Search results for: data exchange.

Authors: Kyoung-Mi Lee, Youn-Mi Lee

Abstract:

This paper proposes a way to track persons by making use of multiple non-overlapping cameras. Tracking persons on multiple non-overlapping cameras enables data communication among cameras through the network connection between a camera and a computer, while at the same time transferring human feature data captured by a camera to another camera that is connected via the network. To track persons with a camera and send the tracking data to another camera, the proposed system uses a hierarchical human model that comprises a head, a torso, and legs. The feature data of the person being modeled are transferred to the server, after which the server sends the feature data of the human model to the cameras connected over the network. This enables a camera that captures a person's movement entering its vision to keep tracking the recognized person with the use of the feature data transferred from the server.

Keywords: Person tracking, human model, networked cameras, vision-based surveillance.

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Authors: V. Hernandez-Perez, M. Abdulkadir, B. J. Azzopardi

Abstract:

In this work, new experimental data for slugging frequency in inclined gas-liquid flow are reported, and a new correlation is proposed. Scale experiments were carried out using a mixture of air and water in a 6 m long pipe. Two different pipe diameters were used, namely, 38 and 67 mm. The data were taken with capacitance type sensors at a data acquisition frequency of 200 Hz over an interval of 60 seconds. For the range of flow conditions studied, the liquid superficial velocity is observed to influence the frequency strongly. A comparison of the present data with correlations available in the literature reveals a lack of agreement. A new correlation for slug frequency has been proposed for the inclined flow, which represents the main contribution of this work.

Keywords: slug frequency, inclined flow

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Authors: Yu-Kyung Kang, Suk-Hyung Hwang, Kyoung-Mo Yang

Abstract:

The tagging data of (users, tags and resources) constitutes a folksonomy that is the user-driven and bottom-up approach to organizing and classifying information on the Web. Tagging data stored in the folksonomy include a lot of very useful information and knowledge. However, appropriate approach for analyzing tagging data and discovering hidden knowledge from them still remains one of the main problems on the folksonomy mining researches. In this paper, we have proposed a folksonomy data mining approach based on FCA for discovering hidden knowledge easily from folksonomy. Also we have demonstrated how our proposed approach can be applied in the collaborative tagging system through our experiment. Our proposed approach can be applied to some interesting areas such as social network analysis, semantic web mining and so on.

Keywords: Folksonomy data mining, formal concept analysis, collaborative tagging, conceptual knowledge discovery, classification.

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Authors: Nazaket Gazieva

Abstract:

Voice biometric data associated with physiological, psychological and other factors are widely used in forensic phonoscopy. There are various methods for identifying and verifying a person by voice. This article explores the minimum speech signal data as individual parameters of a speech signal. Monozygotic twins are believed to be genetically identical. Using the minimum data of the speech signal, we came to the conclusion that the voice imprint of monozygotic twins is individual. According to the conclusion of the experiment, we can conclude that the minimum indicators of the speech signal are more stable and reliable for phonoscopic examinations.

Keywords: Biometric voice prints, fundamental frequency, phonogram, speech signal, temporal characteristics.

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Authors: Ruchika Malhotra, Megha Khanna

Abstract:

The development of change prediction models can help the software practitioners in planning testing and inspection resources at early phases of software development. However, a major challenge faced during the training process of any classification model is the imbalanced nature of the software quality data. A data with very few minority outcome categories leads to inefficient learning process and a classification model developed from the imbalanced data generally does not predict these minority categories correctly. Thus, for a given dataset, a minority of classes may be change prone whereas a majority of classes may be non-change prone. This study explores various alternatives for adeptly handling the imbalanced software quality data using different sampling methods and effective MetaCost learners. The study also analyzes and justifies the use of different performance metrics while dealing with the imbalanced data. In order to empirically validate different alternatives, the study uses change data from three application packages of open-source Android data set and evaluates the performance of six different machine learning techniques. The results of the study indicate extensive improvement in the performance of the classification models when using resampling method and robust performance measures.

Keywords: Change proneness, empirical validation, imbalanced learning, machine learning techniques, object-oriented metrics.

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Authors: Maria Cecilia G. Cantos, Lorena W. Rabago, Bartolome T. Tanguilig III

Abstract:

This paper describes a conducive and structured information exchange environment for the students of the College of Computer Studies in Manuel S. Enverga University Foundation in. The system was developed to help the students to check their academic result, manage profile, make self-enlistment and assist the students to manage their academic status that can be viewed also in mobile phones. Developing class schedules in a traditional way is a long process that involves making many numbers of choices. With Hill Climbing Algorithm, however, the process of class scheduling, particularly with regards to courses to be taken by the student aligned with the curriculum, can perform these processes and end up with an optimum solution. The proponent used Rapid Application Development (RAD) for the system development method. The proponent also used the PHP as the programming language and MySQL as the database.

Keywords: Hill climbing algorithm, integrated system, mobile web-based, student information system.

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Authors: A. Pashayev, D. Askerov, R.Sadiqov, A. Samedov, C. Ardil

Abstract:

In contrast to existing methods which do not take into account multiconnectivity in a broad sense of this term, we develop mathematical models and highly effective combination (BIEM and FDM) numerical methods of calculation of stationary and cvazistationary temperature field of a profile part of a blade with convective cooling (from the point of view of realization on PC). The theoretical substantiation of these methods is proved by appropriate theorems. For it, converging quadrature processes have been developed and the estimations of errors in the terms of A.Ziqmound continuity modules have been received. For visualization of profiles are used: the method of the least squares with automatic conjecture, device spline, smooth replenishment and neural nets. Boundary conditions of heat exchange are determined from the solution of the corresponding integral equations and empirical relationships. The reliability of designed methods is proved by calculation and experimental investigations heat and hydraulic characteristics of the gas turbine 1st stage nozzle blade

Keywords: multiconnected systems, method of the boundary integrated equations, splines, neural networks.

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Authors: C. A. Alves, A. I. Calvo, A. Castro, R. Fraile, M. Evtyugina, E. F. Bate-Epey

Abstract:

In July 2012, an indoor/outdoor monitoring programme was undertaken in two university sports facilities: a fronton and a gymnasium. Comfort parameters (temperature, relative humidity, CO and CO2) and total volatile organic compounds (VOCs) were continuously monitored. Concentrations of NO2, carbonyl compounds and individual VOCs were obtained. Low volume samplers were used to collect particulate matter (PM10). The minimum ventilation rates stipulated for acceptable indoor air quality were observed in both sports facilities. It was found that cleaning activities may have a large influence on the VOC levels. Acrolein was one of the most abundant carbonyl compounds, showing concentrations above the recommended limit. Formaldehyde was detected at levels lower than those commonly reported for other indoor environments. The PM10 concentrations obtained during the occupancy periods ranged between 38 and 43μgm-3 in the fronton and from 154 to 198μgm-3 in the gymnasium.

Keywords: Air exchange rates, carbonyls, gymnasiums, indoor air quality, PM10, VOCs.

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Authors: A. Pashayev, D. Askerov, C. Ardil, R. Sadiqov

Abstract:

In contrast to existing methods which do not take into account multiconnectivity in a broad sense of this term, we develop mathematical models and highly effective combination (BIEM and FDM) numerical methods of calculation of stationary and quasi-stationary temperature field of a profile part of a blade with convective cooling (from the point of view of realization on PC). The theoretical substantiation of these methods is proved by appropriate theorems. For it, converging quadrature processes have been developed and the estimations of errors in the terms of A.Ziqmound continuity modules have been received. For visualization of profiles are used: the method of the least squares with automatic conjecture, device spline, smooth replenishment and neural nets. Boundary conditions of heat exchange are determined from the solution of the corresponding integral equations and empirical relationships. The reliability of designed methods is proved by calculation and experimental investigations heat and hydraulic characteristics of the gas turbine first stage nozzle blade.

Keywords: Multiconnected systems, method of the boundary integrated equations, splines, neural networks.

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Authors: Leena N. Fukey, Surya S. Issac

Abstract:

This review paper aims at understanding the importance of implementing sustainable green practices in the current hotel industry and the perception of the same from the point of view of the customers as well as the industry experts. Many hotels have benefited from green management such as enhanced reputation of the firm and more worth customers. For the business standing, it reduces business’s cost for posting advertisements and the clear hotel’s orientation shows hotels’ positive image which might increase employees’ recognition toward the business. Sustainability in business is the growth in lively processes which enable people to understand the potential to protect the Earth’s existent support systems. Well, looking to the future today’s green concerns will definitely become facet of more synchronized business environment, perhaps the concerns discussed in this study, may exchange a few words which hotels may consider in near future to widen awareness and improve business model.

Keywords: Environmental Protection, Green Hotel Concept, Hotel Industry, Sustainability.

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Authors: Rasaki O. Olanrewaju

Abstract:

The driven processes of Wiener and Lévy are known self-standing Gaussian-Markov processes for fitting non-linear dynamical Vasciek model. In this paper, a coincidental Gaussian density stationarity condition and autocorrelation function of the two driven processes were established. This led to the conflation of Wiener and Lévy processes so as to investigate the efficiency of estimates incorporated into the one-dimensional Vasciek model that was estimated via the Maximum Likelihood (ML) technique. The conditional laws of drift, diffusion and stationarity process was ascertained for the individual Wiener and Lévy processes as well as the commingle of the two processes for a fixed effect and Autoregressive like Vasciek model when subjected to financial series; exchange rate of Naira-CFA Franc. In addition, the model performance error of the sub-merged driven process was miniature compared to the self-standing driven process of Wiener and Lévy.

Keywords: Wiener process, Lévy process, Vasciek model, drift, diffusion, Gaussian density stationary.

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Authors: Kitti Koonsanit, Chuleerat Jaruskulchai, Poonsak Miphokasap, Apisit Eiumnoh

Abstract:

In the end of the day, meteorological data and environmental data becomes widely used such as plant varieties selection system. Variety plant selection for planted area is of almost importance for all crops, including varieties of sugarcane. Since sugarcane have many varieties. Variety plant non selection for planting may not be adapted to the climate or soil conditions for planted area. Poor growth, bloom drop, poor fruit, and low price are to be from varieties which were not recommended for those planted area. This paper presents plant varieties selection system for planted areas in Thailand from meteorological data and environmental data by the use of decision tree techniques. With this software developed as an environmental data analysis tool, it can analyze resulting easier and faster. Our software is a front end of WEKA that provides fundamental data mining functions such as classify, clustering, and analysis functions. It also supports pre-processing, analysis, and decision tree output with exporting result. After that, our software can export and display data result to Google maps API in order to display result and plot plant icons effectively.

Keywords: Plant varieties selection system, decision tree, expert recommendation.

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Authors: Tsunwai Gary Yip

Abstract:

Phase locked loops for data links operating at 10 Gb/s or faster are low phase noise devices designed to operate with a low jitter reference clock. Characterization of their jitter transfer function is difficult because the intrinsic noise of the device is comparable to the random noise level in the reference clock signal. A linear model is proposed to account for the intrinsic noise of a PLL. The intrinsic noise data of a PLL for 10 Gb/s links is presented. The jitter transfer function of a PLL in a test chip for 12.8 Gb/s data links was determined in experiments using the 400 MHz reference clock as the source of simultaneous excitations over a wide range of frequency. The result shows that the PLL jitter transfer function can be approximated by a second order linear model.

Keywords: Intrinsic phase noise, jitter in data link, PLL jitter transfer function, high speed clocking in electronic circuit

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Authors: Ahmed Jassim Shkarah, Mohd Yusoff Bin Sulaiman, Md Razali bin Hj Ayob

Abstract:

A 3D-conjugate numerical investigation was conducted to predict heat transfer characteristics in a rectangular cross-sectional micro-channel employing simultaneously developing Tow-phase flows. The sole purpose for analyzing two phase flow heat transfer in rectangular micro channel is to pin point what are the different factors affecting this phenomenon. Different methods and techniques have been undertaken to analyze the equations arising constituting the flow of heat from gas phase to liquid phase and vice versa.Different models of micro channels have been identified and analyzed. How the geometry of micro channels affects their activity i.e. of circular and non-circular geometry has also been reviewed. To the study the results average Nusselt no plotted against the Reynolds no has been taken into consideration to study average heat exchange in micro channels against applied heat flux. High heat fluxes up to 140 W/cm2 were applied to investigate micro-channel thermal characteristics.

Keywords: Tow Phase flow, Micro channel, VOF.

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Authors: Chen May Oh, Nadzrah Abu Bakar

Abstract:

This case study investigates the areas of self-reflection through the written content of four university students’ blogs. The study was undertaken to explore the categories of self-reflection in relation to the use of blogs. Data collection methods included downloading students’ blog entries and recording individual interviews to further support the data. Data was analyzed using computer assisted qualitative data analysis software, Nvivo, to categories and code the data. The categories of self-reflection revealed in the findings showed that university students used blogs to reflect on (1) life in varsity, (2) emotions and feelings, (3) various relationships, (4) personal growth, (5) spirituality, (6) health conditions, (7) busyness with daily chores, (8) gifts for people and themselves and (9) personal interests. Overall, all four of the students had positive experiences and felt satisfied using blogs for self-reflection.

Keywords: Blogging, personal growth, self-reflection, university students.

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Authors: Pejman Hosseinioun, Hasan Shakeri, Ghasem Ghorbanirostam

Abstract:

In recent years, we have seen an increasing importance of research and study on knowledge source, decision support systems, data mining and procedure of knowledge discovery in data bases and it is considered that each of these aspects affects the others. In this article, we have merged information source and knowledge source to suggest a knowledge based system within limits of management based on storing and restoring of knowledge to manage information and improve decision making and resources. In this article, we have used method of data mining and Apriori algorithm in procedure of knowledge discovery one of the problems of Apriori algorithm is that, a user should specify the minimum threshold for supporting the regularity. Imagine that a user wants to apply Apriori algorithm for a database with millions of transactions. Definitely, the user does not have necessary knowledge of all existing transactions in that database, and therefore cannot specify a suitable threshold. Our purpose in this article is to improve Apriori algorithm. To achieve our goal, we tried using fuzzy logic to put data in different clusters before applying the Apriori algorithm for existing data in the database and we also try to suggest the most suitable threshold to the user automatically.

Keywords: Decision support system, data mining, knowledge discovery, data discovery, fuzzy logic.

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Authors: Chin Tangtarntana

Abstract:

The main purpose of this study was to investigate the effects of animation in offensive product advertising. Experiment was conducted to collect consumer responses toward animated and static ads of offensive and non-offensive products. The study was conducted by distributing questionnaires to the target respondents. According to statistics from Innovative Internet Research Center, Thailand, majority of internet users are 18 – 44 years old. The results revealed an interaction between ad design and offensive product. Specifically, when used in offensive product advertisements, animated ads were not effective for consumer attention, but yielded positive response in terms of attitude toward product. The findings support that information processing model is accurate in predicting consumer cognitive response toward cartoon ads, whereas U&G, arousal, and distinctive theory is more accurate in predicting consumer affective response. In practical, these findings can also be used to guide ad designers and marketers that are suitable for offensive products.

Keywords: Animation, banner ad design, consumer responses, offensive product advertising, stock exchange of Thailand.

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Authors: Moth'd Belal. Al-Daoud

Abstract:

Clustering is a very well known technique in data mining. One of the most widely used clustering techniques is the k-means algorithm. Solutions obtained from this technique are dependent on the initialization of cluster centers. In this article we propose a new algorithm to initialize the clusters. The proposed algorithm is based on finding a set of medians extracted from a dimension with maximum variance. The algorithm has been applied to different data sets and good results are obtained.

Keywords: clustering, k-means, data mining.

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Authors: Kittisak Kerdprasop, Nittaya Kerdprasop

Abstract:

Frequent pattern discovery over data stream is a hard problem because a continuously generated nature of stream does not allow a revisit on each data element. Furthermore, pattern discovery process must be fast to produce timely results. Based on these requirements, we propose an approximate approach to tackle the problem of discovering frequent patterns over continuous stream. Our approximation algorithm is intended to be applied to process a stream prior to the pattern discovery process. The results of approximate frequent pattern discovery have been reported in the paper.

Keywords: Frequent pattern discovery, Approximate algorithm, Data stream analysis.

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Authors: Zhou Yu, Jiang Feng

Abstract:

An adaptive Chinese hand-talking system is presented in this paper. By analyzing the 3 data collecting strategies for new users, the adaptation framework including supervised and unsupervised adaptation methods is proposed. For supervised adaptation, affinity propagation (AP) is used to extract exemplar subsets, and enhanced maximum a posteriori / vector field smoothing (eMAP/VFS) is proposed to pool the adaptation data among different models. For unsupervised adaptation, polynomial segment models (PSMs) are used to help hidden Markov models (HMMs) to accurately label the unlabeled data, then the "labeled" data together with signerindependent models are inputted to MAP algorithm to generate signer-adapted models. Experimental results show that the proposed framework can execute both supervised adaptation with small amount of labeled data and unsupervised adaptation with large amount of unlabeled data to tailor the original models, and both achieve improvements on the performance of recognition rate.

Keywords: sign language recognition, signer adaptation, eMAP/VFS, polynomial segment model.

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Authors: P. Kumsawat, N. Pimpru, K. Attakitmongcol, A.Srikaew

Abstract:

In this paper, we proposed an efficient data compression strategy exploiting the multi-resolution characteristic of the wavelet transform. We have developed a sensor node called “Smart Sensor Node; SSN". The main goals of the SSN design are lightweight, minimal power consumption, modular design and robust circuitry. The SSN is made up of four basic components which are a sensing unit, a processing unit, a transceiver unit and a power unit. FiOStd evaluation board is chosen as the main controller of the SSN for its low costs and high performance. The software coding of the implementation was done using Simulink model and MATLAB programming language. The experimental results show that the proposed data compression technique yields recover signal with good quality. This technique can be applied to compress the collected data to reduce the data communication as well as the energy consumption of the sensor and so the lifetime of sensor node can be extended.

Keywords: Wireless sensor network, wavelet transform, data compression, ZigBee, skipped high-pass sub-band.

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Authors: Shilpi Kushwaha, Suparna Sodaye, P. Padmaja

Abstract:

Palm shell obtained from coastal part of southern India was studied for the removal for the adsorption of Hg (II) ions. Batch adsorption experiments were carried out as a function of pH, concentration of Hg (II) ions, time, temperature and adsorbent dose. Maximum removal was seen in the range pH 4.0- pH 7.0. The palm shell powder used as adsorbent was characterized for its surface area, SEM, PXRD, FTIR, ion exchange capacity, moisture content, and bulk density, soluble content in water and acid and pH. The experimental results were analyzed using Langmuir I, II, III, IV and Freundlich adsorption isotherms. The batch sorption kinetics was studied for the first order reversible reaction, pseudo first order; pseudo second order reaction and the intra-particle diffusion reaction. The biomass was successfully used for removal Hg (II) from synthetic and industrial effluents and the technique appears industrially applicable and viable.

Keywords: Biosorbent, mercury removal, borassus flabellifer, isotherms, kinetics, palm shell.

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Authors: Uzma Bashir, Jamaludin Md. Ali

Abstract:

This study is concerned with the visualization of monotone data using a piecewise C1 rational trigonometric interpolating scheme. Four positive shape parameters are incorporated in the structure of rational trigonometric spline. Conditions on two of these parameters are derived to attain the monotonicity of monotone data and othertwo are leftfree. Figures are used widely to exhibit that the proposed scheme produces graphically smooth monotone curves.

Keywords: Trigonometric splines, Monotone data, Shape preserving, C1 monotone interpolant.

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Authors: Pham Van Nha, Le Cam Binh

Abstract:

Particle swarm optimization (PSO) is a population-based stochastic optimization algorithm. PSO was inspired by the natural behavior of birds and fish in migration and foraging for food. PSO is considered as a multidisciplinary optimization model that can be applied in various optimization problems. PSO’s ideas are simple and easy to understand but PSO is only applied in simple model problems. We think that in order to expand the applicability of PSO in complex problems, PSO should be described more explicitly in the form of a mathematical model. In this paper, we represent PSO in a mathematical model and apply in the multivariate data classification. First, PSOs general mathematical model (MPSO) is analyzed as a universal optimization model. Then, Model of Optimal Centroids (MOC) is proposed for the multivariate data classification. Experiments were conducted on some benchmark data sets to prove the effectiveness of MOC compared with several proposed schemes.

Keywords: Analysis of optimization, artificial intelligence-based optimization, optimization for learning and data analysis, global optimization.

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Authors: M. Govindarajan, R. M.Chandrasekaran

Abstract:

Text data mining is a process of exploratory data analysis. Classification maps data into predefined groups or classes. It is often referred to as supervised learning because the classes are determined before examining the data. This paper describes proposed radial basis function Classifier that performs comparative crossvalidation for existing radial basis function Classifier. The feasibility and the benefits of the proposed approach are demonstrated by means of data mining problem: direct Marketing. Direct marketing has become an important application field of data mining. Comparative Cross-validation involves estimation of accuracy by either stratified k-fold cross-validation or equivalent repeated random subsampling. While the proposed method may have high bias; its performance (accuracy estimation in our case) may be poor due to high variance. Thus the accuracy with proposed radial basis function Classifier was less than with the existing radial basis function Classifier. However there is smaller the improvement in runtime and larger improvement in precision and recall. In the proposed method Classification accuracy and prediction accuracy are determined where the prediction accuracy is comparatively high.

Keywords: Text Data Mining, Comparative Cross-validation, Radial Basis Function, runtime, accuracy.

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Authors: Mohammad Sadeghi, Behrouz Heidari, Korush Montazeri

Abstract:

A novel thermo-sensitive superabsorbent hydrogel with salt- and pH-responsiveness properties was obtained by grafting of mixtures of acrylic acid (AA) and N-isopropylacrylamide (NIPAM) monomers onto kappa-carrageenan, kC, using ammonium persulfate (APS) as a free radical initiator in the presence of methylene bisacrylamide (MBA) as a crosslinker. Infrared spectroscopy was carried out to confirm the chemical structure of the hydrogel. Moreover, morphology of the samples was examined by scanning electron microscopy (SEM). The effect of MBA concentration and AA/NIPAM weight ratio on the water absorbency capacity has been investigated. The swelling variations of hydrogels were explained according to swelling theory based on the hydrogel chemical structure. The hydrogels exhibited salt-sensitivity and cation exchange properties. The temperature- and pH-reversibility properties of the hydrogels make the intelligent polymers as good candidates for considering as potential carriers for bioactive agents, e.g. drugs.

Keywords: superabsorbent, carrageenan, acrylic acid, Nisopropylacrylamide, hydrogel, swelling

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Authors: Ginhsuan Li, Chiuyun Hung, Desheng Chen, Yiwen Wang

Abstract:

Application-Specific Instruction (ASI ) set Processors (ASIP) have become an important design choice for embedded systems due to runtime flexibility, which cannot be provided by custom ASIC solutions. One major bottleneck in maximizing ASIP performance is the limitation on the data bandwidth between the General Purpose Register File (GPRF) and ASIs. This paper presents the Implicit Registers (IRs) to provide the desirable data bandwidth. An ASI Input/Output model is proposed to formulate the overheads of the additional data transfer between the GPRF and IRs, therefore, an IRs allocation algorithm is used to achieve the better performance by minimizing the number of extra data transfer instructions. The experiment results show an up to 3.33x speedup compared to the results without using IRs.

Keywords: Application-Specific Instruction-set Processors, data bandwidth, configurable processor, implicit register.

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Authors: Hiroyuki Ohsaki, Makoto Imase

Abstract:

In Grid computing, a data transfer protocol called GridFTP has been widely used for efficiently transferring a large volume of data. Currently, two versions of GridFTP protocols, GridFTP version 1 (GridFTP v1) and GridFTP version 2 (GridFTP v2), have been proposed in the GGF. GridFTP v2 supports several advanced features such as data streaming, dynamic resource allocation, and checksum transfer, by defining a transfer mode called X-block mode. However, in the literature, effectiveness of GridFTP v2 has not been fully investigated. In this paper, we therefore quantitatively evaluate performance of GridFTP v1 and GridFTP v2 using mathematical analysis and simulation experiments. We reveal the performance limitation of GridFTP v1, and quantitatively show effectiveness of GridFTP v2. Through several numerical examples, we show that by utilizing the data streaming feature, the average file transfer time of GridFTP v2 is significantly smaller than that of GridFTP v1.

Keywords: Grid Computing, GridFTP, Performance Evaluation, Queuing Theory.

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Authors: K. Indra Gandhi

Abstract:

Wireless Sensor Networks (WSNs) have always been characterized for application-specific sensing, relaying and collection of information for further analysis. However, software development was not considered as a separate entity in this process of data collection which has posed severe limitations on the software development for WSN. Software development for WSN is a complex process since the components involved are data-driven, network-driven and application-driven in nature. This implies that there is a tremendous need for the separation of concern from the software development perspective. A layered approach for developing data acquisition design based on Model Driven Development (MDD) has been proposed as the sensed data collection process itself varies depending upon the application taken into consideration. This work focuses on the layered view of the data acquisition process so as to ease the software point of development. A metamodel has been proposed that enables reusability and realization of the software development as an adaptable component for WSN systems. Further, observing users perception indicates that proposed model helps in improving the programmer's productivity by realizing the collaborative system involved.

Keywords: Model-driven development, wireless sensor networks, data acquisition, separation of concern, layered design.

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Authors: Abeer K. Jameel, Harry Evdorides

Abstract:

Iraq is a middle income country where the road safety issue is considered one of the leading causes of deaths. To control the road risk issue, the Iraqi Ministry of Planning, General Statistical Organization started to organise a collection system of traffic accidents data with details related to their causes and severity. These data are published as an annual report. In this paper, a review of the available crash data in Iraq will be presented. The available data represent the rate of accidents in aggregated level and classified according to their types, road users’ details, and crash severity, type of vehicles, causes and number of causalities. The review is according to the types of models used in road safety studies and research, and according to the required road safety data in the road constructions tasks. The available data are also compared with the road safety dataset published in the United Kingdom as an example of developed country. It is concluded that the data in Iraq are suitable for descriptive and exploratory models, aggregated level comparison analysis, and evaluation and monitoring the progress of the overall traffic safety performance. However, important traffic safety studies require disaggregated level of data and details related to the factors of the likelihood of traffic crashes. Some studies require spatial geographic details such as the location of the accidents which is essential in ranking the roads according to their level of safety, and name the most dangerous roads in Iraq which requires tactic plan to control this issue. Global Road safety agencies interested in solve this problem in low and middle-income countries have designed road safety assessment methodologies which are basing on the road attributes data only. Therefore, in this research it is recommended to use one of these methodologies.

Keywords: Data availability, Iraq, road safety.

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