Search results for: Artificial communication

Authors: Talal Alsulaiman, Khaldoun Khashanah

Abstract:

In this paper, we provided a literature survey on the artificial stock problem (ASM). The paper began by exploring the complexity of the stock market and the needs for ASM. ASM aims to investigate the link between individual behaviors (micro level) and financial market dynamics (macro level). The variety of patterns at the macro level is a function of the AFM complexity. The financial market system is a complex system where the relationship between the micro and macro level cannot be captured analytically. Computational approaches, such as simulation, are expected to comprehend this connection. Agent-based simulation is a simulation technique commonly used to build AFMs. The paper proceeds by discussing the components of the ASM. We consider the roles of behavioral finance (BF) alongside the traditionally risk-averse assumption in the construction of agent’s attributes. Also, the influence of social networks in the developing of agents interactions is addressed. Network topologies such as a small world, distance-based, and scale-free networks may be utilized to outline economic collaborations. In addition, the primary methods for developing agents learning and adaptive abilities have been summarized. These incorporated approach such as Genetic Algorithm, Genetic Programming, Artificial neural network and Reinforcement Learning. In addition, the most common statistical properties (the stylized facts) of stock that are used for calibration and validation of ASM are discussed. Besides, we have reviewed the major related previous studies and categorize the utilized approaches as a part of these studies. Finally, research directions and potential research questions are argued. The research directions of ASM may focus on the macro level by analyzing the market dynamic or on the micro level by investigating the wealth distributions of the agents.

Keywords: Artificial stock markets, agent based simulation, bounded rationality, behavioral finance, artificial neural network, interaction, scale-free networks.

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Authors: Marina Laškarin, Vlado Galičić

Abstract:

Quick adoption of e-business and emerging influence of “Electronic Word of Mouth e-WOM” communication on guests made leading hotel brands successful examples of electronic guest relationship management. Main reasons behind such success are well established procedures in collection, analysis and usage of highly valuable data available on the Internet, generated through some form of e-GRM programme. E-GRM is more than just a technology solution. It’s a system which balance respective guest demands, hotel technological capabilities and organizational culture of employees, discharging the universal approach in guest relations “same for all”. The purpose of this research derives from the necessity of determining the importance of monitoring and applying e-WOM communication as one of the methods used in managing guest relations. This paper analyses and compares different hotelier’s opinions on e-WOM communication.

Keywords: Brand loyalty, e-WOM communication, GRM programmes.

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Authors: Omer F. Cansiz, Said M. Easa

Abstract:

The purpose of this study is mainly to predict collision frequency on the horizontal tangents combined with vertical curves using artificial neural network methods. The proposed ANN models are compared with existing regression models. First, the variables that affect collision frequency were investigated. It was found that only the annual average daily traffic, section length, access density, the rate of vertical curvature, smaller curve radius before and after the tangent were statistically significant according to related combinations. Second, three statistical models (negative binomial, zero inflated Poisson and zero inflated negative binomial) were developed using the significant variables for three alignment combinations. Third, ANN models are developed by applying the same variables for each combination. The results clearly show that the ANN models have the lowest mean square error value than those of the statistical models. Similarly, the AIC values of the ANN models are smaller to those of the regression models for all the combinations. Consequently, the ANN models have better statistical performances than statistical models for estimating collision frequency. The ANN models presented in this paper are recommended for evaluating the safety impacts 3D alignment elements on horizontal tangents.

Keywords: Collision frequency, horizontal tangent, 3D two-lane highway, negative binomial, zero inflated Poisson, artificial neural network.

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Authors: Martín Agüero, Franco Madou, Gabriela Esperón, Daniela López De Luise

Abstract:

This paper presents a software quality support tool, a Java source code evaluator and a code profiler based on computational intelligence techniques. It is Java prototype software developed by AI Group [1] from the Research Laboratories at Universidad de Palermo: an Intelligent Java Analyzer (in Spanish: Analizador Java Inteligente, AJI). It represents a new approach to evaluate and identify inaccurate source code usage and transitively, the software product itself. The aim of this project is to provide the software development industry with a new tool to increase software quality by extending the value of source code metrics through computational intelligence.

Keywords: Software metrics, artificial intelligence, neuralnetworks, clustering algorithms, expert systems

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Authors: Mansour I. Abbadi, Abdel-Rahman M. Jaradat

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In this paper, a technique is proposed to implement an artificial voltage-controlled capacitance or inductance which can replace the well-known varactor diode in many applications. The technique is based on injecting the current of a voltage-controlled current source onto a fixed capacitor or inductor. Then, by controlling the transconductance of the current source by an external bias voltage, a voltage-controlled capacitive or inductive reactance is obtained. The proposed voltage-controlled reactance devices can be designed to work anywhere in the frequency spectrum. Practical circuits for the proposed voltage-controlled reactances are suggested and simulated.

Keywords: voltage-controlled capacitance, voltage-controlled inductance, varactor diode, variable transconductance.

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Authors: Mohsen Hayati, Yazdan Shirvany

Abstract:

In this paper, the application of neural networks to study the design of short-term load forecasting (STLF) Systems for Illam state located in west of Iran was explored. One important architecture of neural networks named Multi-Layer Perceptron (MLP) to model STLF systems was used. Our study based on MLP was trained and tested using three years (2004-2006) data. The results show that MLP network has the minimum forecasting error and can be considered as a good method to model the STLF systems.

Keywords: Artificial neural networks, Forecasting, Multi-layer perceptron.

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Authors: Jung Ah Park, Zhijie Zhao, Doug Young Suh, Joern Ostermann

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In this paper, we propose an effective relay communication for layered video transmission as an alternative to make the most of limited resources in a wireless communication network where loss often occurs. Relaying brings stable multimedia services to end clients, compared to multiple description coding (MDC). Also, retransmission of only parity data about one or more video layer using channel coder to the end client of the relay device is paramount to the robustness of the loss situation. Using these methods in resource-constrained environments, such as real-time user created content (UCC) with layered video transmission, can provide high-quality services even in a poor communication environment. Minimal services are also possible. The mathematical analysis shows that the proposed method reduced the probability of GOP loss rate compared to MDC and raptor code without relay. The GOP loss rate is about zero, while MDC and raptor code without relay have a GOP loss rate of 36% and 70% in case of 10% frame loss rate.

Keywords: Relay communication, Multiple Description Coding, Scalable Video Coding

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Authors: A. Greco, N. Mammone, F.C. Morabito, M.Versaci

Abstract:

This paper is mainly concerned with the application of a novel technique of data interpretation to the characterization and classification of measurements of plasma columns in Tokamak reactors for nuclear fusion applications. The proposed method exploits several concepts derived from soft computing theory. In particular, Artifical Neural Networks have been exploited to classify magnetic variables useful to determine shape and position of the plasma with a reduced computational complexity. The proposed technique is used to analyze simulated databases of plasma equilibria based on ITER geometry configuration. As well as demonstrating the successful recovery of scalar equilibrium parameters, we show that the technique can yield practical advantages compares with earlier methods.

Keywords: Tokamak, sensors, artificial neural network.

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Authors: Firas M. Tuaimah

Abstract:

This paper presents an Artificial Neural Network based approach for short-term load forecasting and exactly for two days ahead. Two seasons have been discussed for Iraqi power system, namely summer and winter; the hourly load demand is the most important input variables for ANN based load forecasting. The recorded daily load profile with a lead time of 1-48 hours for July and December of the year 2012 was obtained from the operation and control center that belongs to the Ministry of Iraqi electricity.

The results of the comparison show that the neural network gives a good prediction for the load forecasting and for two days ahead.

Keywords: Short-Term Load Forecasting, Artificial Neural Networks, Back propagation learning.

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Authors: Sheroz Khan, A. F. Salami, W. A. Lawal, AHM Zahirul Alam, Shihab Abdel Hameed, M. J. E.Salami

Abstract:

In this paper, a multi-branch power line is modeled using ABCD matrix to show its worth as a communication channel. The model is simulated using MATLAB in an effort to investigate the effects of multiple loading, multipath, and those as a result of load mismatching. The channel transfer function is obtained and investigated using different cable lengths, and different number of bridge taps under given loading conditions.

Keywords: Power line Communication, Transfer Function, Channel Modeling, Signal Transmission.

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Authors: Lubna Alhinti, Heidi Christensen, Stuart Cunningham

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People with speech disorders may rely on augmentative and alternative communication (AAC) technologies to help them communicate. However, the limitations of the current AAC technologies act as barriers to the optimal use of these technologies in daily communication settings. The ability to communicate effectively relies on a number of factors that are not limited to the intelligibility of the spoken words. In fact, non-verbal cues play a critical role in the correct comprehension of messages and having to rely on verbal communication only, as is the case with current AAC technology, may contribute to problems in communication. This is especially true for people’s ability to express their feelings and emotions, which are communicated to a large part through non-verbal cues. This paper focuses on understanding more about the non-verbal communication ability of people with dysarthria, with the overarching aim of this research being to improve AAC technology by allowing people with dysarthria to better communicate emotions. Preliminary survey results are presented that gives an understanding of how people with dysarthria convey emotions, what emotions that are important for them to get across, what emotions that are difficult for them to convey, and whether there is a difference in communicating emotions when speaking to familiar versus unfamiliar people.

Keywords: Alternative and augmentative communication technology, dysarthria, speech emotion recognition, VIVOCA.

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Authors: P. H. Mukti, I. Kurniawati, F. Oktaviansyah, A. D. Adhitya, N. Rachmadani, R. Corputty, G. Hendrantoro, T. Fukusako

Abstract:

HF Communication system is one of the attractive fields among many researchers since it can be reached long-distance areas with low-cost. This long-distance communication can be achieved by exploiting the ionosphere as a transmission medium for the HF radio wave. However, due to the dynamic nature of ionosphere, the channel characteristic of HF communication has to be investigated in order to gives better performances. Many techniques to characterize HF channel are available in the literature. However, none of those techniques describe the HF channel characteristic in low-latitude regions, especially equatorial areas. Since the ionosphere around equatorial region has an ESF phenomenon, it becomes an important investigation to characterize the wideband HF Channel in low-latitude region. On the other sides, the appearance of software-defined radio attracts the interest of many researchers. Accordingly, in this paper a SDR-based channel measurement system is proposed to be used for characterizing the HF channel in low-latitude region.

Keywords: Channel Characteristic, HF Communication System, LabVIEW, Software-Defined Radio, Universal Software Radio Pheripheral.

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Authors: H. Khorashadi-Zadeh, M. R. Aghaebrahimi

Abstract:

A novel application of neural network approach to fault classification and fault location of Medium voltage cables is demonstrated in this paper. Different faults on a protected cable should be classified and located correctly. This paper presents the use of neural networks as a pattern classifier algorithm to perform these tasks. The proposed scheme is insensitive to variation of different parameters such as fault type, fault resistance, and fault inception angle. Studies show that the proposed technique is able to offer high accuracy in both of the fault classification and fault location tasks.

Keywords: Artificial neural networks, cable, fault location andfault classification.

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Authors: Anjum Iqbal, Mohd Aizaini Maarof

Abstract:

Artificial Immune System (AIS) is relatively naive paradigm for intelligent computations. The inspiration for AIS is derived from natural Immune System (IS). Classically it is believed that IS strives to discriminate between self and non-self. Most of the existing AIS research is based on this approach. Danger Theory (DT) argues this approach and proposes that IS fights against danger producing elements and tolerates others. We, the computational researchers, are not concerned with the arguments among immunologists but try to extract from it novel abstractions for intelligent computation. This paper aims to follow DT inspiration for intelligent data processing. The approach may introduce new avenue in intelligent processing. The data used is system calls data that is potentially significant in intrusion detection applications.

Keywords: artificial immune system, danger theory, intelligent processing, system calls

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Authors: A. Hossain, A. S. W. Kurny

Abstract:

The factors necessary to obtain an optimal heat treatment that influence the hardness and resistivity of Al-6Si-0.5Mg casting alloys with Cu or/and Ni additions were investigated. The alloys were homogenised (24hr at 500^oC), solutionized (2hr at 540^oC) and artificially ageing at various times and temperatures. The alloys were aged isochronally for 60 minutes at temperatures up to 400^oC and isothermally at 150, 175, 200, 225, 250 & 300^oC for different periods in the range 15 to 360 minutes. The hardness and electrical resistivity of the alloys were measured for various artificial ageing times and temperatures. From the isochronal ageing treatment, hardness found maximum ageing at 225^oC. And from the isothermal ageing treatment, hardness found maximum for 60 minutes at 225^oC. So the optimal heat treatment consists of 60 minutes ageing at 225^oC.

Keywords: Ageing, Al-Si-Mg alloy, hardness, resistivity.

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Authors: Abdolali Mortazavi, Faegheh Taheran

Abstract:

By giving an overview of previous arguments and findings concerned with the concept of competitive advantage, first, we define the overall concept of competitive advantage and discuss nuances of understanding such an important and strategic idea. Finally, by considering the major concerns of marketing academia, including globalization, Artificial Intelligence (AI)-based technologies, consumer well-being, and internal coopetition between a firm’s units, fruitful avenues to be explored by future studies are presented in the form of research propositions. In the end, relevant gaps mentioned by numerous studies that are worth investigating are demonstrated.

Keywords: Artificial Intelligence, competitive advantage, consumer well-being, coopetition, globalization, literature review, temporary competitive advantage.

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Authors: Jiří Barta

Abstract:

The paper deals with results of a project “Interoperability Workplaces to Support Teaching of Security Management in a Computer Network". This project is focused on the perspectives and possibilities of "new approaches" to education, training and crisis communication of rescue teams in the Czech Republic. It means that common technologies considering new perspectives are used to educate selected members of crisis management. The main part concentrates on possibilities of application of new technology and computer-aided tools to education and training of Integrated Rescue System teams.This project uses the COST principle for the creation of specialized centers and for all communication between these workplaces.

Keywords: Communication of Crisis Management, Information System, Interoperability, specializedcenter, Security Oriented Information System.

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Authors: B. Kuiper

Abstract:

When Dwight D. Eisenhower delivered his final Presidential speech in 1961, he was using the opportunity to bid farewell to America, but he was also trying to warn his fellow countrymen about deeper challenges threatening the country. In this analysis, Eisenhower’s speech is examined in light of the impact it had on American culture, communication concepts, and political ramifications. The paper initially highlights the previous literature on the speech, especially in light of its 50^th anniversary, and reveals a man whose main concern was how the speech’s words would affect his beloved country. The painstaking approach to the wording of the speech to reveal the intent is key, particularly in light of analyzing the motivations according to “virtuous communication.” This philosophical construct indicates that Eisenhower’s Farewell Address was crafted carefully according to a departing President’s deepest values and concerns, concepts that he wanted to pass along to his successor, to his country, and even to the world.

Keywords: Eisenhower, mass communication, political speech, rhetoric.

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Authors: Hadeel S. Haj Aliwi, Saleh A. Alomari, Putra Sumari

Abstract:

Nowadays, Multimedia Communication has been developed and improved rapidly in order to enable users to communicate between each other over the Internet. In general, the multimedia communication consists of audio and video communication. However, this paper focuses on audio streams. The audio translation between protocols is a very critical issue due to solving the communication problems between any two protocols, as well as it enables people around the world to talk with each other at anywhere and anytime even they use different protocols. In this paper, a proposed method for an audio translation module between two protocols has been presented. These two protocols are InterAsterisk eXchange Protocol (IAX) and Real Time Switching Control Protocol (RSW), which they are widely used to provide two ways audio transfer feature. The result of this work is to introduce possibility of interworking together.

Keywords: Multimedia, VoIP, Interworking, InterAsterisk eXchange Protocol (IAX), Real Time Switching Control Criteria (REW)

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Authors: Muthana Saleh Alalaki, Michael Opoku Agyeman

Abstract:

The growth in the number of Intellectual Properties (IPs) or the number of cores on the same chip becomes a critical issue in System-on-Chip (SoC) due to the intra-communication problem between the chip elements. As a result, Network-on-Chip (NoC) has emerged as a system architecture to overcome intra-communication issues. This paper presents a study of recent contributions on simulation tools for NoC. Furthermore, an overview of NoC is covered as well as a comparison between some NoC simulators to help facilitate research in on-chip communication.

Keywords: Network-on-Chip, System-on-Chip, embedded systems, computer architecture.

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Authors: Andrus Pedai, Igor Astrov

Abstract:

The focus of this paper is to compare common approaches for Systems of Innovation (SI) and identify proactive alternatives for driving the innovation. Proactive approaches will also consider short and medium term perspectives with developments in the field of Computer Technology and Artificial Intelligence. Concerning Computer Technology and Large Connected Information Systems, it is reasonable to predict that during current or the next century intelligence and innovation will be separated from the constraints of human driven management. After this happens, humans will be no longer driving the innovation and there is possibility that SI for new intelligent systems will set its own targets and exclude humans. Over long time scale these developments could result in scenario, which will lead to the development of larger, cross galactic (universal) proactive SI and Intelligence.

Keywords: Artificial intelligence, DARPA, Moore’s law, proactive innovation, singularity, systems of innovation.

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Authors: Mughal Yar M, Israr Ul Haq, Bushra Noman

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The stem cells have ability to differentiated themselves through mitotic cell division and various range of specialized cell types. Cellular differentiation is a way by which few specialized cell develops into more specialized.This paper studies the fundamental problem of computational schema for an artificial neural network based on chemical, physical and biological variables of state. By doing this type of study system could be model for a viable propagation of various economically important stem cells differentiation. This paper proposes various differentiation outcomes of artificial neural network into variety of potential specialized cells on implementing MATLAB version 2009. A feed-forward back propagation kind of network was created to input vector (five input elements) with single hidden layer and one output unit in output layer. The efficiency of neural network was done by the assessment of results achieved from this study with that of experimental data input and chosen target data. The propose solution for the efficiency of artificial neural network assessed by the comparatative analysis of “Mean Square Error" at zero epochs. There are different variables of data in order to test the targeted results.

Keywords: Computational shcmin, meiosis, mitosis, neuralnetwork, Stem cell SOM;

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Authors: Farzaneh Ahmadzadeh

Abstract:

Quality control charts are very effective in detecting out of control signals but when a control chart signals an out of control condition of the process mean, searching for a special cause in the vicinity of the signal time would not always lead to prompt identification of the source(s) of the out of control condition as the change point in the process parameter(s) is usually different from the signal time. It is very important to manufacturer to determine at what point and which parameters in the past caused the signal. Early warning of process change would expedite the search for the special causes and enhance quality at lower cost. In this paper the quality variables under investigation are assumed to follow a multivariate normal distribution with known means and variance-covariance matrix and the process means after one step change remain at the new level until the special cause is being identified and removed, also it is supposed that only one variable could be changed at the same time. This research applies artificial neural network (ANN) to identify the time the change occurred and the parameter which caused the change or shift. The performance of the approach was assessed through a computer simulation experiment. The results show that neural network performs effectively and equally well for the whole shift magnitude which has been considered.

Keywords: Artificial neural network, change point estimation, monte carlo simulation, multivariate exponentially weighted movingaverage

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Authors: N. N. Mosola, S. J. Molete, L. S. Masoebe, M. Letsae

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Hand gesture recognition is a technique used to locate, detect, and recognize a hand gesture. Detection and recognition are concepts of Artificial Intelligence (AI). AI concepts are applicable in Human Computer Interaction (HCI), Expert systems (ES), etc. Hand gesture recognition can be used in sign language interpretation. Sign language is a visual communication tool. This tool is used mostly by deaf societies and those with speech disorder. Communication barriers exist when societies with speech disorder interact with others. This research aims to build a hand recognition system for Lesotho’s Sesotho and English language interpretation. The system will help to bridge the communication problems encountered by the mentioned societies. The system has various processing modules. The modules consist of a hand detection engine, image processing engine, feature extraction, and sign recognition. Detection is a process of identifying an object. The proposed system uses Canny pruning Haar and Haarcascade detection algorithms. Canny pruning implements the Canny edge detection. This is an optimal image processing algorithm. It is used to detect edges of an object. The system employs a skin detection algorithm. The skin detection performs background subtraction, computes the convex hull, and the centroid to assist in the detection process. Recognition is a process of gesture classification. Template matching classifies each hand gesture in real-time. The system was tested using various experiments. The results obtained show that time, distance, and light are factors that affect the rate of detection and ultimately recognition. Detection rate is directly proportional to the distance of the hand from the camera. Different lighting conditions were considered. The more the light intensity, the faster the detection rate. Based on the results obtained from this research, the applied methodologies are efficient and provide a plausible solution towards a light-weight, inexpensive system which can be used for sign language interpretation.

Keywords: Canny pruning, hand recognition, machine learning, skin tracking.

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Authors: Boudene Maamar, Xu Mai

Abstract:

Optical Intersatellite Links (OISLs) are wireless communications using optical signals to interconnect satellites. It is expected to be the next generation wireless communication technology according to its inherent characteristics like: an increased bandwidth, a high data rate, a data transmission security, an immunity to interference, and an unregulated spectrum etc. Optical space links are the best choice for the classical communication schemes due to its distinctive properties; high frequency, small antenna diameter and lowest transmitted power, which are critical factors to define a space communication. This paper discusses the development of free space technology and analyses the parameters and factors to establish a reliable intersatellite links using an optical signal to exchange data between satellites.

Keywords: Optical intersatellite links, optical wireless communications, free space optical communications, next generation wireless communication.

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Authors: G. Settanni, A. Panarese, R. Vaira, A. Galiano

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Nowadays, artificial intelligence is used successfully in the field of e-commerce for its ability to learn from a large amount of data. In this research study, a prototype software platform was designed and implemented in order to suggest to users the most suitable products for their needs. The platform includes a recommender system based on artificial intelligence algorithms that provide suggestions and decision support to the customer. Specifically, support vector machine algorithms have been implemented combined with natural language processing techniques that allow the user to interact with the system, express their requests and receive suggestions. The interested user can access the web platform on the internet using a computer, tablet or mobile phone, register, provide the necessary information and view the products that the system deems them the most appropriate. The platform also integrates a dashboard that allows the use of the various functions, which the platform is equipped with, in an intuitive and simple way. Also, Long Short-Term Memory algorithms have been implemented and trained on historical data in order to predict customer scores of the different items. Items with the highest scores are recommended to customers.

Keywords: Deep Learning, Long Short-Term Memory, Machine Learning, Recommender Systems, Support Vector Machine.

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Authors: K. Raghuwaiya, B. Sharma, J. Vanualailai

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This paper presents a set of artificial potential field functions that improves upon, in general, the motion planning and posture control, with theoretically guaranteed point and posture stabilities, convergence and collision avoidance properties of the general3-trailer system in a priori known environment. We basically design and inject two new concepts; ghost walls and the distance optimization technique (DOT) to strengthen point and posture stabilities, in the sense of Lyapunov, of our dynamical model. This new combination of techniques emerges as a convenient mechanism for obtaining feasible orientations at the target positions with an overall reduction in the complexity of the navigation laws. Simulations are provided to demonstrate the effectiveness of the controls laws.

Keywords: Artificial potential fields, 3-trailer systems, motion planning, posture.

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Authors: Tiina Brandt, Isaac Wanasika

Abstract:

Culturally diverse global companies need to understand cultural differences between leaders and employees from different backgrounds. Communication is culturally contingent and has a significant impact on effective execution of leadership goals. The awareness of cultural variations related to communication and interactions will help leaders modify their own behavior, and consequently improve the execution of goals and avoid unnecessary faux pas. Our focus is on young adults that have experienced cultural integration, culturally diverse surroundings in schools and universities, and cultural travels. Our central research problem is to understand the impact of different national cultures on communication. We focus on four countries with distinct national cultures and spatial distribution. The countries are Finland, Indonesia, Russia and USA. Our sample is based on business students (n = 225) from various backgrounds in the four countries. Their responses of communication and leadership styles were analyzed using ANOVA and post-hoc test. Results indicate that culture impacts on communication behavior. Even young culturally-exposed adults with cultural awareness and experience demonstrate cultural differences in their behavior. Apparently, culture is a deeply seated trait that cannot be completely neutralized by environmental variables. Our study offers valuable input for leadership training programs and for expatriates when recognizing specific differences on leaders’ behavior due to culture.

Keywords: Culture, communication, Finland, Indonesia, Russia, USA.

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Authors: José Neves, M. Rosário Martins, Fátima Candeias, Diana Ferreira, Sílvia Arantes, Júlio Cruz-Morais, Guida Gomes, Joaquim Macedo, António Abelha, Henrique Vicente

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Some plants of genus Schinus have been used in the folk medicine as topical antiseptic, digestive, purgative, diuretic, analgesic or antidepressant, and also for respiratory and urinary infections. Chemical composition of essential oils of S. molle and S. terebinthifolius had been evaluated and presented high variability according with the part of the plant studied and with the geographic and climatic regions. The pharmacological properties, namely antimicrobial, anti-tumoural and anti-inflammatory activities are conditioned by chemical composition of essential oils. Taking into account the difficulty to infer the pharmacological properties of Schinus essential oils without hard experimental approach, this work will focus on the development of a decision support system, in terms of its knowledge representation and reasoning procedures, under a formal framework based on Logic Programming, complemented with an approach to computing centered on Artificial Neural Networks and the respective Degree-of-Confidence that one has on such an occurrence.

Keywords: Artificial neuronal networks, essential oils, knowledge representation and reasoning, logic programming, Schinus molle L, Schinus terebinthifolius raddi.

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Authors: Djalal Eddine Khodja, Boukhemis Chetate

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In this paper, an automatic system of diagnosis was developed to detect and locate in real time the defects of the wound rotor asynchronous machine associated to electronic converter. For this purpose, we have treated the signals of the measured parameters (current and speed) to use them firstly, as indicating variables of the machine defects under study and, secondly, as inputs to the Artificial Neuron Network (ANN) for their classification in order to detect the defect type in progress. Once a defect is detected, the interpretation system of information will give the type of the defect and its place of appearance.

Keywords: Artificial Neuron Networks (ANN), Effective Value (RMS), Experimental results, Failure detection Indicating values, Motor-converter unit.

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