Search results for: Artificial mind

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

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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: Kamel Khoualdi, Radia Benghezal

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Research in distributed artificial intelligence and multiagent systems consider how a set of distributed entities can interact and coordinate their actions in order to solve a given problem. In this paper an overview of this concept and its evolution is presented particularly its application in the design of intelligent tutoring systems. An intelligent tutor based on the concept of agent and centered specifically on the design of a pedagogue agent is illustrated. Our work has two goals: the first one concerns the architecture aspect and the design of a tutor using multiagent approach. The second one deals particularly with the design of a part of a tutor system: the pedagogue agent.

Keywords: Intelligent tutoring systems, Multiagent systems, Pedagogue agent, Planning.

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Authors: Shi-Yu Lu, Chung-Han Yeh, Li-Ping Chen, Yu-Cheng Chang

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This paper uses both quantitative and qualitative approaches to survey the current status of AI-related applications and the structure of key AI jobs in Taiwan's high-tech manufacturing industry, as well as the demand for professional AI talents, skills, and training. The result shows that AI applications and talent demand vary from different industries in many aspects, including technologies used, talent structure, and training methods. This paper serves as a reference for the government to establish appropriate talent training programs, and to reduce the demand gap for professional AI talents in Taiwan manufacturers.

Keywords: Artificial intelligence, manufacturing, talent, training.

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Authors: Abdel-Badeeh M. Salem

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Case based reasoning (CBR) methodology presents a foundation for a new technology of building intelligent computeraided diagnoses systems. This Technology directly addresses the problems found in the traditional Artificial Intelligence (AI) techniques, e.g. the problems of knowledge acquisition, remembering, robust and maintenance. This paper discusses the CBR methodology, the research issues and technical aspects of implementing intelligent medical diagnoses systems. Successful applications in cancer and heart diseases developed by Medical Informatics Research Group at Ain Shams University are also discussed.

Keywords: Medical Informatics, Computer-Aided MedicalDiagnoses, AI in Medicine, Case-Based Reasoning.

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Authors: Ljubomir Nikolic, Larisa Trichtchenko

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The connection between solar activity and adverse phenomena in the Earth’s environment that can affect space and ground based technologies has spurred interest in Space Weather (SW) research. A great effort has been put on the development of suitable models that can provide advanced forecast of SW events. With the progress in computational technology, it is becoming possible to develop operational large scale physics based models which can incorporate the most important physical processes and domains of the Sun-Earth system. In order to enhance our SW prediction capabilities we are developing advanced numerical tools. With operational requirements in mind, our goal is to develop a modular simulation framework of propagation of the disturbances from the Sun through interplanetary space to the Earth. Here, we report and discuss on the development of coronal field and solar wind components for a large scale MHD code. The model for these components is based on a potential field source surface model and an empirical Wang-Sheeley-Arge solar wind relation. 

Keywords: Space weather, numerical modeling, coronal field, solar wind.

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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: A. M. John-Otumu, M. M. Rahman, O. C. Nwokonkwo, M. C. Onuoha

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Online social media networks have long served as a primary arena for group conversations, gossip, text-based information sharing and distribution. The use of natural language processing techniques for text classification and unbiased decision making has not been far-fetched. Proper classification of these textual information in a given context has also been very difficult. As a result, a systematic review was conducted from previous literature on sentiment classification and AI-based techniques. The study was done in order to gain a better understanding of the process of designing and developing a robust and more accurate sentiment classifier that could correctly classify social media textual information of a given context between hate speech and inverted compliments with a high level of accuracy using the knowledge gain from the evaluation of different artificial intelligence techniques reviewed. The study evaluated over 250 articles from digital sources like ACM digital library, Google Scholar, and IEEE Xplore; and whittled down the number of research to 52 articles. Findings revealed that deep learning approaches such as Convolutional Neural Network (CNN), Recurrent Neural Network (RNN), Bidirectional Encoder Representations from Transformer (BERT), and Long Short-Term Memory (LSTM) outperformed various machine learning techniques in terms of performance accuracy. A large dataset is also required to develop a robust sentiment classifier. Results also revealed that data can be obtained from places like Twitter, movie reviews, Kaggle, Stanford Sentiment Treebank (SST), and SemEval Task4 based on the required domain. The hybrid deep learning techniques like CNN+LSTM, CNN+ Gated Recurrent Unit (GRU), CNN+BERT outperformed single deep learning techniques and machine learning techniques. Python programming language outperformed Java programming language in terms of development simplicity and AI-based library functionalities. Finally, the study recommended the findings obtained for building robust sentiment classifier in the future.

Keywords: Artificial Intelligence, Natural Language Processing, Sentiment Analysis, Social Network, Text.

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Authors: J.H. Low, C.O. Wong, E.J. Han, K.R Kim K.C. Jung, H.K. Yang

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This paper proposes an Interactive Chinese Character Learning System (ICCLS) based on pictorial evolution as an edutainment concept in computer-based learning of language. The advantage of the language origination itself is taken as a learning platform due to the complexity in Chinese language as compared to other types of languages. Users especially children enjoy more by utilize this learning system because they are able to memories the Chinese Character easily and understand more of the origin of the Chinese character under pleasurable learning environment, compares to traditional approach which children need to rote learning Chinese Character under un-pleasurable environment. Skeletonization is used as the representation of Chinese character and object with an animated pictograph evolution to facilitate the learning of the language. Shortest skeleton path matching technique is employed for fast and accurate matching in our implementation. User is required to either write a word or draw a simple 2D object in the input panel and the matched word and object will be displayed as well as the pictograph evolution to instill learning. The target of computer-based learning system is for pre-school children between 4 to 6 years old to learn Chinese characters in a flexible and entertaining manner besides utilizing visual and mind mapping strategy as learning methodology.

Keywords: Computer-based learning, Chinese character, pictograph evolution, skeletonization.

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Authors: Saeed Mohammed Baneamoon, Rosalina Abdul Salam

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Robotic system is an important area in artificial intelligence that aims at developing the performance techniques of the robot and making it more efficient and more effective in choosing its correct behavior. In this paper the distributed learning classifier system is used for designing a simulated control system for robot to perform complex behaviors. A set of enhanced approaches that support default hierarchies formation is suggested and compared with each other in order to make the simulated robot more effective in mapping the input to the correct output behavior.

Keywords: Learning Classifier System, Default Hierarchies, Robot Behaviors.

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Authors: Raid R. O. Al-Nima, S. S. Dlay, W. L. Woo

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A relationship between face and signature biometrics is established in this paper. A new approach is developed to predict faces from signatures by using artificial intelligence. A multilayer perceptron (MLP) neural network is used to generate face details from features extracted from signatures, here face is the physical biometric and signatures is the behavioural biometric. The new method establishes a relationship between the two biometrics and regenerates a visible face image from the signature features. Furthermore, the performance efficiencies of our new technique are demonstrated in terms of minimum error rates compared to published work.

Keywords: Behavioural biometric, Face biometric, Neural network, Physical biometric, Signature biometric.

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Authors: A. Jabbari, R. Jedermann, W. Lang

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The new idea of this research is application of a new fault detection and isolation (FDI) technique for supervision of sensor networks in transportation system. In measurement systems, it is necessary to detect all types of faults and failures, based on predefined algorithm. Last improvements in artificial neural network studies (ANN) led to using them for some FDI purposes. In this paper, application of new probabilistic neural network features for data approximation and data classification are considered for plausibility check in temperature measurement. For this purpose, two-phase FDI mechanism was considered for residual generation and evaluation.

Keywords: Fault detection and Isolation, Neural network, Temperature measurement, measurement approximation and classification.

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Authors: P. Soda, G.Iannello

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In this paper we address the issue of classifying the fluorescent intensity of a sample in Indirect Immuno-Fluorescence (IIF). Since IIF is a subjective, semi-quantitative test in its very nature, we discuss a strategy to reliably label the image data set by using the diagnoses performed by different physicians. Then, we discuss image pre-processing, feature extraction and selection. Finally, we propose two ANN-based classifiers that can separate intrinsically dubious samples and whose error tolerance can be flexibly set. Measured performance shows error rates less than 1%, which candidates the method to be used in daily medical practice either to perform pre-selection of cases to be examined, or to act as a second reader.

Keywords: Artificial neural networks, computer aided diagnosis, image classification, indirect immuno-fluorescence, pattern recognition.

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Authors: Gholam Hossein Naseri, Manucher Tamizi

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Light is one of the most important qualitative and symbolic factors and has a special position in architecture and urban development in regard to practical function. The main function of light, either natural or artificial, is lighting up the environment and the constructional forms which is called lighting. However, light is used to redefine the urban spaces by architectural genius with regard to three aesthetic, conceptual and symbolic factors. In architecture and urban development, light has a function beyond lighting up the environment, and the designers consider it as one of the basic components. The present research aims at studying the function of light and color in architectural view and their effects in buildings.

Keywords: Architectural View , Color , Light

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Authors: Manuela Nayantara Jeyaraj

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Green IT is a term that refers to the collective strategic and tactical practices that unswervingly condense the carbon footprint to a diminished proportion in an establishment’s computing procedures. This concept has been tightly knit with IT related organizations; hence it has been precluded to be applied within non-IT organizations in Sri Lanka. With the turn of the century, computing technologies have taken over commonplace activities in every nook and corner in Sri Lanka, which is still on the verge of moving forth in its march towards being a developed country. Hence, it needs to be recursively proven that non-IT industries are well-bound to adhere to ‘Green IT’ practices as well, in order to reduce their carbon footprint and move towards considering the practicality of implementing Green-IT practices within their work-arounds. There are several spheres that need to be taken into account in creating awareness of ‘Green IT’, such as the economic breach, technologies available, legislative bounds, community mind-set and many more. This paper tends to reconnoiter causes that currently restrain non-IT organizations from considering Green IT concepts. By doing so, it is expected to prove the beneficial providence gained by implementing this concept within the organization. The ultimate goal is to propose feasible ‘Green IT’ practices that could be implemented within the context of Sri Lankan non-IT sectors in order to ensure that organization’s sustainable growth towards a long term existence.

Keywords: Computing practices, green IT, non-IT industries, Sri Lanka, sustainability.

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Authors: Nhon Do, Tuyen Trong Tran, Phan Hoai Truong

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Nowadays e-Learning is more popular, in Vietnam especially. In e-learning, materials for studying are very important. It is necessary to design the knowledge base systems and expert systems which support for searching, querying, solving of problems. The ontology, which was called Computational Object Knowledge Base Ontology (COB-ONT), is a useful tool for designing knowledge base systems in practice. In this paper, a design method for knowledge base systems in education using COKB-ONT will be presented. We also present the design of a knowledge base system that supports studying knowledge and solving problems in higher mathematics.

Keywords: artificial intelligence, knowledge base systems, ontology, educational software.

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Authors: Nitai Biswas, Prasenjit Kapas, Arumay Jana, Asish Paul

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Introduction: Motivation is basic drive for all kinds of action. It has direct influence on academic achievement and sports performance that builds urge to incentive values of success. In other words, it can be defined as the need for success to attain excellence. Anxiety in pre competition especially in sports formulates positive inward settings in mind to overcome the challenge. There is a tendency to perceive competitive situations as some threatening issues and to respond them with feelings of apprehension and tension. Aim: Aim of the study was to compare the achievement motivation and competition anxiety among three different classes of students. Methods and Materials: To conduct the study the researcher has taken 131 male subjects from three different classes as Extra Department, Bachelor of Physical Education-I and Master of Physical EducationII, aged 19-28 years. Achievement motivation and sports competition anxiety were measured by the questionnaire. To analyze the data mean, standard deviation for each parameter as descriptive statistics and one way analysis of variance as inferential statistics were employed. Results: From the result of the study in achievement motivation (p ≥ 0.05) and competition anxiety (p ≥ 0.05) no significant differences were found among the said three groups. Conclusion: The study concluded that all three groups had almost the same state of achievement motivation and sports competition anxiety.

Keywords: Anxiety, sports psychology, sports competition anxiety, achievement motivation, academic hierarchy.

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Authors: Masami Usui

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The 21th century has already witnessed the rapid globalization of catastrophes caused by layered political, social, religious, cultural, and environmental conflicts. The post 9/11 literature that reflects these characteristics retells the experiences of those who are, whether directly or indirectly, involved in the globalized catastrophes of enlarging and endangering their boundaries and consequences. With an Irish-Turkish origin, a Dutch and British educational background, and as an American green-card holder, Joseph O’Neill challenges this changing circumstances of the expanding crisis. In his controversial novel, Netherland (2008), O’Neill embodies the deeply-rooted compromises, the transplanted conflicts, and human internalized crisis in post 9/11 New York City. O’Neill presents to us the transition between Netherland to New York with a post-colonial perspective. This internalized conflicts are revised in The Dog (2014) in which a newly-constructing and expanding global city of gold, Dubai, represents the transitional location from New York City. Through these two novels, words and voices are migrating beyond cultural and political boundaries and discussing what a collective mind embodies in this globalized society.  

Keywords: American literature, global literature, cultural studies, political science.

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Authors: Dipankar Dhabak, Soumya Pandit

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This paper presents an adaptive technique for generation of data required for construction of artificial neural network-based performance model of nano-scale CMOS inverter circuit. The training data are generated from the samples through SPICE simulation. The proposed algorithm has been compared to standard progressive sampling algorithms like arithmetic sampling and geometric sampling. The advantages of the present approach over the others have been demonstrated. The ANN predicted results have been compared with actual SPICE results. A very good accuracy has been obtained.

Keywords: CMOS Inverter, Nano-scale, Adaptive Sampling, ArtificialNeural Network

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Authors: Truong Quang Dang Khoa, Masahiro Nakagawa

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Chaos and fractals are novel fields of physics and mathematics showing up a new way of universe viewpoint and creating many ideas to solve several present problems. In this paper, a novel algorithm based on the chaotic sequence generator with the highest ability to adapt and reach the global optima is proposed. The adaptive ability of proposal algorithm is flexible in 2 steps. The first one is a breadth-first search and the second one is a depth-first search. The proposal algorithm is examined by 2 functions, the Camel function and the Schaffer function. Furthermore, the proposal algorithm is applied to optimize training Multilayer Neural Networks.

Keywords: learning and evolutionary computing, Chaos Optimization Algorithm, Artificial Neural Networks, nonlinear optimization, intelligent computational technologies.

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Authors: Raluca Ionela Maxim

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Designing a gender responsive Science, Technology, Engineering and Mathematics (STEM) mobile game based learning solution (mGBL) is a challenge in terms of content, gamification level and equal engagement of girls and boys. The goal of this case study was to research and create a high-fidelity prototype design of a mobile game that contains role-models as avatars that guide and expose girls and boys to STEM learning content. For this research purpose it was applied the methodology of design sprint with five-phase process that combines design thinking principles. The technique of this methodology comprises smart interviews with STEM experts, mind-map creation, sketching, prototyping and usability testing of the interactive prototype of the gender responsive STEM mGBL. The results have shown that the effect of the avatar/role model had a positive impact. Therefore, by exposing students (boys and girls) to STEM role models in an mGBL tool is helpful for the decreasing of the gender inequalities in STEM fields.

Keywords: Design thinking, design sprint, gender-responsive STEM education, mobile game based learning, role-models.

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Authors: Elnaz Afshari, Siamak Najarian

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Having considered tactile sensing and palpation of a surgeon in order to detect kidney stone during open surgery; we present the 2D model of nephrolithiasis (two dimensional model of kidney containing a simulated stone). The effects of stone existence that appear on the surface of kidney (because of exerting mechanical load) are determined. Using Finite element method, it is illustrated that the created stress patterns on the surface of kidney and stress graphs not only show existence of stone inside kidney, but also show its exact location.

Keywords: Nephrolithiasis, Minimally Invasive Surgery, Artificial Tactile Sensing, Finite Element Method.

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Authors: Ahmed S. Fayed, Umima M. Mansour

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Three polyvinyl chloride membrane sensors were developed for the electrochemical evaluation of ferrous, manganese and zinc ions. The sensors were used for assaying metal ions in cervical mucus (CM) of Egyptian river buffalo-cows (Bubalus bubalis) as their levels vary dependent on cyclical hormone variation during different phases of estrus cycle. The presented sensors are based on using ionophores, β-cyclodextrin (β-CD), hydroxypropyl β-cyclodextrin (HP-β-CD) and sulfocalix-4-arene (SCAL) for sensors 1, 2 and 3 for Fe²⁺, Mn²⁺ and Zn²⁺, respectively. Dioctyl phthalate (DOP) was used as the plasticizer in a polymeric matrix of polyvinylchloride (PVC). For increasing the selectivity and sensitivity of the sensors, each sensor was enriched with a suitable complexing agent, which enhanced the sensor’s response. For sensor 1, β-CD was mixed with bathophenanthroline; for sensor 2, porphyrin was incorporated with HP-β-CD; while for sensor 3, oxine was the used complexing agent with SCAL. Linear responses of 10^-7-10^-2 M with cationic slopes of 53.46, 45.01 and 50.96 over pH range 4-8 were obtained using coated graphite sensors for ferrous, manganese and zinc ionic solutions, respectively. The three sensors were validated, according to the IUPAC guidelines. The obtained results by the presented potentiometric procedures were statistically analyzed and compared with those obtained by atomic absorption spectrophotometric method (AAS). No significant differences for either accuracy or precision were observed between the two techniques. Successful application for the determination of the three studied cations in CM, for the purpose to determine the proper time for artificial insemination (AI) was achieved. The results were compared with those obtained upon analyzing the samples by AAS. Proper detection of estrus and correct time of AI was necessary to maximize the production of buffaloes. In this experiment, 30 multi-parous buffalo-cows were in second to third lactation and weighting 415-530 kg, and were synchronized with OVSynch protocol. Samples were taken in three times around ovulation, on day 8 of OVSynch protocol, on day 9 (20 h before AI) and on day 10 (1 h before AI). Beside analysis of trace elements (Fe²⁺, Mn²⁺ and Zn²⁺) in CM using the three sensors, the samples were analyzed for the three cations and also Cu²⁺ by AAS in the CM samples and blood samples. The results obtained were correlated with hormonal analysis of serum samples and ultrasonography for the purpose of determining of the optimum time of AI. The results showed significant differences and powerful correlation with Zn²⁺ composition of CM during heat phase and the ovulation time, indicating that the parameter could be used as a tool to decide optimal time of AI in buffalo-cows.

Keywords: PVC sensors, buffalo-cows, cyclodextrins, atomic absorption spectrophotometry, artificial insemination, OVSynch protocol.

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Authors: N. AboulAtta, G. Ezizah, N. Yousif , S. Fathy

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The stilling basins are commonly used to dissipate the energy and protect the downstream floor from erosion. The aim of the present experimental work is to improve the roughened stilling basin using T-shape roughness instead of the regular cubic one and design this new shape. As a result of the present work the best intensity and the best roughness length are identified. Also, it is found that the T-shape roughness save materials and reduce the jump length compared to the cubic one. Sensitivity analysis was performed and it was noticed that the change in the length of jump is more sensitive to the change in roughness length than the change in intensity.

Keywords: hydraulic jump, energy dissipater, roughened bed, stilling basin.

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Authors: Ehsan Amid, Sina Rezaei Aghdam

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In this paper, a novel method for recognition of musical instruments in a polyphonic music is presented by using an embedded hidden Markov model (EHMM). EHMM is a doubly embedded HMM structure where each state of the external HMM is an independent HMM. The classification is accomplished for two different internal HMM structures where GMMs are used as likelihood estimators for the internal HMMs. The results are compared to those achieved by an artificial neural network with two hidden layers. Appropriate classification accuracies were achieved both for solo instrument performance and instrument combinations which demonstrates that the new approach outperforms the similar classification methods by means of the dynamic of the signal.

Keywords: hidden Markov model (HMM), embedded hidden Markov models (EHMM), MFCC, musical instrument.

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Authors: Sevil Yildiz

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In parallel, broadcasting has changed rapidly with the changing of the world at the same area. Broadcasting is also influenced and reshaped in terms of the emergence of new communication technologies. These developments have resulted a lot of economic and social consequences. The most important consequences of these results are those of the powers of the governments to control over the means of communication and control mechanisms related to the descriptions of the new issues. For this purpose, autonomous and independent regulatory bodies have been established by the state. One of these regulatory bodies is the Radio and Television Supreme Council, which to be established in 1994, with the Code no 3984. Today’s Radio and Television Supreme Council which is responsible for the regulation of the radio and television broadcasts all across Turkey has an important and effective position as autonomous and independent regulatory body. The Radio and Television Supreme Council acts as being a remarkable organizer for a sensitive area of radio and television broadcasting on one hand, and the area of democratic, liberal and keep in mind the concept of the public interest by putting certain principles for the functioning of the Board control, in the context of media policy as one of the central organs, on the other hand. In this study, the role of the Radio and Television Supreme Council is examined in accordance with the Code no 3894 in order to control over the communication and control mechanisms as well as the examination of the changes in the duties of the Code No. 6112, dated 2011.

Keywords: Regulatory Boards, Radio and Television Supreme Council.

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Authors: S. Jadid, S. Jalilzadeh

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In this paper, an improved technique for contingency ranking using artificial neural network (ANN) is presented. The proposed approach is based on multi-layer perceptrons trained by backpropagation to contingency analysis. Severity indices in dynamic stability assessment are presented. These indices are based on the concept of coherency and three dot products of the system variables. It is well known that some indices work better than others for a particular power system. This paper along with test results using several different systems, demonstrates that combination of indices with ANN provides better ranking than a single index. The presented results are obtained through the use of power system simulation (PSS/E) and MATLAB 6.5 software.

Keywords: composite indices, transient stability, neural network.

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Authors: D. Goustouridis, A. Sideris, I. Sdrolias, G. Loizos, N.-Alexander Tatlas, S. M. Potirakis

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Both daily and long-term management of a heavy-duty vehicles and construction machinery fleet is an extremely complicated and hard to solve issue. This is mainly due to the diversity of the fleet vehicles – machinery, which concerns not only the vehicle types, but also their age/efficiency, as well as the fleet volume, which is often of the order of hundreds or even thousands of vehicles/machineries. In the present paper we present “InteligentLogger”, a holistic heavy-duty fleet management system covering a wide range of diverse fleet vehicles. This is based on specifically designed hardware and software for the automated vehicle health status and operational cost monitoring, for smart maintenance. InteligentLogger is characterized by high adaptability that permits to be tailored to practically any heavy-duty vehicle/machinery (of different technologies -modern or legacy- and of dissimilar uses). Contrary to conventional logistic systems, which are characterized by raised operational costs and often errors, InteligentLogger provides a cost-effective and reliable integrated solution for the e-management and e-maintenance of the fleet members. The InteligentLogger system offers the following unique features that guarantee successful heavy-duty vehicles/machineries fleet management: (a) Recording and storage of operating data of motorized construction machinery, in a reliable way and in real time, using specifically designed Internet of Things (IoT) sensor nodes that communicate through the available network infrastructures, e.g., 3G/LTE; (b) Use on any machine, regardless of its age, in a universal way; (c) Flexibility and complete customization both in terms of data collection, integration with 3rd party systems, as well as in terms of processing and drawing conclusions; (d) Validation, error reporting & correction, as well as update of the system’s database; (e) Artificial intelligence (AI) software, for processing information in real time, identifying out-of-normal behavior and generating alerts; (f) A MicroStrategy based enterprise BI, for modeling information and producing reports, dashboards, and alerts focusing on vehicles– machinery optimal usage, as well as maintenance and scraping policies; (g) Modular structure that allows low implementation costs in the basic fully functional version, but offers scalability without requiring a complete system upgrade.

Keywords: E-maintenance, predictive maintenance, IoT sensor nodes, cost optimization, artificial intelligence, heavy-duty vehicles.

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Authors: Swapneel U. Naphade, Dushyant A. Patil, Satyabodh M. Kulkarni

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In this work, we propose the concept and geometrical design of a soil moisture control system (SMCS) module by following the product development approach to develop an inexpensive, easy to use and quick to install product targeted towards agriculture practitioners. The module delivers water to the agricultural land efficiently by sensing the soil moisture and activating the delivery valve. We start with identifying the general needs of the potential customer. Then, based on customer needs we establish product specifications and identify important measuring quantities to evaluate our product. Keeping in mind the specifications, we develop various conceptual solutions of the product and select the best solution through concept screening and selection matrices. Then, we develop the product architecture by integrating the systems into the final product. In the end, the geometric design is done using human factors engineering concepts like heuristic analysis, task analysis, and human error reduction analysis. The result of human factors analysis reveals the remedies which should be applied while designing the geometry and software components of the product. We find that to design the best grip in terms of comfort and applied force, for a power-type grip, a grip-diameter of 35 mm is the most ideal.

Keywords: Agriculture, human factors, product design, soil moisture control.

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Authors: Carlos V. Regueiro, Jose E. Domenech, Roberto Iglesias, Jose L. Correa

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In this work a visual and reactive contour following behaviour is learned by reinforcement. With artificial vision the environment is perceived in 3D, and it is possible to avoid obstacles that are invisible to other sensors that are more common in mobile robotics. Reinforcement learning reduces the need for intervention in behaviour design, and simplifies its adjustment to the environment, the robot and the task. In order to facilitate its generalisation to other behaviours and to reduce the role of the designer, we propose a regular image-based codification of states. Even though this is much more difficult, our implementation converges and is robust. Results are presented with a Pioneer 2 AT on a Gazebo 3D simulator.

Keywords: Image-based State Codification, Mobile Robotics, ReinforcementLearning, Visual Behaviour.

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Authors: Venus Marza, Amin Seyyedi, Luiz Fernando Capretz

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Software estimation accuracy is among the greatest challenges for software developers. This study aimed at building and evaluating a neuro-fuzzy model to estimate software projects development time. The forty-one modules developed from ten programs were used as dataset. Our proposed approach is compared with fuzzy logic and neural network model and Results show that the value of MMRE (Mean of Magnitude of Relative Error) applying neuro-fuzzy was substantially lower than MMRE applying fuzzy logic and neural network.

Keywords: Artificial Neural Network, Fuzzy Logic, Neuro-Fuzzy, Software Estimation

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