1 (2,1) = 0.303841 w 1 (3,1) = 0.801999 w 1 (4,1) = –0.655468 w 1 (5,1) = –0.112933 θ 1\n\t\t\t\t\t\t\t1 = 1.69522 | \n\t\t\t\t\t\tw 2 (1,1) = –1.24339 w 2 (2,1) = 1.41557 w 2 (3,1) = –1.98177 w 2 (4,1) = –2.18655 θ 1\n\t\t\t\t\t\t\t2 = 2.91066 | \n\t\t\t\t\t
2 | \n\t\t\t\t\t\tw 1 (1,2) = 0.138613 w 1 (2,2) = –1.16098 w 1 (3,2) = 1.01521 w 1 (4,2) = –0.128065 w 1 (5,2) = 0.915597 θ 2\n\t\t\t\t\t\t\t1 = – 0.890606 | \n\t\t\t\t\t\t\n\t\t\t\t\t |
3 | \n\t\t\t\t\t\tw 1 (1,3) = –0.537022 w 1 (2,3) = 1.64986 w 1 (3,3) = –1.1164 w 1 (4,3) = –2.64625 w 1 (5,3) = 1.49825 θ 3\n\t\t\t\t\t\t\t1 = –1.15733 | \n\t\t\t\t\t\t\n\t\t\t\t\t |
4 | \n\t\t\t\t\t\tw 1 (1,4) = –1.13048 w 1 (2,4) = 1.87005 w 1 (3,4) = –0.716303 w 1 (4,4) = –3.13684 w 1 (5,4) = 2.4126 θ 4\n\t\t\t\t\t\t\t1 = 1.53233 | \n\t\t\t\t\t\t\n\t\t\t\t\t |
Weights and thresholds of ANN used to model the inverter in Fig. 5.
To show the quality of the approximation procedure and the generalisation capabilities of the ANN, a new example circuit is now considered. It consists of two inverters. The first (the driver) is considered to be analog as in Fig. 5. The second (the load) is considered to be digital. The whole is depicted in Fig. 9a. The voltage at the A/D interface (
To get reference data for modelling, the logic part was substituted by its circuit equivalent as shown in Fig. 9b. SPICE-like simulation was performed and the results are depicted in Fig. 11 denoted as “simulated”. Here the
Implementation of the model for mixed-signal simulation is depicted in Fig. 9c. Here the loading effects are modelled by the ANN. The simulation results are given in Fig. 11. denoted by “ANN”. Note that for multi-input circuits separate models (tables similar to Table 1.) have to be created for every distinct input terminal. One needs a behavioural simulator to exercise such a model (Litovski et al., 2001). This concludes the discussion related to modelling of the A/D interface.
\n\t\t\tCircuits used for verification. a) Analog inverter loaded by logic inverter, b) analog inverter loaded by analog inverter that generates reference signal
Signal exciting the circuits in
Response (
For modelling of the D/A interface, the output circuit of the digital part is to be represented by a circuit that is supposed to drive an analog load. Note that mixed-mode simulation is considered. This means that an event scheduler is active, marking the controlling input of the digital circuit (Litovski & Zwolinski, 1997b). The event scheduler does not allow for two inputs to be active simultaneously because that is considered as a hazard. Hence, modelling the output of an inverter is general enough for verification of the modelling procedure.
\n\t\t\ta) Simple D/A conversion circuit, b) Current generator waveform
Modelling of the D/A interface is more complex problem than modelling of the A/D interface, because we need to generate voltage waveform that excites the analog part of the circuit out of a set of logic states. Conversion algorithms are mostly based on synthesis of an electronic circuit that replaces the logic element’s output, and is connected as an excitation to the particular node. Logic gate’s delays also need to be considered and extracted by the event scheduler.
\n\t\t\tThe simplest solution of the D/A conversion is illustrated in Fig. 12. (Zwolinski et al., 1989).
\n\t\t\tThere is a branch consisting of a constant conductance
Ratios
A more complex output circuit is shown in Fig. 13. (Arnout & De Man, 1978). There are two voltage generators (
D/A conversion with voltage levels.
To further improve accuracy one may use the meliorated version depicted in Fig. 14. (Acuna et al., 1990). Sequence of pairs (
Conversion when using several signal states on the logic gate output.
D/A conversion using pair of voltage controlled resistors.
In the circuit in Fig. 15. (Corman & Wimborow, 1988), the logic gate’s output is observed as a voltage divider output. The capacitance values are constant and determined by the user if needed, and resistances are nonlinear and determined by user. In the circuits depicted in Figs. 14. and 15., the logic signal is firstly converted into electrical one and then values of this analog signal are discretized by comparing to sequence of thresholds. On that basis switches (Fig. 14.) or resistors values (Fig. 15.) are controlled. The circuits in previous examples approximate analog signal by discontinuous functions, what is inappropriate for most nonlinear circuit analysis methods.
\n\t\t\tExample of an output circuit approximated by analytical function is given in (Petković & Litovski, 1989; Petković & Litovski, 1991). Only nonlinear resistance is included, and using an approximation procedure, analytical expressions were produced expressing the output resistance dependence on the output voltage. Fig. 16. represents the output resistance of a CMOS inverter as a function of the output voltage. The dashed line is an approximation that was expressed in closed form.
\n\t\t\tThe circuit depicted in Fig. 17. (Petković & Stojanović, 1992) includes output capacitances also. It consists of a nonlinear controlled ideal voltage generator
Output resistance approximation.
D/A conversion using nonlinear reactive part.
Output impedance model.
Time-dependent resistors are used in (Nichols et al., 1992). The model of the output impedance of a logic gate is shown in Fig. 18. The values of the resistances
Similar solution where resistors change their values is given in (Brown et al., 1994).
\n\t\t\tIn the next, solution based on artificial neural networks is given. Main property of this solution is its topological generality. Namely, we have no need to look for the topology of the model depending on the approximation procedure or on the topology of the digital original. Simply, the topology is always the same. In addition, the approximating function is general in the sense that only the parameters within the approximating function are mapping the properties of the instantiated digital circuit.
\n\t\t\tThe topology of the new model is depicted in Fig. 19. In the figure,
and
Circuit representation of the model expressed by (1) and (2).
Here,
First results are shown in Fig. 20. Here the output waveforms of the original inverter and the model are shown to illustrate the quality of the approximation procedure. Unloaded circuits are simulated. The ANN has five input units (their role being the same as in Table 1.), three hidden units, and one output unit. Weights and thresholds are given in Table 2.
\n\t\t\tNo. | \n\t\t\t\t\t\tHidden-layer neurons (First figure stands for the input neuron) | \n\t\t\t\t\t\tOutput neuron (First figure stands for the hidden neuron) | \n\t\t\t\t\t
1 | \n\t\t\t\t\t\tw 1 (1,1) = 2.28185 w 1 (2,1) = –3.51137 w 1 (3,1) = 1.36815 w 1 (4,1) = 3.54312 w 1 (5,1) = –1.37367 θ 1 1 = –1.3177 | \n\t\t\t\t\t\tw 2 (1,1) = 0.644039 w 2 (2,1) = 0.644042 w 2 (3,1) = 0.644043 θ 1 2 = – 0.408248 | \n\t\t\t\t\t
2 | \n\t\t\t\t\t\tw 1 (1,2) = 2.28187 w 1 (2,2) = –3.51135 w 1 (3,2) = 1.36816 w 1 (4,2) = 3.54312 w 1 (5,2) = –1.37366 θ 2 1 = –1.31769 | \n\t\t\t\t\t\t\n\t\t\t\t\t |
3 | \n\t\t\t\t\t\tw 1 (1,3) = 2.28187 w 1 (2,3) = –3.51135 w 1 (3,3) = 1.36816 w 1 (4,3) = 3.54313 w 1 (5,3) = –1.37366 θ 3 1 = –1.31769 | \n\t\t\t\t\t\t\n\t\t\t\t\t |
Weights and thresholds of ANN used to model the inverter circuit.
Responses: 1) of unloaded CMOS inverter (considered as digital output) and 2) of the new model.
The following three examples are intended to check the modelling procedure based on situations not present during training. The first trace (marked 1)) in Fig. 21. is the output voltage of an inverter being loaded by an inverter, all modelled by regular transistor models, i.e., obtained by regular circuit simulation. The second one (marked 2)) represents the response of the same circuit with the ANN model used for the driving part and circuit model for the loading. This situation was not encountered in the training process. Excellent agreement was obtained, especially in the steepest part of the response that defines both the gain and the delay of the loaded inverter.
\n\t\t\tFurther, Fig. 22. gives a similar comparison the loading element here being a transmission line modelled by a
Responses of 1) inverter loaded by inverter, 2) a model loaded by inverter, and 3) an ANN (modelling the output) loaded by an ANN modelling the input of an inverter.
Responses of 1) an inverter loaded by RC \n\t\t\t\t\t\t
\n\t\t\t\t\t\t
Mixed-level analog behavioural modelling may need application of both concepts. In some situations, one will need to model the output circuit of the driver but in other cases, one will need to model the input circuit of the load; at very high levels of presentation, one will need both. Such an example for the D/A interface is given in Fig. 21. Here trace 3) represents a response obtained by behavioural simulation using ANN models for both the driver and the load. In this way, the type of modelling we propose offers the opportunity to be implemented in analog behavioural simulation at any level.
\n\t\t\tResponses of a) inverter loaded by a diode and b) ANN model loaded by a diode.
An approach to the modelling of the A/D and D/A interface in mixed-mode circuit using ANNs has been described. The main difference in these two is the type of the input signal used for capturing the dynamic properties of the circuit to be modelled. For the D/A interface we use a ramp being, simply, the natural signal, while a sinusoidal signal was used for the input impedance modelling at the A/D interface in conjunction with general two-terminal non-linear dynamic modelling.
\n\t\t\tTo summarise, a new method for modelling non-linear dynamic electronic circuits is described and applied to the modelling of A/D and D/A interfaces for mixed-signal simulation. It is
Microwave radiation creates energy increase in the mineral crystals by friction so as the material body can partially permit radiation. Hence, thermal body heat increases with mechanical vibration stress. In that circumstance, the mineral crystals can generate thermal crack space regarding the permittivity and contents. In this study, the easy heating to 90°C, over the effect of microwave energy managed the melting waste sludge with asphalt bitumen contents in the retort reactor. By the melting character of asphalt in the furnace during that process, Şırnak asphaltite slime, a type of bitumen coal was investigated for compaction change and compressing period.
Aggregate is the main raw material of road superstructures as in many construction manufacturing. The properties of the aggregate, which forms a large part of the bituminous hot mix used in the superstructure, greatly affect the mixing performance. Therefore, it may be difficult to obtain aggregates that provide the required properties for BSKs and the aggregate costs are higher [1, 2, 3, 4].
Hazardous radioactive or wet industrial sludge wastes processed for the recovery of metal with sulfuric acid, and methods for oxidized products with decay for acidic harmful substances. Thus, both soil wastes, complex carbon of sludge, and agricultural biomass wastes are evaluated. As well as other organic materials such as iron slime material and cellulosic material, they can be evaluated for high wetness. This waste was mixed by cleaning the acid mixture of the waste industry iron and chromium foundry sludge by pelletizing it with salt and mixing with the pelletized to cellulosic with exposed to decay time. This alkali salt is further salted then trapped. Disposal of sludge covers for scrapping has been examined on the impervious barrier at the bottom of large pools. As the coating of the bitumen mixture of the block pond size of these sludge wastes, the acidic solution with a solids content of 11.5% and hazardous radiation and the asphalt covering 10 mm hazardous wastewater pellets were degraded there in the dimensions of 10 mm. With this storage method, water resources are conserved and agricultural settings are also advantageous for improvement and environment. In our country, it is spread over a wide area outside the wide rocky soils in Siirt and Hakkari. The seepage of heavy metal ions or acidic chelate, mixing to streams should be neutralized by oxidizing reagents such as ozone or neutralizing alkaline washing so that it is reduced effluent contamination by high levels of heavy metals. The waste leaching liquors such as Hg, Pb, Cr, Cd, Cu, Zn, Fe, SO4 rates were contaminated freshwater sources near urbanization areas. The oxidation recycling of residual fly ash contaminated waters was a serious threat to the radioactive level. The hazardous chemical substance reacting that deteriorated environment was eliminated by pasting asphalt mixture and the following use as road pavement or filler source for waterproof barrier construction (Figure 1).
The 3D view of Mazıdağı, Mardin. EtiBakır Mazıdağı phosphoric acid, sulfuric acid, metal leaching, and metal electrowinning plants.
The Mazıdağı urbanization fieşd and freshwater dam lake, Mardin city is getting high ecological water safety threat on its population and density of immigrants by metal leaching phosphoric acid and sulfuric acid usage increase, its seepage, soil quality, and quantity of heavy metal in the soil. The main purpose for hazardous waste management in the Mazıdağ Phosphoric Acid and Electrowining Plant is easily controlled deposition of waste sludges without affecting water contamination. The water treatment plant in Mardin Eti Bakır Mazıdağı Plant will improve drinking water quality to be preserved. However, tailings containing hematite and iron sulfide with a high amount of sulfate and phosphate salts and tailing ponds water greatly threaten the ecology and near agricultural fields with a lack of irrigation.
The compost sludge volume was 10–20% in pasting, 90–95% of the volume was compost filler matters, 15% of the volume consists of fly ash fines [5, 6, 7, 8]. The primary or secondary cause of compaction in paste and asphalt composts deteriorates the use of unsuitable coarse aggregates or the use of aggregates containing undesirable shaped substances [7, 8, 9, 10, 11, 12, 13, 14].
Type of aggregate surface roughness, flatness, gradation, such as the characteristics of the bitumen binder thaw fatigue and tire performance has great importance on the asphalt composite track [14, 15, 16, 17, 18, 19, 20, 21] Aggregate-asphalt mixtures must meet certain requirements to be used as a pavement. These conditions are given in the Technical Specifications for coatings [21, 22, 23, 24]. Natural stone crush aggregates are preferred in road superstructure construction in our country. But in many countries, natural aggregates as well as, artificial aggregates have been used in road construction. Aggregates are grouped as light, normal, and heavy aggregate considering the unit weight. These aggregates used in road construction in our country are mostly included in the normal and heavy aggregate class. In recent years, the use of artificially obtained light aggregates in road construction has found application in some countries.
The use of microwave melting in the production of asphalt composts reduces the use of cheap filler waste raw material resources, even the removal of sludge waste and controlled dumping requires substantial environmental benefits. In addition, the usage of fly ash in the asphalt compost production process allows the recovery of non-hazardous waste materials; thus, freshwater management, ecological, and economic benefits [25, 26, 27, 28, 29, 30, 31, 32, 33, 34].
In this study, first all experiments were carried out to determine the physical properties of natural crushed stone aggregates and fly ash to be used in the mixture [34]. Sludge waste-melted asphalt briquettes were produced using Şırnak quarry limestone and asphaltite slime, aggregate using limestone, and char as compost mixing aggregate
The area was chosen as tailing pond area about 500 m away from the quarry and the sludged matter is wet at that 14 and 23.1% water of the dumping site near the Mazıdağı freshwater lake. Tailing ponds of metal leaching unit is near freshwater dam lake. On this lack of water for irrigation and drinking water demand of plant suffers from a relatively high potential of instability of tailing effluents seepages to groundwater levels by flood hazard and heavy rains. Geolayers for tailing ponds is providing control of the heavy metal-containing effluents seepages.
Şırnak asphaltite slime in the evaluation of local natural filler allows the production of bitumen binding strength of paste [14, 15, 16]. Weak strength of paste of asphalt compost reduces the contamination by increased fly ash filler use [17, 18, 19]. Plant for pasting of heavy metal sludge and composting by coal waste slime of Şırnak will improve drinking water quality to be preserved in Mardin.
The sludge matter hazards are seen on the ground come to seepage over the agricultural and freshwater sources in the area. In this case, it is clear that toxic parameters on the sludges will be compacted in the laboratories, avoiding the permanent dissolution values over 325 ppm to below 413 ppm–52 ppm. In this study, the toxic metal contaminants at lower levels than the threat level are about below 10 ppm. However, it was over 210 mg/l with some near groundwater wells and wet soils with leaks by uncontrolled seepages near tailings pond in Mazıdağ EtiBakır Plant area.
The well water heavy metal contamination levels were determined as given in Table 1.
Char sludge and asphalt composite compaction as the mining wastes was also decreased the permeability of bottom layers in the dumping mining landfill field. The chemical composition of asphalt paste compost matters is given in Table 2.
As a result of the Marshall calculations to determine the optimum amount of asphalt and type for high compaction is made with all three correlations, it is clear that if the lower limits of the aggregate types given in the specification are used in the sludge asphalt paste mixtures, a low binder will be required and the cost of the mixture will decrease. Bitumen properties of the sludge asphalt paste are given in Table 3. The physical properties of each produced sample were determined. The water sorption and porosity of the samples were determined by a series of soil standard experiments. In addition, compost quality comparison is made considering the use and supply of the waste materials used.
Effluent, mg/l | Tailing ponds sludge1 effluent | Tailing ponds sludge2 effluent | Tailing ponds sludge1 | Tailing ponds sludge2 | Well 1 irrigation soil water | Well 2 irrigation soil water | Dam irrigation soil water |
---|---|---|---|---|---|---|---|
Cu | 780 | 780 | 12.3 | 14.11 | 70 | 4.71 | 4.71 |
Pb | 158 | 158 | 23.2 | 12.58 | 18 | 5.7 | 5.2 |
Fe | 403.3 | 403.3 | 59 | 93.3 | 43.3 | 60.62 | 67.62 |
K + Na | 852 | 852 | 8.7 | 8.52 | 552 | ≥70 | ≥50 |
Cd | 276.2 | 276.2 | 14.1 | 14.72 | 47 | 16 | 15 |
Mn | 123 | 123 | 24.2 | 43.3 | 13 | ≤25 | ≤25 |
Zn | 372 | 372 | 15.7 | 7.2 | 57 | ≤15 | ≤15 |
PO4 | 1010 | 1010 | 2.8 | 2.10 | 220 | ≤5 | ≤5 |
SO4 | 5700 | 5700 | 1.9 | 0.67 | 670 | ≤15 | ≤15 |
Cu | 124.1 | 124.1 | 52.3 | 48.71 | 40.71 | ||
Pb | 312.5 | 312.5 | 23.2 | 24.53 | 11.53 | ||
Fe | 444.3 | 444.3 | 5.9 | 7.62 | 5.62 | ||
K + Na | 747.5 | 747.5 | 81.7 | 81.46 | 88.6 | ≥70 | ≥50 |
Cd | 246.7 | 246.7 | 10.1 | 9.56 | 19.56 | ||
Mn | 272 | 272 | 1.5 | 3.02 | 1.02 | ≤5 | ≤5 |
Zn | 3330 | 3330 | 2.4 | 2.41 | 2.41 | ≤5 | ≤5 |
PO4 | 11,065 | 11,065 | 2.8 | 2.44 | 2.44 | ||
SO4 | 5798 | 5798 | 1.9 | 0.37 | 0.55 |
The metal contents of the tailing pond sludges of the Mazıdağ EtiBakır plant and the potential soil well waters.
Component % | Şırnak asphaltite slime | Şırnak shale | Şırnak asphaltite char | Mazıdağı waste sludge | Şırnak asphaltite coal fly ash |
---|---|---|---|---|---|
SiO2 | 43.1 | 50.50 | 50.50 | 60.13 | 41.4 |
Al2O3 | 13.3 | 12.61 | 14.61 | 17.22 | 18.1 |
Fe2O3 | 9.5 | 14.30 | 24.30 | 4.59 | 4.2 |
CaO | 7.4 | 12.30 | 2.30 | 2.48 | 18.4 |
MgO | 3.7 | 2.3 | 1.28 | 2.17 | 4.0 |
K2O | 2.5 | 2.0 | 2.51 | 3.51 | 2.1 |
Na2O | 1.3 | 1.3 | 1.35 | 4.35 | 1.5 |
Ign.Loss. | 38.9 | 6.6 | 12.21 | 4.12 | 1.6 |
SO3 | 0.2 | 1.2 | 0.12 | 0.52 | 0.2 |
Chemical composition of fillers of char composite present in the hazardous sludge pasting sample.
Bitumen properties | |
---|---|
ASTM test | Ortalama Değerler |
60–70 | |
180°C | |
230°C | |
45.5°C | |
1034 |
The bitumen matter properties in the asphalt pasting sludge studies.
This study determined optimum volume reduction by compost compaction at finer particle size fraction rates and distribution factors for compaction to packed density. Finally, a compaction volume rate of 32% could be managed by microwave melting and following pressing under 3 tones load for 50 mm diameter mold.
The physical and mechanical strength values investigated are given in Table 4 with respect to standards. The oil addition as easy pressing through the mold in compaction is optimized at below 150-micron particle size fractions. The bitumen content was recovered back with a 95.7% recovery rate in compacting fine solids as given in Table 5 following microwave melting.
Test, 0–4.75 mm | Şırnak asphaltite slime | Şırnak asphaltite char mm | Şırnak fly ash | Standartlar |
---|---|---|---|---|
Water sorption (%) | 3.54 | 1.63 | 0.81 | ASTM C 127 |
Los angeles (%) | 27 | 26 | 23–38 | ASTM C 131 |
Fineness (%) | 15.5 | 3.7 | 4.5 | ASTM C 117 |
Organic matter mad. | — | — | — | ASTM C 40 |
Thawing (%) | 11 | 9 | 7.7 | ASTM C 88 |
Abrasion (%) | — | ≥%50 | ≥%50 | |
Density (gr/cm3) | 2.576 | 2.642 | 2.677 | ASTM C 127 |
Rough weight (gr/cm3) | 1.61 | 1.40 | 1.41 | ASTM C 29 |
Compact weight (gr/cm3) | 1.91 | 1.62 | 1.64 | ASTM C 29 |
Granule properties, fineness of Şırnak limestone compost fillers present in the composite sample regarding ASTM standards.
Şırnak asphaltite slime | Şırnak asphaltite char | Şırnak fly ash | |
---|---|---|---|
Density (gr/cm3) | 1.855 | 1.655 | 1.855 |
Rough weight (gr/cm3) | 1.32 | 1.23 | 1.32 |
Compact weight (gr/cm3) | 1.84 | 1.84 | 1.94 |
Water sorption (%) | 14.5 | 15.5 | 17.5 |
Moisture (%) | 0.2 | 0.1 | 0.2 |
Şırnak Asphaltite slime, char granule properties, fineness of Şırnak char and fly ash fillers present in the composite sample.
Ground samples are sieved as mentioned in the standard method and sedimentation test. The particle gradation and size distribution were determined according to the chart in Figure 2. Figure 3 shows the gradation of asphalt paste fillers (ASTM C136) [11].
All of the base and bottom base layers without binders are weighted by bituminous hot mixtures.
Changes in Gaudin-Schumann particle size distribution of paste filler material.
The sludge wastes in the Mazıdağ tailing pond are given in Table 1.
The gradation factors and formula is the oldest McKessen - Fricstad formula for calculating asphalt content. The proposed binder addition amount is determined by the formula given below for asphalt bitumen bound aggregate composts [11, 12].
P: Binder content in% by weight of aggregate a:% of aggregate remaining on sieve No 10.
S: 1% by weight of aggregate remaining between sieves No. 10 and 200.
F: % by weight of the aggregate passing through the sieve No.200.
The amphoric formula is commonly used in the gradation calculation of the compacting paving rock with asphalt. The bitumen content in asphaltic mixtures was determined by the following correlation.
P: Asphalt content of % by weight of aggregate specific gravity of aggregate distribution factor α = 2.65/γ
γ: Aggregate specific gravity.
k: Aggregate wealth module (3 to 3.5 coefficient).
F: Aggregate fine content %.
S: specific surface area of aggregate (m2/kg).
Total Shear strength = 0.25G + 2.3P + 12SI + I35F.
G:% by weight of aggregates greater than 6.3 mm.
S:% by weight of the aggregates remaining between 6.3 mm–0.315 mm (# 50).
As it is seen in both experimental methods and empirical relations, an important factor affecting asphalt content is the aggregate gradation used to determine the asphalt content in asphaltic mixtures. The effect of aggregate gradation on the asphalt content was investigated in three parts. In the first part, binding contents of binder and wear layers aggregate gradations were found. In the second part, we investigated how aggregates passing through screens 1/2 ”, 4, and 8 affect the contents of the binder.
The asphalt contents required for the lower and upper limits of the compost gradations are illustrated in Figure 2 using the ASTM standards [14]. In Figure 2, the aggregate gradation for road pavement requiring at least asphalt content for the binder layer is the lower limit of type 3 providing high stability strength under layer. The upper limit of type 2 is within the upper limits providing high wear resistivity on the road pavement. For the ductility, it is type 1, which requires the medium binding content among the lower and upper limits of gradation.
The standard abrasion criteria of aggregates are determined by standard tumbling tests giving values of shattering by water and tumbling act [15]. The Şırnak asphaltite, shale, and char show low durability values in Los Angeles values among 40–55%. Regarding grain size of limestone aggregates, the compost properties are given in Table 6.
Şırnak limestone | ||||
---|---|---|---|---|
Size, mm | 0–4.75 | 4.75–9.5 mm | 9.5–25 | Standards |
Water (%) | * (3.54) | 1.63 | 0.81 | ASTM C 127 |
Los Angeles (%) | 44 | 55 | 73.804 | ASTM C 131 |
Fine (%) | 11.3 | 1.27 | 0.45 | ASTM C 117 |
Organic binder | Berrak | Berrak | Berrak | ASTM C 40 |
Thaw. (%) | * | * | 6.69 | ASTM C 88 |
Abrasion. (%) | * | %50 ‘den Fazla | %50 ‘den Fazla | |
γ Density (gr/cm3) | 2.576 | 2.642 | 2.677 | ASTM C 127 |
Rough density γk gr/cm3) | 1.61 | 1.40 | 1.41 | ASTM C 29 |
Compacted density (gr/cm3) | 1.91 | 1.62 | 1.64 | ASTM C 29 |
The physical parameters of Şırnak limestone in paste compost.
Stability is a significant parameter of compost impermeability for sludge paste avoiding contact with water sources in the landfill. The lowest asphalt binder at 3.5–4% weight rate in the compost increase the wear resistivity and stability high enough to resist compaction loads and contact to potential water seepages.
However, very high stability means a very hard pasting mixture even a high amount of fine fillers for sludge pasting was required. On the other side ductility and durability decrease for the pastes by a high amount of thermal or stress cracking. The microwave heating provides the low asphalt content use in pasting and even easier compacting in this study. Although the asphalt leak of 0.1% occurred in the tests gasoil was used emulsification of asphalt due to reducing heterogeneous mixing and easy wetting. The high compaction of sludge and use of fly ash at 20–25% volume rate increased compaction ability and reduced the permeability. The permeability of sludge compost shows the resistance of the asphalt coating to the passage of air or water.
The permeability over 109 D is wished from waste pastes to avoid the hazardous effect of sludge contamination to the soil or water sources.
The impermeability is determined by the percentage of air voids in the mixture of low asphalt percentage and high voids in the design make the layer highly permeable.
By the way of microwave radiation at 10 minutes period increased compaction load to 1500 kg with 20 mm shear compaction distance in the barrel of 70 mm diameter of test mold. The followed process in sludge pasting is illustrated in Figure 4.
Microwave experimentation flowsheet for sludge pasting with asphalt.
The hazardous sludge threat is widened in similar areas. The urbanization districts which are at 1 km distance to Mazıdağı on the north of the Metal recovery plant and the tailing pond area of Mazıdağı Plant (Figure 5) were examined with permeability and hydrology of land in different locations at 100 m away. However, in this study char carbon reduces to contaminated soil and irrigation water sources by metal absorption ability. 20–10% volume rate of char in the compost will decrease dissolution amount to water at ten-fold times by homogeneous mixing under microwave melting radiation on surface interference. The compaction ability is even increased absorption amount by addition to char and coal slime to the pasting. The coverage binding bitumen and wetting effect of asphalt is improved by the addition of char carbon content of compost.
Satellite view of Mazıdağı, Mardin. EtiBakır Mazıdağı metal leaching and electrowinning plants.
In the present study, the microwave melted mixture of a Sirnak asphaltite slime below 100 microns as a carbon sample with coal pyrite improved the microwave melting effect before compaction. This resulted in almost complete melting of the compost sludge and ash material as seen in Figure 4.
The medium-coarse content at 4.5 mm–2 mm provided the well gradation and optimum pasting method at an amount 25% weight rate compost fillers as illustrated in Figure 6. The finer size below 0.2 mm increased 50% weight rate determines the lowest asphalt content of the paste gradation used in the sludge mixture depending on the surface area. In this method, we briefly follow the following mixture types as given in Table 7.
Views of marl of Sirnak, limestone b, and c, d. after chemical interaction aggregate image.
Mixture component % | Sludge waste/ slag char | Sırnak limestone | Şırnak marl | Fly ash | Asphalt |
---|---|---|---|---|---|
A | 65 | 3 | 2 | 25 | 10 |
A2 | 65 | 3 | 2 | 20 | 10 |
A3 | 55 | 5 | 5 | 20 | 15 |
C | 65 | 4 | 1 | 20 | 10 |
C2 | 60 | 4 | 1 | 20 | 15 |
F | 65 | 9 | 1 | 20 | 10 |
F2 | 60 | 9 | 1 | 20 | 15 |
Char, Şırnak asphaltite sludge compost paste filler matrix composition in Şırnak City.
The binder percentages are about 4.5–5% weight rate corresponding to the optimum compaction value so as the percentage of the space specified in the compaction. The binder compaction space percentages are the percentage of asphalt volume collected. The arithmetic averages of the bulk content were found as the best compaction asphalt content (the percentage of the aggregate weight in the mixture). This value is checked on the yield curve and the corresponding flow value is checked for compliance with the specification.
The filler materials used in the pasting compost at 20% volume rate are viewed in Figure 6. Shale particles contained high porosity reaching 7.8% in the compost. The limestone’s water absorption values were lower with asphaltite slime at about 2–3.5%. The filler mixing combinations are given in Table 7.
The effect of fly ash and Şırnak asphaltite and shale on compost density with asphalt mixing is illustrated in Figure 7.
Relative compaction changes of paste fill with Şırnak limestone, asphaltite slime char, and Şırnak shale after load indentation.
In this study, the mechanical properties of local limestone and mine waste stone of Şırnak asphaltite slime and shale are used as filler for the purpose of asphalt sludge filler paste production. The waste slime asphaltite and Şırnak char are ground below 4 mm at the coarser part of 5% weight ratio. Şırnak shale and 15% Silopi fly ash are prepared as a binder cementing matter of sludge mixture of paste. The pressed blocks were manufactured in 50 × 50 × 10 mm like pile blocks, 10 mm thick bending strength, impact resistance, friction, abrasion loss, compaction distance were determined by the experiments. The ability of paste in the pile blocks to compact loss asphalt bitumen and water desorption are analyzed.
These experiments show that local rock cement mixtures and elaborate the application of cementing technique with silica fume used and it prevents the coating applied to moisturize the strengthening of historic buildings Sirnak region as a result and is determined to carry out the consolidation.
It is determined that the 90°C temperature accelerates the melting of asphalt bitumen. These technological applications can be further developed with the evaluability of local natural stone powder in paste backfill. The strength of sludge paste pile blocks produced is reduced 7.2 to 6.4 MPa. Lower asphalt weight increased mechanical strength of pasted pile block with compaction been advantageous. Thus, the ideal compacting load of 100 kg tight aggregates with the block and pasted block resistance of the produced slag mixture may arise from 8.3 to 9.2 MPa.
The results are shown in Figures 8 and 9. Indentation tests of the rock types were determined by a drill machine at 10 mm bit diameter due to the correlation of rock strengths underground mining cavity conditions.
Compression strength of paste fill material rocks.
Point load I strength of paste fill material rocks.
Asphalt and fly ash binders are raised to 10–45% weight ratio at different mixtures and 20% wet hazardous sludge and strength properties of prepared mixture paste with asphalt melted compost.
The water/binder (w/B) ratio is decided to be 20%/10–45% as a result of preliminary experiments. Pasting 5% melted asphalt is sufficient. The amount of each series fly ash composting fines are sorted asphalt and sludge in pile blocks and determined the compressive strength after drying blocks.
Fly ash fine-texture and sludge mixing were homogeneous and the contamination act of sludge decreased at half amount rate by addition of 20% fly ash addition to paste mixture. The char carbon will also ten times decrease the metal contamination to water sources. The texture of low asphalt and emulsified hıgh bitumen content lowered the compaction resistance by increasing structure strength.
Especially the compact loading resistivity increased over 1500 kg for 70 mm barrel loading on which the resistance is kept as high as 20 mm displacement as high. Sand content of sludge was lower than the limestone so that this gradation provided high durability and less cracking during compaction loading final product briquettes and lower abrasion resistance.
Figure 10 shows the 1000 kg loading was suitable for long durability and optımum briquetting outputs. The stability was varied depending on the amount of fly ash and Şırnak asphaltite slime contained in the pasting relative to the pore contents in the micro-structural texture of asphalt compost. The pore density will decrease by low asphalt content and compaction resulting in the development of impermeable surface on the compost briquettes consequently.
Char addition weight of pile paste blocks with paste fill vs. UCS test results: 1. Shale . 2. Sirnak limestone 3. Sirnak limestone.
The apparent uniaxial compressive strength test of Şırnak limestone showed sufficient substrate gradation and porous texture with high Los Angeles values of 67% at 4.5 mm granules. The gradation was suitable for high compaction ability and Şırnak limestone exhibited low porosity and water sorption 0.8%.
The higher compaction over 1000 kg provided sufficient permeability and compression strength values and higher shear resistance with lower cracking over time period of dynamical stress loads related to landfill application.
Shear stress
Normal stress
Plasticity index
Liquid limit
Plastic limit
Optimum water content
Natural unit volume weight
Saturated unit volume weight
Dry unit volume weight
Maximum dry unit volume weight
Grain unit volume weight
Permeability coefficient
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The aim of this article is ensuring quality of service (QoS) in IMS network. Admission control (AC) is used to manage incoming traffic and to prevent the network congestion. The main function of AC is to maximize the utilization of network resources and to ensure the level of QoS. AC was applied on constant bit rate (CBR) and variable bit rate (VBR) traffic. Three methods were chosen for VBR traffic and they were compared. The last part of the article deals with simulations CBR and VBR traffic before and after application of AC.",book:{id:"6449",slug:"proceedings-of-the-3rd-czech-china-scientific-conference-2017",title:"Proceedings of the 3rd Czech-China Scientific Conference 2017",fullTitle:"Proceedings of the 3rd Czech-China Scientific Conference 2017"},signatures:"Ivan Baroňák, Michal Čuba, Chien-Ming Chen and Ladislav Beháň",authors:[{id:"200987",title:"Prof.",name:"Jaromir",middleName:null,surname:"Gottvald",slug:"jaromir-gottvald",fullName:"Jaromir Gottvald"}]},{id:"57130",doi:"10.5772/intechopen.71105",title:"Mobile Probe for Cellular Network Coverage and Quality Measurement",slug:"mobile-probe-for-cellular-network-coverage-and-quality-measurement",totalDownloads:1357,totalCrossrefCites:1,totalDimensionsCites:1,abstract:"This article describes a proposal of the probe application used for 2G–4G mobile network coverage and speech quality measurement. It is based on Android platform, most commonly used operation system for mobile phones. Measured results are visualized in the form of a map using GPS location. There are few tests available focusing on the applications that are most often used: test of the network coverage, speed of the websites loading, data rate test and voice quality test. The results are analyzed directly in the application and are also available over the web interface form. Individual results can be exported to standard output .csv, .json and .xml formats for further analysis.",book:{id:"6449",slug:"proceedings-of-the-3rd-czech-china-scientific-conference-2017",title:"Proceedings of the 3rd Czech-China Scientific Conference 2017",fullTitle:"Proceedings of the 3rd Czech-China Scientific Conference 2017"},signatures:"David Vasicek, Martin Mikulec, Erik Gresak, Filip Rezac and Erik\nChromy",authors:[{id:"200987",title:"Prof.",name:"Jaromir",middleName:null,surname:"Gottvald",slug:"jaromir-gottvald",fullName:"Jaromir Gottvald"}]},{id:"57132",doi:"10.5772/intechopen.71099",title:"Prepaid Voice Services Based on OpenBTS Platform",slug:"prepaid-voice-services-based-on-openbts-platform",totalDownloads:1622,totalCrossrefCites:1,totalDimensionsCites:1,abstract:"This article describes the design and implementation of prepaid voice services based on OpenBTS platform. By using various programming languages and open-source software tools, we can integrate prepaid voice services with this system, so its functionality is resembled as much as possible the operation of traditional GSM network provider. This article also provides description of how customers will approach their billing services, how they will access their accounts and pay their invoices.",book:{id:"6449",slug:"proceedings-of-the-3rd-czech-china-scientific-conference-2017",title:"Proceedings of the 3rd Czech-China Scientific Conference 2017",fullTitle:"Proceedings of the 3rd Czech-China Scientific Conference 2017"},signatures:"Ladislav Behan, Lukas Orcik, Filip Rezac, Ivan Baronak and Jerry\nChun Wei Lin",authors:[{id:"200987",title:"Prof.",name:"Jaromir",middleName:null,surname:"Gottvald",slug:"jaromir-gottvald",fullName:"Jaromir Gottvald"}]},{id:"57113",doi:"10.5772/intechopen.71100",title:"Study of Admission Control Methods for IPTV Services",slug:"study-of-admission-control-methods-for-iptv-services",totalDownloads:999,totalCrossrefCites:0,totalDimensionsCites:0,abstract:"The paper deals with admission control methods used in Internet Protocol (IP) Multimedia Subsystem. The purpose of implementing AC methods in IP Multimedia Subsystem (IMS) is to control the access of incoming connections to network resources. At the Institute of Telecommunications, we have built an experimental laboratory, which is used to test these methods. In this paper, we focus on Internet Protocol Television (IPTV) services; therefore, we have created a variable bit-rate IPTV traffic generator that is used as the input to the network, so we can test the behavior of selected AC methods. They are implemented in a simulated IPTV service provider access network, so we can examine the effects of variable bit-rate IPTV streams on the decisions made by those methods. To calculate the required bandwidth of an input stream, two simulation scenarios with different number of input packets were performed. One of these AC methods was modified where the peak input rate parameter of an IPTV stream was replaced by the average bit-rate of this stream. 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Previous researches stated the various characteristics of Chinese labor market. However, with rapid development, the labor market in China has some new and unpredicted changes in recent years. With the comprehensive, rigorous, and consistent data investigated from 2000 to 2015, which come from the National Bureau of Statistic of China (NBSC), this paper does a descriptive research on verification of common features stated in the previous literature, disclosing some new features and changes of current Chinese labor market. These features include the following: (1) the average wage in society keeps increasing with a relative decrease of return to education; (2) the old pattern of labor mobility, from rural area to urban area, is steady; however, the growth rate of urban population keeps decreasing, and the mobility of labor forces showed significant regional inequality; (3) the effectiveness and conduction of labor law and regulation are challenged by labor market segmentation caused by informal employment; and (4) the labor force participation rate (LFPR) in China keeps stable after 2010, with four different definitions. This paper designs a new way of measurement of informal sectors and indicates that the labor force participation rate in China is steady, not declining, after 2010. This analysis not only provides a complete understating of the current Chinese labor market but also indicates the potential impact and problem caused by these new and changing features of Chinese labor market for researcher and policy-maker.",book:{id:"6449",slug:"proceedings-of-the-3rd-czech-china-scientific-conference-2017",title:"Proceedings of the 3rd Czech-China Scientific Conference 2017",fullTitle:"Proceedings of the 3rd Czech-China Scientific Conference 2017"},signatures:"Yajun Meng",authors:[{id:"200987",title:"Prof.",name:"Jaromir",middleName:null,surname:"Gottvald",slug:"jaromir-gottvald",fullName:"Jaromir Gottvald"}]}],mostDownloadedChaptersLast30Days:[{id:"57114",title:"New Features of Labor Market and Their Impact in China",slug:"new-features-of-labor-market-and-their-impact-in-china",totalDownloads:1225,totalCrossrefCites:0,totalDimensionsCites:0,abstract:"After 30 years of development, China has great transaction of the labor market from a government-controlled market to a market-driven market. Previous researches stated the various characteristics of Chinese labor market. However, with rapid development, the labor market in China has some new and unpredicted changes in recent years. With the comprehensive, rigorous, and consistent data investigated from 2000 to 2015, which come from the National Bureau of Statistic of China (NBSC), this paper does a descriptive research on verification of common features stated in the previous literature, disclosing some new features and changes of current Chinese labor market. These features include the following: (1) the average wage in society keeps increasing with a relative decrease of return to education; (2) the old pattern of labor mobility, from rural area to urban area, is steady; however, the growth rate of urban population keeps decreasing, and the mobility of labor forces showed significant regional inequality; (3) the effectiveness and conduction of labor law and regulation are challenged by labor market segmentation caused by informal employment; and (4) the labor force participation rate (LFPR) in China keeps stable after 2010, with four different definitions. This paper designs a new way of measurement of informal sectors and indicates that the labor force participation rate in China is steady, not declining, after 2010. This analysis not only provides a complete understating of the current Chinese labor market but also indicates the potential impact and problem caused by these new and changing features of Chinese labor market for researcher and policy-maker.",book:{id:"6449",slug:"proceedings-of-the-3rd-czech-china-scientific-conference-2017",title:"Proceedings of the 3rd Czech-China Scientific Conference 2017",fullTitle:"Proceedings of the 3rd Czech-China Scientific Conference 2017"},signatures:"Yajun Meng",authors:[{id:"200987",title:"Prof.",name:"Jaromir",middleName:null,surname:"Gottvald",slug:"jaromir-gottvald",fullName:"Jaromir Gottvald"}]},{id:"57132",title:"Prepaid Voice Services Based on OpenBTS Platform",slug:"prepaid-voice-services-based-on-openbts-platform",totalDownloads:1623,totalCrossrefCites:1,totalDimensionsCites:1,abstract:"This article describes the design and implementation of prepaid voice services based on OpenBTS platform. By using various programming languages and open-source software tools, we can integrate prepaid voice services with this system, so its functionality is resembled as much as possible the operation of traditional GSM network provider. This article also provides description of how customers will approach their billing services, how they will access their accounts and pay their invoices.",book:{id:"6449",slug:"proceedings-of-the-3rd-czech-china-scientific-conference-2017",title:"Proceedings of the 3rd Czech-China Scientific Conference 2017",fullTitle:"Proceedings of the 3rd Czech-China Scientific Conference 2017"},signatures:"Ladislav Behan, Lukas Orcik, Filip Rezac, Ivan Baronak and Jerry\nChun Wei Lin",authors:[{id:"200987",title:"Prof.",name:"Jaromir",middleName:null,surname:"Gottvald",slug:"jaromir-gottvald",fullName:"Jaromir Gottvald"}]},{id:"57128",title:"Employing Monitoring System to Analyze Incidents in Computer Network",slug:"employing-monitoring-system-to-analyze-incidents-in-computer-network",totalDownloads:1230,totalCrossrefCites:0,totalDimensionsCites:0,abstract:"Today, network technologies can handle throughputs or up to 100 Gbps, transporting 200 million packets per second on a single link. Such high bandwidths impact network flow analysis and as a result require significantly more powerful hardware. Methods used today concentrate mainly on analyses of data flows and patterns. It is nearly impossible to actively look for anomalies in network packets and flows. A small amount of change of monitoring patterns could result in big increase in potentially false positive incidents. This paper focuses on multi-criteria analyses of systems generated data in order to predict incidents. We prove that system generated monitoring data are an appropriate source to analyze and allow for much more focused and less computationally intensive monitoring operations. By using appropriate mathematical methods to analyze stored data, it is possible to obtain useful information. During our work, some interesting anomalies in networks were found by utilizing simple data correlations using monitoring system Zabbix. Afterwards, we prepared and pre-processed data to classify servers and hosts by their behavior. We concluded that it is possible to say that deeper analysis is possible thanks to Zabbix monitoring system and its features like Open-Source core, documented API and SQL backend for data. The result of this work is a new approach to analysis containing algorithms which allow to identify significant items in monitoring system.",book:{id:"6449",slug:"proceedings-of-the-3rd-czech-china-scientific-conference-2017",title:"Proceedings of the 3rd Czech-China Scientific Conference 2017",fullTitle:"Proceedings of the 3rd Czech-China Scientific Conference 2017"},signatures:"Lukáš Macura, Jan Rozhon and Jerry Chun-Wei Lin",authors:[{id:"200987",title:"Prof.",name:"Jaromir",middleName:null,surname:"Gottvald",slug:"jaromir-gottvald",fullName:"Jaromir Gottvald"}]},{id:"57130",title:"Mobile Probe for Cellular Network Coverage and Quality Measurement",slug:"mobile-probe-for-cellular-network-coverage-and-quality-measurement",totalDownloads:1359,totalCrossrefCites:1,totalDimensionsCites:1,abstract:"This article describes a proposal of the probe application used for 2G–4G mobile network coverage and speech quality measurement. It is based on Android platform, most commonly used operation system for mobile phones. Measured results are visualized in the form of a map using GPS location. There are few tests available focusing on the applications that are most often used: test of the network coverage, speed of the websites loading, data rate test and voice quality test. The results are analyzed directly in the application and are also available over the web interface form. Individual results can be exported to standard output .csv, .json and .xml formats for further analysis.",book:{id:"6449",slug:"proceedings-of-the-3rd-czech-china-scientific-conference-2017",title:"Proceedings of the 3rd Czech-China Scientific Conference 2017",fullTitle:"Proceedings of the 3rd Czech-China Scientific Conference 2017"},signatures:"David Vasicek, Martin Mikulec, Erik Gresak, Filip Rezac and Erik\nChromy",authors:[{id:"200987",title:"Prof.",name:"Jaromir",middleName:null,surname:"Gottvald",slug:"jaromir-gottvald",fullName:"Jaromir Gottvald"}]},{id:"57112",title:"Traffic Management by Admission Control in IMS Networks",slug:"traffic-management-by-admission-control-in-ims-networks",totalDownloads:998,totalCrossrefCites:1,totalDimensionsCites:1,abstract:"The paper deals with traffic management in IP multimedia subsystem (IMS) networks. The aim of this article is ensuring quality of service (QoS) in IMS network. Admission control (AC) is used to manage incoming traffic and to prevent the network congestion. The main function of AC is to maximize the utilization of network resources and to ensure the level of QoS. AC was applied on constant bit rate (CBR) and variable bit rate (VBR) traffic. Three methods were chosen for VBR traffic and they were compared. The last part of the article deals with simulations CBR and VBR traffic before and after application of AC.",book:{id:"6449",slug:"proceedings-of-the-3rd-czech-china-scientific-conference-2017",title:"Proceedings of the 3rd Czech-China Scientific Conference 2017",fullTitle:"Proceedings of the 3rd Czech-China Scientific Conference 2017"},signatures:"Ivan Baroňák, Michal Čuba, Chien-Ming Chen and Ladislav Beháň",authors:[{id:"200987",title:"Prof.",name:"Jaromir",middleName:null,surname:"Gottvald",slug:"jaromir-gottvald",fullName:"Jaromir Gottvald"}]}],onlineFirstChaptersFilter:{topicId:"809",limit:6,offset:0},onlineFirstChaptersCollection:[],onlineFirstChaptersTotal:0},preDownload:{success:null,errors:{}},subscriptionForm:{success:null,errors:{}},aboutIntechopen:{},privacyPolicy:{},peerReviewing:{},howOpenAccessPublishingWithIntechopenWorks:{},sponsorshipBooks:{sponsorshipBooks:[],offset:0,limit:8,total:null},allSeries:{pteSeriesList:[],lsSeriesList:[],hsSeriesList:[],sshSeriesList:[],testimonialsList:[]},series:{item:{id:"14",title:"Artificial Intelligence",doi:"10.5772/intechopen.79920",issn:"2633-1403",scope:"Artificial Intelligence (AI) is a rapidly developing multidisciplinary research area that aims to solve increasingly complex problems. In today's highly integrated world, AI promises to become a robust and powerful means for obtaining solutions to previously unsolvable problems. This Series is intended for researchers and students alike interested in this fascinating field and its many applications.",coverUrl:"https://cdn.intechopen.com/series/covers/14.jpg",latestPublicationDate:"May 18th, 2022",hasOnlineFirst:!0,numberOfPublishedBooks:9,editor:{id:"218714",title:"Prof.",name:"Andries",middleName:null,surname:"Engelbrecht",slug:"andries-engelbrecht",fullName:"Andries Engelbrecht",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRNR8QAO/Profile_Picture_1622640468300",biography:"Andries Engelbrecht received the Masters and PhD degrees in Computer Science from the University of Stellenbosch, South Africa, in 1994 and 1999 respectively. He is currently appointed as the Voigt Chair in Data Science in the Department of Industrial Engineering, with a joint appointment as Professor in the Computer Science Division, Stellenbosch University. Prior to his appointment at Stellenbosch University, he has been at the University of Pretoria, Department of Computer Science (1998-2018), where he was appointed as South Africa Research Chair in Artifical Intelligence (2007-2018), the head of the Department of Computer Science (2008-2017), and Director of the Institute for Big Data and Data Science (2017-2018). In addition to a number of research articles, he has written two books, Computational Intelligence: An Introduction and Fundamentals of Computational Swarm Intelligence.",institutionString:null,institution:{name:"Stellenbosch University",institutionURL:null,country:{name:"South Africa"}}},editorTwo:null,editorThree:null},subseries:{},overviewPageOFChapters:[],overviewPagePublishedBooks:[],openForSubmissionBooks:{},onlineFirstChapters:{},subseriesFiltersForOFChapters:[],publishedBooks:{},subseriesFiltersForPublishedBooks:[],publicationYearFilters:[],authors:{paginationCount:148,paginationItems:[{id:"165328",title:"Dr.",name:"Vahid",middleName:null,surname:"Asadpour",slug:"vahid-asadpour",fullName:"Vahid Asadpour",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/165328/images/system/165328.jpg",biography:"Vahid Asadpour, MS, Ph.D., is currently with the Department of Research and Evaluation, Kaiser Permanente Southern California. He has both an MS and Ph.D. in Biomedical Engineering. He was previously a research scientist at the University of California Los Angeles (UCLA) and visiting professor and researcher at the University of North Dakota. He is currently working in artificial intelligence and its applications in medical signal processing. In addition, he is using digital signal processing in medical imaging and speech processing. Dr. Asadpour has developed brain-computer interfacing algorithms and has published books, book chapters, and several journal and conference papers in this field and other areas of intelligent signal processing. He has also designed medical devices, including a laser Doppler monitoring system.",institutionString:"Kaiser Permanente Southern California",institution:null},{id:"169608",title:"Prof.",name:"Marian",middleName:null,surname:"Găiceanu",slug:"marian-gaiceanu",fullName:"Marian Găiceanu",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/169608/images/system/169608.png",biography:"Prof. Dr. Marian Gaiceanu graduated from the Naval and Electrical Engineering Faculty, Dunarea de Jos University of Galati, Romania, in 1997. He received a Ph.D. (Magna Cum Laude) in Electrical Engineering in 2002. Since 2017, Dr. Gaiceanu has been a Ph.D. supervisor for students in Electrical Engineering. He has been employed at Dunarea de Jos University of Galati since 1996, where he is currently a professor. Dr. Gaiceanu is a member of the National Council for Attesting Titles, Diplomas and Certificates, an expert of the Executive Agency for Higher Education, Research Funding, and a member of the Senate of the Dunarea de Jos University of Galati. He has been the head of the Integrated Energy Conversion Systems and Advanced Control of Complex Processes Research Center, Romania, since 2016. He has conducted several projects in power converter systems for electrical drives, power quality, PEM and SOFC fuel cell power converters for utilities, electric vehicles, and marine applications with the Department of Regulation and Control, SIEI S.pA. (2002–2004) and the Polytechnic University of Turin, Italy (2002–2004, 2006–2007). He is a member of the Institute of Electrical and Electronics Engineers (IEEE) and cofounder-member of the IEEE Power Electronics Romanian Chapter. He is a guest editor at Energies and an academic book editor for IntechOpen. He is also a member of the editorial boards of the Journal of Electrical Engineering, Electronics, Control and Computer Science and Sustainability. Dr. Gaiceanu has been General Chairman of the IEEE International Symposium on Electrical and Electronics Engineering in the last six editions.",institutionString:'"Dunarea de Jos" University of Galati',institution:{name:'"Dunarea de Jos" University of Galati',country:{name:"Romania"}}},{id:"4519",title:"Prof.",name:"Jaydip",middleName:null,surname:"Sen",slug:"jaydip-sen",fullName:"Jaydip Sen",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/4519/images/system/4519.jpeg",biography:"Jaydip Sen is associated with Praxis Business School, Kolkata, India, as a professor in the Department of Data Science. His research areas include security and privacy issues in computing and communication, intrusion detection systems, machine learning, deep learning, and artificial intelligence in the financial domain. He has more than 200 publications in reputed international journals, refereed conference proceedings, and 20 book chapters in books published by internationally renowned publishing houses, such as Springer, CRC press, IGI Global, etc. Currently, he is serving on the editorial board of the prestigious journal Frontiers in Communications and Networks and in the technical program committees of a number of high-ranked international conferences organized by the IEEE, USA, and the ACM, USA. He has been listed among the top 2% of scientists in the world for the last three consecutive years, 2019 to 2021 as per studies conducted by the Stanford University, USA.",institutionString:"Praxis Business School",institution:null},{id:"320071",title:"Dr.",name:"Sidra",middleName:null,surname:"Mehtab",slug:"sidra-mehtab",fullName:"Sidra Mehtab",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y00002v6KHoQAM/Profile_Picture_1584512086360",biography:"Sidra Mehtab has completed her BS with honors in Physics from Calcutta University, India in 2018. She has done MS in Data Science and Analytics from Maulana Abul Kalam Azad University of Technology (MAKAUT), Kolkata, India in 2020. Her research areas include Econometrics, Time Series Analysis, Machine Learning, Deep Learning, Artificial Intelligence, and Computer and Network Security with a particular focus on Cyber Security Analytics. Ms. Mehtab has published seven papers in international conferences and one of her papers has been accepted for publication in a reputable international journal. She has won the best paper awards in two prestigious international conferences – BAICONF 2019, and ICADCML 2021, organized in the Indian Institute of Management, Bangalore, India in December 2019, and SOA University, Bhubaneswar, India in January 2021. Besides, Ms. Mehtab has also published two book chapters in two books. Seven of her book chapters will be published in a volume shortly in 2021 by Cambridge Scholars’ Press, UK. Currently, she is working as the joint editor of two edited volumes on Time Series Analysis and Forecasting to be published in the first half of 2021 by an international house. Currently, she is working as a Data Scientist with an MNC in Delhi, India.",institutionString:"NSHM College of Management and Technology",institution:null},{id:"226240",title:"Dr.",name:"Andri Irfan",middleName:null,surname:"Rifai",slug:"andri-irfan-rifai",fullName:"Andri Irfan Rifai",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/226240/images/7412_n.jpg",biography:"Andri IRFAN is a Senior Lecturer of Civil Engineering and Planning. He completed the PhD at the Universitas Indonesia & Universidade do Minho with Sandwich Program Scholarship from the Directorate General of Higher Education and LPDP scholarship. He has been teaching for more than 19 years and much active to applied his knowledge in the project construction in Indonesia. His research interest ranges from pavement management system to advanced data mining techniques for transportation engineering. He has published more than 50 papers in journals and 2 books.",institutionString:null,institution:{name:"Universitas Internasional Batam",country:{name:"Indonesia"}}},{id:"314576",title:"Dr.",name:"Ibai",middleName:null,surname:"Laña",slug:"ibai-lana",fullName:"Ibai Laña",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/314576/images/system/314576.jpg",biography:"Dr. Ibai Laña works at TECNALIA as a data analyst. He received his Ph.D. in Artificial Intelligence from the University of the Basque Country (UPV/EHU), Spain, in 2018. He is currently a senior researcher at TECNALIA. His research interests fall within the intersection of intelligent transportation systems, machine learning, traffic data analysis, and data science. He has dealt with urban traffic forecasting problems, applying machine learning models and evolutionary algorithms. He has experience in origin-destination matrix estimation or point of interest and trajectory detection. Working with large volumes of data has given him a good command of big data processing tools and NoSQL databases. He has also been a visiting scholar at the Knowledge Engineering and Discovery Research Institute, Auckland University of Technology.",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"314575",title:"Dr.",name:"Jesus",middleName:null,surname:"L. Lobo",slug:"jesus-l.-lobo",fullName:"Jesus L. Lobo",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/314575/images/system/314575.png",biography:"Dr. Jesús López is currently based in Bilbao (Spain) working at TECNALIA as Artificial Intelligence Research Scientist. In most cases, a project idea or a new research line needs to be investigated to see if it is good enough to take into production or to focus on it. That is exactly what he does, diving into Machine Learning algorithms and technologies to help TECNALIA to decide whether something is great in theory or will actually impact on the product or processes of its projects. So, he is expert at framing experiments, developing hypotheses, and proving whether they’re true or not, in order to investigate fundamental problems with a longer time horizon. He is also able to design and develop PoCs and system prototypes in simulation. He has participated in several national and internacional R&D projects.\n\nAs another relevant part of his everyday research work, he usually publishes his findings in reputed scientific refereed journals and international conferences, occasionally acting as reviewer and Programme Commitee member. Concretely, since 2018 he has published 9 JCR (8 Q1) journal papers, 9 conference papers (e.g. ECML PKDD 2021), and he has co-edited a book. He is also active in popular science writing data science stories for reputed blogs (KDNuggets, TowardsDataScience, Naukas). Besides, he has recently embarked on mentoring programmes as mentor, and has also worked as data science trainer.",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"103779",title:"Prof.",name:"Yalcin",middleName:null,surname:"Isler",slug:"yalcin-isler",fullName:"Yalcin Isler",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRyQ8QAK/Profile_Picture_1628834958734",biography:"Yalcin Isler (1971 - Burdur / Turkey) received the B.Sc. degree in the Department of Electrical and Electronics Engineering from Anadolu University, Eskisehir, Turkey, in 1993, the M.Sc. degree from the Department of Electronics and Communication Engineering, Suleyman Demirel University, Isparta, Turkey, in 1996, the Ph.D. degree from the Department of Electrical and Electronics Engineering, Dokuz Eylul University, Izmir, Turkey, in 2009, and the Competence of Associate Professorship from the Turkish Interuniversity Council in 2019.\n\nHe was Lecturer at Burdur Vocational School in Suleyman Demirel University (1993-2000, Burdur / Turkey), Software Engineer (2000-2002, Izmir / Turkey), Research Assistant in Bulent Ecevit University (2002-2003, Zonguldak / Turkey), Research Assistant in Dokuz Eylul University (2003-2010, Izmir / Turkey), Assistant Professor at the Department of Electrical and Electronics Engineering in Bulent Ecevit University (2010-2012, Zonguldak / Turkey), Assistant Professor at the Department of Biomedical Engineering in Izmir Katip Celebi University (2012-2019, Izmir / Turkey). He is an Associate Professor at the Department of Biomedical Engineering at Izmir Katip Celebi University, Izmir / Turkey, since 2019. In addition to academics, he has also founded Islerya Medical and Information Technologies Company, Izmir / Turkey, since 2017.\n\nHis main research interests cover biomedical signal processing, pattern recognition, medical device design, programming, and embedded systems. He has many scientific papers and participated in several projects in these study fields. He was an IEEE Student Member (2009-2011) and IEEE Member (2011-2014) and has been IEEE Senior Member since 2014.",institutionString:null,institution:{name:"Izmir Kâtip Çelebi University",country:{name:"Turkey"}}},{id:"339677",title:"Dr.",name:"Mrinmoy",middleName:null,surname:"Roy",slug:"mrinmoy-roy",fullName:"Mrinmoy Roy",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/339677/images/16768_n.jpg",biography:"An accomplished Sales & Marketing professional with 12 years of cross-functional experience in well-known organisations such as CIPLA, LUPIN, GLENMARK, ASTRAZENECA across different segment of Sales & Marketing, International Business, Institutional Business, Product Management, Strategic Marketing of HIV, Oncology, Derma, Respiratory, Anti-Diabetic, Nutraceutical & Stomatological Product Portfolio and Generic as well as Chronic Critical Care Portfolio. A First Class MBA in International Business & Strategic Marketing, B.Pharm, D.Pharm, Google Certified Digital Marketing Professional. Qualified PhD Candidate in Operations and Management with special focus on Artificial Intelligence and Machine Learning adoption, analysis and use in Healthcare, Hospital & Pharma Domain. Seasoned with diverse therapy area of Pharmaceutical Sales & Marketing ranging from generating revenue through generating prescriptions, launching new products, and making them big brands with continuous strategy execution at the Physician and Patients level. Moved from Sales to Marketing and Business Development for 3.5 years in South East Asian Market operating from Manila, Philippines. Came back to India and handled and developed Brands such as Gluconorm, Lupisulin, Supracal, Absolut Woman, Hemozink, Fabiflu (For COVID 19), and many more. In my previous assignment I used to develop and execute strategies on Sales & Marketing, Commercialization & Business Development for Institution and Corporate Hospital Business portfolio of Oncology Therapy Area for AstraZeneca Pharma India Ltd. Being a Research Scholar and Student of ‘Operations Research & Management: Artificial Intelligence’ I published several pioneer research papers and book chapters on the same in Internationally reputed journals and Books indexed in Scopus, Springer and Ei Compendex, Google Scholar etc. Currently, I am launching PGDM Pharmaceutical Management Program in IIHMR Bangalore and spearheading the course curriculum and structure of the same. I am interested in Collaboration for Healthcare Innovation, Pharma AI Innovation, Future trend in Marketing and Management with incubation on Healthcare, Healthcare IT startups, AI-ML Modelling and Healthcare Algorithm based training module development. I am also an affiliated member of the Institute of Management Consultant of India, looking forward to Healthcare, Healthcare IT and Innovation, Pharma and Hospital Management Consulting works.",institutionString:null,institution:{name:"Lovely Professional University",country:{name:"India"}}},{id:"1063",title:"Prof.",name:"Constantin",middleName:null,surname:"Volosencu",slug:"constantin-volosencu",fullName:"Constantin Volosencu",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/1063/images/system/1063.png",biography:"Prof. Dr. Constantin Voloşencu graduated as an engineer from\nPolitehnica University of Timișoara, Romania, where he also\nobtained a doctorate degree. He is currently a full professor in\nthe Department of Automation and Applied Informatics at the\nsame university. Dr. Voloşencu is the author of ten books, seven\nbook chapters, and more than 160 papers published in journals\nand conference proceedings. He has also edited twelve books and\nhas twenty-seven patents to his name. He is a manager of research grants, editor in\nchief and member of international journal editorial boards, a former plenary speaker, a member of scientific committees, and chair at international conferences. His\nresearch is in the fields of control systems, control of electric drives, fuzzy control\nsystems, neural network applications, fault detection and diagnosis, sensor network\napplications, monitoring of distributed parameter systems, and power ultrasound\napplications. He has developed automation equipment for machine tools, spooling\nmachines, high-power ultrasound processes, and more.",institutionString:"Polytechnic University of Timişoara",institution:{name:"Polytechnic University of Timişoara",country:{name:"Romania"}}},{id:"221364",title:"Dr.",name:"Eneko",middleName:null,surname:"Osaba",slug:"eneko-osaba",fullName:"Eneko Osaba",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/221364/images/system/221364.jpg",biography:"Dr. Eneko Osaba works at TECNALIA as a senior researcher. He obtained his Ph.D. in Artificial Intelligence in 2015. He has participated in more than twenty-five local and European research projects, and in the publication of more than 130 papers. He has performed several stays at universities in the United Kingdom, Italy, and Malta. Dr. Osaba has served as a program committee member in more than forty international conferences and participated in organizing activities in more than ten international conferences. He is a member of the editorial board of the International Journal of Artificial Intelligence, Data in Brief, and Journal of Advanced Transportation. He is also a guest editor for the Journal of Computational Science, Neurocomputing, Swarm, and Evolutionary Computation and IEEE ITS Magazine.",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"275829",title:"Dr.",name:"Esther",middleName:null,surname:"Villar-Rodriguez",slug:"esther-villar-rodriguez",fullName:"Esther Villar-Rodriguez",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/275829/images/system/275829.jpg",biography:"Dr. Esther Villar obtained a Ph.D. in Information and Communication Technologies from the University of Alcalá, Spain, in 2015. She obtained a degree in Computer Science from the University of Deusto, Spain, in 2010, and an MSc in Computer Languages and Systems from the National University of Distance Education, Spain, in 2012. Her areas of interest and knowledge include natural language processing (NLP), detection of impersonation in social networks, semantic web, and machine learning. Dr. Esther Villar made several contributions at conferences and publishing in various journals in those fields. Currently, she is working within the OPTIMA (Optimization Modeling & Analytics) business of TECNALIA’s ICT Division as a data scientist in projects related to the prediction and optimization of management and industrial processes (resource planning, energy efficiency, etc).",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"49813",title:"Dr.",name:"Javier",middleName:null,surname:"Del Ser",slug:"javier-del-ser",fullName:"Javier Del Ser",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/49813/images/system/49813.png",biography:"Prof. Dr. Javier Del Ser received his first PhD in Telecommunication Engineering (Cum Laude) from the University of Navarra, Spain, in 2006, and a second PhD in Computational Intelligence (Summa Cum Laude) from the University of Alcala, Spain, in 2013. He is currently a principal researcher in data analytics and optimisation at TECNALIA (Spain), a visiting fellow at the Basque Center for Applied Mathematics (BCAM) and a part-time lecturer at the University of the Basque Country (UPV/EHU). His research interests gravitate on the use of descriptive, prescriptive and predictive algorithms for data mining and optimization in a diverse range of application fields such as Energy, Transport, Telecommunications, Health and Industry, among others. In these fields he has published more than 240 articles, co-supervised 8 Ph.D. theses, edited 6 books, coauthored 7 patents and participated/led more than 40 research projects. He is a Senior Member of the IEEE, and a recipient of the Biscay Talent prize for his academic career.",institutionString:"Tecnalia Research & Innovation",institution:null},{id:"278948",title:"Dr.",name:"Carlos Pedro",middleName:null,surname:"Gonçalves",slug:"carlos-pedro-goncalves",fullName:"Carlos Pedro Gonçalves",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRcmyQAC/Profile_Picture_1564224512145",biography:'Carlos Pedro Gonçalves (PhD) is an Associate Professor at Lusophone University of Humanities and Technologies and a researcher on Complexity Sciences, Quantum Technologies, Artificial Intelligence, Strategic Studies, Studies in Intelligence and Security, FinTech and Financial Risk Modeling. He is also a progammer with programming experience in:\n\nA) Quantum Computing using Qiskit Python module and IBM Quantum Experience Platform, with software developed on the simulation of Quantum Artificial Neural Networks and Quantum Cybersecurity;\n\nB) Artificial Intelligence and Machine learning programming in Python;\n\nC) Artificial Intelligence, Multiagent Systems Modeling and System Dynamics Modeling in Netlogo, with models developed in the areas of Chaos Theory, Econophysics, Artificial Intelligence, Classical and Quantum Complex Systems Science, with the Econophysics models having been cited worldwide and incorporated in PhD programs by different Universities.\n\nReceived an Arctic Code Vault Contributor status by GitHub, due to having developed open source software preserved in the \\"Arctic Code Vault\\" for future generations (https://archiveprogram.github.com/arctic-vault/), with the Strategy Analyzer A.I. module for decision making support (based on his PhD thesis, used in his Classes on Decision Making and in Strategic Intelligence Consulting Activities) and QNeural Python Quantum Neural Network simulator also preserved in the \\"Arctic Code Vault\\", for access to these software modules see: https://github.com/cpgoncalves. He is also a peer reviewer with outsanding review status from Elsevier journals, including Physica A, Neurocomputing and Engineering Applications of Artificial Intelligence. Science CV available at: https://www.cienciavitae.pt//pt/8E1C-A8B3-78C5 and ORCID: https://orcid.org/0000-0002-0298-3974',institutionString:"University of Lisbon",institution:{name:"Universidade Lusófona",country:{name:"Portugal"}}},{id:"241400",title:"Prof.",name:"Mohammed",middleName:null,surname:"Bsiss",slug:"mohammed-bsiss",fullName:"Mohammed Bsiss",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/241400/images/8062_n.jpg",biography:null,institutionString:null,institution:null},{id:"276128",title:"Dr.",name:"Hira",middleName:null,surname:"Fatima",slug:"hira-fatima",fullName:"Hira Fatima",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/276128/images/14420_n.jpg",biography:"Dr. Hira Fatima\nAssistant Professor\nDepartment of Mathematics\nInstitute of Applied Science\nMangalayatan University, Aligarh\nMobile: no : 8532041179\nhirafatima2014@gmal.com\n\nDr. Hira Fatima has received his Ph.D. degree in pure Mathematics from Aligarh Muslim University, Aligarh India. Currently working as an Assistant Professor in the Department of Mathematics, Institute of Applied Science, Mangalayatan University, Aligarh. She taught so many courses of Mathematics of UG and PG level. Her research Area of Expertise is Functional Analysis & Sequence Spaces. She has been working on Ideal Convergence of double sequence. She has published 17 research papers in National and International Journals including Cogent Mathematics, Filomat, Journal of Intelligent and Fuzzy Systems, Advances in Difference Equations, Journal of Mathematical Analysis, Journal of Mathematical & Computer Science etc. She has also reviewed few research papers for the and international journals. 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