\r\n\tHydroxyapatite (HA) is an important member of the calcium phosphate chemical family. It has been used in several medical applications for the past decades, due to its chemical similarity to the mineral phase of bone and high biocompatibility. Several studies demonstrated that bone mineral presents several ion substitutions, so in order to prepare a synthetic material with an even closer composition to bone mineral, HA has been prepared with the incorporation of several ions like, silicon or fluoride. These ions induced not only structural changes on HA lattice, but also on its biocompatibility. \r\n\tSignificant advances in nanotechnologies resulted in the preparation of HA in different forms, with a wider range of applications, from support to drug and gene delivery. \r\n\tThis book aims to collect the most relevant information regarding HA properties, modifications and its application in the biomedical field.
",isbn:null,printIsbn:"979-953-307-X-X",pdfIsbn:null,doi:null,price:0,priceEur:0,priceUsd:0,slug:null,numberOfPages:0,isOpenForSubmission:!1,hash:"6a3c2d529bd0b7fb6d259f00b4562d77",bookSignature:"Dr. Claudia Manuela da Cunha Ferreira Botelho",publishedDate:null,coverURL:"https://cdn.intechopen.com/books/images_new/8199.jpg",keywords:"Apatite, Chemical and Physical Structure, Hydrothermal Synthesis, Synthesis from Biogenic Sources, Mineralization, Bone Structure, Vascularization, Resorption, Silicon, Improved Bioactivity,Bone Substitute, Drug and Gene Carrier",numberOfDownloads:null,numberOfWosCitations:0,numberOfCrossrefCitations:0,numberOfDimensionsCitations:null,numberOfTotalCitations:null,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"October 4th 2019",dateEndSecondStepPublish:"February 17th 2020",dateEndThirdStepPublish:"April 17th 2020",dateEndFourthStepPublish:"July 6th 2020",dateEndFifthStepPublish:"September 4th 2020",remainingDaysToSecondStep:"a year",secondStepPassed:!0,currentStepOfPublishingProcess:5,editedByType:null,kuFlag:!1,biosketch:null,coeditorOneBiosketch:null,coeditorTwoBiosketch:null,coeditorThreeBiosketch:null,coeditorFourBiosketch:null,coeditorFiveBiosketch:null,editors:[{id:"258963",title:"Dr.",name:"Claudia Manuela",middleName:null,surname:"Da Cunha Ferreira Botelho",slug:"claudia-manuela-da-cunha-ferreira-botelho",fullName:"Claudia Manuela Da Cunha Ferreira Botelho",profilePictureURL:"https://mts.intechopen.com/storage/users/258963/images/system/258963.jpg",biography:"Claudia Botelho obtained a PhD in Science Engineering from Porto University, Portugal, in 2005. 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1. Introduction
Milk is an important food commodity in the world as it provides calcium, phosphorous, magnesium, and protein which are all essential for human health. Adequate consumption of milk from early childhood and throughout life strengthens bones and protects against diseases. Consuming dairy product, especially milk, can increase children bone health and development, develop a positive brain concentrations of glutathione (GSH), and increase the body’s resistance against many infectious diseases and diseases caused by malnutrition and reduce cancer risk [1, 2, 3, 4]. Milk can directly be consumed or manufactured into other dairy products such as cheese, ice cream, butter, ghee, cream, yogurt, etc. Milk provides the following beneficial nutrients in varying quantities [5, 6, 7, 8]:
Calcium—for healthy bones and teeth
Phosphorous—for energy release
Magnesium—for muscle function
Protein—for growth and repair
Vitamin B12—for production of healthy cells
Vitamin A—for good eyesight and immune function
Zinc—for immune function
Riboflavin—for healthy skin
Folate—for production of healthy cells
Vitamin C—for the formation of healthy connective tissues
Iodine—for regulation of the body’s rate of metabolism (how quickly the body burns energy and the rate of growth
As community realizes the importance of milk product in their life, it boosted the demand for milk production. As consequence, the number of dairy cattle farmers and productivity should be increased. The government needs an approach to increase fresh milk production. One of the methods to increase the milk productivity is maintaining cow facilities and developing them to be more comfortable for the cattle (cage, free stall, floor, etc.). Several researchers investigated the dairy cattle comfort including cow house and respective facilities. Cook et al. reported that physical accommodation of dairy cattle should provide a relatively dry area for the dairy cattle to lie down and be comfortable [9]. Dairy cow overcrowds could reduce rest time, increase idle standing in alleys, alter feeding behavior, and, in general, reduce cow comfort [10]. A study conducted on 47 farms in Northeastern Spain explained the significant effect of a stall on the productivity of dairy cow and impact on milk production and cow health [11]. The cow facilities should be constructed to minimize time to reach food and water. Free stall facility is usually selected to minimize the effect of weather changes and improve cleanliness and cow comfort. Dairy facilities should be designed to keep the cows and calves comfortable in order to maintain dry matter intake (DMI) and thus maximize economic production. Other studies have reported similar results. Based on Jim Reynolds research, the cattle comfort can be identified into five factors for heat stress, sanitation, free stall design, walking surface, and walking distance [12]. In short, dairy cattle facilities are an important factor of key success in milk business, and it should be designed to keep the cow and calves comfortable in order to maintain milk quality and thus maximize economic production.
In order to provide a solution to comfort design for dairy cow facilities, the physical ergonomics knowledge is needed. The important knowledge of physical ergonomics area for a human body is defined as anthropometry. It studies the variation of the human body dimensions in static and dynamics condition [13]. Using the same analogy, this study converts the concept of anthropometry into the concept of zoometry to study the impact of variation of animal body dimensions. This analogy imagines that animal (cow) requires comfort in order to gain optimal milk production, similar to human. A human requires comfort at work in order to reach high productivity. Zoometry is derived from Greek ζώο (zó̱o) which means animal and μέτρον (metrí̱ste) that means a measurement. Zoometry concept is defined as static and dynamics animal measurement dimension in order to determine the physical variation of the specific animal population. This research utilized dairy cattle zoometry concept to design cattle facility (house, free stall, floor, etc.) in order to increase the dairy cattle comfort and milk production. This study considers static and dynamic measurement because it constitutes cattle main activity. There are three main activities that are affected by the static and dynamic condition such as feeding, lying, and standing or transition events between lying and standing. Zoometry concept can deter cattle from annoyances or uncomfortable facility. The research promotes pioneer strategy to improve the cow comfort using zoometry concept.
Directly and manually measuring dairy cattle dimensions based on zoometry concept is time-consuming and costly. Analysis data of dairy cattle dimensions can be employed to eliminate the problems. Unfortunately, relationship complexity of each dimension on dairy cattle is hard to describe in mathematics formula or in the regression model. Artificial intelligence back propagation neural network (BPNN) I was used in determining the best solution. It can eliminate some cost and improve efficiency. The BPNN model can be utilized to predict pattern making-related body dimensions by inputting few key dairy cattle body dimensions.
2. Zoometry concept
2.1. Anthropometry
The first step to understand the zoometry concept is knowing the anthropometry concept. Cattle zoometry concept is adapting the principles of anthropometry rules for human dimensions. Anthropometry is human body measurement method in a population and analyzes that measurement for various purposes. This measurement could be utilized in architecture, product design, clothing design, child nutrients, design workplace, etc. The ISO 7250-1: 2008 intended to explain as a guide for an engineer who is required to determine the size of human physic for their job [14]. The knowledge on human body, technical measurement, and statistic are very important to obtain a higher quality of anthropometry implementation. Anthropometry will improve work facilities capable to facilitate a person in working physically through ease of reach and access and through the process of cognition of a job [15, 16].
The anthropometry will set up an economical design work facility which means from a marketing point of view, these facilities could be built cheaply. On the other hand, although the design is made with cheaply but can support the performance of human according to the technical needs. Some considerations that can be utilized in anthropometry include data utilized to indicate the characteristics of the target population with limitations contained in the field conditions. The criteria utilized for the design are appropriate for user facilities. The data collected are expected to represent broad conditions that can be utilized for a wider population [17]. The posture utilized by every individual work will be influenced by the body and tool dimension as well as facilities used. The level of relationship between work facility and posture is influenced by the characteristics and frequency of interaction between the two. Generally, anthropometry is divided in into two branches: static anthropometry and dynamic anthropometry [18, 19]. The static anthropometry deals with the measurement process when the human body is in a stable position or in a static condition. On the other hand, dynamic anthropometry deals with measurement process that relates to the measurement of range of human body movement, for example, of arm movement, walking position, and head movement to reach an object.
2.2. Cattle psychology and physiology
Similar to humans, cows are also able to perform a process of cognitive response to the symptoms of the surrounding environment. Cows perform various activities inside an environment which is described in Table 1 [20].
No
Activities
Daily allocation (hour)
1
Eating
2–5
2
Lying
12–14
3
Interaction
2–3
4
Ruminating
7–10
5
Drinking
0.5
6
Outside pen
2.5–3.5
Table 1.
Cow activity.
Dairy cattle cognitive process is exhibited in performing activities by responding to surrounding environment, which is described as follows [21]:
ability to distinguish objects around;
have a certain emotional level that can be formed because of the interaction with the surrounding environment;
ability to show an emotional reaction which is a reflection of the process of cognition;
have a different personality from one to another; and
ability to conduct social learning.
Dairy cattle psychology respects to some conditions, e.g., conditions of the cage, SUI as the comfort index, cow’s desire to always be in a lying position, cattle density in the room, comfortable and clean sitting position, high-quality feed and drinks, minimum competition to obtain food and drink, cow gets enough room to conduct activity, anti-slip floor, comfortable air cycle, comfortable lighting, and a shady spot [22, 23].
Dairy cattle behaviors are well developed in feeding, environment/microclimate condition, facility design, house, and social communication. The dairy cattle are able to distinguish red, yellow, green, and blue colors. However capability in differentiating between green and blue is poor [24]. Moreover, cattle are able to distinguish simple shapes such as triangles, circles, and line. Color information is important in cow facility design to increase dairy cattle comfort. In the free area, the cow automatically moves from the dark to light area. They tend to avoid strong contrast between sun and shadow. Comparing to human hearing capability, cow possesses almost similar frequency range and are able to listen to high tones that human cannot hear. Cattle hearing is important in inter- and intra-species communication [25]. Cattle sense of touch is important in determining which herbage is rejected or accepted. The secondary/special olfactory system can detect pheromones, volatile chemicals that are important in reproduction and feed selection [26].
Cattle communicate by sending out a different signal such as poses, sound, and smells [24]. A high density of cattle inside the house limits the freedom movement and can increase social stress. Cattle possess a distinct circadian rhythm, in which the main rest, feed, and rumination activities vary according to a fixed pattern. Grazing occupies a large amount of time for dairy cows about 8 hours/day. Grazing behavior is affected by many factors, including environmental conditions and plant species. In a dairy herd of Friesian cows, it was found that there was a consistent order for lying down and standing up [27]. The natural lying down behavior begins when the animal sniffs at the ground while it slowly moves forward. The head and body of the fully developed cow are thrust 0.60–0.70 m forward during the lying down process. When a cow wants to get up in a natural way, it firstly rises to its knees, and afterward the hind part of its body is swung up via the knees, which function as a rocking point.
There are many kinds of dairy cattle, e.g., fries Holland (the Netherlands), Shorthorn (UK), Holstein Friesian (the Netherlands), Jersey (the UK, France), Brown Swiss (Switzerland), Red Danish (Denmark), Drought Master (Australia), etc. The dairy cattle in Indonesia is dominated by Holstein Friesian possessing white and black spot or red spot. The female cow has average weight = 560 Kg to 725 Kg, and the male cow has average weight = 820 Kg to 1000 Kg. The dairy cattle have to grow up from calf, adult cow, mature cow, and old cow. A new-born calf weighs from 90 to 100 pound and has height from 32 to 36 inches. The 6-month-old heifer starts to graze (eat grass) in the pasture. Heifer usually has weight about 400 pounds with height from 38 to 42 inch. Yearling cow has to weight about 700 pounds and height from 47 to 52 inch and still has quite a bit of growing to do before it joins milking herd in another year. Two-year-old dairy cattle start to produce milk and keep on growing for next few years to be a mature cow. It weighs 1200 pound and has height from 53.5 to 55 inch. The last stage is mature cow which has more than 1500 pound and produces optimal milk. Holstein Friesian can produce milk around 57.000 Kg per year with low fat content at approximately 3.5 to 3.7% [28].
Cow body dimension will influence the horizontal movement of the cow when it gets up or lies down. It uses space around 3 m. The moving forward motion is 0.6 m, and minimum distance to the bedding from the head or neck of the cow is approximately 0.2 m [24]. The reach of dairy cattle during feed intake depends on the type of tether and feed alley height. The body length of the cow, from the shoulder area to the tail head and spine, is not flexible which make it difficult for the cow to make sharp changes of direction while it is walking. Therefore much space is required when a cow turns. The range of vision of cattle covers 330–3600, and the field of vision covered by both eyes at the same time is 25–300.
Similar to a human dimension, there are several things that can affect dairy cattle dimension as defined in measurements as follows:
Species
Any different taxonomic levels will have a tendency of different dimensions. The higher differences level of the taxonomy will have higher different dimensions as well. Zoometry measurement should be taken in the similar to animal species (types).
Phase development
Animals that undergo metamorphosis or change in phase of development will have different dimensions in every phase of its path.
Age
Animal body size will vary in each period of growth.
Gender
Male generally has larger body dimensions than females.
Clumps
Diversity clumps in the animals lead to a tendency of difference in size in any dimension zoometry.
2.3. Zoometry concept
Similar to anthropometry for human body dimensions, the zoometry concept concerned with the comparative measurement of the animal body and its part as well as the variables which impact these measurements. The main goal of zoometry is to increase the cattle comfortability which can influence physiological and psychological condition. The good physiological and psychological conditions will increase the amount of daily milk production. Zoometry can be utilized to define the best size of cattle facilities, such as cage size, stall, floor, etc.
The first step to create the zoometry concept is developing a database of cattle dimensions. The zoometry data of dairy cattle are collected from dairy farmers in Indonesia with an average age between 3.5 to 6 years old (optimal daily milk production). Total dairy cattle taken as the sample was around 500 samples. Generally, the measurement is divided into two sections for static dimension (mentioned later as static zoometry) data and for cow movement (dynamic zoometry) data. Equipment used in this research are a paper sheet, pen, ruler, stopwatch, and handy cam. The static measurement focused on the cow body dimension, e.g., length of the body, length of the leg, body width, neck length, etc. The dynamic zoometry is taken when the cow is engaged in physical activity. The measurement focused on cow movement (walking), moving the tail, moving head during drink or eating, and standing up to lying down or vice versa. To obtain detailed measurement, some videos have been taken during the measurement process. Briefly, statistic test for normality and validity data are presented in zoometry data analysis.
Figure 1 exhibits one example of measuring the static zoometry for a dairy cow. All measurers have received training before they start working on the dairy farm. Training included how to measure, understanding zoometry concept, knowing the dairy cattle behaviors, and implementing the animal research ethics. Measurements are made under tight control supervision. The quality control procedures during and after survey are explained afterward.
Figure 1.
Dairy cattle zoometry measurement for static and dynamic data.
The research investigated zoometry for dairy cattle for both of static and dynamic zoometry measurements. Zoometry concept is important to understand the dairy cattle lives. Zoometry dimension is defined in both static and dynamic measurement of cattle body dimensions and cattle behaviors. There are 16 dimensions of static zoometry for dairy cattle. Figure 2a and b defined all the dimension (D1, D2, D3,.., D16) of static zoometry in the 2D Picture. The dimensions D1 to D10 explain the position in the front view of dairy cattle (lengthwise direction), and the dimension of D11 to D13 describes in the lateral direction of dairy cattle. The D1 is for the height of the head, D2 is the height of the body, D3 is the length of neck + head, D14 is head width, D15 is the length of tail, and D16 is the length of horns.
Figure 2.
Static zoometry dimensions: (a) front view of cow dimensions (D1 to D10) and (b) the backside of cow dimensions (D11 to D13).
Table 2 shows some of the results of static zoometry measurement in 16 dimensions as mentioned before with 25 data, respectively. Homogeneity tests are used to ensure when the data collection of cow body size is in a uniform condition without any specific arrangement. According to the data, the average of data and the deviation standard are calculated for all dimensions (D1–D16), as example, D1 has average D¯= 39.64 and deviation standard (σ1) = 2.68. Moreover, D1 has lower control limit (LCL) = 34.17, and upper control limit (UCL) = 44.47 is categorized in homogeneity data. The same way, the other static cattle dimensions (D2–D16) are also categorized in homogeneity data. As a result the data measurement is ready to use for the next step of sufficient data test.
No
Explanation
Dairy cattle dimension
1
2
—
499
500
D1
Height of the head
36
38
—
38
40
D2
Height of cow body
77
78
—
78
79
D3
Length of the head + neck
104
106
—
104
105
—
—
—
—
—
—
—
D15
Length of the tail
114
113
—
115
120
D16
Length of the corn
9
14
—
10
8
Table 2.
Data measurement results from 500 number of source data of cattle for static dairy cattle dimension.
Sufficient data test for static cattle dimensions is determined based on formula 1. To calculate the number of data requirement (N′), the research select confidence level of collecting data 95% (k = 2), and error = 5% (s = 0.05) which has N′ = 7. As a result the data D1 can be categorized in sufficient data (N′ < N). Using the same way, the data of the other dimension D2–D16 all are categorized in sufficient data:
E1
where N′ = data should be taken.
N = data have been collected
k = level of confidence
s = level of error
xi = observation data
N\'=2/0.0525966289−98329832=7
Human dynamic anthropometry is concerned with the measurement of human work or human motion, e.g., hand movement, sitting down, turning, etc. In analogy with human data, the dynamic zoometry is defined with animal measurement (dairy cattle) on movement and cattle behaviors, e.g., vertical head movement to reach food, the vertical movement to lie down/get up, tail movement, etc. The data is very important in designing the comfortable cattle facilities, e.g., free stall, watering system, floor, house, and feeding rack. Figure 3 explains the dimensions of dairy cattle dynamic zoometry. There are seven dimensions for D17 to D23. Following statements explained dynamic dimension:
D17 dimension is angle scope for vertical movement of a cow head.
D18 dimension is angle scope for horizontal movement of a cow head.
D19 dimension is leg reach on walking movement.
D20 dimension is angle scope for horizontal movement of cow tail.
D21 dimension is length for laying down movement.
D22 dimension is length for raising movement.
D23 dimension is width for lying down or getting up movement.
To increase comfort during rising or lie down movement, the resting area must provide cattle with the easy movement for vertical, forward, and lateral movement without obstruction, injury, or fear. A rising motion includes the freedom to lunge forward, bob the head up or down, and stride forward. Resting motion also includes the freedom to lunge forward and bob the head. Each time the cow lies down, a cow puts about two-thirds of body weight on its front knees. Then the knees drop freely to the floor from a height of 20 to 30 centimeter. Therefore it is very important to provide best-quality bedding; as consequence, the cow can painlessly lie down at any time. The easy method to know the comfort level is to look at and check how fast a cow lies down in a cubicle.
3. Back propagation neural network (BPNN)
A neural network can be described as a black box that knows how to process input system to create useful outputs. Neural network is defined as “interconnected assembly of simple processing elements, units or nodes, whose functionality is loosely based on the animal neuron [29]. The processing ability of the network is stored in the inter-unit connection strengths, or weights, obtained by a process of adaptation to, or learning from, a set of training patterns.” The NN calculation is very complex and difficult to understand by using a mathematical model. Neural network copied the working system of the biological nervous system as an example for the brain to process the information. Other experts define the neural network (NN) as a powerful data modeling tool capable to capture and represent complex input/output relationships involving many factors [30].
The most common neural network model is the multilayer perceptron (MLP) which contains three layers: input layer, hidden layer, and an output layer. This type of neural network is known as a supervised network because it requires the desired output in order to learn. The goal of this type of network is to create a model that correctly maps the input to the output using historical data; therefore, the model can then be utilized to produce an output when the desired output is unknown. The MLP and many other neural networks learn using an algorithm called “back propagation” [31]. The goal of a back propagation neural network (BPNN) is to minimize the error which in the project is shown as a mean square error (MSE). With each presentation, the output of the neural network is compared to the desired output, and an error is computed. This error is then fed back (back propagated) to the neural network and utilized to adjust the weights such that the error decreases with each iteration and the neural model gets increasingly closer to producing the desired output. This process is known as “training.” Figure 4 describes how the BPNN system works to minimize the gap between target and output by adjusting network weight.
Figure 4.
Description of BPNN training the data sets [29].
BPNN works in three parts of a database called the set of training data, set of cross validation data, and set of testing data. Training data is utilized in the neural network to learn the databases’ correlation and its function as an input data. Cross validation data is utilized to evaluate the performance of the learning process to avoid over-training. Testing data is utilized to evaluate the performance of the training when it is complete. Production input data was fed into the trained neural network to produce an output. There is no evidence of references which explained how to divide the composition of training data, for cross validation and testing. The training data is required for a neural network to predict aerodynamic coefficient [32]. The paper shows manual NN training comparisons based on different transfer functions and training datasets. It is noted that dataset is an important part to obtain a better MSE performance. Commonly, the training data is >60%, the cross validation is ≈15%, and testing data is ≈10%.
Structure of BPNN model is a key performance to accelerate for reducing the gap between NN output and target during training the system. The BPNN structure contains a number of neurons, transfer function, and a number of hidden layers. The common method to create the BPNN structure is by the trial-and-error method. The method will be time-consuming during the training procedure. The optimal design of neural network using the Taguchi Method [33]. Moreover, we can use taguchi method to optimize the structure of BPNN for a limited amount of data [34]. Genetic algorithm (GA) is utilized to optimize the adjustment of the weight values during the training process.
Figure 5 chronologically explains the interconnection between BPNN and GA applications to adjust weight parameter in the quick propagation learning rule. The activities in Figure 5 contain collection and preparation of data, define robust (optimum) NN architectures, initialize population (connection weights and thresholds), assign input and output values to NN, compute hidden layer values, compute output values, and compute fitness using MSE formula. To find the best NN weight, at the start of the genetic algorithm, an initial population of chromosomes is created. The gene values are assigned to the initial weights of the network, and the network is trained based on the back propagation neural network (BPNN) algorithm. The next step of the algorithm is the fitness values of all the chromosomes of population evaluated; the inverse of MSE is regarded as the fitness function of GA. The individual’s genes are modified by crossover and mutation process. These operations result in a new-generation population of chromosomes. The generational process is repeated until convergence condition has been achieved. The weights of the BPNN network are created via a global optimization using GA, which increases the quality and the performance of the BPNN model. In the end, the neural network was trained with selected weight connection. According to the reference [36], the best BPNN structure is described as follows: one hidden layer, initial neuron = 17, tanh transfer function between input and hidden layer, the linear sigmoid transfer function between the hidden layer and output layer, quick propagation learning algorithm, and 5000 epochs. GA parameters are selected as follows: the Roulette rule is employed to select the best chromosome based on proportionality to its rank, the initial values for learning rate and momentum are 0.5000 and 0.0166, number of population is 50 chromosomes and epoch number was 100 at maximum, initial network weight factor is 0.1074, mutation probability is 0.01, and heuristic crossover was utilized.
Figure 5.
Neuro-genetic algorithm in BPNN development [35].
4. Construction of prediction model for cattle facilities using BPNN
The dairy cattle facilities should support cattle activities such as resting, drinking, eating, and milking. The facilities must guarantee the cattle will averse being stuck, injuries, and stress behaviors. The best facilities are indicated by cattle comfort level and increasing milk production. Moreover, the floor should not be warm and humid to reduce possible skin injuries and added thermal comfort. The other facility is a watering system; a watering cup should have an opening of at least 0.06 m2, approximately 30 cm in diameters or similar opening size [13]. It is recommended that the main water supply is ring connected and that the water is under a constant pressure. The best method of watering is supplying via service pipe; it will make sure fresh water is always supplied with a minimum amount of dirt. The free stall is very important for cattle to provide comfortable space for rest. Nigel B. Cook [9] research on free stall design for maximum cow comfort reported that 11.3 hours is needed for lying down in the stall and 2.9 hours for standing in the stall a day, in total 14.2 hours per day contact with free stall (around = 59.17%). The cow must have free stall design correctly sized as it correlates with milk production. A lot of farmers reduce stall length and width in order to save construction cost. It will reduce the level of cow comfort and milk production. Free stall should be designed correctly and maintained and should be sloped from front to back and provide a comfortable surface.
To control the steps of the research which are logically right, flowchart of developing and implementing the zoometry concept is presented as can be seen in Figure 6. According to the graph, the next step after collecting the static and dynamic data is doing the statistic test for checking the data quality. Manual measuring for dynamics data is time-consuming and costly and requires more energy, e.g., measuring the length for raising movement. The database construction is developed based on Tables 2 and 3, Table 2 as input data and Table 3 as desired data. As a result, BPNN can predict easily the dynamics zoometry dimension from any inputs of static zoometry dimension. To look for the best neural network structure, at the same time, the GA method is employed during NN training. BPNN module is ready to use to be part of designing the cattle comfort facilities, e.g., free stall, cattle house, etc.
Figure 6.
Flowchart of developing and implementing the zoometry concept using BPNN module.
No
Explanation
Dairy cattle dimension (cm)
1
2
—
499
500
D17
Vertical head movement (0)
50
55
—
43
45
D18
Horizontal head movement (0)
200
220
—
225
240
D19
Step walking (cm)
53
72
—
77
64
D20
Cow tail movement (0)
120
110
—
112
103
D21
Space for lying down (cm)
313
309
—
312
318
D22
Space for getting up (cm)
300
296
—
299
205
D23
Width space (cm)
132
130
—
120
118
Table 3.
Data measurement results from 500 dairy cattle for dynamic dairy cattle dimension.
Figure 7 describes BPNN training result using genetic algorithm (GA) optimization in one replication. According to the graph, the training process will stop in 49 generations with mean square error (MSE) = 0.0287. BPNN model is ready to predict any input data to determine output data (dynamics data). The BPNN model is very useful for the user conduct test to determine cow behavior correlated with cow dimensions in design process. The user can put any “normal value” of static cattle dimensions (D1 to D16) to predict dynamics cattle dimension (D17 to D23). As example, the input values are D1 = 38 cm, D2 = 78 cm, D3 = 109 cm, D4 = 157 cm, D5 = 137 cm, D6 = 51 cm, D7 = 58 cm, D8 = 41 cm, D9 = 61 cm, D10 = 118 cm, D11 = 63 cm, D12 = 47 cm, D13 = 31 cm, D14 = 19 cm, D15 = 122 cm, and D16 = 14 cm, and produced output values are D17 = 52 cm, D18 = 214 cm, D19 = 54 cm, D20 = 121 cm, D21 = 312 cm, D22 = 301 cm, and D23 = 130 cm. The following stage involved implementing the zoometry concept and BPNN model to evaluate and redesign the cattle facilities. The first step of designing the cattle house is defined the house parameters which are described as follows:
Length of cattle house (L)
Figure 7.
Static and dynamic zoometry training in BPNN-GA application.
Length of cattle house is defined as the total summation of length for lying down and length for getting up minus cattle length or L = D¯21 + D¯22 – (D¯3 + D¯4). Based on data in Table 1 for D¯3 + D¯4 and BPNN test for D¯21 + D¯22, L has average 346.67 cm and deviation standard σ = 6.71 cm then by using percentile 95th will produce Lzoometry = 346.67 cm + 1.64 × 6.71 cm = 357.67 cm.
Width of cattle house (W)
The width of cattle house is defined as the space for lying down or getting up easily or defined in D23. Based on the data in BPNN test, D23 has value = 125.96 cm and deviation standard σ = 3.70 cm and then using percentile 95th will produce Wzoometry = 125.96 cm + 1.64 × 3.70 cm = 132.03 cm
Height of cattle house (H)
Height of cattle house is defined as the summation of D¯2 + D¯9 + (D¯3 × tan (0.5 × D¯17)). Based on the data in Table 1 and BPNN test, H has average 194.64 cm and deviation standard σ = 6.49 cm and then by using percentile 95th will produce Hzoometry = 194.64 cm + 1.64 × 6.49 cm = 205.28 cm.
Cattle house design is recommended based on the results of zoometry calculation of length, width, and height. The cattle house design should have minimum value of length = 357.67 cm, width = 132.03 cm, and height = 205.28 cm. The height dimension of cattle house must consider the other factors such as air circulation, lighting, and the other facilities especially in a tropical climate with higher level of temperature and relative humidity. It can increase the heat stress index, which finally reduces milk production. In the United States, climate change that makes higher temperature and humidity than normal is likely to affect milk production because dairy cows are sensitive to excessive temperature and humidity.
5. Conclusion(s)
The paper has successfully developed the concept of zoometry to describe the dimensions of dairy cattle to design facilities. There are two zoometry for static and dynamics condition with a total number of dimensions at 16 and 7. The chapter successfully presented the BPNN training as the complexity of dynamic data (cattle motion behavior) correlated with cattle dimension. The paper also describes how to implement the zoometry concept in order to develop cattle house design. This method could be used to design other facilities such as free stall, watering system, designing floor, and feeding rack.
Using 500 cattle data source, the zoometry concept still fluctuates despite success in homogeny test and data-sufficient test. As consequence, a huge number of dimension data is required to obtain steady zoometry. The zoometry concept will be an important topic of research in the future correlated with cattle comfort and cattle productivity.
\n',keywords:"animal comfort, cattle cage, facility design, neural network, zoometry, ergonomics, milk productivity",chapterPDFUrl:"https://cdn.intechopen.com/pdfs/61243.pdf",chapterXML:"https://mts.intechopen.com/source/xml/61243.xml",downloadPdfUrl:"/chapter/pdf-download/61243",previewPdfUrl:"/chapter/pdf-preview/61243",totalDownloads:458,totalViews:164,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,dateSubmitted:"November 14th 2017",dateReviewed:"February 9th 2018",datePrePublished:null,datePublished:"June 27th 2018",dateFinished:null,readingETA:"0",abstract:"The dairy cattle productivity is largely dependent on the facility quality and environmental condition. Various researchers had conducted a study in this field, but it is not developing the knowledge of animal dimensions and behaviors correlated with their facility design. Complexities of dynamics zoometry depend on cow behaviors that they are forced to use neural network (NN) approach. Hence, the purpose of this chapter is to create the concept of static and dynamic zoometry to guide the ergonomics facilities design. The research started with study literature on anthropometry, dairy cattle, facility design, and neural network. The following step is collecting the static zoometry data in 16 dimensions and dynamics zoometry in 7 dimensions. On the one hand, static data is utilized as an input factor. On the other hand, dynamic data is utilized as desire factor of back propagation neural network (BPNN) model. The result of BPNN training is utilized to design the dairy cattle facilities, e.g., cage with minimal length = 357.67 cm, width = 132.03 cm (per tail), and height = 205.28 cm. The chapter successfully developed the concept of zoometry approach and BPNN model as a pioneer of implementing comfort knowledge.",reviewType:"peer-reviewed",bibtexUrl:"/chapter/bibtex/61243",risUrl:"/chapter/ris/61243",book:{slug:"artificial-intelligence-emerging-trends-and-applications"},signatures:"Sugiono Sugiono, Rudy Soenoko and Rio Prasetyo Lukodono",authors:[{id:"234186",title:"Ph.D.",name:"Sugiono",middleName:null,surname:"Sugiono",fullName:"Sugiono Sugiono",slug:"sugiono-sugiono",email:"sugiono_ub@ub.ac.id",position:null,institution:null}],sections:[{id:"sec_1",title:"1. Introduction",level:"1"},{id:"sec_2",title:"2. Zoometry concept",level:"1"},{id:"sec_2_2",title:"2.1. Anthropometry",level:"2"},{id:"sec_3_2",title:"2.2. Cattle psychology and physiology",level:"2"},{id:"sec_4_2",title:"2.3. Zoometry concept",level:"2"},{id:"sec_6",title:"3. Back propagation neural network (BPNN)",level:"1"},{id:"sec_7",title:"4. Construction of prediction model for cattle facilities using BPNN",level:"1"},{id:"sec_8",title:"5. Conclusion(s)",level:"1"}],chapterReferences:[{id:"B1",body:'Rozenberg S, Body JJ, Bruyère O, Bergmann P, Brandi ML, Cooper C, Reginster JY, et al. Effects of dairy products consumption on health: Benefits and beliefs—A Commentary from the Belgian Bone Club and the European Society for Clinical and Economic aspects of osteoporosis, osteoarthritis and musculoskeletal diseases. Calcified Tissue International. 2016. https://doi.org/10.1007/s00223-015-0062-x'},{id:"B2",body:'Choi IY, Lee P, Denney DR, Spaeth K, Nast O, Ptomey L, Sullivan DK, et al. Dairy intake is associated with brain glutathione concentration in older adults. American Journal of Clinical Nutrition. 2015;101(2):287-293. https://doi.org/10.3945/ajcn.114.096701'},{id:"B3",body:'Faghih A, Anoosheh M, Ahmadi F, Ghofranipoor F. The effect of boy students’ participation on consumption of milk and dairy. 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Industrial Engineering, Universitas Brawijaya, Indonesia
Industrial Engineering, Universitas Brawijaya, Indonesia
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1. Introduction
Lots of evidence has accumulated that online content influences people. It has even been pointed out that computer algorithms sometimes know us better than we know ourselves. They can detect our interests by the searches we do and the web pages we open. If this were not so, businesses would not advertise on the Web. But does that mean we humans are just a slower, less systematic kind of computer? How different are computers and living organisms?
Peirce’s most difficult category is Firstness. It is difficult because it is about things before we really begin to think about them or even recognize their “otherness.” Secondness, which consists in that otherness, and Thirdness, which contains our categorizations or general conceptions of things, are fairly straightforward. In Peirce’s categorical system Firstness lies at the base of Secondness and Thirdness. Before anything is different or general, it is itself.
There is an enlightening passage where Peirce lays out the relation of Secondness to Thirdness:
I should not wonder if somebody were to suggest that perhaps the idea of a law is essential to the idea of one thing acting upon another. But surely that would be the most untenable suggestion in the world considering that there is no one who after lifelong discipline in looking at things from the necessitarian point of view has ever been able to train himself to dismiss the idea that he can perform any specifiable act of the will. It is one of the most singular instances of how a preconceived theory will blind a man to facts that many necessitarians seem to think that nobody really believes in the freedom of the will, the fact being that he himself believes in it when he is not theorizing. However, I do not think it worthwhile to quarrel about that. Have your necessitarianism if you approve of it; but I still think you must admit that no law of nature makes a stone fall, or a Leyden jar to discharge, or a steam engine to work ([1], pp. 89-90).
Here he is arguing against the popular “necessitarianism” of his day, which we generally call “determinism” in English today. Its claim is that every single fact of our experience is determined by natural laws. If you know the state of facts at any time, you can deduce what the facts will be at any other time by those laws ([1], p. 325). Peirce says this implies there is no real increase in diversity in the world. Whatever diversity exists today would have existed at the beginning of the universe. Natural processes only rearrange things; they do not create anything new ([1], pp. 334-335).
Now, actually, there are several objections one could make to the passage. The most obvious is that, of course, stones do fall because there is a law of nature, gravitation. What Peirce is saying is that when a stone falls, some other single entity, such as perhaps my foot hitting it, is the occasion for that law to operate. That is Secondness. He is arguing that my foot hitting the stone is not predictable by that or any other law.
A more difficult problem is his statement that no one can “train himself” to believe he cannot make certain choices. It seems people often do train themselves to believe that. In fact, maybe that is what depression consists in, the belief you cannot do things you would like to do. But I believe Peirce is speaking here in a more “ideal,” philosophical sense: does the philosopher really believe he cannot make choices?
2. Wilden on computer technology
How we understand the human brain has important implications for the freedom of the will. In a 1972 piece, Anthony Wilden lays out a distinction between “analog and digital communication” ([2], pp. 155-195). Wilden is attempting to show what elements of electronic technology may correspond to the nervous systems of organisms, and his discussion of analog and digital brings out some interesting parallels. He says our nervous system includes both analog and digital elements, laying out in detail how nerve axons transmit messages to the synaptic connections between cells. The transmission is at first an analog one, meaning that it is about “difference” on a continuous scale. Eventually the message passed in the axon reaches a certain “threshold,” and it becomes a matter of “opposition” rather than difference ([2], pp. 174-176). This is now a digital message. Wilden points out that genes are digitally coded but depend upon related enzymes, which are analog elements ([2], p. 158). Digitalization is always necessary whenever an important “boundary” or “frame” needs to be added to an analog continuum. As Wilden puts it:
[The organism] introduces a desired closure into a continuum, which distinguishes a certain “part,” and by the same act constitutes himself as distinct in some way from the environment he perceives ([2], p. 174).
The digital splits the world into discrete elements and helps us experience our individuality. The connection of this concept to Secondness is clear.
In another chapter of the same book, he suggests the analog may correspond to Peirce’s Thirdness, but he admits he does not understand Peirce’s categories very well [3]. He suggests Firstness is the Real and Secondness, the Imaginary. This misconstrues them. Something imaginary is a Second when we find out it is imaginary; until then, it is an aspect of our freedom, which is Firstness. As Peirce would put it, Firstness is the “monadic” aspect of our experience. He says:
I can imagine a consciousness whose whole life, alike when wide awake and when drowsy or dreaming, should consist of nothing at all but a violet color or a stink of rotten cabbage. It is purely a question of what I can imagine and not of what psychological laws permit ([1], p. 81).
Consciousness has this monadic aspect that is complete unto itself and not dependent on anything external. Firstness is predominant in the ideas of “freshness, life, freedom” as well as feeling, as opposed to perception, will, and thought ([1], pp. 78-79). When we find out something is imaginary, we are essentially acknowledging a dyadic relation, a relation between what something is and what it is not (Secondness). There is also an element of Thirdness that comes into this, in that becoming convinced something is not real is coming to a sense of the persistence or stability of that reality ([1], p. 247). That is a triadic relation, because it involves a sense of connecting links between things, things yet to come as well as in the past. It is saying, “I will not see evidence of it in the future.” Thirdness has a necessary connection to future time. For example, evolution is Thirdness because it is the emergence of things in time. Education is Thirdness because it means becoming aware of more things and different categories of things.
3. Pre-Wilden views of analog and digital
Wilden cites John von Neumann’s classic work The Computer and the Brain ([2], pp. 157-158). Von Neumann talked about analog and digital computers but did not interpret human cognition in terms of the analog. Analog computers work by representing numbers by units of actual physical quantities, while digital machines represent them “as in conventional writing or printing, i.e. as a sequence of decimal digits” ([4], pp. 3, 6). He thought our cognition was basically digital with some analog features ([4], p. 58). He emphasized the binary nature of nerve impulses. They were basically “on–off switches,” and he put less emphasis on the threshold features Wilden emphasized ([4], pp. 40-44). What is “non-digital-like” in our brains is the result of their working statistically rather than analogically. If we imagine computing machines to have existed prior to the human brain, we might say the brain gave up precision in arithmetic to gain “an improvement in logics” ([4], p. 80). The nervous system uses two types of communication, the “non-arithmetical” and the “arithmetical.” The latter includes “communications of orders,” which are logical. Our nervous systems require less “logical depth” than digital computers, so statistical information is adequate ([4], pp. 76-82).
Hubert L. Dreyfus conceptualized human cognition in terms of the analog in his 1965 book Alchemy and Artificial Intelligence but appears to have given up that understanding in his later work On the Internet (2009). In the first work, he lays out three areas that digital computers are unable to handle: fringe consciousness, essence/accident discrimination, and ambiguity tolerance [5]. Dreyfus’s conception of the analog appears to have influenced Wilden ([2], p. 157). One problem he lays out in some detail is language processing. It is difficult to understand language as simply a list of words in sentences constructed by rules. Dreyfus cites Wittgenstein on how our understanding of language appears to be inseparably connected to the way we live. Our lives provide us with the context that makes words and sentences understandable ([6], p. 33). This is an example of “tacit” knowledge and ambiguity tolerance. He cites Bar-Hillel for the view that machines can only make good translations of language if they can learn ([6], p. 35).
Dreyfus quotes a statement by Bullock on “graded synaptic potential,” similar to Wilden’s “threshold effects,” arguing that the nervous system is a “complex analog device” rather than digital ([6], p. 56). He goes on to speculate on “wet” computers that simulate the way the human brain works, perhaps taking the form of an analog computer using ion solutions whose electrical properties change to model relationships. However, he cites Maurice Merleau-Ponty for doubts this would be adequate, since the human body as a whole plays an important role in facilitating intelligent behavior ([6], p. 59). This is the primary theme of Dreyfus’s later work, On the Internet.
4. Post-Wilden views of analog and digital
Dreyfus has made an ongoing effort to monitor the progress of Artificial Intelligence and appears to make an effort to evaluate it as generously as possible. For example, he admits the development of Google, with its weighting of web pages by their apparent importance to searchers, shows some of his skepticism was excessive ([7], pp. 21-24). Google shows a computer can get a sort of indirect knowledge of what web pages are about without really understanding them ([7], p. 22). If a lot of searchers have shown interest in a page, that indicates something about its content. However, it says nothing about the correctness of the content. The interest of people in a page may be due to irrational factors or manipulation by the publisher.
Dreyfus says the big problem with AI is the computer’s lack of “embodiment.” Humans have common sense, and this is inextricably tied to our having bodies ([7], pp. 18-20). This appears to have replaced the concept of the “analog” for him. After all, analog computers are just another kind of machine. As Von Neumann showed, analog computers are used to do arithmetic ([4], p. 3). They are really just a different way to represent quantities. Our common sense comes from our not being machines.
However, there may be another sense in which the analog is relevant. Wilden pointed out that the human programmer provides a “necessary analog component to complement the amazing brute-force problem-solving capabilities of the digital computer” ([2], p. 157). Computers operate on codes, and a code as a whole is an analog of something. It is a way to get computers, with their ones and zeroes which are mostly meaningless to us, to do useful work by modeling some human activity such as writing or playing games. Von Neumann showed that digital computers have this power because they have memory ([4], pp. 19-20). This allows them to do things besides arithmetic. The programmer can instruct the computer to transform its numerical memory into something non-numerical. Nonetheless, one can argue the computer has no knowledge of the world. It is primarily a kind of mental prosthesis that allows us to perform certain functions faster and more accurately.
There is a connection between this and Peirce’s semiotic theory. The computer code functions as a kind of “icon,” in that its relation to a human cognitive activity is one of similarity ([1], p. 102). The skill of the programmer consists in her ability to make the program as analogous to the human activity as possible, while making sure the computer is consistently able to perform the actions. When she does not do a good enough job, the program, and perhaps the computer as a whole, “crashes.”
In the book, Dreyfus makes a contrast between Plato, who pushed a “disembodied” conception of human personality, and Nietzsche, who emphasized our embodiment ([7], p. 5). Dreyfus is particularly doubtful about the efficacy of distance learning. He goes through the stages of learning from the novice, the advanced beginner, competence, proficiency, expertise and, finally, mastery and shows how the body and emotion are increasingly necessary as one progresses up the scale. Have not the Stoics and Descartes taught us that we make the most progress without emotion? ([7], p. 32) Dreyfus argues that learning above the stage of novice requires a level of emotion. We must want to succeed and worry about not measuring up. The teacher provides a model of commitment, and if we are not physically present with him or her, we lack the cues necessary for progress:
If the teacher is detached and computer-like, the students will be too. Conversely, if the teacher shows his involvement in the way he pursues the truth, considers daring hypotheses and interpretations, is open to students’ suggestions and objections, and emotionally dwells on the choices that have led him to his conclusions and actions, the students will be more likely to let their own successes and failures matter to them ([7], p. 33).
In a 2018 article, Beatrice Fazi attempts to build on the work of Gilles Deleuze to create a “digital esthetics” [8]. While Deleuze did not talk about computers very much, his work implied that the digital could not participate in the esthetic or creativity, central aspects of his philosophy. Digital computers depend on discreteness, on determinacy, but for Deleuze, indeterminacy was essential to life. Is there any way the digital can play a role in creativity? She surveys some attempts to make computers “creativity and esthetics friendly.” One approach is to link the operation of the computer to the lived experience of users (“embedded computing”). This provides an “analog” or “embodied” supplement to the computer’s cold, digital operation. Anna Munster made a particularly vivid attempt at this by emphasizing that the analog and the digital that come together in human-computer interaction are “more than the sum of their parts” ([8], pp. 12-13). Humans and computers working together have the potential to produce novel elements neither could produce on their own.
Fazi is not entirely satisfied with this solution. It is problematic because it ties the value of the digital to the analog (or embodied) elements, and she wants to believe the digital, or more precisely the computational, is valuable in itself. She calls her desired conception a “computational esthetics.” This must go beyond “the discrete features of digital technologies, such as digits and pixels” to include also the “finite steps that characterize computation as an axiomatic and algorithmic method” ([8], p. 16). She discusses the work of Alan Turing in formalizing the nature of computing processes. He showed they work via precise, finite routines, but also that certain problems could not be solved in this way. They are “incomputable” because the steps they require are infinite ([8], p. 21). Gödel’s Theorem showed that the computational depends ultimately on formal axioms arising from indeterminacy, since they cannot be deduced from the formal system themselves ([8], p. 20). Thus Fazi ends with a computational esthetics broadly compatible with Deleuze. The computational is valuable for its “systematizing and rationalizing logical capacity” ([8], p. 16) while not undermining indeterminacy and freedom.
5. The second cognitive revolution
A development bearing on all these questions is what has been called “the Second Cognitive Revolution.” Dreyfus was an important person in the history of this movement [9]. Rom Harré has summarized the direction of the movement by saying the earlier Cognitive Revolution was too focused on cognition as governed by formal rules and schemata. It had been an advancement over earlier understandings which interpreted the mind as simply receiving external stimuli passively. We do not just respond to our environment; we also have complex “representations” of it. The movement drew on the work of Turing to conceive of the brain as an “information processing device” ([10], p. 181). It was primarily digital in nature since digital computers contain representations of the world in their memories. By the mid-80’s, it was clear that a more subtle understanding of language was necessary to really understand human cognition. This involved rejecting the whole Cartesian model of thought as something internal and seeing how it functions within life as a whole, especially in its social aspects. Ludwig Wittgenstein had a major role here with his concept of “language games,” of language as a sort of set of recipes rather than formalizable rules. As Harré points out, the First Cognitive Revolution had been too trapped in “the presumptions of individualism” ([10], p. 181). In fact, social cognitive processes precede individual ones.
In Dreyfus’s contribution to the same volume, he argues against the concept of representation altogether ([11], pp. 39-73). Drawing on the work of Walter Freeman, he argues for what he calls a “Heideggerian” or “Merleau-Pontian” artificial intelligence ([11], p. 58) to solve the “frame problem.” Both machines and living organisms encounter facts in the world, but the frame problem asks how a machine might be programmed so it can assign significance to novel facts. As he puts it, speaking of a closely related “binding problem”:
How can the brain keep track of which facts in its representation of the current world are relevant to which other facts? … [A]s long as the mind/brain is thought of as passively receiving meaningless inputs that need to have significance and relevance added to them, the binding problem has remained unsolved and is almost certainly unsolvable ([11], p. 59).
Drawing on Freeman’s work with rabbits, Dreyfus, in line with his emphasis on embodiment, argues that organisms select relevant elements in the world based upon their prior experiences and purposes (feeding, defense, reproduction, etc.). He lays out Freeman’s analysis of how “cell assemblies” in the animal are activated by sensory stimuli such as smell. These assemblies are self-organizing, bringing together different parts of the animal’s brain and body, not just passive receptors but directed by its active concerns. Drawing on Merleau-Ponty, he calls the interaction of the organism’s nervous system and the environment “basins of attraction” ([11], p. 62). The binding problem is simply a result of trying to interpret the animal from the researcher’s perspective rather than that of the animal ([11], p. 61). He suggests machines might be designed to function the same way ([11], pp. 68-73).
In the following chapter of the volume, H.M. Collins raises some serious problems with Dreyfus’s proposal [12]. The difficulty is that it does not explain what is unique about humans. As Terrence Deacon argued in his Symbolic Species [13], symbolization is what is distinctive to humans. We share with animals an immediate “indexical” (in Peirce’s terms) engagement with items in our environment (Seconds), but since we also use “symbols” (in Peirce’s sense), involving conventional (shared) signifiers for general aspects of the world (Thirds), an element of representation seems inherent to our cognition. It would seem, in fact, that this symbolic element must be “digital” in Wilden’s sense, in that it provides a stable, discrete representation of general aspects of the world while permitting us also to speak of particular things and persons (Seconds) and feelings and esthetic qualities (Firsts). As Peirce would say, it is only because we use the lower “iconic” and “indexical” forms of signs that symbols emerge as possible ([1], p. 115). The meaningfulness of symbols stands on their foundation. Peirce’s pragmatic theory of meaning analyzes the meaning of concepts as generalizations of expected experience, which would have to take the form of indexes and icons ([1], 272-273. There Peirce seems to deny the iconic element, but if we understand the relationship between indexes and icons in his understanding, an iconic element is inseparable from indexes).
So where does that leave Wittgenstein’s conception of language as a collection of recipes, inextricably linked to our “embodied” ways of living? In reality, Peirce’s theory is very close to it. Words are only meaningful to the extent we have “interpretants” for them, which are our habitual and fallible ways of seeing things as we consider signs [14].
6. Implications for free will
Another contribution in the same volume is “The Illusion of Free Will and its Acceptance” by Giuseppe Trautteur ([15], pp. 191-203). The purpose of the article is argue for what he calls “double feel” ([15], p. 199), the apparent truth that people can be both convinced that they have free choice and realize theoretically that there is no evidence for free will. He talks at length about the scientific evidence for free will and concludes it is not there. He even cites the experiments published by Kornhuber and Deecke which showed that neural commands initiating action precede our conscious awareness of making decisions ([15], p. 194). While he is aware of the indeterminacy of microscopic quantum events, he is convinced that macroscopic events are strictly determined by natural law ([15], p. 193).
Trautteur expresses a great deal of sorrow about this and says it cannot help but undermine ethics and religion ([15], p. 200). Why are we creatures that seem to insist on this illusion? Trautteur entertains the proposals of Clore and Damasio that we are born with “markers” for “cognitive feelings” such as the sense of volition ([15], p. 198).
To respond to this I would like to go back to something I mentioned at the beginning. Peirce criticized necessitarianism for denying that there is any increase in diversity in nature. Natural laws just rearrange the preexisting diversity. He thought this idea was intolerable for any view of the world that attempted to understand creativity in any sense. Firstness is manifested in the variety of the world, and perhaps one could even argue that “internet addiction” is somehow dependent on it. To borrow a phrase from Dreyfus, a person addicted to online content is not “detached and computer-like” ([7], p. 33). Our ability to get addicted appears to depend on computers showing us interesting things, and this depends on diversity. Without Firstness, the internet would be a bore. Especially with the development of the World Wide Web, digital computers can convey analog information like sights and sounds. They are not just for number crunching or word processing.
Peirce’s theory was that lawfulness (Thirdness) was growing in the universe. As he says:
At present, the course of events is approximately determined by law. In the past that approximation was less perfect; in the future it will be more perfect. The tendency to obey laws has always been and always will be growing. ([1], p. 358).
Perhaps we can move away from a focus on proving what determines each of our actions and consider the possibility that creativity itself is the best evidence of indeterminacy. Purely “free” choices do not have to happen constantly as long as they can happen at times.
7. Computer algorithms and determinism: a case study
In a July 7, 2019 article in the New York Times, Patrick Berlinquette writes of his experiences using “The Redirect Method,” a program targeting Google searchers with ads to influence searchers’ behavior [16]. He acknowledges that marketers like himself profit by “exploiting impatience and impulsiveness,” but he wants to show online ads can do positive things, too. “Redirect” gives counter-messages to a person’s apparent interests. Berlinquette experimented on influencing two groups of troubled people, those who were suicidal and those who might become mass shooters. He was helped in setting up the programs by the experience of the National Suicide Prevention Lifeline and the Redirect Method’s experiences reaching out to ISIS sympathizers. The ISIS campaign provided Google with a blueprint that shows, step by step, how to create redirect ads to influence people. Google has a suicide algorithm, but it has gaps he attempted to fill. He says he would measure the success of his algorithm by how many people clicked on his ad and called the number on his web site, linked to the national helpline. There was a similar link for people who seemed interested in perpetrating shootings.
He was quite successful with suicidal people but not with shooters. With the first, the “conversion rate,” the rate of people responding, was 28% compared with the usual Google rate of 4%. With shooters, the success rate was low, though he does not give an exact percentage. Why would the success rate be different for the two groups? My guess is that it is not due to some flaw in his mass shooter algorithm, but because the desires of the two groups are different. Suicidal people usually want help. If someone reaches out, they will respond. People considering mass murders are not interested in talking to anyone, or at least the chance of their wanting to is much less. The explanation lies in their inner desires rather than some external manipulation. In Peirce’s terms, it is Firstness, not Secondness or Thirdness.
8. Conclusion
The 1975 film The Stepford Wives depicts a wealthy suburb of New York, Stepford, where wives appear to be unnaturally obedient to their husbands [17]. One wife moves to Stepford with her husband and gets progressively more worried the longer she is there. Every now and then, one of her friends suddenly changes to this unnaturally “submissive” personality. While it is a horror film, it’s difficult not to laugh when the women suddenly change. In real life, no one changes that way, even gradually.
I believe the analyses laid out by Peirce, Wilden, Deleuze, and Fazi make it highly doubtful computers can actually change our values. The most they can do is take advantage of desires we already have. Under their influence, we will do some things we would not otherwise have done, but our basic personal orientations will remain intact.
Thanks
I want to thank John Meador, Dean of UAB Libraries, for funding this project. Thanks also to my colleagues Laura Simpson, Kevin Hébert, Linda Burrow, and Dorothy Ogden for encouragement and help. I no longer work with them, but Valerie S. Gordon, Scott Plutchak, Susan Matveyeva, and Nancy Deyoe also deserve thanks. Finally, my learned late friend Lee Lowrie and Dr. Marge Steiner deserve praise for making my work possible.
\n',keywords:"computers, analog, digital, freedom, determinism, semiotics, esthetics, embodiment, algorithms, addiction",chapterPDFUrl:"https://cdn.intechopen.com/pdfs/69515.pdf",chapterXML:"https://mts.intechopen.com/source/xml/69515.xml",downloadPdfUrl:"/chapter/pdf-download/69515",previewPdfUrl:"/chapter/pdf-preview/69515",totalDownloads:330,totalViews:0,totalCrossrefCites:0,dateSubmitted:"June 11th 2019",dateReviewed:"September 7th 2019",datePrePublished:"October 11th 2019",datePublished:"June 17th 2020",dateFinished:null,readingETA:"0",abstract:"Discussions of computer technology often touch on matters of free will. Can living organisms, especially human beings, be interpreted as like computers? Much writing on computers today assumes that digital technology shows freedom of the will is illusory. Charles S. Peirce (1839-1914) had quite a bit to say about the freedom of the will and its relation to the laws of nature. This chapter provides evidence from a number of writers on computers and related matters which bears on his analysis. Peirce’s category of Firstness has a great deal to contribute to our understanding of freedom as well as human responsibility, but its true meaning requires quite a bit of explanation.",reviewType:"peer-reviewed",bibtexUrl:"/chapter/bibtex/69515",risUrl:"/chapter/ris/69515",signatures:"Ted Gemberling",book:{id:"7311",title:"Cognitive and Intermedial Semiotics",subtitle:null,fullTitle:"Cognitive and Intermedial Semiotics",slug:"cognitive-and-intermedial-semiotics",publishedDate:"June 17th 2020",bookSignature:"Marta Silvera-Roig and Asunción López-Varela Azcárate",coverURL:"https://cdn.intechopen.com/books/images_new/7311.jpg",licenceType:"CC BY 3.0",editedByType:"Edited by",editors:[{id:"302728",title:"Dr.",name:"Marta",middleName:null,surname:"Silvera-Roig",slug:"marta-silvera-roig",fullName:"Marta Silvera-Roig"}],productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"}},authors:[{id:"308016",title:"Dr.",name:"Ted",middleName:null,surname:"Gemberling",fullName:"Ted Gemberling",slug:"ted-gemberling",email:"tgemberl@uab.edu",position:null,institution:null}],sections:[{id:"sec_1",title:"1. Introduction",level:"1"},{id:"sec_2",title:"2. Wilden on computer technology",level:"1"},{id:"sec_3",title:"3. Pre-Wilden views of analog and digital",level:"1"},{id:"sec_4",title:"4. Post-Wilden views of analog and digital",level:"1"},{id:"sec_5",title:"5. The second cognitive revolution",level:"1"},{id:"sec_6",title:"6. Implications for free will",level:"1"},{id:"sec_7",title:"7. Computer algorithms and determinism: a case study",level:"1"},{id:"sec_8",title:"8. Conclusion",level:"1"},{id:"sec_9",title:"Thanks",level:"1"}],chapterReferences:[{id:"B1",body:'Peirce CS. Philosophical Writings. New York: Dover; 1955'},{id:"B2",body:'Wilden A. Analogue and digital communication. In: System and Structure. London: Tavistock. 1972:155-195'},{id:"B3",body:'Wilden A. System and Structure. London: Tavistock; 1972. pp. 267-268'},{id:"B4",body:'Von Neumann J. The Computer and the Brain. New Haven: Yale University Press; 1958'},{id:"B5",body:'Dreyfus HL. Alchemy and Artificial Intelligence. 1965. p. iii. Available from: https://www.rand.org/content/dam/rand/pubs/papers/2006/P3244.pdf [Accessed: 21 July 2019]'},{id:"B6",body:'Dreyfus HL. Alchemy and Artificial Intelligence. p. 33'},{id:"B7",body:'Dreyfus HL. On the Internet. 2nd ed. London: Routledge; 2009'},{id:"B8",body:'Fazi MB. Digital aesthetics: The discrete and the continuous. Theory, Culture and Society. 2019;36(1):3-26. DOI: 10.1177/0263276418770243'},{id:"B9",body:'Leidlmair K. After Cognitivism: A Reassessment of Cognitive Science and Philosophy. Dordrecht: Springer; 2009. p. vii'},{id:"B10",body:'Harré R. The second cognitive revolution. In: Leidlmair K: After Cognitivism. p. 181'},{id:"B11",body:'Dreyfus HL. How representational cognitivism failed and is being replaced by body/world coupling. In: Leidlmair K: After Cognitivism'},{id:"B12",body:'Collins HM. The new orthodoxy: humans, animals, Heidegger and Dreyfus. In: Leidlmair K: After Cognitivism'},{id:"B13",body:'Deacon TW. The Symbolic Species: The Co-Evolution of Language and the Brain. New York: W.W. Norton; 1997'},{id:"B14",body:'Gemberling T. FRSAD, semiotics and FRBR-LRM. Cataloging and Classification Quarterly. 2016;54(2):138-139'},{id:"B15",body:'Trautteur G. The illusion of free will and its acceptance. In: Leidlmair K: After Cognitivism'},{id:"B16",body:'Berlinquette A. I used Google ads for social engineering. It worked. New York Times. 7 July 2019. Available from: https://www.nytimes.com [Accessed: 23 July 2019]'},{id:"B17",body:'The Stepford Wives [Internet description]. 1975. Available from: https://www.imdb.com/title/tt0073747/?ref_=nv_sr_2?ref_=nv_sr_2 [Accessed: 23 July 2019]'}],footnotes:[],contributors:[{corresp:"yes",contributorFullName:"Ted Gemberling",address:"tgemberl@uab.edu",affiliation:'
University of Alabama at Birmingham, Birmingham, Alabama, United States
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