Search results for: Artificial animal intelligence

Authors: Ibrahim M. S. Shnawa

Abstract:

Attempts were made to identify anuran glial cells. They were found as nervous tissue resident. Having stage dependent morphotype changes, whereby, appeared as an ovoid to oval in resting state and amoeboid mrophotypes in activated state, stained fairly with methylene blue and take up Pelikane blue 10% aqueous solution, as well as having the ability to phagocytize heat killed Staphylococcus aureus. They were delineated from the migrating peripheral monocytes by morphotypic and morphometeric differences. Such criteria were consistence with glial cells. Thus, the anuran glial cells are being identified in the frog Rana ridibunda Pallas 1771 and this animal can be of use as a simple model for the immunobiology of glial cells.

Keywords: Amoeboid cell, bacterial phagocytosis, Glial cells, Resting.

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Authors: Ahmed G. Mahgoub, Dahlia H. Hafez, Mostafa A. Abu Kiefa

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The Cone Penetration Test (CPT) is a common in-situ test which generally investigates a much greater volume of soil more quickly than possible from sampling and laboratory tests. Therefore, it has the potential to realize both cost savings and assessment of soil properties rapidly and continuously. The principle objective of this paper is to demonstrate the feasibility and efficiency of using artificial neural networks (ANNs) to predict the soil angle of internal friction (Φ) and the soil modulus of elasticity (E) from CPT results considering the uncertainties and non-linearities of the soil. In addition, ANNs are used to study the influence of different parameters and recommend which parameters should be included as input parameters to improve the prediction. Neural networks discover relationships in the input data sets through the iterative presentation of the data and intrinsic mapping characteristics of neural topologies. General Regression Neural Network (GRNN) is one of the powerful neural network architectures which is utilized in this study. A large amount of field and experimental data including CPT results, plate load tests, direct shear box, grain size distribution and calculated data of overburden pressure was obtained from a large project in the United Arab Emirates. This data was used for the training and the validation of the neural network. A comparison was made between the obtained results from the ANN's approach, and some common traditional correlations that predict Φ and E from CPT results with respect to the actual results of the collected data. The results show that the ANN is a very powerful tool. Very good agreement was obtained between estimated results from ANN and actual measured results with comparison to other correlations available in the literature. The study recommends some easily available parameters that should be included in the estimation of the soil properties to improve the prediction models. It is shown that the use of friction ration in the estimation of Φ and the use of fines content in the estimation of E considerable improve the prediction models.

Keywords: Angle of internal friction, Cone penetrating test, General regression neural network, Soil modulus of elasticity.

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Authors: Chei-Chang Chiou, Sen-Wei Wang, Yu-Min Wang

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The purpose of this study is to investigate the relationship between corporate governance and pricing for initial public offerings (IPOs). Empirical result finds that the prediction of pricing of IPOs with corporate governance added can have a rather higher degree of predicting accuracy than that of non governance added during the training and testing samples. Therefore, it can be observed that corporate governance mechanism can affect the pricing of IPOs

Keywords: Artificial neural networks, corporate governance, initial public offerings.

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Authors: Songyi Kim, Kwangwoo Lee, Seungjoo Kim, Dongho Won

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RFID (Radio Frequency IDentification) system has been widely used in our life, such as transport systems, passports, automotive, animal tracking, human implants, library, and so on. However, the RFID authentication protocols between RF (Radio Frequency) tags and the RF readers have been bring about various privacy problems that anonymity of the tags, tracking, eavesdropping, and so on. Many researchers have proposed the solution of the problems. However, they still have the problem, such as location privacy, mutual authentication. In this paper, we show the problems of the previous protocols, and then we propose a more secure and efficient RFID authentication protocol.

Keywords: RFID, mutual authentication, serverless, anonymity.

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Authors: J. Sepitka, J. Lukes, J. Reznicek

Abstract:

Hysitron TriboIndenterTM TI 950 system has been used for studying the local viscoelastic properties of porcine intervertebral disc end plate by means of nanoscale mechanical dynamic analysis. The specimen of an endplate was cut from fresh porcine vertebra dissected from 16 month animal. The lumbar spine motion segments were dissected and 5 millimeter thick plates of vertebral body, endplate and annulus fibrosus were prepared for nanoindentation. The surface of the sample was kept in physiological solution during nanoindentation experiment. We obtained mechanical characteristics of different areas of native endplate (endplate middle and vertebra and annulus fibrosus boundary).

Keywords: nanoindentation, DMA, endplate, cartilage

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Authors: A. Anastasopoulou, A. Kolios, T. Somorin, A. Sowale, Y. Jiang, B. Fidalgo, A. Parker, L. Williams, M. Collins, E. J. McAdam, S. Tyrrel

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Developing countries are nowadays confronted with great challenges related to domestic sanitation services in view of the imminent water scarcity. Contemporary sanitation technologies established in these countries are likely to pose health risks unless waste management standards are followed properly. This paper provides a solution to sustainable sanitation with the development of an innovative toilet system, called Nano Membrane Toilet (NMT), which has been developed by Cranfield University and sponsored by the Bill & Melinda Gates Foundation. The particular technology converts human faeces into energy through gasification and provides treated wastewater from urine through membrane filtration. In order to evaluate the environmental profile of the NMT system, a deterministic life cycle assessment (LCA) has been conducted in SimaPro software employing the Ecoinvent v3.3 database. The particular study has determined the most contributory factors to the environmental footprint of the NMT system. However, as sensitivity analysis has identified certain critical operating parameters for the robustness of the LCA results, adopting a stochastic approach to the Life Cycle Inventory (LCI) will comprehensively capture the input data uncertainty and enhance the credibility of the LCA outcome. For that purpose, Monte Carlo simulations, in combination with an artificial neural network (ANN) model, have been conducted for the input parameters of raw material, produced electricity, NO_X emissions, amount of ash and transportation of fertilizer. The given analysis has provided the distribution and the confidence intervals of the selected impact categories and, in turn, more credible conclusions are drawn on the respective LCIA (Life Cycle Impact Assessment) profile of NMT system. Last but not least, the specific study will also yield essential insights into the methodological framework that can be adopted in the environmental impact assessment of other complex engineering systems subject to a high level of input data uncertainty.

Keywords: Sanitation systems, nano membrane toilet, LCA, stochastic uncertainty analysis, Monte Carlo Simulations, artificial neural network.

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Authors: A. Páchová

Abstract:

Working memory (WM) can be defined as the system which actively holds information in the mind to do tasks in spite of the distraction. Contrary, short-term memory (STM) is a system that represents the capacity for the active storing of information without distraction. There has been accumulating evidence that these types of memory are related to higher cognition (HC). The aim of this study was to verify the relationship between HC and memory (visual STM and WM, auditory STM and WM). 59 primary school children were tested by intelligence test, mathematical tasks (HC) and memory subtests. We have shown that visual but not auditory memory is a significant predictor of higher cognition. The relevance of these results are discussed.

Keywords: higher cognition, long-term memory, short-term memory, working memory

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Authors: Abdesh Toleubayev, Rinat Zhumatayev, Kulzhazira Toleubayeva

Abstract:

Mounds are one of the most valuable sources of information on various aspects of life, household skills, rituals and beliefs of the ancient peoples of Kazakhstan. Moreover, the objects associated with the cult of the burial of the dead are the most informative, and often the only source of knowledge about past eras. The present study is devoted to some results of the excavations carried out on the mound "Baygetobe" of Shilikti burial ground. The purpose of the work is associated with certain categories of grave goods and reading "Fine Text" of Shilikti graves, whose structure is the same for burials of nobles and ordinary graves. The safety of a royal burial mounds, the integrity and completeness of the source are of particular value for studying.

Keywords: Animal style, barrow, Baygetobe, dromos, Shilikty.

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Authors: Lily Ingsrisawang, Supawadee Ingsriswang, Saisuda Somchit, Prasert Aungsuratana, Warawut Khantiyanan

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This paper presents the methodology from machine learning approaches for short-term rain forecasting system. Decision Tree, Artificial Neural Network (ANN), and Support Vector Machine (SVM) were applied to develop classification and prediction models for rainfall forecasts. The goals of this presentation are to demonstrate (1) how feature selection can be used to identify the relationships between rainfall occurrences and other weather conditions and (2) what models can be developed and deployed for predicting the accurate rainfall estimates to support the decisions to launch the cloud seeding operations in the northeastern part of Thailand. Datasets collected during 2004-2006 from the Chalermprakiat Royal Rain Making Research Center at Hua Hin, Prachuap Khiri khan, the Chalermprakiat Royal Rain Making Research Center at Pimai, Nakhon Ratchasima and Thai Meteorological Department (TMD). A total of 179 records with 57 features was merged and matched by unique date. There are three main parts in this work. Firstly, a decision tree induction algorithm (C4.5) was used to classify the rain status into either rain or no-rain. The overall accuracy of classification tree achieves 94.41% with the five-fold cross validation. The C4.5 algorithm was also used to classify the rain amount into three classes as no-rain (0-0.1 mm.), few-rain (0.1- 10 mm.), and moderate-rain (>10 mm.) and the overall accuracy of classification tree achieves 62.57%. Secondly, an ANN was applied to predict the rainfall amount and the root mean square error (RMSE) were used to measure the training and testing errors of the ANN. It is found that the ANN yields a lower RMSE at 0.171 for daily rainfall estimates, when compared to next-day and next-2-day estimation. Thirdly, the ANN and SVM techniques were also used to classify the rain amount into three classes as no-rain, few-rain, and moderate-rain as above. The results achieved in 68.15% and 69.10% of overall accuracy of same-day prediction for the ANN and SVM models, respectively. The obtained results illustrated the comparison of the predictive power of different methods for rainfall estimation.

Keywords: Machine learning, decision tree, artificial neural network, support vector machine, root mean square error.

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Authors: Rohit Gupta, Ruchika

Abstract:

In this paper, a PSO based fractional order PID (FOPID) controller is proposed for concentration control of an isothermal Continuous Stirred Tank Reactor (CSTR) problem. CSTR is used to carry out chemical reactions in industries, which possesses complex nonlinear dynamic characteristics. Particle Swarm Optimization algorithm technique, which is an evolutionary optimization technique based on the movement and intelligence of swarm is proposed for tuning of the controller for this system. Comparisons of proposed controller with conventional and fuzzy based controller illustrate the superiority of proposed PSO-FOPID controller.

Keywords: CSTR, Fractional Order PID Controller, Partical Swarm Optimization.

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Authors: Wiroon Sriborrirux, Sorakrai Kraipui, Nakorn Indra-Payoong

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One of the most importance of intelligence in-car and roadside systems is the cooperative vehicle-infrastructure system. In Thailand, ITS technologies are rapidly growing and real-time vehicle information is considerably needed for ITS applications; for example, vehicle fleet tracking and control and road traffic monitoring systems. This paper defines the communication protocols and software design for middleware components of B-VIS (Burapha Vehicle-Infrastructure System). The proposed B-VIS middleware architecture serves the needs of a distributed RFID sensor network and simplifies some intricate details of several communication standards.

Keywords: Middleware, RFID sensor network, Cooperativevehicle-infrastructure system, Enterprise Java Bean.

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Authors: Mouna Mallem, Majid Tlidjane

Abstract:

The study realized on alive lambs in two different areas mountain and plain in Batna region, aims to demonstrate the possible effect of field type on cupric status of lambs, through evaluation of copper contents in the chain: soil – plant – animal by atomic absorption spectrophotometry. This comparative study also allowed the investigation of the influence of the age and the season. The results obtained show that contents of copper in the soil, forage in the same way as in the plasma of lambs are higher in the plain than in the mountainous area; however, the difference is significant only between the values of feed.

Keywords: Copper, Forage, Lambs, Plasma copper.

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Authors: Wenbin Zhang, Hantian Wu, Jian Tang

Abstract:

An artificial neural network is a mathematical model inspired by biological neural networks. There are several kinds of neural networks and they are widely used in many areas, such as: prediction, detection, and classification. Meanwhile, in day to day life, people always have to make many difficult decisions. For example, the coach of a soccer club has to decide which offensive player to be selected to play in a certain game. This work describes a novel Neural Network using a combination of the General Regression Neural Network and the Probabilistic Neural Networks to help a soccer coach make an informed decision.

Keywords: General Regression Neural Network, Probabilistic Neural Networks, Neural function.

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Authors: Hemant Kumar, Nilendu Das

Abstract:

A study based on ANN structure gives us the information to predict the size of the future in realizing a past event. ANN, IMD (Indian meteorological department) data and remote sensing were used to enable a number of parameters for calculating the size that may occur in the future. A threshold selected specifically above the high-frequency harvest reached the area during the selected seismic activity. In the field of human and local biodiversity it remains to obtain the right parameter compared to the frequency of impact. But during the study the assumption is that predicting seismic activity is a difficult process, not because of the parameters involved here, which can be analyzed and funded in research activity.

Keywords: ANN, Bayesian class, earthquakes, IMD.

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Authors: Snežana T. Tanasković, Sonja M. Gvozdenac, Branka D. Popović, Vesna M. Đurović, Matthias Erb

Abstract:

Western corn rootworm – WCR (Diabrotica virgifera sp.virgifera, Coleoptera, Chrysomelidae) is economically the most important pest of maize worldwide. WCR natural population is already very abundant on Serbian fields, and keeps increasing each year. Tolerance is recognized by larger root size and bigger root regrowth. Severe larval injuries cause lack of compensatory regrowth and lead to reduction of plant growth and yield. The aim of this research was to evaluate tolerance of commercial Serbian maize hybrid NS 640, under natural WCR infestation and under conditions of artificial infestation, and to obtain the information about its tolerance to WCR larval feeding in two consecutive years. Field experiments were conducted in 2015 and 2016, in Bečej (Vojvodina province, Serbia). In experimental field, 96 plants were selected, marked and arranged in 48 pairs. Each pair represented two plants. The first plant was artificially infested with 4 mL WCR egg suspension in agar (550 eggs plant^-1) in the root zone (D plant). The second plant represented control plant (C plant) with injection of 4 mL distilled water in root zone. The experimental field was inspected weekly. A hybrid tolerance was assessed based on root injury level and root mass. Root injury was rated using the Node-Injury Scale 1-6, during the last field inspection (September – October). Comparing the root injuries on D and C plants in 2015, more severe damages were recorded on D plants (12 plants - rate 5 and 17 plants - rate 6) compared to C plants (2 plants - rate 5 and 8 plants - rate 6). Also, the highest number of plants with healthy roots (rate 1), was registered in the control (25 plants), while only 4 D plants were rated as injury level 1. In 2016, root injuries caused by WCR larvae on D and C plants did not differ significantly. The reason is the difference in climatic conditions between the years. The 2015 was extremely dry and more suitable for WCR larval development and movement in the soil, compared to 2016. Thus, more severe damages appeared on artificially infested plants (D plants). Root mass was in strong correlation with the level of root injury, but did not differ significantly between D and C plants, in both years.

Keywords: D. v. virgifera, maize, root injury, tolerance.

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Authors: Carsten Röcker

Abstract:

This paper illustrates why existing technology acceptance models are only of limited use for predicting and explaining the adoption of future information and communication technologies. It starts with a general overview over technology adoption processes, and presents several theories for the acceptance as well as adoption of traditional information technologies. This is followed by an overview over the recent developments in the area of information and communication technologies. Based on the arguments elaborated in these sections, it is shown why the factors used to predict adoption in existing systems, will not be sufficient for explaining the adoption of future information and communication technologies.

Keywords: Technology Diffusion, Technology AcceptanceModels, Ambient Intelligence, Ubiquitous and Pervasive Computing.

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Authors: H. El Ayech, A. Trabelsi

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In this article we are going to discuss the improvement of the multi classes- classification problem using multi layer Perceptron. The considered approach consists in breaking down the n-class problem into two-classes- subproblems. The training of each two-class subproblem is made independently; as for the phase of test, we are going to confront a vector that we want to classify to all two classes- models, the elected class will be the strongest one that won-t lose any competition with the other classes. Rates of recognition gotten with the multi class-s approach by two-class-s decomposition are clearly better that those gotten by the simple multi class-s approach.

Keywords: Artificial neural network, letter-recognition, Multi class Classification, Multi Layer Perceptron.

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Authors: Y. J. Huang, C. H. Chang

Abstract:

In this paper, an intelligent automatic parking control method is proposed. First, the dynamical equation of the rear parking control is derived. Then a fuzzy logic control is proposed to perform the parking planning process. Further, a rear neural network is proposed for the steering control. Through the simulations and experiments, the intelligent auto-parking mode controllers have been shown to achieve the demanded goals with satisfactory control performance and to guarantee the system robustness under parametric variations and external disturbances. To improve some shortcomings and limitations in conventional parking mode control and further to reduce consumption time and prime cost.

Keywords: Auto-parking system, Fuzzy control, Neural network, Robust

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Authors: Federico Cabitza, Bernardo Dal Seno

Abstract:

In this paper DJess is presented, a novel distributed production system that provides an infrastructure for factual and procedural knowledge sharing. DJess is a Java package that provides programmers with a lightweight middleware by which inference systems implemented in Jess and running on different nodes of a network can communicate. Communication and coordination among inference systems (agents) is achieved through the ability of each agent to transparently and asynchronously reason on inferred knowledge (facts) that might be collected and asserted by other agents on the basis of inference code (rules) that might be either local or transmitted by any node to any other node.

Keywords: Knowledge-Based Systems, Expert Systems, Distributed Inference Systems, Parallel Production Systems, Ambient Intelligence, Mobile Agents.

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Authors: V. A. Vieira, M. P. Sforcini, V. Endo, G. C. Magioni, M. D. S. Oliveira

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The main goal of this paper was evaluate the effect of diets containing different levels of probiotic on performance and milk composition of lactating cows. Eight Holstein cows were distributed in two 4x4 Latin square. The diets were based on corn silage, concentrate and the treatment (0, 3, 6 or 9 grams of probiotic/animal/day). It was evaluated the dry matter intake of nutrients, milk yield and composition. The use of probiotics did not affect the nutrient intake (p>0.05) neither the daily milk production or corrected to 4% fat (p>0.05). However, it was observed that there was a significant fall in milk composition with higher levels of probiotics supplementation. These results emphasize the need of further studies with different experimental designs or improve the number of Latin square with longer periods of adaptation.

Keywords: Dairy cow, milk composition, probiotics.

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Authors: Kumiko Aoki

Abstract:

Japan is known to be a technological powerhouse, being noted for its automobiles, consumer electronics, laptop computers, portable gaming devices, and more recently healing animal robots. Japan is also noted for its popular culture; manga, anime, novels, films, character goods, game programs, cosplay cafes, karaoke and so on. It may be natural for people outside Japan to assume that e-learning in Japan must be well advanced and innovative. In reality, the application of technologies in education in Japan is far behind of other developed countries. Especially in higher education, apathy of students towards their study prevails and teachers continue ignoring such student attitudes. E-learning, which is supposed to revolutionalize the way people learn as it has potentials to enable more student-centered learning, has not been realized in Japan and mostly used to perpetuate the teachercentered teaching in a different format.

Keywords: e-learning, Higher Education, ICT in Education, Japan

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Authors: Ren-Jieh Kuo, Chun-Shou Huang

Abstract:

The research of juice flavor forecasting has become more important in China. Due to the fast economic growth in China, many different kinds of juices have been introduced to the market. If a beverage company can understand their customers’ preference well, the juice can be served more attractive. Thus, this study intends to introducing the basic theory and computing process of grapes juice flavor forecasting based on support vector regression (SVR). Applying SVR, BPN, and LR to forecast the flavor of grapes juice in real data shows that SVR is more suitable and effective at predicting performance.

Keywords: Flavor forecasting, artificial neural networks, support vector regression, grape juice flavor.

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Authors: V. Viliene, A. Raceviciute-Stupeliene, V. Sasyte, V. Slausgalvis, R. Gruzauskas, J. Al-Saifi

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Animal nutritionists and scientists have searched for alternative measures to improve the production. One of such alternative is use of organic acids as feed additive in animal nutrition. The study was conducted to investigate the impact of butyric acids, calcium formate, organic acids, and its salts (BCOS) additives on rabbit’s productive performance, carcass traits and meat quality. The study was conducted with 14 Californian breed rabbits. The rabbits were assigned to two treatment groups (seven rabbits per each treatment group). The dietary treatments were 1) control diet, 2) diet supplemented with a mixture BCOS - 2 kg/t of feed. Growth performance characteristics (body weight, daily weight gain, daily feed intake, feed conversion ratio, mortality) were evaluated. Rabbits were slaughtered; carcass characteristics and meat quality were evaluated. Samples loin and hind leg meat were analysed to determine carcass characteristics, pH and colour measurements, cholesterol, and malonyldialdehyde (MDA) content in loin and hind leg meat. Differences between treatments were significant for body weight (1.30 vs. 1.36 kg; P<0.05), daily weight gain (16.60 vs. 17.85 g; P<0.05), and daily feed intake (78.25 vs. 80.58 g; P<0.05) for control and experimental group respectively for the entire experimental period (from 28–77 days old). No significant differences were found in feed conversion ratio and mortality. The feed additives insertion in the diets did not significantly influence the carcass yield or the proportions of the various carcass parts and organs. Differences between treatments were significant for pH value after 48h in loin (5.86 vs. 5.74; P<0.05), hind leg meat (6.62 vs. 6.65; P<0.05), more intense colour b* of loin (5.57 vs. 6.06; P<0.05), less intense colour a* (14.99 vs. 13.15; P<0.05) in hind leg meat. Cholesterol content in hind leg meat decreased by 17.67 mg/100g compared to control group (P<0.05). After storage for three months, MDA concentration decreased in loin and hind leg meat by 0.3 μmol/kg and 0.26 μmol/kg respectively compared to that of the control group (P<0.05). The results of this study suggest that BCOS could potentially be used in rabbit nutrition with consequent benefits on the rabbits’ productivity and nutritional quality of rabbit meat for consumers.

Keywords: Butyric acids, calcium formate, meat quality, organic acids salts, rabbits, productivity.

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Authors: Halim Djerroud, Arab Ali Cherif

Abstract:

We assume that conscious functions are implemented automatically. In other words that consciousness as well as the non-consciousness aspect of human thought, planning and perception, are produced by biologically adaptive algorithms. We propose that the mechanisms of consciousness can be produced using similar adaptive algorithms to those executed by the mechanism. In this paper, we present a computational model of consciousness, the ”Global Abstraction Workspace” which is an internal environmental modelling perceived as a multi-agent system. This system is able to evolve and generate new data and processes as well as actions in the environment.

Keywords: Artificial consciousness, cognitive architecture, global abstraction workspace, mutli-agents system.

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Authors: P. R. Jayathilaka, K.L. Jayaratne, H.L. Premaratne

Abstract:

This research presented in this paper is an on-going project of an application of neural network and fuzzy models to evaluate the sociological factors which affect the educational performance of the students in Sri Lanka. One of its major goals is to prepare the grounds to device a counseling tool which helps these students for a better performance at their examinations, especially at their G.C.E O/L (General Certificate of Education-Ordinary Level) examination. Closely related sociological factors are collected as raw data and the noise of these data are filtered through the fuzzy interface and the supervised neural network is being utilized to recognize the performance patterns against the chosen social factors.

Keywords: Education, Fuzzy, neural network, prediction, Sociology

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Authors: Oleksandr Poliakov, Olena Chepenyuk, Yevgen Pashkov, Mykhaylo Kalinin, Vadym Kramar

Abstract:

In one of the prosthesis designs for lower limb transfemoral amputations artificial knee joints with polycentric mechanisms are used. Such prostheses are characterized by high stability during the stance phase of the movement. The existing variety of polycentric mechanisms indicates the possibility of finding the optimal prosthesis design satisfying several quality criteria.In this paper we present a multicriteria method for the synthesis of the artifical polycentric knee mechanism based on the uniform systematic study of the design parameters space and on the analysis of Pareto optimal solutions.

Keywords: Optimalcriteria, polycentric knee, prosthesis, synthesis, transfemoral amputee.

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Authors: Sunita Verma , Divya Tiwari, Ajay Verma

Abstract:

Water samples were collected from river Pandu at six stations where human and animal activities were high. Composite samples were analyzed for dissolved oxygen (DO), biochemical oxygen demand (BOD), chemical oxygen demand (COD) , pH values during dry and wet seasons as well as the harmattan period. The total data points were used to establish relationships between the parameters and data were also subjected to statistical analysis and expressed as mean ± standard error of mean (SEM) at a level of significance of p<0.05. Regression analysis was carried out to establish relationships if any between studied parameters and relationships in form of scatter plots were obtained between DO/BOD, COD/DO, BOD/COD, COD/pH, BOD/pH and DO/pH. The high to moderate correlation coefficient observed, R2 ranged from 0.68 to 0.15 between these parameters.

Keywords: BOD, DO, COD, pH, Regression analysis.

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Authors: Kamila Janovská, Šárka Vilamová, Petr Besta, Iveta Vozňáková, Roman Kozel

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Quantitative methods of economic decision-making as the methodological base of the so called operational research represent an important set of tools for managing complex economic systems,both at the microeconomic level and on the macroeconomic scale. Mathematical models of controlled and controlling processes allow, by means of artificial experiments, obtaining information foroptimalor optimum approaching managerial decision-making.The quantitative methods of economic decision-making usually include a methodology known as structural analysis -an analysisof interdisciplinary production-consumption relations.

Keywords: economic decision-making, mathematical methods, structuralanalysis, technical coefficient

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Authors: Rade M. Ciric, Nikola L. J. Rajakovic

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This paper presents a curriculum of the subject small power plants and renewable energy sources, dealing with the concept of distributed generation, renewable energy sources, hydropower, wind farms, geothermal power plants, cogeneration plants, biogas plants of agriculture and animal origin, solar power and fuel cells. The course is taught the manner of connecting small power plants to the grid, the impact of small generators on the distribution system, as well as economic, environmental and legal aspects of operation of distributed generators.

Keywords: Distributed generation, renewable energy sources, techno-economic analysis, energy policy, curriculum.

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Authors: Samat Turganbekov, Zhakan Mol

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This article examines the emergence and development of the Kazakhstan species of humanism. The biggest challenge for Kazakhstan in terms of humanism is connected with advocating human values in parallel to promoting national interests; preserving the continuity of traditions in various spheres of life, business and culture. This should be a common goal for the entire society, the main direction for a national intelligence, and a platform for the state policy. An idea worth considering is a formation of national humanist tradition model; the challenges are adapting people to live in the context of new industrial and innovative economic conditions, keeping the balance during intensive economic development of the country, and ensuring social harmony in the society.

Keywords: Kazakh humanism, humanist tradition, national culture, spiritual and moral priority, national interest.

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