Search results for: air data system

Authors: V. Nagaraju, Tapas Bapu. B. R, Beryl J. Victor

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In this paper cognitive radio is presented and the spectrum overlay cognitive radio antenna system is detailed. A UWB antenna with frequency reconfigurable characteristics is proposed. The reconfigurability is achieved when the filter is integrated to the feeding line of the single port overlay cognitive radio. When activated, the filter can transform the UWB frequency response into a reconfigurable narrowband one, which is suitable for the communication operation of the CR system. Here single port overlay cognitive radio antenna is designed and simulated using Ansoft High Frequency Structure Simulator (HFSS).

Keywords: Band-pass filter, Cognitive radio, filtenna, frequency reconfigurable, ultra-wideband antenna.

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Authors: Naci Kalkan, Ihsan Dagtekin

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Passive design responds to improve indoor thermal comfort and minimize the energy consumption. The present research analyzed the how efficiently passive solar technologies generate heating and cooling and provide the system integration for domestic applications. In addition to this, the aim of this study is to increase the efficiency of solar systems system with integration some innovation and optimization. As a result, outputs of the project might start a new sector to provide environmentally friendly and cheap cooling for domestic use.

Keywords: Passive Solar Systems, Heating, Cooling, Thermal Comfort, Ventilation Systems.

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Authors: Mona F. M. Mursi, Ghazy M.R. Assassa, Hatim A. Aboalsamh, Khaled Alghathbar

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The challenge in the case of image authentication is that in many cases images need to be subjected to non malicious operations like compression, so the authentication techniques need to be compression tolerant. In this paper we propose an image authentication system that is tolerant to JPEG lossy compression operations. A scheme for JPEG grey scale images is proposed based on a data embedding method that is based on a secret key and a secret mapping vector in the frequency domain. An encrypted feature vector extracted from the image DCT coefficients, is embedded redundantly, and invisibly in the marked image. On the receiver side, the feature vector from the received image is derived again and compared against the extracted watermark to verify the image authenticity. The proposed scheme is robust against JPEG compression up to a maximum compression of approximately 80%,, but sensitive to malicious attacks such as cutting and pasting.

Keywords: Authentication, DCT, JPEG, Watermarking.

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Authors: Levan Sabauri

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Audit is an independent inspection of the financial statement of the audited person and expresses the opinion of an auditor on the reliability of this statement. The auditor’s activity (auditor’s service) is realized by auditing organizations, individual auditors in connection to conduction of an audit and rendering of audit accompanying services. The profession of auditor means a high level of responsibility for rendered service. Results of decisions made by information users depend on the quality of the auditor’s conclusion. Owners, investors, creditors, and society rely on the opinion of the auditor under the condition that inspection was conducted with good quality. Therefore, the existence of the well-functioning audit quality control system for the administering of the audit is an important issue. An efficient audit quality control system is a substantial challenge that many countries face worldwide, especially those states where these systems are being formed within the respective reform program. The presented article reflects on the best practices of the leading countries, the assumptions and recommendations for the financial accounting, reporting and audit; current reforms in Georgia are made based on this comparative analysis.

Keywords: Audit quality control, audit program, financial statement, perspective analysis.

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Authors: Mohammed Abdalla Osman Mukhtar, Azween Abdullah, Alan Giffin Downe

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Model mapping and transformation are important processes in high level system abstractions, and form the cornerstone of model-driven architecture (MDA) techniques. Considerable research in this field has devoted attention to static system abstraction, despite the fact that most systems are dynamic with high frequency changes in behavior. In this paper we provide an overview of work that has been done with regard to behavior model mapping and transformation, based on: (1) the completeness of the platform independent model (PIM); (2) semantics of behavioral models; (3) languages supporting behavior model transformation processes; and (4) an evaluation of model composition to effect the best approach to describing large systems with high complexity.

Keywords: MDA; PIM, PSM, QVT, Model Transformation

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Authors: Hossein Jafari, Xiangfang Li, Lijun Qian, Alexander Aved, Timothy Kroecker

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Traditionally in sensor networks and recently in the Internet of Things, numerous heterogeneous sensors are deployed in distributed manner to monitor a phenomenon that often can be model by an underlying stochastic process. The big time-series data collected by the sensors must be analyzed to detect change in the stochastic process as quickly as possible with tolerable false alarm rate. However, sensors may have different accuracy and sensitivity range, and they decay along time. As a result, the big time-series data collected by the sensors will contain uncertainties and sometimes they are conflicting. In this study, we present a framework to take advantage of Evidence Theory (a.k.a. Dempster-Shafer and Dezert-Smarandache Theories) capabilities of representing and managing uncertainty and conflict to fast change detection and effectively deal with complementary hypotheses. Specifically, Kullback-Leibler divergence is used as the similarity metric to calculate the distances between the estimated current distribution with the pre- and post-change distributions. Then mass functions are calculated and related combination rules are applied to combine the mass values among all sensors. Furthermore, we applied the method to estimate the minimum number of sensors needed to combine, so computational efficiency could be improved. Cumulative sum test is then applied on the ratio of pignistic probability to detect and declare the change for decision making purpose. Simulation results using both synthetic data and real data from experimental setup demonstrate the effectiveness of the presented schemes.

Keywords: CUSUM, evidence theory, KL divergence, quickest change detection, time series data.

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Authors: Riad Saraiji, Scott Sizer, Emily Yance-Houser, Felix Bermejo

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The use of a Geographic Information System (GIS) in roadway lighting to show the state of street-lighting and nighttime accident is demonstrated. Geographical maps were generated showing colored streets based on how much of the street's length is illuminated. The night to daytime accidents ratio at intersections were found along with the state of lighting at those intersections. The result is a method to show the state of street-lighting at roads and intersections and a quick guide for decision makers to implement strategies for better street-lighting to reduce night time traffic accidents in a particular district.

Keywords: GIS. Roadway lighting, Traffic Accidents

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Authors: R. May, K. Jinno, I. Yusoff

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The paper aims at evaluating the effects of heavy groundwater withdrawal and artificial groundwater recharge of an ex-mining pond to the aquifer system of the Langat Basin through the three-dimensional (3D) numerical modeling. Many mining sites have been left behind from the massive mining exploitations in Malaysia during the England colonization era and from the last few decades. These sites are able to accommodate more than a million cubic meters of water from precipitation, runoff, groundwater, and river. Most of the time, the mining sites are turned into ponds for recreational activities. In the current study, an artificial groundwater recharge from an ex-mining pond in the Langat Basin was proposed due to its capacity to store >50 million m3 of water. The location of the pond is near the Langat River and opposite a steel company where >4 million gallons of groundwater is withdrawn on a daily basis. The 3D numerical simulation was developed using the Groundwater Modeling System (GMS). The calibrated model (error about 0.7 m) was utilized to simulate two scenarios (1) Case 1: artificial recharge pond with no pumping and (2) Case 2: artificial pond with pumping. The results showed that in Case 1, the pond played a very important role in supplying additional water to the aquifer and river. About 90,916 m3/d of water from the pond, 1,173 m3/d from the Langat River, and 67,424 m3/d from the direct recharge of precipitation infiltrated into the aquifer system. In Case 2, due to the abstraction of groundwater from a company, it caused a steep depression around the wells, river, and pond. The result of the water budget showed an increase rate of inflow in the pond and river with 92,493m3/d and 3,881m3/d respectively. The outcome of the current study provides useful information of the aquifer behavior of the Langat Basin.

Keywords: Groundwater and surface water interaction, groundwater modeling, GMS, artificial recharge pond, ex-mining site.

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Authors: Widod Budiharto, Muhsin Shodiq, Bayu Kanigoro, Jurike V. Moniaga Hutomo

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We present a BeeBot, Binus Multi-client Intelligent Telepresence Robot, a custom-build robot system specifically designed for teleconference with multiple person using omni directional actuator. The robot is controlled using a computer networks, so the manager/supervisor can direct the robot to the intended person to start a discussion/inspection. People tracking and autonomous navigation are intelligent features of this robot. We build a web application for controlling the multi-client telepresence robot and open-source teleconference system used. Experimental result presented and we evaluated its performance.

Keywords: Telepresence robot, robot vision, intelligent robot.

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Authors: J. Fernandez de Canete, S. Fernandez-Calvo, I. García-Moral

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This paper presents and discusses the application of the object-oriented modelling software SIMSCAPE to hydraulic systems, with particular reference to multivariable proportional-integral-derivative (PID) control. As a result, a particular modelling approach of a double cylinder-piston coupled system is proposed and motivated, and the SIMULINK based PID tuning tool has also been used to select the proper controller parameters. The paper demonstrates the usefulness of the object-oriented approach when both physical modelling and control are tackled.

Keywords: Object-oriented modeling, multivariable hydraulic system, multivariable PID control, computer simulation.

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Authors: Li Hongwei

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In this paper, a predator-prey model with time delay and habitat complexity is investigated. By analyzing the characteristic equations, the local stability of each feasible equilibria of the system is discussed and the existence of a Hopf bifurcation at the coexistence equilibrium is established. By choosing the sum of two delays as a bifurcation parameter, we show that Hopf bifurcations can occur as  crosses some critical values. By deriving the equation describing the flow on the center manifold, we can determine the direction of the Hopf bifurcations and the stability of the bifurcating periodic solutions. Numerical simulations are carried out to illustrate the main theoretical results.

Keywords: Predator-prey system, delay, habitat complexity, HOPF bifurcation.

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Authors: Myeongjin Park, Ohmin Kwon, Juhyun Park, Sangmoon Lee

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This paper proposes improved delay-dependent stability conditions of the linear time-delay systems of neutral type. The proposed methods employ a suitable Lyapunov-Krasovskii’s functional and a new form of the augmented system. New delay-dependent stability criteria for the systems are established in terms of Linear matrix inequalities (LMIs) which can be easily solved by various effective optimization algorithms. Numerical examples showed that the proposed method is effective and can provide less conservative results.

Keywords: Neutral systems, Time-delay, Stability, Lyapunovmethod, LMI.

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Authors: Argaw T. Gurmu, Muhammad N. Mahmood

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The objective of this research is to identify the architecture and construction management students’ learning challenges of the building measurement. This research used the survey data obtained collected from the students who completed the building measurement unit. NVivo qualitative data analysis software was used to identify relevant themes. The analysis of the qualitative data revealed the major learning difficulties such as inadequacy of practice questions for the examination, inability to work as a team, lack of detailed understanding of the prerequisite units, insufficiency of the time allocated for tutorials and incompatibility of lecture and tutorial schedules. The output of this research can be used as a basis for improving the teaching and learning activities in construction measurement units.

Keywords: Building measurement, construction management, learning challenges, evaluate survey.

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Authors: M. Benattou, K. Tamine

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This paper presents a distributed intrusion detection system IDS, based on the concept of specialized distributed agents community representing agents with the same purpose for detecting distributed attacks. The semantic of intrusion events occurring in a predetermined network has been defined. The correlation rules referring the process which our proposed IDS combines the captured events that is distributed both spatially and temporally. And then the proposed IDS tries to extract significant and broad patterns for set of well-known attacks. The primary goal of our work is to provide intrusion detection and real-time prevention capability against insider attacks in distributed and fully automated environments.

Keywords: Mobile agent, specialized agent, interpreter agent, event rules, correlation.

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Authors: Dharmveer Singh Rajput , P. K. Singh, Mahua Bhattacharya

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Clustering in high dimensional space is a difficult problem which is recurrent in many fields of science and engineering, e.g., bioinformatics, image processing, pattern reorganization and data mining. In high dimensional space some of the dimensions are likely to be irrelevant, thus hiding the possible clustering. In very high dimensions it is common for all the objects in a dataset to be nearly equidistant from each other, completely masking the clusters. Hence, performance of the clustering algorithm decreases. In this paper, we propose an algorithmic framework which combines the (reduct) concept of rough set theory with the k-means algorithm to remove the irrelevant dimensions in a high dimensional space and obtain appropriate clusters. Our experiment on test data shows that this framework increases efficiency of the clustering process and accuracy of the results.

Keywords: High dimensional clustering, sub-space, k-means, rough set, discernibility matrix.

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Authors: K. Vidya, V.Rhymend Uthariaraj

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Traffic Engineering (TE) is the process of controlling how traffic flows through a network in order to facilitate efficient and reliable network operations while simultaneously optimizing network resource utilization and traffic performance. TE improves the management of data traffic within a network and provides the better utilization of network resources. Many research works considers intra and inter Traffic Engineering separately. But in reality one influences the other. Hence the effective network performances of both inter and intra Autonomous Systems (AS) are not optimized properly. To achieve a better Joint Optimization of both Intra and Inter AS TE, we propose a joint Optimization technique by considering intra-AS features during inter – AS TE and vice versa. This work considers the important criterion say latency within an AS and between ASes. and proposes a Bi-Criteria Latency optimization model. Hence an overall network performance can be improved by considering this jointoptimization technique in terms of Latency.

Keywords: Inter-Domain Routing , Measurement, OptimizationPerformance, Traffic Engineering.

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Authors: Junyou Shi, Weiwei Cui

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Testability modeling is a commonly used method in testability design and analysis of system. A dependency matrix will be obtained from testability modeling, and we will give a quantitative evaluation about fault detection and isolation. Based on the dependency matrix, we can obtain the diagnosis tree. The tree provides the procedures of the fault detection and isolation. But the dependency matrix usually includes built-in test (BIT) and manual test in fact. BIT runs the test automatically and is not limited by the procedures. The method above cannot give a more efficient diagnosis and use the advantages of the BIT. A Comprehensive method of fault detection and isolation is proposed. This method combines the advantages of the BIT and Manual test by splitting the matrix. The result of the case study shows that the method is effective.

Keywords: BIT, fault detection, fault isolation, testability modeling.

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Authors: Kwok Tak Kit

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The government and community have raised their awareness of the benefits of water reuse. Deforestation has a significant effect to climate change as it causes the drying out of the tropical rainforest and hence increases the chance of natural threaten the storage and supply of clean water. This paper focuses on discussion of the relationship of the natural water collection system, afforestation and country parks towards environmental sustainability and circular economy, with a case study of water conservation policy and strategy in Hong Kong and Singapore for further research.

Keywords: Afforestation, environmental sustainability, water conservation, circular economy, climate change.

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Authors: Chih-Hui Chiu, Chun-Hsien Lin

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In this study, a robust intelligent backstepping tracking control (RIBTC) system combined with adaptive output recurrent cerebellar model articulation control (AORCMAC) and H∞ control technique is proposed for wheeled inverted pendulums (WIPs) real-time control with exact system dynamics unknown. Moreover, a robust H∞ controller is designed to attenuate the effect of the residual approximation errors and external disturbances with desired attenuation level. The experimental results indicate that the WIPs can stand upright stably when using the proposed RIBTC.

Keywords: Wheeled inverted pendulum, backsteppingtracking control, H∞ control, adaptive output recurrentcerebellar model articulation control.

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Authors: T. Denkçeken, M. Canpolat, Đ. Bassorgun, S. Yücel, M.A. Çiftçioğlu, M. Baykara Murat Canpolat , Tuba Denkçeken , Đbrahim Bassorgun , Selçuk Yücel , M. Akif Çiftçioğlu , Mehmet Baykara

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Elastic light single-scattering spectroscopy system with a single optical fiber probe was employed to differentiate cancerous prostate tissue from non-cancerous prostate tissue ex-vivo just after radical prostatectomy. First, ELSSS spectra were acquired from cancerous prostate tissue to define its spectral features. Then, spectra were acquired from normal prostate tissue to define difference in spectral features between the cancerous and normal prostate tissues. Of the total 66 tissue samples were evaluated from nine patients by ELSSS system. Comparing of histopathology results and ELSSS measurements revealed that sign of the spectral slopes of cancerous prostate tissue is negative and non-cancerous tissue is positive in the wavelength range from 450 to 750 nm. Based on the correlation between histopathology results and sign of the spectral slopes, ELSSS system differentiates cancerous prostate tissue from non- cancerous with a sensitivity of 0.95 and a specificity of 0.94.

Keywords: Diagnosis, prostatic neoplasm, prostatectomy, spectrum analysis

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Authors: Rupesh K. Gopal, Saroj K. Meher

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In this report we present a rule-based approach to detect anomalous telephone calls. The method described here uses subscriber usage CDR (call detail record) data sampled over two observation periods: study period and test period. The study period contains call records of customers- non-anomalous behaviour. Customers are first grouped according to their similar usage behaviour (like, average number of local calls per week, etc). For customers in each group, we develop a probabilistic model to describe their usage. Next, we use maximum likelihood estimation (MLE) to estimate the parameters of the calling behaviour. Then we determine thresholds by calculating acceptable change within a group. MLE is used on the data in the test period to estimate the parameters of the calling behaviour. These parameters are compared against thresholds. Any deviation beyond the threshold is used to raise an alarm. This method has the advantage of identifying local anomalies as compared to techniques which identify global anomalies. The method is tested for 90 days of study data and 10 days of test data of telecom customers. For medium to large deviations in the data in test window, the method is able to identify 90% of anomalous usage with less than 1% false alarm rate.

Keywords: Subscription fraud, fraud detection, anomalydetection, maximum likelihood estimation, rule based systems.

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Authors: Chandrika M.J., Lariyah M.S., Alicia Y.C. Tang

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Ontology is widely being used as a tool for organizing information, creating the relation between the subjects within the defined knowledge domain area. Various fields such as Civil, Biology, and Management have successful integrated ontology in decision support systems for managing domain knowledge and to assist their decision makers. Gross pollutant traps (GPT) are devices used in trapping and preventing large items or hazardous particles in polluting and entering our waterways. However choosing and determining GPT is a challenge in Malaysia as there are inadequate GPT data repositories being captured and shared. Hence ontology is needed to capture, organize and represent this knowledge into meaningful information which can be contributed to the efficiency of GPT selection in Malaysia urbanization. A GPT Ontology framework is therefore built as the first step to capture GPT knowledge which will then be integrated into the decision support system. This paper will provide several examples of the GPT ontology, and explain how it is constructed by using the Protégé tool.

Keywords: Gross pollutant Trap, Ontology, Protégé.

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Authors: Nareelux Suwannobol, Supap Chobkhayan

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The aim of this study was to investigate the pregnancy outcomes of teenage mothers at DanKhunThot hospital, Nakhon Ratchasima, Thailand. A retrospective descriptive study was conducted in 573 of teenage pregnant from charts reviewed from 1st October 2010-31st March, 2012. Data were analyzed by frequency distribution, mean and Standard Deviation. The results shown several problems and negatives outcomes of pregnancy in teenager such as not attended prenatal care, Low birth weight infants, death fetus in utero and other complications. The results of this study can be utilized in the development of prenatal, perinatal and post natal care services, especially in DanKhunthot Hospital contexts. Moreover, the results were present to the District Health Care committees in order to enhance health care service system for teenage pregnancy of DanKhunthot District in further.

Keywords: Teenage mothers, Pregnancy outcome, Neonatal outcomes, Maternal outcomes.

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Authors: Shohei Maruyama, Yasuo Matsuyama, Sachiyo Aburatani

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Development of a method to estimate gene functions is an important task in bioinformatics. One of the approaches for the annotation is the identification of the metabolic pathway that genes are involved in. Since gene expression data reflect various intracellular phenomena, those data are considered to be related with genes’ functions. However, it has been difficult to estimate the gene function with high accuracy. It is considered that the low accuracy of the estimation is caused by the difficulty of accurately measuring a gene expression. Even though they are measured under the same condition, the gene expressions will vary usually. In this study, we proposed a feature extraction method focusing on the variability of gene expressions to estimate the genes' metabolic pathway accurately. First, we estimated the distribution of each gene expression from replicate data. Next, we calculated the similarity between all gene pairs by KL divergence, which is a method for calculating the similarity between distributions. Finally, we utilized the similarity vectors as feature vectors and trained the multiclass SVM for identifying the genes' metabolic pathway. To evaluate our developed method, we applied the method to budding yeast and trained the multiclass SVM for identifying the seven metabolic pathways. As a result, the accuracy that calculated by our developed method was higher than the one that calculated from the raw gene expression data. Thus, our developed method combined with KL divergence is useful for identifying the genes' metabolic pathway.

Keywords: Metabolic pathways, gene expression data, microarray, Kullback–Leibler divergence, KL divergence, support vector machines, SVM, machine learning.

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Authors: C. Rajan, K. Geetha, S. Geetha

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The motivation of image compression technique is to reduce the irrelevance and redundancy of the image data in order to store or pass data in an efficient way from one place to another place. There are several types of compression methods available. Without the help of compression technique, the file size is knowingly larger, usually several megabytes, but by doing the compression technique, it is possible to reduce file size up to 10% as of the original without noticeable loss in quality. Image compression can be lossless or lossy. The compression technique can be applied to images, audio, video and text data. This research work mainly concentrates on methods of encoding, DCT, compression methods, security, etc. Different methodologies and network simulations have been analyzed here. Various methods of compression methodologies and its performance metrics has been investigated and presented in a table manner.

Keywords: Image compression techniques, encoding, DCT, lossy compression, lossless compression, JPEG.

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Authors: Mohammed Z. Khedher, Gheith A. Abandah, Ahmed M. Al-Khawaldeh

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Recognition of characters greatly depends upon the features used. Several features of the handwritten Arabic characters are selected and discussed. An off-line recognition system based on the selected features was built. The system was trained and tested with realistic samples of handwritten Arabic characters. Evaluation of the importance and accuracy of the selected features is made. The recognition based on the selected features give average accuracies of 88% and 70% for the numbers and letters, respectively. Further improvements are achieved by using feature weights based on insights gained from the accuracies of individual features.

Keywords: Arabic handwritten characters, Feature extraction, Off-line recognition, Optical character recognition.

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Authors: Yongxin Yuan

Abstract:

The problem of updating damped gyroscopic systems using measured modal data can be mathematically formulated as following two problems. Problem I: Given Ma ∈ Rn×n, Λ = diag{λ1, ··· , λp} ∈ Cp×p, X = [x1, ··· , xp] ∈ Cn×p, where p<n and both Λ and X are closed under complex conjugation in the sense that λ2j = λ¯2j−1 ∈ C, x2j = ¯x2j−1 ∈ Cn for j = 1, ··· , l, and λk ∈ R, xk ∈ Rn for k = 2l + 1, ··· , p, find real-valued symmetric matrices D,K and a real-valued skew-symmetric matrix G (that is, GT = −G) such that MaXΛ2 + (D + G)XΛ + KX = 0. Problem II: Given real-valued symmetric matrices Da, Ka ∈ Rn×n and a real-valued skew-symmetric matrix Ga, find (D, ˆ G, ˆ Kˆ ) ∈ SE such that Dˆ −Da2+Gˆ−Ga2+Kˆ −Ka2 = min(D,G,K)∈SE (D− Da2 + G − Ga2 + K − Ka2), where SE is the solution set of Problem I and · is the Frobenius norm. This paper presents an iterative algorithm to solve Problem I and Problem II. By using the proposed iterative method, a solution of Problem I can be obtained within finite iteration steps in the absence of roundoff errors, and the minimum Frobenius norm solution of Problem I can be obtained by choosing a special kind of initial matrices. Moreover, the optimal approximation solution (D, ˆ G, ˆ Kˆ ) of Problem II can be obtained by finding the minimum Frobenius norm solution of a changed Problem I. A numerical example shows that the introduced iterative algorithm is quite efficient.

Keywords: Model updating, iterative algorithm, gyroscopic system, partially prescribed spectral data, optimal approximation.

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Authors: David W.S. Tai, Ren-Cheng Zhang, Sheng-Hung Chang, Chin-Pin Chen, Jia-Ling Chen

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This study reports results of a meta-analytic path analysis e-learning Acceptance Model with k = 27 studies, Databases searched included Information Sciences Institute (ISI) website. Variables recorded included perceived usefulness, perceived ease of use, attitude toward behavior, and behavioral intention to use e-learning. A correlation matrix of these variables was derived from meta-analytic data and then analyzed by using structural path analysis to test the fitness of the e-learning acceptance model to the observed aggregated data. Results showed the revised hypothesized model to be a reasonable, good fit to aggregated data. Furthermore, discussions and implications are given in this article.

Keywords: E-learning, Meta Analytic Path Analysis, Technology Acceptance Model

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Authors: Suelane Garcia Fontes, Silvio Luiz Stanzani, Pedro L. Pizzigatti Corrła Ronaldo G. Morato

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Environmental changes and major natural disasters are most prevalent in the world due to the damage that humanity has caused to nature and these damages directly affect the lives of animals. Thus, the study of animal behavior and their interactions with the environment can provide knowledge that guides researchers and public agencies in preservation and conservation actions. Exploratory analysis of animal movement can determine the patterns of animal behavior and with technological advances the ability of animals to be tracked and, consequently, behavioral studies have been expanded. There is a lot of research on animal movement and behavior, but we note that a proposal that combines resources and allows for exploratory analysis of animal movement and provide statistical measures on individual animal behavior and its interaction with the environment is missing. The contribution of this paper is to present the framework AniMoveMineR, a unified solution that aggregates trajectory analysis and data mining techniques to explore animal movement data and provide a first step in responding questions about the animal individual behavior and their interactions with other animals over time and space. We evaluated the framework through the use of monitored jaguar data in the city of Miranda Pantanal, Brazil, in order to verify if the use of AniMoveMineR allows to identify the interaction level between these jaguars. The results were positive and provided indications about the individual behavior of jaguars and about which jaguars have the highest or lowest correlation.

Keywords: Data mining, data science, trajectory, animal behavior.

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Authors: Gerrit Alves, Jürgen Roßmann, Roland Wischnewski

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Today, transport and logistic systems are often tightly integrated in the production. Lean production and just-in-time delivering create multiple constraints that have to be fulfilled. As transport networks often have evolved over time they are very expensive to change. This paper describes a discrete-event-simulation system which simulates transportation models using real time resource routing and collision avoidance. It allows for the specification of own control algorithms and validation of new strategies. The simulation is integrated into a virtual reality (VR) environment and can be displayed in 3-D to show the progress. Simulation elements can be selected through VR metaphors. All data gathered during the simulation can be presented as a detailed summary afterwards. The included cost-benefit calculation can help to optimize the financial outcome. The operation of this approach is shown by the example of a timber harvest simulation.

Keywords: Discrete-Event-Simulation, Logistic, Simulation, Virtual Reality.

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