Search results for: virtual learning environment

Authors: Farhad Asadi, Mohammad Javad Mollakazemi

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In this paper, Bayesian online inference in models of data series are constructed by change-points algorithm, which separated the observed time series into independent series and study the change and variation of the regime of the data with related statistical characteristics. variation of statistical characteristics of time series data often represent separated phenomena in the some dynamical system, like a change in state of brain dynamical reflected in EEG signal data measurement or a change in important regime of data in many dynamical system. In this paper, prediction algorithm for studying change point location in some time series data is simulated. It is verified that pattern of proposed distribution of data has important factor on simpler and smother fluctuation of hazard rate parameter and also for better identification of change point locations. Finally, the conditions of how the time series distribution effect on factors in this approach are explained and validated with different time series databases for some dynamical system.

Keywords: Time series, fluctuation in statistical characteristics, optimal learning.

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Authors: Parvinder S. Sandhu, Sunil Khullar, Satpreet Singh, Simranjit K. Bains, Manpreet Kaur, Gurvinder Singh

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Fault-proneness of a software module is the probability that the module contains faults. To predict faultproneness of modules different techniques have been proposed which includes statistical methods, machine learning techniques, neural network techniques and clustering techniques. The aim of proposed study is to explore whether metrics available in the early lifecycle (i.e. requirement metrics), metrics available in the late lifecycle (i.e. code metrics) and metrics available in the early lifecycle (i.e. requirement metrics) combined with metrics available in the late lifecycle (i.e. code metrics) can be used to identify fault prone modules using Genetic Algorithm technique. This approach has been tested with real time defect C Programming language datasets of NASA software projects. The results show that the fusion of requirement and code metric is the best prediction model for detecting the faults as compared with commonly used code based model.

Keywords: Genetic Algorithm, Fault Proneness, Software Faultand Software Quality.

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Authors: Sunny Arora, Meghal A. Desai

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An impetus towards green consumerism and implementation of sustainable techniques, consumption of natural products and utilization of environment friendly techniques have gained accelerated acceptance. Butein, a natural colorant, has many medicinal properties apart from its use in dyeing industries. Extraction of butein from the flowers of flame of forest was carried out using ultrasonication bath. Solid loading (2-6 g), extraction time (30-50 min), volume of solvent (30-50 mL) and types of solvent (methanol, ethanol and water) have been studied to maximize the yield of butein using the Taguchi method. The highest yield of butein 4.67% (w/w) was obtained using 4 g of plant material, 40 min of extraction time and 30 mL volume of methanol as a solvent. The present method provided a greater reduction in extraction time compared to the conventional method of extraction. Hence, the outcome of the present investigation could further be utilized to develop the method at a higher scale.

Keywords: Butein, flowers of flame of forest, Taguchi method, ultrasonic bath.

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Authors: Tayebeh Saghapour, Sara Moridpour, Russell George Thompson

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One of the common aims of transport policy makers is to switch people’s travel to active transport. For this purpose, a variety of transport goals and investments should be programmed to increase the propensity towards active transport mode choice. This paper aims to investigate whether built environment features in neighbourhoods could enhance the odds of active transportation. The present study introduces an index measuring public transport accessibility (PTAI), and a walkability index along with socioeconomic variables to investigate mode choice behaviour. Using travel behaviour data, an ordered logit regression model is applied to examine the impacts of explanatory variables on walking trips. The findings indicated that high rates of active travel are consistently associated with higher levels of walking and public transport accessibility.

Keywords: Active transport, public transport accessibility, walkability, ordered logit model.

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Authors: Payam Mousavi, Andrew L. Stewart, Huiwen You, Aryeh F. G. Fayerman

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We present a decision-support tool to assist an operator in the detection and tracking of a suspect vehicle traveling to an unknown target destination. Multiple data sources, such as traffic cameras, traffic information, weather, etc., are integrated and processed in real-time to infer a suspect’s intended destination chosen from a list of pre-determined high-value targets. Previously, we presented our work in the detection and tracking of vehicles using traffic and airborne cameras. Here, we focus on the fusion and processing of that information to predict a suspect’s behavior. The network of cameras is represented by a directional graph, where the edges correspond to direct road connections between the nodes and the edge weights are proportional to the average time it takes to travel from one node to another. For our experiments, we construct our graph based on the greater Los Angeles subset of the Caltrans’s “Performance Measurement System” (PeMS) dataset. We propose a Bayesian approach where a posterior probability for each target is continuously updated based on detections of the suspect in the live video feeds. Additionally, we introduce the concept of ‘soft interventions’, inspired by the field of Causal Inference. Soft interventions are herein defined as interventions that do not immediately interfere with the suspect’s movements; rather, a soft intervention may induce the suspect into making a new decision, ultimately making their intent more transparent. For example, a soft intervention could be temporarily closing a road a few blocks from the suspect’s current location, which may require the suspect to change their current course. The objective of these interventions is to gain the maximum amount of information about the suspect’s intent in the shortest possible time. Our system currently operates in a human-on-the-loop mode where at each step, a set of recommendations are presented to the operator to aid in decision-making. In principle, the system could operate autonomously, only prompting the operator for critical decisions, allowing the system to significantly scale up to larger areas and multiple suspects. Once the intended target is identified with sufficient confidence, the vehicle is reported to the authorities to take further action. Other recommendations include a selection of road closures, i.e., soft interventions, or to continue monitoring. We evaluate the performance of the proposed system using simulated scenarios where the suspect, starting at random locations, takes a noisy shortest path to their intended target. In all scenarios, the suspect’s intended target is unknown to our system. The decision thresholds are selected to maximize the chances of determining the suspect’s intended target in the minimum amount of time and with the smallest number of interventions. We conclude by discussing the limitations of our current approach to motivate a machine learning approach, based on reinforcement learning in order to relax some of the current limiting assumptions.

Keywords: Autonomous surveillance, Bayesian reasoning, decision-support, interventions, patterns-of-life, predictive analytics, predictive insights.

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Authors: Ugur Karakaya, Hasan Bulent Kantarcı

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In this study, firstly democratic thoughts which directly or indirectly affect economic development and/or the interaction between authoritarian regimes and the economic development and the direction and channels of this interaction were studied and then the study tried to determine how democracy affects economic development. It was concluded that the positive contributions of democracy to economic development were more determinant than the effects that were either negative or restrictive in terms of development. When compared to autocracy, since democracy is more successful in managing social conflicts, ensuring political stability and preventing social disasters such as famine, it contributes more to economic development. Democracy also facilitates delegation of authority, provides a stable investment environment and accelerates mobilization of resources in accordance with economic growth/development. Democracy leads to an increase in human capital accumulation and increases the growth rate through reducing income inequality. It can be said that democratic regimes are the most appropriate ones in terms of increasing economic performance and supporting economic development through their strong institutional structures and the assurance they will ensure in property rights.

Keywords: Autocratic Regime, Democracy, Economic Development, Economic Freedom.

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Authors: Houshmand E. Masoumi

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Residential self-selection has gained increasing attention in the Western travel behavior research during the past decade. Many studies in the US, UK, and Germany conclude that the role of individuals’ residential location choice on commute travel behavior is more important than that of the built environment or at least it has considerable effects. However the effectiveness of location choice in many countries and cultures like Iran is unclear. This study examines the self-selections in two neighborhoods in Tehran. As a part of a research about the influences of land use on travel behavior information about people’s location preferences was collected by direct questioning. The findings show that the main reasons for selecting the location of residential units are related to socio-economic factors such as rise of house price and affordability of house prices. Transportation has little impacts on location decisions. Moreover, residential self-selection accounts for only 3 to 7.5 percent of the pedestrian, PT, and car trips.

Keywords: Residential self-selection, Tehran, travel behavior, urban transportation.

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Authors: Ishrar Tabassum, Jay Andrew Saptok, Khalid Raihan Kabir, Elmee Tabassum

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The purpose of this study is to bring light to the current state of the working environments in the corporate environment and other such institutions with a particular focus on the Bangladesh National Building Code (BNBC) and its guidelines for accommodating the physically disabled. Data were collected via semi-formal interviews, site visits and focus groups conducted using a preset questionnaire as the guidelines. After conducting surveys at corporate offices of 20 organizations from major commercial sectors in Dhaka city, the auditing showed many inadequacies, as aside from the larger corporate offices, the offices have little to no accessibility for the physically disabled. This study hopes to shed light on the fact that the existing BNBCs lack of emphasis on ensuring the accessibility of the handicapped in corporate buildings in the hope that, in the future, the physically disabled will have greater opportunities at being productive members of the workforce.

Keywords: Person with disability, PWD, corporate buildings, Dhaka City.

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Authors: K. M. Doraiswamy, Lakshminarayana Merugu, B. C. Jinaga

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This paper explains the cause of nonlinearity in floor attenuation hither to left unexplained. The performance degradation occurring in air interface for GSM signals is quantitatively analysed using the concept of Radiating Columns of buildings. The signal levels were measured using Wireless Network Optimising Drive Test Tool (E6474A of Agilent Technologies). The measurements were taken in reflected signal environment under usual fading conditions on actual GSM signals radiated from base stations. A mathematical model is derived from the measurements to predict the GSM signal levels in different floors. It was applied on three buildings and found that the predicted signal levels deviated from the measured levels with in +/- 2 dB for all floors. It is more accurate than the prediction models based on Floor Attenuation Factor. It can be used for planning proper indoor coverage in multi storey buildings.

Keywords: GSM air interface, nonlinear attenuation, multistory building, radiating columns, ground conduction and floor attenuation factor.

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Authors: Usa Sutthisakorn, Samchai Jirapatarasil

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This paper aims to present knowledge management for solving economic problem and poverty in Thai community. A community in Thailand is studied as a case study for master plan or social and economic plan which derived form the research people conducted by themselves in their community. The result shows that community uses knowledge management in recording income and expense, analyzing their consumption, and then systematic planning of the production, distribution and consumption in the community. Besides, community enterprises, that people create as the by-products of master plan, can facilitate diverse economic activities which are able to reduce economic problem and poverty. The knowledge that people gain from solving their problem through building community enterprises are both tacit and explicit knowledge. Four styles of knowledge conversion: socialization,externalization, combination and internalization, are used. Besides, knowledge sharing inside the organization, between organizations and its environment are found. Keywordsknowledge management, community enterprise, Thailand.

Keywords: knowledge management, community enterprise, Thailand

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Authors: Jocelyn Sackey, Priscilla Boahemaa, Mohammed A. Sanda

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This study explored the relationship between occupational stress and the perceived effectiveness of men and women managers in Ghanaian organizations. The exploration is underlined by attempt to understand the degree to which male and female managers in Ghanaian organizations experience occupational stress at the workplace. The purpose is to examine the sources and extents of occupational stress experienced by male and female managers in Ghana. Data was collected using questionnaires and analyzed using both descriptive statistics and correlation analysis. The results showed that female managers in Ghana are more likely to report of more stress experiences in the workplace than their male counterparts. The female managers are more likely to perceive role conflict and alienation as job stressors while the male managers perceived blocked career as a major source of workplace stress. It is concluded that despite the female managers experiencing enormous level of occupational stress, there was no significant differences between their managerial effectiveness and that of the male.

Keywords: Gender, job stress, managerial effectiveness, organizational environment

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Authors: Elham Serkani, Hossein Gharaee Garakani, Naser Mohammadzadeh, Elaheh Vaezpour

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Intrusion detection systems (IDS) are the main components of network security. These systems analyze the network events for intrusion detection. The design of an IDS is through the training of normal traffic data or attack. The methods of machine learning are the best ways to design IDSs. In the method presented in this article, the pruning algorithm of C5.0 decision tree is being used to reduce the features of traffic data used and training IDS by the least square vector algorithm (LS-SVM). Then, the remaining features are arranged according to the predictor importance criterion. The least important features are eliminated in the order. The remaining features of this stage, which have created the highest level of accuracy in LS-SVM, are selected as the final features. The features obtained, compared to other similar articles which have examined the selected features in the least squared support vector machine model, are better in the accuracy, true positive rate, and false positive. The results are tested by the UNSW-NB15 dataset.

Keywords: Intrusion detection system, decision tree, support vector machine, feature selection.

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Authors: Hui Fang Huang Su, Leanne Lai, Pei-Fen Li, Mei-Hwei Ho, Yu-Wen Chiu

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This study aimed to provide a practical, systematic, and comprehensive intervention for children with Autism Spectrum Disorder (ASD). A pilot study of quasi-experimental pre-post intervention with control group design was conducted to evaluate if the mathematical intervention (Project MIND - Math Is Not Difficult) increases the math comprehension of children with ASD Children with ASD in the primary grades (K-1, 2) participated in math interventions to enhance their math comprehension and cognitive ability. The Bracken basic concept scale was used to evaluate subjects’ language skills, cognitive development, and school readiness. The study found that our systemic interventions of Project MIND significantly improved the mathematical and cognitive abilities in children with autism. The results of this study may lead to a major change in effective and adequate health care services for children with ASD and their families. All statistical analyses were performed with the IBM SPSS Statistics Version 25 for Windows. The significant level was set at 0.05 P-value.

Keywords: Young Children, Autism, Mathematics, Curriculum, teaching and learning, children with special needs, Project MIND.

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Authors: Hala Abdel hameed, Hazem M. El-Bakry, Torky Sultan

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There are many issues that affect modeling and designing real-time databases. One of those issues is maintaining consistency between the actual state of the real-time object of the external environment and its images as reflected by all its replicas distributed over multiple nodes. The need to improve the scalability is another important issue. In this paper, we present a general framework to design a replicated real-time database for small to medium scale systems and maintain all timing constrains. In order to extend the idea for modeling a large scale database, we present a general outline that consider improving the scalability by using an existing static segmentation algorithm applied on the whole database, with the intent to lower the degree of replication, enables segments to have individual degrees of replication with the purpose of avoiding excessive resource usage, which all together contribute in solving the scalability problem for DRTDBS.

Keywords: Database modeling, Distributed database, Real time databases, Replication

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Authors: M. Saleem Khan, Khaled Benkrid

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This paper presents the development techniques for a complete autonomous design model of an advanced train control system and gives a new approach for the implementation of multi-agents based system. This research work proposes to develop a novel control system to enhance the efficiency of the vehicles under constraints of various conditions, and contributes in stability and controllability issues, considering relevant safety and operational requirements with command control communication and various sensors to avoid accidents. The approach of speed scheduling, management and control in local and distributed environment is given to fulfill the dire needs of modern trend and enhance the vehicles control systems in automation. These techniques suggest the state of the art microelectronic technology with accuracy and stability as forefront goals.

Keywords: Multi-agents, Railway vehicle control system, autonomous design, Train management, Speed scheduling andcontrol.

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Authors: Bassam Istanbouli

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Organizations are living in a very competitive and dynamic environment which is constantly changing. In order to achieve a high level of service, the products and processes of these organizations need to be flexible and evolvable. If the supply chains are not modular and well designed, changes can bring combinatorial effects to most areas of a company from its management, financial, documentation, logistics and its information structure. Applying the normalized system’s concept to segments of the supply chain may help in reducing those ripple effects, but it may also increase lead times. Lead times are important and can become a decisive element in gaining customers. Industries are always under the pressure in providing good quality products, at competitive prices, when and how the customer wants them. Most of the time, the customers want their orders now, if not yesterday. The above concept will be proven by examining lead times in a manufacturing example before and after applying normalized systems concept to that segment of the chain. We will then show that although we can minimize the combinatorial effects when changes occur, the lead times will be increased.

Keywords: Supply chain, lead time, normalization, modular.

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Authors: Stefanie Rukavina, Sascha Gruss, Steffen Walter, Holger Hoffmann, Harald C. Traue

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OPEN_EmoRec_II is an open multimodal corpus with experimentally induced emotions. In the first half of the experiment, emotions were induced with standardized picture material and in the second half during a human-computer interaction (HCI), realized with a wizard-of-oz design. The induced emotions are based on the dimensional theory of emotions (valence, arousal and dominance). These emotional sequences - recorded with multimodal data (facial reactions, speech, audio and physiological reactions) during a naturalistic-like HCI-environment one can improve classification methods on a multimodal level. This database is the result of an HCI-experiment, for which 30 subjects in total agreed to a publication of their data including the video material for research purposes*. The now available open corpus contains sensory signal of: video, audio, physiology (SCL, respiration, BVP, EMG Corrugator supercilii, EMG Zygomaticus Major) and facial reactions annotations.

Keywords: Open multimodal emotion corpus, annotated labels.

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Authors: Stefanie Rukavina, Sascha Gruss, Steffen Walter, Holger Hoffmann, Harald C. Traue

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OPEN_EmoRec_II is an open multimodal corpus with experimentally induced emotions. In the first half of the experiment, emotions were induced with standardized picture material and in the second half during a human-computer interaction (HCI), realized with a wizard-of-oz design. The induced emotions are based on the dimensional theory of emotions (valence, arousal and dominance). These emotional sequences - recorded with multimodal data (facial reactions, speech, audio and physiological reactions) during a naturalistic-like HCI-environment one can improve classification methods on a multimodal level. This database is the result of an HCI-experiment, for which 30 subjects in total agreed to a publication of their data including the video material for research purposes*. The now available open corpus contains sensory signal of: video, audio, physiology (SCL, respiration, BVP, EMG Corrugator supercilii, EMG Zygomaticus Major) and facial reactions annotations.

Keywords: Open multimodal emotion corpus, annotated labels.

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Authors: Proud Arunrangsiwed, Sarinya Kongtieng

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Teachers and university lecturers face an unsolved problem, which is students’ multitasking behaviors during class time, such as texting or playing a game. It is important to examine the most powerful predictor that can result in students’ educational performances. Meta-analysis was used to analyze the research articles, which were published with the keywords, multitasking, class performance, and texting. We selected 14 research articles published during 2008-2013 from online databases, and four articles met the predetermined inclusion criteria. Effect size of each pair of variables was used as the dependent variable. The findings revealed that the students’ expectancy and value on SNSs usages is the best significant predictor of their educational performances, followed by their motivation and ability in using SNSs, prior educational performances, usage behaviors of SNSs in class, and their personal characteristics, respectively. Future study should conduct a longitudinal design to better understand the effect of multitasking in the classroom.

Keywords: Meta-regression analysis, social networking site use, academic performance, multitasking, motivation.

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Authors: Nirjhar Roy, V. R. Komma, Jitendra Kumar

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In the supply chain management customer is the most significant component and mass customization is mostly related to customers because it is the capability of any industry or organization to deliver highly customized products and its services to the respective customers with flexibility and integration, providing such a variety of products that nearly everyone can find what they want. Today all over the world many companies and markets are facing varied situations that at one side customers are demanding that their orders should be completed as quickly as possible while on other hand it requires highly customized products and services. By applying mass customization some companies face unwanted cost and complexity. Now they are realizing that they should completely examine what kind of customization would be best suited for their companies. In this paper authors review some approaches and principles which show effect in supply chain management that can be adopted and used by companies for quickly meeting the customer orders at reduced cost, with minimum amount of inventory and maximum efficiency.

Keywords: Mass customization and supply chain management.

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Authors: S. Graeff-Hönninger, J. Pfenning, V. Gutsal, S. Wolf, S. Zikeli, W. Claupein

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Broccoli is considered as being a rich source of AOX like flavonoids, polyphenols, anthocyanins etc. and of major interest especially in the organic sector. However, AOX is environment dependent and often varies between cultivars. Aim of the study was to investigate the impact of cultivar and harvest date on AOX in broccoli. Activity of the AOX was determined using a Photochem®-Analyzer and a kit of reagent solutions for analysis. Results of the study showed that the lipid (ACL) and water-soluble antioxidant potential (AWC) of broccoli heads varied significantly between the four harvesting dates, but not among the different cultivars. The highest concentration of ACL was measured in broccoli heads harvested in September 2011, followed by heads harvested at the beginning of July in 2012. ACW was highest in heads harvested in October 2011. Lowest concentrations of ACW were measured in heads harvested in June 2012. Overall, the study indicated that the harvest date and thus growing conditions seem to be of high importance for final antioxidant capacity of broccoli.

Keywords: Antioxidant activity, open pollinating, organic agriculture.

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Authors: Roselyn A. Maaño

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Eyes are an essential and conspicuous organ of the human body. Human eyes are outward and inward portals of the body that allows to see the outside world and provides glimpses into ones inner thoughts and feelings. Inevitable blindness and visual impairments may results from eye-related disease, trauma, or congenital or degenerative conditions that cannot be corrected by conventional means. The study emphasizes innovative tools that will serve as an aid to the blind and visually impaired (VI) individuals. The researchers fabricated a prototype that utilizes the Microsoft Kinect for Windows and Arduino microcontroller board. The prototype facilitates advanced gesture recognition, voice recognition, obstacle detection and indoor environment navigation. Open Computer Vision (OpenCV) performs image analysis, and gesture tracking to transform Kinect data to the desired output. A computer vision technology device provides greater accessibility for those with vision impairments.

Keywords: Algorithms, Blind, Computer Vision, Embedded Systems, Image Analysis.

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Authors: S. M. Biondi, V. Catania, R. Di Natale, A. R. Intilisano, D. Panno

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One of the major goals of Spoken Dialog Systems (SDS) is to understand what the user utters. In the SDS domain, the Spoken Language Understanding (SLU) Module classifies user utterances by means of a pre-definite conceptual knowledge. The SLU module is able to recognize only the meaning previously included in its knowledge base. Due the vastity of that knowledge, the information storing is a very expensive process. Updating and managing the knowledge base are time-consuming and error-prone processes because of the rapidly growing number of entities like proper nouns and domain-specific nouns. This paper proposes a solution to the problem of Name Entity Recognition (NER) applied to a SDS domain. The proposed solution attempts to automatically recognize the meaning associated with an utterance by using the PANKOW (Pattern based Annotation through Knowledge On the Web) method at runtime. The method being proposed extracts information from the Web to increase the SLU knowledge module and reduces the development effort. In particular, the Google Search Engine is used to extract information from the Facebook social network.

Keywords: Spoken Dialog System, Spoken Language Understanding, Web Semantic, Name Entity Recognition.

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Authors: S. K. Aruna, S. Chitra

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This research paper presents a framework for classifying Magnetic Resonance Imaging (MRI) images for Dementia. Dementia, an age-related cognitive decline is indicated by degeneration of cortical and sub-cortical structures. Characterizing morphological changes helps understand disease development and contributes to early prediction and prevention of the disease. Modelling, that captures the brain’s structural variability and which is valid in disease classification and interpretation is very challenging. Features are extracted using Gabor filter with 0, 30, 60, 90 orientations and Gray Level Co-occurrence Matrix (GLCM). It is proposed to normalize and fuse the features. Independent Component Analysis (ICA) selects features. Support Vector Machine (SVM) classifier with different kernels is evaluated, for efficiency to classify dementia. This study evaluates the presented framework using MRI images from OASIS dataset for identifying dementia. Results showed that the proposed feature fusion classifier achieves higher classification accuracy.

Keywords: Magnetic resonance imaging, dementia, Gabor filter, gray level co-occurrence matrix, support vector machine.

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Authors: Tatsuya Kasuga, Hidehisa Shimada, Kimio Oguchi

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Recent rapid progress in ICT (Information and Communication Technology) has advanced the penetration of sensor networks (SNs) and their attractive applications. Agriculture is one of the fields well able to benefit from ICT. Plant factories control several parameters related to plant growth in closed areas such as air temperature, humidity, water, culture medium concentration, and artificial lighting by using computers and AI (Artificial Intelligence) is being researched in order to obtain stable and safe production of vegetables and medicinal plants all year anywhere, and attain self-sufficiency in food. By providing isolation from the natural environment, a plant factory can achieve higher productivity and safe products. However, the biggest issue with plant factories is the return on investment. Profits are tenuous because of the large initial investments and running costs, i.e. electric power, incurred. At present, LED (Light Emitting Diode) lights are being adopted because they are more energy-efficient and encourage photosynthesis better than the fluorescent lamps used in the past. However, further cost reduction is essential. This paper introduces experiments that reveal which color of LED lighting best enhances the growth of cultured radish sprouts. Radish sprouts were cultivated in the experimental environment formed by a hydroponics kit with three cultivation shelves (28 samples per shelf) each with an artificial lighting rack. Seven LED arrays of different color (white, blue, yellow green, green, yellow, orange, and red) were compared with a fluorescent lamp as the control. Lighting duration was set to 12 hours a day. Normal water with no fertilizer was circulated. Seven days after germination, the length, weight and area of leaf of each sample were measured. Electrical power consumption for all lighting arrangements was also measured. Results and discussions: As to average sample length, no clear difference was observed in terms of color. As regards weight, orange LED was less effective and the difference was significant (p < 0.05). As to leaf area, blue, yellow and orange LEDs were significantly less effective. However, all LEDs offered higher productivity per W consumed than the fluorescent lamp. Of the LEDs, the blue LED array attained the best results in terms of length, weight and area of leaf per W consumed. Conclusion and future works: An experiment on radish sprout cultivation under 7 different color LED arrays showed no clear difference in terms of sample size. However, if electrical power consumption is considered, LEDs offered about twice the growth rate of the fluorescent lamp. Among them, blue LEDs showed the best performance. Further cost reduction e.g. low power lighting remains a big issue for actual system deployment. An automatic plant monitoring system with sensors is another study target.

Keywords: Electric power consumption, LED color, LED lighting, plant factory.

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Authors: Alicia Heraz, Claude Frasson

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This paper investigates how the use of machine learning techniques can significantly predict the three major dimensions of learner-s emotions (pleasure, arousal and dominance) from brainwaves. This study has adopted an experimentation in which participants were exposed to a set of pictures from the International Affective Picture System (IAPS) while their electrical brain activity was recorded with an electroencephalogram (EEG). The pictures were already rated in a previous study via the affective rating system Self-Assessment Manikin (SAM) to assess the three dimensions of pleasure, arousal, and dominance. For each picture, we took the mean of these values for all subjects used in this previous study and associated them to the recorded brainwaves of the participants in our study. Correlation and regression analyses confirmed the hypothesis that brainwave measures could significantly predict emotional dimensions. This can be very useful in the case of impassive, taciturn or disabled learners. Standard classification techniques were used to assess the reliability of the automatic detection of learners- three major dimensions from the brainwaves. We discuss the results and the pertinence of such a method to assess learner-s emotions and integrate it into a brainwavesensing Intelligent Tutoring System.

Keywords: Algorithms, brainwaves, emotional dimensions, performance.

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Authors: Rossi A. Hassad

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There is widespread emphasis on reform in the teaching of introductory statistics at the college level. Underpinning this reform is a consensus among educators and practitioners that traditional curricular materials and pedagogical strategies have not been effective in promoting statistical literacy, a competency that is becoming increasingly necessary for effective decision-making and evidence-based practice. This paper explains the historical context of, and rationale for reform-oriented teaching of introductory statistics (at the college level) in the health, social and behavioral sciences (evidence-based disciplines). A firm understanding and appreciation of the basis for change in pedagogical approach is important, in order to facilitate commitment to reform, consensus building on appropriate strategies, and adoption and maintenance of best practices. In essence, reform-oriented pedagogy, in this context, is a function of the interaction among content, pedagogy, technology, and assessment. The challenge is to create an appropriate balance among these domains.

Keywords: Reform-oriented, reform, introductory statistics, health, behavioral sciences, evidence-based, psychology, teaching, learning.

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Authors: John B. McQuillen, David F. Chao, Nancy R. Hall, Brian J. Motil, Nengli Zhang

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Future space vehicles will require the use of non-toxic, cryogenic propellants, because of the performance advantages over the toxic hypergolic propellants and also because of the environmental and handling concerns. A prototypical capillary flow liquid acquisition device (LAD) for cryogenic propellants was fabricated with a mesh screen, covering a rectangular flow channel with a cylindrical outlet tube, and was tested with liquid oxygen (LOX). In order to better understand the performance in various gravity environments and orientations with different submersion depths of the LAD, a series of computational fluid dynamics (CFD) simulations of LOX flow through the LAD screen channel, including horizontally and vertically submersions of the LAD channel assembly at normal gravity environment was conducted. Gravity effects on the flow field in LAD channel are inspected and analyzed through comparing the simulations.

Keywords: Liquid acquisition device, cryogenic propellants, CFD simulation, vertically submerged screen channel, gravity effects.

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Authors: Luísa P. Cruz-Lopes, Artur Figueirinha, Isabel Brás, Bruno Esteves

Abstract:

Portugal is an important wine and olive oil producer, activities which generate a high quantity of residues commonly called grape stalks and olive cake, respectively. In this work grape stalks and olive cake were used as lignocellulosic adsorbents for wastewater containing lead treatment. To attain a better knowledge of the factors that could influence the quality of the treated wastewater, a chemical characterization of the materials used in the treatment was done. To access the ecotoxicological safety of the treated wastewater, several tests were performed.

The results of the toxicity test show that the samples leachate has a mild effect on the living models tested. The tests performed in lemna and bacteria were the most sensible to toxicity effects of the samples. The results obtained in this work evidenced the importance of use of simple and fast toxicity tests to predict impacts in the environment.

Keywords: Chemical composition, ecotoxicological, lignocellulosic residues, safety.

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Authors: M. Mokhtarzadeh, M. Taheri Qomi, M. Nikafrooz, A. Atashafrooz

Abstract:

The purpose of the present study was to investigate the effectiveness of using motion graphics as a learning medium on training hearing aids maintenance skills to hearing-impaired children. The statistical population of this study consisted of all children with hearing loss in Ahvaz city, at age 4 to 7 years old. As the sample, 60, whom were selected by multistage random sampling, were randomly assigned to two groups; experimental (30 children) and control (30 children) groups. The research method was experimental and the design was pretest-posttest with the control group. The intervention consisted of a 2-minute motion graphics clip to train hearing aids maintenance skills. Data were collected using a 9-question researcher-made questionnaire. The data were analyzed by using one-way analysis of covariance. Results showed that the training of hearing aids maintenance skills with motion graphics was significantly effective for those children. The results of this study can be used by educators, teachers, professionals, and parents to train children with disabilities or normal students.

Keywords: Hearing-impaired children, hearing aids, hearing aids maintenance skill, and motion graphics.

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