Search results for: spatial information expression

Authors: Jong Woo Kim, Go Bong Choi, Sang Hwan Son, Dae Shik Kim, Jung Chul Suh, Jong Min Lee

Abstract:

The Markov decision process (MDP) based methodology is implemented in order to establish the optimal schedule which minimizes the cost. Formulation of MDP problem is presented using the information about the current state of pipe, improvement cost, failure cost and pipe deterioration model. The objective function and detailed algorithm of dynamic programming (DP) are modified due to the difficulty of implementing the conventional DP approaches. The optimal schedule derived from suggested model is compared to several policies via Monte Carlo simulation. Validity of the solution and improvement in computational time are proved.

Keywords: Markov decision processes, Dynamic Programming, Monte Carlo simulation, Periodic replacement, Weibull distribution.

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Authors: Dariush Semnani, Javad Yekrang, Hossein Ghayoor

Abstract:

Concerning the measurement of friction properties of textiles and fabrics using Kawabata Evaluation System (KES), whose output is constrained to the surface friction factor of fabric, and no other data would be generated; this research has been conducted to gain information about surface roughness regarding its surface friction factor. To assess roughness properties of light nonwovens, a 3-dimensional model of a surface has been simulated with regular sinuous waves through it as an ideal surface. A new factor was defined, namely Surface Roughness Factor, through comparing roughness properties of simulated surface and real specimens. The relation between the proposed factor and friction factor of specimens has been analyzed by regression, and results showed a meaningful correlation between them. It can be inferred that the new presented factor can be used as an acceptable criterion for evaluating the roughness properties of light nonwoven fabrics.

Keywords: Surface roughness, Nonwoven, Machine vision, Image processing.

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Authors: JongKuk Kim, HernSoo Hahn, Uei-Joong Yoo, MyungJin Bae

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In this paper, we propose a method of alter duration in frequency domain that control prosody in real time after pitch alteration. If there has a method to alteration duration freely among prosody information, that may used in several fields such as speech impediment person's pronunciation proof reading or language study. The pitch alteration method used control prosody altered by PSOLA synthesis method which is in time domain processing method. However, the duration of pitch alteration speech is changed by the frequency domain. In this paper, we altered the duration with the method of duration alteration by Fast Fourier Transformation in frequency domain. Consequently, the intelligibility of the pitch and duration are controlled has a slight decrease than the case when only pitch is changed, but the proposed algorithm obtained the higher MOS score about naturalness.

Keywords: PSOLA, Pitch Alteration, Duration Control.

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Authors: Sheena Mathew, K. Poulose Jacob

Abstract:

Extensive use of the Internet coupled with the marvelous growth in e-commerce and m-commerce has created a huge demand for information security. The Secure Socket Layer (SSL) protocol is the most widely used security protocol in the Internet which meets this demand. It provides protection against eaves droppings, tampering and forgery. The cryptographic algorithms RC4 and HMAC have been in use for achieving security services like confidentiality and authentication in the SSL. But recent attacks against RC4 and HMAC have raised questions in the confidence on these algorithms. Hence two novel cryptographic algorithms MAJE4 and MACJER-320 have been proposed as substitutes for them. The focus of this work is to demonstrate the performance of these new algorithms and suggest them as dependable alternatives to satisfy the need of security services in SSL. The performance evaluation has been done by using practical implementation method.

Keywords: Confidentiality, HMAC, Integrity, MACJER-320, MAJE4, RC4, Secure Socket Layer

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Authors: Djamel Saba, Fatima Zohra Laallam, Brahim Berbaoui

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This paper presents a contribution to the design of a multi-agent for the energy management system in a hybrid energy system (SEH). The multi-agent-based energy-coordination management system (MA-ECMS) is based mainly on coordination between agents. The agents share the tasks and exchange information through communications protocols to achieve the main goal. This intelligent system can fully manage the consumption and production or simply to make proposals for action he thinks is best. The initial step is to give a presentation for the system that we want to model in order to understand all the details as much as possible. In our case, it is to implement a system for simulating a process control of energy management.

Keywords: Multi agents system, hybrid energy system, communications protocols, modelization, simulation, control process, energy management.

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Authors: Yasmin Tantawi, Mary Beth Rosson

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In response to the dearth of information about emoji use for different purposes in different settings, this paper investigates the paralinguistic function of emojis within Twitter communication in the United States. To conduct this investigation, the Twitter feeds from 16 population centers spread throughout the United States were collected from the Twitter public API. One hundred tweets were collected from each population center, totaling to 1,600 tweets. Tweets containing emojis were next extracted using the “emot” Python package; these were then analyzed via the IBM Watson API Natural Language Understanding module to identify the topics discussed. A manual content analysis was then conducted to ascertain the paralinguistic and emotional features of the emojis used in these tweets. We present our characterization of emoji usage in Twitter and discuss implications for the design of Twitter and other text-based communication tools.

Keywords: Computer mediated communication, content analysis, paralinguistics, sociology.

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Authors: Ilkka J. Virtanen

Abstract:

Tacit knowledge has been one of the most discussed and contradictory concepts in the field of knowledge management since the mid 1990s. The concept is used relatively vaguely to refer to any type of information that is difficult to articulate, which has led to discussions about the original meaning of the concept (adopted from Polanyi-s philosophy) and the nature of tacit knowing. It is proposed that the subject should be approached from the perspective of cognitive science in order to connect tacit knowledge to empirically studied cognitive phenomena. Some of the most important examples of tacit knowing presented by Polanyi are analyzed in order to trace the cognitive mechanisms of tacit knowing and to promote better understanding of the nature of tacit knowledge. The cognitive approach to Polanyi-s theory reveals that the tacit/explicit typology of knowledge often presented in the knowledge management literature is not only artificial but totally opposite approach compared to Polanyi-s thinking.

Keywords: Cognitive science, explicit knowledge, knowledgemanagement, tacit knowledge.

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Authors: S. Souli, Z. Lachiri

Abstract:

In this paper we propose a robust environmental sound classification approach, based on spectrograms features driven from log-Gabor filters. This approach includes two methods. In the first methods, the spectrograms are passed through an appropriate log-Gabor filter banks and the outputs are averaged and underwent an optimal feature selection procedure based on a mutual information criteria. The second method uses the same steps but applied only to three patches extracted from each spectrogram.

To investigate the accuracy of the proposed methods, we conduct experiments using a large database containing 10 environmental sound classes. The classification results based on Multiclass Support Vector Machines show that the second method is the most efficient with an average classification accuracy of 89.62 %.

Keywords: Environmental sounds, Log-Gabor filters, Spectrogram, SVM Multiclass, Visual features.

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Authors: S. Wongkoon, M. Pollar, M. Jaroensutasinee, K. Jaroensutasinee

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This study aimed at developing a forecasting model on the number of Dengue Haemorrhagic Fever (DHF) incidence in Northern Thailand using time series analysis. We developed Seasonal Autoregressive Integrated Moving Average (SARIMA) models on the data collected between 2003-2006 and then validated the models using the data collected between January-September 2007. The results showed that the regressive forecast curves were consistent with the pattern of actual values. The most suitable model was the SARIMA(2,0,1)(0,2,0)12 model with a Akaike Information Criterion (AIC) of 12.2931 and a Mean Absolute Percent Error (MAPE) of 8.91713. The SARIMA(2,0,1)(0,2,0)12 model fitting was adequate for the data with the Portmanteau statistic Q20 = 8.98644 ( x20,95= 27.5871, P>0.05). This indicated that there was no significant autocorrelation between residuals at different lag times in the SARIMA(2,0,1)(0,2,0)12 model.

Keywords: Dengue, SARIMA, Time Series Analysis, Northern Thailand.

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Authors: Krisada Sungkhamanee

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The objectives of this research are to search the management pattern of Bang Khonthi lodging entrepreneurs for sufficient economy ways, to know the threat that affects this sector and design fit arrangement model to sustain their business with Samut Songkram style. What will happen if they do not use this approach? Will they have a financial crisis? The data and information are collected by informal discussions with 8 managers and 400 questionnaires. A mixed methods of both qualitative research and quantitative research are used. Bent Flyvbjerg-s phronesis is utilized for this analysis. Our research will prove that sufficient economy can help small business firms to solve their problems. We think that the results of our research will be a financial model to solve many problems of the entrepreneurs and this way will can be a model for other provinces of Thailand.

Keywords: Bang Khonthi, Lodging Business, Sufficient Economy.

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Authors: Saipunidzam Mahamad, Mohammad Noor Ibrahim, Rozana Kasbon, Chap Samol

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Animated graph gives some good impressions in presenting information. However, not many people are able to produce it because the process of generating an animated graph requires some technical skills. This work presents Content Management System with Animated Graph (CMS-AG). It is a webbased system enabling users to produce an effective and interactive graphical report in a short time period. It allows for three levels of user authentication, provides update profile, account management, template management, graph management, and track changes. The system development applies incremental development approach, object-oriented concepts and Web programming technologies. The design architecture promotes new technology of reporting. It also helps user cut off unnecessary expenses, save time and learn new things on different levels of users. In this paper, the developed system is described.

Keywords: Animated Graph, Content Management System.

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Authors: Federica Fornaciari

Abstract:

The current study begins with an awareness that today-s media environment is characterized by technological development and a new way of reading caused by the introduction of the Internet. The researcher conducted a meta analysis framed within Technological Determinism to investigate the process of hypertext reading, its differences from linear reading and the effects such differences can have on people-s ways of mentally structuring their world. The relationship between literacy and the comprehension achieved by reading hypertexts is also investigated. The results show hypertexts are not always user friendly. People experience hyperlinks as interruptions that distract their attention generating comprehension and disorientation. On one hand hypertextual jumping reading generates interruptions that finally make people lose their concentration. On the other hand hypertexts fascinate people who would rather read a document in such a format even though the outcome is often frustrating and affects their ability to elaborate and retain information.

Keywords: Hypertext reading, Internet, non-linearity.

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Authors: S. Jakšić, B. Žmuk

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The paper investigates the key factors of export dynamics for a set of Central and Southeast European (CSEE) countries in the context of current economic and financial crisis. In order to model the export dynamics a Global Vector Auto Regressive (GVAR) model is defined. As opposed to models which model each country separately, the GVAR combines all country models in a global model which enables obtaining important information on spillover effects in the context of globalisation and rising international linkages. The results of the study indicate that for most of the CSEE countries, exports are mainly driven by domestic shocks, both in the short run and in the long run. This study is the first application of the GVAR model to studying the export dynamics in the CSEE countries and therefore the results of the study present an important empirical contribution.

Keywords: Export, GFEVD, Global VAR, International trade, weak exogeneity.

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Authors: María S. Avila-García, John N. Carter, Robert I. Damper

Abstract:

An important problem in speech research is the automatic extraction of information about the shape and dimensions of the vocal tract during real-time speech production. We have previously developed Southampton dynamic magnetic resonance imaging (SDMRI) as an approach to the solution of this problem.However, the SDMRI images are very noisy so that shape extraction is a major challenge. In this paper, we address the problem of tongue shape extraction, which poses difficulties because this is a highly deforming non-parametric shape. We show that combining active shape models with the dynamic Hough transform allows the tongue shape to be reliably tracked in the image sequence.

Keywords: Vocal tract imaging, speech production, active shapemodels, dynamic Hough transform, object tracking.

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Authors: Yi-Pin Hsu, Shin-Yu Lin

Abstract:

In order to protect original data, watermarking is first consideration direction for digital information copyright. In addition, to achieve high quality image, the algorithm maybe can not run on embedded system because the computation is very complexity. However, almost nowadays algorithms need to build on consumer production because integrator circuit has a huge progress and cheap price. In this paper, we propose a novel algorithm which efficient inserts watermarking on digital image and very easy to implement on digital signal processor. In further, we select a general and cheap digital signal processor which is made by analog device company to fit consumer application. The experimental results show that the image quality by watermarking insertion can achieve 46 dB can be accepted in human vision and can real-time execute on digital signal processor.

Keywords: watermarking, digital signal processor, embedded system

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Authors: Ahmad Aljaafreh

Abstract:

Safer driver behavior promoting is the main goal of this paper. It is a fact that drivers behavior is relatively safer when being monitored. Thus, in this paper, we propose a monitoring system to report specific driving event as well as the potentially aggressive events for estimation of the driving performance. Our driving monitoring system is composed of two parts. The first part is the in-vehicle embedded system which is composed of a GPS receiver, a two-axis accelerometer, radar sensor, OBD interface, and GPRS modem. The design considerations that led to this architecture is described in this paper. The second part is a web server where an adaptive hierarchical fuzzy system is proposed to classify the driving performance based on the data that is sent by the in-vehicle embedded system and the data that is provided by the geographical information system (GIS). Our system is robust, inexpensive and small enough to fit inside a vehicle without distracting the driver.

Keywords: Driving monitoring system, In-vehicle embedded system, Hierarchical fuzzy system.

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Authors: Salem El-t. Ashoor, Ibtisam M. Ediab

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Zirconium diamine and triamine complexes can possess biological activities. These complexes were synthesised via the reaction of equimolar quantities of 1,10-phenanthroline {NC₃H₃(C₆H₂)NC₃H₃} (L1) or 4-4-amino phenazone {ONC₆H₅(NH)CH(NH₂} (L2) or diphenyl carbizon {HNNCO(NH)₂(C₆H₅)} (L3) with a Zirconium Salt {ZrOCl₂} in a 1:1 ratio to form complexes [{NC₃H₃(C₆H₂)NC₃H₃}ZrOCl₂}] [ZrOCl₂L₁], [{(O₂NC₆H₄(NH)(NH₂)}ZrOCl₂] [ZrOCl₂L₂] and [{HNNCO(NH)₂(C₆H₅)ZrOCl₂}] [ZrOCl₂L₃] respectively. They were characterised using Fourier Transform Infrared (FT-IR) and UV-Visible spectroscopy. Also a variable temperature study of these complexes was completed, using UV-Visible spectroscopy to observe electronic transitions under temperature control. Also a DFT study was done on these complexes via the information from FT-IR and UV-Visible spectroscopy.

These complexes were found to show different inhibition to the growth of bacterial strains of Bacillus spp. & Klebsiella spp. & E. coli & Proteus spp. & Pseudomona spp. at different concentrations (0.001, 0.2 and 1M). For better understanding these complexes were examined by using a Density Functional Theory (DFT) calculation.

Keywords: (1:10-phenanthroline) (L1), 4-4-amino phenazone (L2), diphenyl carbizon (L3), DFT study, antibacterial.

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Authors: C. Ardil

Abstract:

Fuzzy set and intuitionistic fuzzy set are dealing with the imprecision and uncertainty inherent in a complex decision problem. However, sometimes these theories are not sufficient to model indeterminate and inconsistent information encountered in real-life problems. To overcome this insufficiency, the neutrosophic set, which is useful in practical applications, is proposed, triangular neutrosophic numbers and trapezoidal neutrosophic numbers are examined, their definitions and applications are discussed. In this study, a decision making algorithm is developed using neutrosophic set processes and an application is given in fighter aircraft selection as an example of a decision making problem. The estimation of the fighter aircraft selection with the neutrosophic multiple criteria decision analysis method is examined.  

Keywords: neutrosophic set, multiple criteria decision making analysis, fighter aircraft selection, MCDMA, neutrosophic numbers

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Authors: Asish O. Mathew, Lewlyn L. R. Rodrigues

Abstract:

The organizations in the knowledge economy era have recognized the importance of building knowledge assets for sustainable growth and development. In comparison to other industries, Information Technology (IT) enterprises, holds an edge in developing an effective Knowledge Management (KM) programmethanks to their in-house technological abilities. This paper tries to study the various knowledge based incentive programmes and its effect on Knowledge Sharing and Learning in the context of the Indian IT sector. A conceptual model is developed linking KM Incentives, Knowledge Sharing and Learning. A questionnaire study is conducted to collect primary data from the knowledge workers of the IT organizations located in India. The data was analysed using Structural Equation Modeling using Partial Least Square method. The results show a strong influence of knowledge management incentives on knowledge sharing and an indirect influence on learning.

Keywords: Knowledge Management, Knowledge Management Incentives, Knowledge Sharing, Learning.

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Authors: HaeNa Lee, Sun K. Yoo

Abstract:

Volume rendering is widely used in medical CT image visualization. Applying 3D image visualization to diagnosis application can require accurate volume rendering with high resolution. Interpolation is important in medical image processing applications such as image compression or volume resampling. However, it can distort the original image data because of edge blurring or blocking effects when image enhancement procedures were applied. In this paper, we proposed adaptive tension control method exploiting gradient information to achieve high resolution medical image enhancement in volume visualization, where restored images are similar to original images as much as possible. The experimental results show that the proposed method can improve image quality associated with the adaptive tension control efficacy.

Keywords: Tension control, Interpolation, Ray-casting, Medical imaging analysis.

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Authors: Ippei Kamihira, Takashi Nakajima, Taiyo Matsumura, Hikaru Miura, Takashi Ono

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In this research, the goal was construction of a system by which multiple sensors were used to observe the daily life behavior of persons living alone (while respecting their privacy), using this information to judge such conditions as bad physical condition or falling in the home, etc., so that these abnormal conditions can be made known to relatives and third parties. The daily life patterns of persons living alone are expressed by the number of responses of sensors each time that a set time period has elapsed. By comparing data for the prior two weeks, it was possible to judge a situation as “normal” when the person was in good physical condition or as “abnormal” when the person was in bad physical condition.

Keywords: Sensors, Elderly living alone, Abnormality detection, Lifestyle habit.

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Authors: A. J. Al-Graitti, G. A. Khalid, P. Berthelson, A. Mason-Jones, R. Prabhu, M. D. Jones

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Motor vehicle related pedestrian road traffic collisions are a major road safety challenge, since they are a leading cause of death and serious injury worldwide, contributing to a third of the global disease burden. The auto rickshaw, which is a common form of urban transport in many developing countries, plays a major transport role, both as a vehicle for hire and for private use. The most common auto rickshaws are quite unlike ‘typical’ four-wheel motor vehicle, being typically characterised by three wheels, a non-tilting sheet-metal body or open frame construction, a canvas roof and side curtains, a small drivers’ cabin, handlebar controls and a passenger space at the rear. Given the propensity, in developing countries, for auto rickshaws to be used in mixed cityscapes, where pedestrians and vehicles share the roadway, the potential for auto rickshaw impacts with pedestrians is relatively high. Whilst auto rickshaws are used in some Western countries, their limited number and spatial separation from pedestrian walkways, as a result of city planning, has not resulted in significant accident statistics. Thus, auto rickshaws have not been subject to the vehicle impact related pedestrian crash kinematic analyses and/or injury mechanics assessment, typically associated with motor vehicle development in Western Europe, North America and Japan. This study presents a parametric analysis of auto rickshaw related pedestrian impacts by computational simulation, using a Finite Element model of an auto rickshaw and an LS-DYNA 50^th percentile male Hybrid III Anthropometric Test Device (dummy). Parametric variables include auto rickshaw impact velocity, auto rickshaw impact region (front, centre or offset) and relative pedestrian impact position (front, side and rear). The output data of each impact simulation was correlated against reported injury metrics, Head Injury Criterion (front, side and rear), Neck injury Criterion (front, side and rear), Abbreviated Injury Scale and reported risk level and adds greater understanding to the issue of auto rickshaw related pedestrian injury risk. The parametric analyses suggest that pedestrians are subject to a relatively high risk of injury during impacts with an auto rickshaw at velocities of 20 km/h or greater, which during some of the impact simulations may even risk fatalities. The present study provides valuable evidence for informing a series of recommendations and guidelines for making the auto rickshaw safer during collisions with pedestrians. Whilst it is acknowledged that the present research findings are based in the field of safety engineering and may over represent injury risk, compared to “Real World” accidents, many of the simulated interactions produced injury response values significantly greater than current threshold curves and thus, justify their inclusion in the study. To reduce the injury risk level and increase the safety of the auto rickshaw, there should be a reduction in the velocity of the auto rickshaw and, or, consideration of engineering solutions, such as retro fitting injury mitigation technologies to those auto rickshaw contact regions which are the subject of the greatest risk of producing pedestrian injury.

Keywords: Auto Rickshaw, finite element analysis, injury risk level, LS-DYNA, pedestrian impact.

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Authors: Carlos Ramirez, Carlos Concha, Benjamin Valdes

Abstract:

Emotions are related with learning processes and physiological signals can be used to detect them for the personalization of learning resources and to control the pace of instruction. A model of relevant emotions has been developed, where specific combinations of emotions and cognition processes are connected and integrated with the concept of 'flow', in order to improve learning. The cardiac pulse is a reliable signal that carries useful information about the subject-s emotional condition; it is detected using a classroom chair adapted with non invasive EMFi sensor and an acquisition system that generates a ballistocardiogram (BCG), the signal is processed by an algorithm to obtain characteristics that match a specific emotional condition. The complete chair system is presented in this work, along with a framework for the personalization of learning resources.

Keywords: Ballistocardiogram, emotions in learning, noninvasive sensors, personalization of learning resources.

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Authors: F. Matusek, G. Pujolle, R. Reda

Abstract:

Shadow detection is still considered as one of the potential challenges for intelligent automated video surveillance systems. A pre requisite for reliable and accurate detection and tracking is the correct shadow detection and classification. In such a landscape of conditions, privacy issues add more and more complexity and require reliable shadow detection. In this work the intertwining between security, accuracy, reliability and privacy is analyzed and, accordingly, a novel architecture for Privacy Enhancing Video Surveillance (PEVS) is introduced. Shadow detection and masking are dealt with through the combination of two different approaches simultaneously. This results in a unique privacy enhancement, without affecting security. Subsequently, the methodology was employed successfully in a large-scale wireless video surveillance system; privacy relevant information was stored and encrypted on the unit, without transferring it over an un-trusted network.

Keywords: Video Surveillance, Intelligent Video Surveillance, Physical Security, WSSU, Privacy, Shadow Detection.

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Authors: Oluseye Adeniyi Adeleke, Mohd Fadzli Salleh

Abstract:

Cooperative communication provides transmit diversity, even when, due to size constraints, mobile units cannot accommodate multiple antennas. A versatile cooperation method called coded cooperation has been developed, in which cooperation is implemented through channel coding with a view to controlling the errors inherent in wireless communication. In this work we evaluate the performance of coded cooperation in flat Rayleigh fading environment using a concept known as the pair wise error probability (PEP). We derive the PEP for a flat fading scenario in coded cooperation and then compare with the signal-to-noise ratio of the users in the network. Results show that an increase in the SNR leads to a decrease in the PEP. We also carried out simulations to validate the result.

Keywords: Channel state information, coded cooperation, cooperative systems, pairwise-error-probability, Reed-Solomon codes.

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Authors: Ekta Singh, M. P. Singh

Abstract:

The habitat where the present study has been carried out is productive in relation to nutrient quality and they may perform several useful functions, but are also threatened for their existence. Hence, the proposed work, will add much new information about biodiversity of macrophytes in drains and their embankment. All the species were identified with their different stages of growth which encountered on the three selected sites (I, II and III). The number of species occurring at each site is grouped seasonally, i.e. summer, rainy and winter season and the species were further recorded for the study of phytosociology. Phytosociological characters such as frequency, density and abundance were influenced by the climatic, anthropogenic and biotic stresses prevailing at the three study sites. All the species present at the study sites have shown maximum values of frequency, density and abundance in rainy season in comparison to that of summer and winter seasons.

Keywords: Abundance, Biodiversity, Density, Frequency, Macrophytes, Phytosociology.

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Authors: L. Tao, T. J. Sun, Z. H. Li

Abstract:

The knowledge base of welding defect recognition is essentially incomplete. This characteristic determines that the recognition results do not reflect the actual situation. It also has a further influence on the classification of welding quality. This paper is concerned with the study of a rough set based method to reduce the influence and improve the classification accuracy. At first, a rough set model of welding quality intelligent classification has been built. Both condition and decision attributes have been specified. Later on, groups of the representative multiple compound defects have been chosen from the defect library and then classified correctly to form the decision table. Finally, the redundant information of the decision table has been reducted and the optimal decision rules have been reached. By this method, we are able to reclassify the misclassified defects to the right quality level. Compared with the ordinary ones, this method has higher accuracy and better robustness.

Keywords: intelligent decision, rough set, welding defects, welding quality level

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Authors: Siti Aiysyah Tumin

Abstract:

This paper looks at the nature of structural changes—the transition of employment from agriculture, to manufacturing, then to different types of services—in different states in Malaysia and links it to income outcomes for households and workers. Specifically, this paper investigates the conditional association between the concentration of different economic activities and income outcomes (household incomes and employee wages) in almost four decades. Using publicly available state-level employment and income data, we found that significant wage premium was associated with “modern” services (finance, real estate, professional, information and communication), which are urban-based services sectors that employ a larger proportion of skilled and educated workers. However, employment in manufacturing and other services subsectors was significantly associated with a lower income dispersion and inequality, alluding to their importance in welfare improvements.

Keywords: Employment, labour market, structural change, wages.

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Authors: Guy Leshem, Ya'acov Ritov

Abstract:

Traffic Management and Information Systems, which rely on a system of sensors, aim to describe in real-time traffic in urban areas using a set of parameters and estimating them. Though the state of the art focuses on data analysis, little is done in the sense of prediction. In this paper, we describe a machine learning system for traffic flow management and control for a prediction of traffic flow problem. This new algorithm is obtained by combining Random Forests algorithm into Adaboost algorithm as a weak learner. We show that our algorithm performs relatively well on real data, and enables, according to the Traffic Flow Evaluation model, to estimate and predict whether there is congestion or not at a given time on road intersections.

Keywords: Machine Learning, Boosting, Classification, TrafficCongestion, Data Collecting, Magnetic Loop Detectors, SignalizedIntersections, Traffic Signal Timing Optimization.

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Authors: Bruno Trstenjak, Dzenana Donko

Abstract:

Data mining and classification of objects is the process of data analysis, using various machine learning techniques, which is used today in various fields of research. This paper presents a concept of hybrid classification model improved with the expert knowledge. The hybrid model in its algorithm has integrated several machine learning techniques (Information Gain, K-means, and Case-Based Reasoning) and the expert’s knowledge into one. The knowledge of experts is used to determine the importance of features. The paper presents the model algorithm and the results of the case study in which the emphasis was put on achieving the maximum classification accuracy without reducing the number of features.

Keywords: Case based reasoning, classification, expert's knowledge, hybrid model.

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