Table of activities and their dependencies of studied process.
\r\n\tAn update on clinical manifestations, their assessment, monitoring, and imagiology, including peripheral arthritis, enthesopathy, and extra-articular findings, and, the differential diagnosis with other diseases which evolves with axial and peripheral calcifications will be provided.
\r\n\r\n\t
\r\n\tAn important component of this book must be dedicated to the more recent treatments namely with biologic therapies but focusing also on new small molecule inhibitors and experimental therapies.
There are currently a number of formally defined classes of
With the support of these operators, the PPNTS can be extended also to the areas of the project management and the determination of the project critical path with the support of the critical path method (CPM) [10]. The new CPPNET subclass of PPNTS class is then defined in this chapter to represent pure-formed time-dependent processes. It is specially designed for the generalization of the CPM activities charts and their properties. This fact is then demonstrated on the simple project example and its critical path and other properties specification.
This chapter is arranged into the following sections: Section 2 explains the base term of this chapter, that is, process Petri nets with time stamps and introduces the terms of proper-formed, well-formed and pure-formed PPNTS; Section 3 discusses algebraic operators
Let
If
We use the following subsets of the set (
Thus, the elements of the set
The given net
Some commonly used notations for the nets are •
(
The class of all the PNTS will be denoted by
The given PNTS
where ∀
variable
transition
if the transitions
finite nonempty sequence
(
∀
is called
finite nonempty sequence
of the state changes of PNTS
we say the state
the set of all the states
the set of all the markings
the set of all the static states
the set of all the static markings
the function ξ:
the set of all the entry states
the set of all the exit states
the set of all the exit states
The above established concepts are demonstrated in a simple example of the PNTS
Firing of transition
PNTS
Time marking
The transitions
∀
∀
When enabling individual transitions of the given PNTS so-called
The transitions
Firing of the transition
There is no enabled transition in the state
It can then be easily verified that
There are no enabled transitions in the exit state
The set
proper-formed
well-formed
Proper-formed
Well-formed
For instance, if the set
We study the issue of transforming PNTS through precisely defined binary operator
where
PNTS
Symbolic representation of PNTS [
Symbolic representation of PNTS [
If
where PNTS
Symbolic representation of PNTS [
Symbolic representation of PNTS [
If
Critical Path Method (CPM) is a method used in modeling and project management that was developed at the end of 1950s and that is commonly used for all the types of projects including software development [10]. The CPM is the most widely used method of so-called network analysis, even though it is designed to analyze the time consumption of only deterministic projects, that is, projects where the duration of each of their activities is exactly known, including all their sub-activities.
The basis for using CPM is to create a project model that includes:
the list of all activities needed to complete the project,
the time duration of each activity that is constant,
the dependencies between the project activities,
A critical path is then a designation for a sequence of activities whose time duration directly affects the time duration of the entire project. The activities that make up the critical path are then referred to as critical activities. There may be several critical paths in the project. When managing the project, a sequence of activities within a given network chart describing this project that increases the longest total time duration of a project is called its critical path. The critical path within the network chart can be used to determine the shortest time required to complete the project. The application of the CPM method can therefore determine which activities within the studied project are “critical” (i.e., activities on the longest path in the network chart describing the project) and which activities may be delayed in the execution of the project without increasing its total time.
The special class
Symbolic representation of the unary operator
Symbolic representation of PNTS
if
if
if
if
Four simple PNTSs
.
.
.
PNTSs
Note also that the PNTS
PNTS
It is also clear that after the firing of the transition
An example of a simple process is presented in the following paragraphs the characteristics of which will be studied with using of the PPNTS from the CPPNET class. The studied process is described in the following table of activities (see Table 1):
Activity | Duration | Previous activities |
---|---|---|
A | 2 | — |
B | 3 | — |
C | 4 | — |
D | 2 | C |
E | 6 | B, D |
F | 5 | A |
G | 5 | C |
H | 3 | E, F |
Table of activities and their dependencies of studied process.
The CPM chart of the abovementioned process comprising the activities listed in Table 1 is shown in Figure 7 where:
selected activity of the studied process and its duration is associated with each edge of the CPM chart,
each node of the CPM chart is associated with its serial number (indicated in the upper half of the node), the earliest possible activation time of the given node (shown in the lower left quarter of the node) and the possible latest activation time of the given node (shown in the lower right quarter circle of the node),
the desired links of the individual activities are expressed through the oriented edges and their associated nodes in the CPM chart,
the critical path of the CPM chart passes through its nodes where the earliest possible activation time is equal to the latest possible activation time, that is, through nodes 1, 2, 3, 5 and 6, and it is thus formed by A, D, E and H activities (these activities are represented by dashed line graphs in the CPM chart) with a total duration of 15 time units.
CPM chart of process activities listed in
The pure-formed PPNTS
PPNTS
.
Places
In order to find the critical path of the process represented by PPNTS
∀
∀
The PPNTS
PPNTS
It follows directly from the Definition 4 that the value of the critical path function
WHILE (
BEGIN
END;
The critical path of PPNTS
Further research in the field of PNTSs is mainly focused on the definition of additional unary, binary and
Another class currently being studied is the class of multiprocess Petri nets with time stamps that represents the generalization of the class of PNTS. The given multiprocess Petri net with time stamps then represents the finite set of processes each of which is modeled by a separate PNTS that share a common set of resources modeled by its individual resource places and their tokens. Many of the studied properties of the multiprocess Petri nets with time stamps are similar or identical to those of the PNTS class and they allow for a further generalization of the concept of a critical path formed by a sequence of activities of the process modeled by the given multiprocess Petri nets with time stamps.
This chapter was supported by the SGS at the Faculty of Economics, VŠB-TU Ostrava, under Grant Evaluation of comparative applications using cognitive analysis and method of data envelopment analysis, number SP2018/146.
The number of total shoulder arthroplasty (TSA) and reverse total shoulder arthroplasty (RTSA) procedures performed each year has continued to rise, and will continue to rise as the population ages and lives longer (Figure 1) [1, 2, 3]. While shoulder arthroplasty has historically been performed in the inpatient setting, over the several years, many surgeons have moved to performing TSA/RTSA in the outpatient setting. Performing shoulder arthroplasty in the outpatient setting decreases cost to the healthcare system as well as provides an excellent patient experience. Recent studies have shown excellent results with few complications in patients who have undergone outpatient TSA/RTSA [4, 5, 6, 7]. However, not every patient is a candidate for an outpatient shoulder arthroplasty.
Examples of advanced arthritis (Coronal X-ray and axial CT scan).
While a great many patients are candidates for TSA and RTSA, not every patient is a candidate for a shoulder arthroplasty in an outpatient setting. First, some patients may not be comfortable having surgery in an outpatient center and some insurance companies may not be accepted by the outpatient center. In these cases the surgery should be done in the hospital setting. It also helps if patients have a good home support system to help them with activities of daily living following surgery. While they will be able to do many things on their own, there will be some things that they will likely need help with. There are many services an outpatient center does not have that a hospital has, so patients at increased risk for complications, bleeding, breathing issues, etc. should not have their shoulder arthroplasty done in an outpatient center. The authors have developed criteria to determine whether patients are good candidates for shoulder arthroplasty in the outpatient setting.
From a medical perspective, patients who are American Society of Anesthesiology (ASA) 1 and 2 are often eligible. Occasionally patients who are ASA 3 are eligible, but this should be a case-by-case decision. Patients under 65 years of age are often better suited for an outpatient arthroplasty, although older, high functioning patients can be good candidates as well. Patients should be off chronic narcotics before having an outpatient shoulder arthroplasty and must be willing to participate in a multimodal pain management program. Furthermore, the patient should be a good candidate for a regional block for pain control. The following is a list of relative contraindications to patients having their TSA/RTSA in an outpatient setting. Any patients who have conditions on this list may require a proper medical/cardiology and anesthesia evaluation preoperatively.
Cardiac
Significant heart disease
Poor LVEF (<50%)
Ischemic heart disease, stents
CHF
Arrhythmia
Valve replacement
Chronic anticoagulation is a relative contraindication and the decision may be individualized based on circumstances of case
Obesity with BMI > 40
Diabetes with A1C > 8–9
Chronic Anemia with HG < 10
Substantial OSA
Renal insufficiency (creatinine > 1.6)
COPD or pulmonary hypertension
Chronic liver disease
Neurologic issues
CVA or significant neurologic illness
History of frequent falls
History of cognitive dysfunction (dementia, Parkinson’s)
There are several keys to a successful outpatient shoulder arthroplasty. Two of the most important issues surrounding outpatient shoulder arthroplasty are pain control and infection prevention. There are several pieces to pain control including preoperative, intraoperative and postoperative pain management. First, patients undergoing outpatient shoulder arthroplasty are premedicated in the preoperative area prior to surgery. Typically, the authors use 1000 mg of Acetaminophen, 300 mg of Neurontin, and 200 mg of Celecoxib all given orally. The patients are also given regional anesthesia, typically a supraclavicular or interscalene block. The medication used by the anesthesiologist for the block should include a long-acting local anesthetic such as Bupivacaine. Some facilities have moved to using an even longer acting anesthetic such as Bupivacaine liposome injectable suspension (trade name: Exparel), although this can sometimes be cost prohibitive. From an infection prevention perspective, patients are asked to wipe the operative site twice daily with benzoyl peroxide beginning 2 to 3 days prior to surgery and continuing this up until surgery. This helps decrease the C. Acnes load on the skin. Finally, from a timing perspective, it is important to schedule these patients early in the day so they have adequate time to recover before going home. Performing an outpatient arthroplasty later in the day can be tricky and runs the risk that the patient may need to stay overnight.
Once the patient has received their block and preoperative medications they are brought back to the operating room where they are given general anesthesia (Figure 2). A general anesthetic allows for muscle relaxation which facilitates exposure during a shoulder arthroplasty. To minimize the amount of time the patient is under anesthesia and to mitigate infection risk, it is important to perform the TSA/RTSA efficiently. As such, it is important for the surgeon to be comfortable with TSA and RTSA procedures before attempting these in the outpatient setting (Figure 3). Having major delays during the procedure keeps the patient under anesthesia for a longer time and may increase the likelihood that they will not go home after surgery. Furthermore, revision TSA/RTSA are not typically performed in the outpatient setting as these patients often have more pain, lose more blood, and have longer operative times than primary cases (Figure 4). As surgeons get comfortable with sending patients home the same day following TSA/RTSA, we recommend surgeons perform these cases in an inpatient setting to begin with and send the patients home the same day. Once they have successfully sent these patients home the same day they can progress to performing these cases in the outpatient setting.
After general anesthesia, the patient is positioned, draped, and secured in the modified beach chair position.
Instrument and back table organization help expedite the performance of outpatient procedures.
Prior to incision the patient should be given 1 g of IV Tranexamic acid (TXA). This acts as a clot stabilizing agent (it is not prothrombotic) and will help minimize blood loss during the procedure. Cvetanovich et al. performed a prospective, double-blind, placebo-controlled, randomized clinical trial where patients undergoing primary TSA and RTSA were randomized to either receiving 1 g of IV TXA or a placebo to determine if TXA reduced blood loss [8]. The authors included 108 patients (52 for TXA, 56 for placebo) who had no significant differences in preoperative characteristics. They found that the TXA group had significantly lower postoperative blood loss compared with the placebo group. They also found that TXA had lower weight of hemoglobin loss compared with placebo. Similar results were seen in the total knee and total hip arthroplasty literature [9, 10, 11, 12]. Similarly, Gillespie et al. randomized 111 patients who underwent shoulder arthroplasty to receive topical saline or topical saline mixed with 2 g of TXA into the wound at the conclusion of the case and measured postoperative drain output (patients at the time of this study all received a drain. This is not done anymore) [13]. The authors found significantly less blood loss in the TXA group compared to the placebo group (108 mL vs. 170 mL) as well as a greater drop in hemoglobin level in the placebo group compared to the TXA group (2.6 g/dL vs. 1.7 g/dL). As such, we routinely use TXA in all of our outpatient shoulder arthroplasty procedures.
Once the preoperative antibiotics (2 g Cefazolin) and Tranexamic acid have been administered, the TSA/RTSA is performed in the standard fashion. The patient is prepped with a hydrogen peroxide wash to decrease the load of C. Acnes on the skin prior to their chlorhexidine prep [14]. The authors use a deltopectoral approach (Figure 5). As previously mentioned, exposure is key in TSA and RTSA, so it is important to ensure each layer of dissection is complete to avoid shrinking the operative field. The authors perform a subscapularis peel on all TSA and RTSA (Figure 6). Adequate releases on both the humeral and glenoid side will help facilitate glenoid exposure so this is imperative to avoid issues with glenoid pin placement. Once the humeral head cut is made and the glenoid is adequately exposed, the authors use a patient specific guide to place the glenoid pin. A preoperative CT scan is obtained on all patients prior to TSA and RTSA and is unloaded into a preoperative planning software (Virtual Implant Positioning (VIP) Arthrex, Naples FL USA) (Figure 7). The ideal glenoid position can then be planned out, and a reusable guide is used to place the pin in the preoperatively planned position. Once the glenoid component is secured the final humeral implant is placed. The subscapularis is either repaired using a suture anchor repair technique in TSA (SpeedScap, Arthrex, Naples FL, USA) or in transosseous manner with high tensile sutures in RTSA. Based on evidence from the total knee and total hip arthroplasty literature, once the subscapularis has been repaired, it is important to allow the shoulder to soak in dilute betadine for 5 minutes to help decrease the risk of infection [15, 16]. Some surgeons do not allow betadine into operative field as they believe betadine can “burn” tissues. In the author’s opinion, this has not been an issue and the addition of betadine has helped mitigate infection risk. Once the dilute betadine has had time to sit it is irrigated out. Next, 1 g of Vancomycin powder is placed in the incision, part just over the subscapularis and part over the deltopectoral closure [17, 18, 19, 20, 21]. A running absorbable stitch is used to close the skin along with skin glue. A waterproof silver impregnated dressing is utilized to decrease infection risk [22]. During the case the anesthesia team should ensure adequate patient hydration to avoid postoperative dehydration.
Revision surgery is usually more complex and demanding. This can require an osteotomy of the humerus that can then be secured with metal or FiberTape cerclages.
An example of a deltopectoral incision used in outpatient procedures.
As part of the optimal visualization, the subscapularis is identified and released from the humerus via a peel technique.
Preoperative 3D modeling and visualization help execute the surgical plan. This can help minimize the number of trays that need to be available during the procedure. .
Following surgery patients are given a set or oral medication including 1000 mg of Acetaminophen, 300 mg of Neurontin, and 200 mg of Celecoxib. If patients are experiencing pain, medications including ketorolac, oxycodone, or tramadol can be utilized on an as needed basis. Ondansetron should be used to control postoperative nausea. A second dose of IV TXA can be given in the recovery room before discharge. A second dose of antibiotics (2 g Cefazolin) is not routinely used unless it has been more than 8 hours since the preoperative dose and the patient has not gone home. Patients are not sent home with any antibiotics. Patients are sent home with a multimodal pain regimen. Further work is needed to determine the ideal combination of medications, but some of the options to include are: Acetaminophen, Tramadol, Oxycodone, Gabapentin, Celecoxib, Aspirin and Pantoprazole.
The demand for shoulder arthroplasty is projected to exceed that of hip/knee arthroplasty [23]. For instance, it has been reported that a total of 39,072 patients were admitted for total shoulder arthroplasty in 2010, 5 times the number of patients in 1998 [24]. This increase is proportionally associated with the need for effective and feasible physical therapy, which is critical in the recovery pathway following shoulder replacements [25]. Traditionally, physical therapy following shoulder surgery has occurred via in-office supervised visits [26]. Home-based physical therapy reduces costs and decreases the need for travel [27]. Home-based therapy has been shown to be as effective as in-office therapy after total knee arthroplasty and has been utilized for rehabilitation after proximal humerus fracture [28, 29, 30]. It has also been reported to be a safe and effective alternative in the early phase following rotator cuff repair [31]. However, home-based therapy lacks the ability to monitor patient performance, compliance, and progress. Digital health has been incorporated in various medical fields over the past few decades. This process has accelerated since the COVID-19 pandemic which has brought to the forefront of medicine the need to deliver care and rehabilitation remotely. Remote patient monitoring has emerged as a concept in which patient physiologic parameters are measured and remotely delivered to a care team. Within our practice, remote patient monitoring is implemented via a secure cloud-based provider rehabilitation platform that communicates with a patient application powered by marker-less artificial intelligence (AI) technology with a dedicated built-in telemedicine capability (PT Genie; Orlando, FL) (Figure 8).
The patient-facing application (PT Genie) which tacks ROM using AI marker less technology.
At the initial visit patients are instructed on how to use the platform and are provided a QR code to scan and download the app onto their device (Android/iOS). PT Genie has instructions on the home-based exercise protocol, demonstrates the exercises to be performed and keeps track of progress including pain score, completed repetitions and number of sessions all via the AI driven sensor less motion tracking using the front facing camera of a cellphone or a tablet. Monitoring is performed on the web-based clinical dashboard by a dedicated care team, who also monitor the daily progress and communicate with the patients via in-app messages, telemedicine calls, and emails (Figure 9). PT Genie allows the provider to fully customize and control the rehabilitation protocol by adding or modifying exercises to go along with the patient’s pace of recovery, the addition of bands and calculation of force on certain exercises, and the ability to set up a pre habilitation phase, if needed prior to surgery.
A secure telemedicine platform (PT Genie) enables the provider and the patient to communicate and interact remotely.
Several studies have shown the efficacy of outpatient TSA and RTSA compared to inpatient shoulder arthroplasty. Cimino et al. performed a systematic review of 12 studies (194,513 patients, of whom 7162 were outpatients) to evaluate the outcomes following outpatient TSA and RTSA [32]. The average age of the outpatients was 66.6 years while the average age of the inpatients was 70.1 years. The authors found the odds ratio for complications was significantly lower in outpatients than in inpatients. Furthermore, there was no significant difference in rates of 90-day readmission, revision, and infection rate between outpatients with inpatients. Similarly, Fournier et al. reported the results of 61 patients who underwent outpatient TSA and RTSA [6]. There were no cardiopulmonary events that required intervention or hospital admission. These studies evaluated both TSA and RTSA together. This happens commonly because the CPT code for TSA and RTSA is the same (23472). Below are examples of studies that separated outcome based on TSA and RTSA.
i. TSA
Erickson et al. reported the results of 94 patients (average age 60.4, 67.0% male) who underwent TSA 2015–2017 by the senior author. The authors matched this group of patients to a group of 77 patients who underwent TSA as an inpatient. Patients who underwent outpatient TSA saw significant improvement in all clinical outcome scores at both 1 and 2 year postoperatively (Figure 10). There were baseline differences between groups such that patients who underwent inpatient TSA were more likely to be diabetic than those who underwent outpatient TSA. The authors found no significant differences in improvements in clinical outcome scores between inpatients vs. outpatient groups. They noted that complications were more frequent in patients who underwent inpatient TSA (11.4% vs. 2.1%), although this did difference did not reach statistical significance (p = 0.080). Brolin et al. evaluated 30 patients who underwent outpatient TSA at a freestanding ambulatory surgery center and compared them with an age- and comorbidities-matched cohort of 30 patients who underwent inpatient TSA [5]. The authors evaluated 90-day complications, hospital admissions/readmissions and reoperations. There were significant differences between outpatient and inpatient cohorts regarding preoperative demographics. The authors reported no hospital admissions from the outpatient cohort and no readmissions from the inpatient cohort. There was no difference in the complication rates between outpatient (13%) and inpatient (10%) shoulder arthroplasty.
A 2-years follow-up X-ray for an outpatient total shoulder arthroplasty (TSA).
ii. RTSA.
Erickson et al. reported the results on 241 patients (average age 68.9, 52.3% female) who underwent outpatient RTSA between 2015 and 2017 by the senior author (Figure 11). The authors matched this group of patients to a group of 373 patients who underwent RTSA as an inpatient. There were baseline differences between the two groups such that significantly more inpatient RTSA had diabetes (p = 0.007) and had a significantly higher body mass index (p = 0.022). The authors found that patients who underwent outpatient RTSA had significant improvement in all clinical outcome scores at both 1 and 2 year postoperatively (all p < 0.0001). There were no significant differences in improvements in clinical outcome scores between inpatient vs. outpatient RTSA groups. Most importantly, complication rates were significantly lower for patients who underwent RSTA as an outpatient compared to those who underwent RTSA as an inpatient (7.0% vs. 12.7% p = 0.023).
A 2-years follow-up X-ray for an outpatient reverse total shoulder arthroplasty (RTSA).
Many patients are candidates for outpatient TSA and RTSA. Some patients may be better suited to have their surgery performed in the hospital setting while other are excellent candidates for an outpatient surgical center. A thorough preoperative evaluation is critical for proper patient selection and a set protocol is necessary for the day of surgery to ensure proper pain control and to minimize risk of complications and readmissions. When performed properly, patients should expect the same outcomes as those who undergo TSA and RTSA in the inpatient setting with potentially lower complication rates.
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Delac received his B.Sc.E.E. degree in 2003 and is currentlypursuing a Ph.D. degree at the University of Zagreb, Faculty of Electrical Engineering andComputing. His current research interests are digital image analysis, pattern recognition andbiometrics.",institutionString:null,institution:{name:"University of Zagreb",country:{name:"Croatia"}}},{id:"557",title:"Dr.",name:"Andon",middleName:"Venelinov",surname:"Topalov",slug:"andon-topalov",fullName:"Andon Topalov",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/557/images/1927_n.jpg",biography:"Dr. Andon V. Topalov received the MSc degree in Control Engineering from the Faculty of Information Systems, Technologies, and Automation at Moscow State University of Civil Engineering (MGGU) in 1979. He then received his PhD degree in Control Engineering from the Department of Automation and Remote Control at Moscow State Mining University (MGSU), Moscow, in 1984. From 1985 to 1986, he was a Research Fellow in the Research Institute for Electronic Equipment, ZZU AD, Plovdiv, Bulgaria. In 1986, he joined the Department of Control Systems, Technical University of Sofia at the Plovdiv campus, where he is presently a Full Professor. He has held long-term visiting Professor/Scholar positions at various institutions in South Korea, Turkey, Mexico, Greece, Belgium, UK, and Germany. And he has coauthored one book and authored or coauthored more than 80 research papers in conference proceedings and journals. 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From\r\n1964 to 1974, he worked as Assistant in Biochemistry at the School of MedicineUniversidad Nacional de La Plata, Argentina. From 1974 to 1976, he was a Fellowof the National Institutes of Health (NIH) at the University of Connecticut, Health Center, USA. From 1985 to 2004, he served as a Full Professor oBiochemistry at the Universidad Nacional de La Plata, Argentina. He is Member ofthe National Research Council (CONICET), Argentina, and Argentine Society foBiochemistry and Molecular Biology (SAIB). His laboratory has been interested for manyears in the lipid peroxidation of biological membranes from various tissues and different species. Professor Catalá has directed twelve doctoral theses, publishedover 100 papers in peer reviewed journals, several chapters in books andtwelve edited books. Angel Catalá received awards at the 40th InternationaConference Biochemistry of Lipids 1999: Dijon (France). 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He\nreceived a short-term scholarship to carry out his post-doctoral\nstudies abroad, from Japan International Cooperation Agency\n(JICA), in coordination with the Egyptian government. Dr.\nShalaby speaks fluent English and his native Arabic. He has 77\ninternationally published research papers, has attended 15 international conferences, and has contributed to 18 international books and chapters.\nDr. Shalaby works as a reviewer on over one hundred international journals and is\non the editorial board of more than twenty-five international journals. 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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:"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. She is a member of Indian Mathematical Society.",institutionString:null,institution:null},{id:"302698",title:"Dr.",name:"Yao",middleName:null,surname:"Shan",slug:"yao-shan",fullName:"Yao Shan",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Dalian University of Technology",country:{name:"China"}}},{id:"125911",title:"Prof.",name:"Jia-Ching",middleName:null,surname:"Wang",slug:"jia-ching-wang",fullName:"Jia-Ching Wang",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"National Central University",country:{name:"Taiwan"}}},{id:"357085",title:"Mr.",name:"P. Mohan",middleName:null,surname:"Anand",slug:"p.-mohan-anand",fullName:"P. Mohan Anand",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Indian Institute of Technology Kanpur",country:{name:"India"}}},{id:"356696",title:"Ph.D. Student",name:"P.V.",middleName:null,surname:"Sai Charan",slug:"p.v.-sai-charan",fullName:"P.V. Sai Charan",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Indian Institute of Technology Kanpur",country:{name:"India"}}},{id:"357086",title:"Prof.",name:"Sandeep K.",middleName:null,surname:"Shukla",slug:"sandeep-k.-shukla",fullName:"Sandeep K. Shukla",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Indian Institute of Technology Kanpur",country:{name:"India"}}},{id:"356823",title:"MSc.",name:"Seonghee",middleName:null,surname:"Min",slug:"seonghee-min",fullName:"Seonghee Min",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Daegu University",country:{name:"Korea, South"}}},{id:"353307",title:"Prof.",name:"Yoosoo",middleName:null,surname:"Oh",slug:"yoosoo-oh",fullName:"Yoosoo Oh",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:"Yoosoo Oh received his Bachelor's degree in the Department of Electronics and Engineering from Kyungpook National University in 2002. He obtained his Master’s degree in the Department of Information and Communications from Gwangju Institute of Science and Technology (GIST) in 2003. In 2010, he received his Ph.D. degree in the School of Information and Mechatronics from GIST. In the meantime, he was an executed team leader at Culture Technology Institute, GIST, 2010-2012. In 2011, he worked at Lancaster University, the UK as a visiting scholar. In September 2012, he joined Daegu University, where he is currently an associate professor in the School of ICT Conver, Daegu University. Also, he served as the Board of Directors of KSIIS since 2019, and HCI Korea since 2016. From 2017~2019, he worked as a center director of the Mixed Reality Convergence Research Center at Daegu University. From 2015-2017, He worked as a director in the Enterprise Supporting Office of LINC Project Group, Daegu University. His research interests include Activity Fusion & Reasoning, Machine Learning, Context-aware Middleware, Human-Computer Interaction, etc.",institutionString:null,institution:{name:"Daegu Gyeongbuk Institute of Science and Technology",country:{name:"Korea, South"}}},{id:"262719",title:"Dr.",name:"Esma",middleName:null,surname:"Ergüner Özkoç",slug:"esma-erguner-ozkoc",fullName:"Esma Ergüner Özkoç",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Başkent University",country:{name:"Turkey"}}},{id:"419199",title:"Dr.",name:"Qun",middleName:null,surname:"Yang",slug:"qun-yang",fullName:"Qun Yang",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"University of Auckland",country:{name:"New Zealand"}}},{id:"351158",title:"Prof.",name:"David W.",middleName:null,surname:"Anderson",slug:"david-w.-anderson",fullName:"David W. Anderson",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"University of Calgary",country:{name:"Canada"}}},{id:"351159",title:"BSc.",name:"Kalum J.",middleName:null,surname:"Ost",slug:"kalum-j.-ost",fullName:"Kalum J. Ost",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"University of Calgary",country:{name:"Canada"}}},{id:"325029",title:"Dr.",name:"Prem Chand",middleName:null,surname:"Jain",slug:"prem-chand-jain",fullName:"Prem Chand Jain",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Shiv Nadar University",country:{name:"India"}}},{id:"357275",title:"Dr.",name:"Thomas",middleName:null,surname:"Mih",slug:"thomas-mih",fullName:"Thomas Mih",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionS