Search results for: task performance.

Authors: Roshayani Arshad, Suaini Othman, Rohana Othman

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This study examines the effect of Islamic Corporate Social Responsibility disclosure and on corporate reputation as well as performance. These relationships are examined based on content analysis of of annual reports of 17 Islamic banks in Malaysia for 2008, 2009 and 2010. Results of this study provide evidence that CSR activities communicated in corporate annual reports are significantly positively related with corporate reputation as well as firm performance. These results indicate that CSR activities and disclosure from Islamic perspectives are equally important business strategies in creating continuous superior performance for organisations. In addition, it also highlights that organisations need to develop a stakeholder orientation particularly in an environment of increasing pressure from jurisdictions dominated by Islamic stakeholders on organisations engaging in Islamic products to increase their social responsibilities from the Islamic perspectives.

Keywords: Islamic Corporate Social Responsibility, Corporate Reputation, Firm Performance, Islamic Banks

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Authors: M. Sankari, R. Bremananth, C.Meena

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Localization and Recognition of License registration characters from the moving vehicle is a computationally complex task in the field of machine vision and is of substantial interest because of its diverse applications such as cross border security, law enforcement and various other intelligent transportation applications. Previous research used the plate specific details such as aspect ratio, character style, color or dimensions of the plate in the complex task of plate localization. In this paper, license registration character is localized by Enhanced Weight based density map (EWBDM) method, which is independent of such constraints. In connection with our previous method, this paper proposes a method that relaxes constraints in lighting conditions, different fonts of character occurred in the plate and plates with hand-drawn characters in various aspect quotients. The robustness of this method is well suited for applications where the appearance of plates seems to be varied widely. Experimental results show that this approach is suited for recognizing license plates in different external environments. 

Keywords: Character segmentation, Connectivity checking, Edge detection, Image analysis, license plate localization, license number recognition, Quality frame selection

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Authors: Cesar H. Ortega Jimenez, Ignacio Eguia Salinas, Pedro Garrido Vega, Jose A. Dominguez Machuca

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The aim of this study is to identify the conditions of implementation for reconfigurability in summarizing past flexible manufacturing systems (FMS) research by drawing overall conclusions from many separate High Performance Manufacturing (HPM) studies. Meta-analysis will be applied to links between HPM programs and their practices related to FMS and manufacturing performance with particular reference to responsiveness performance. More specifically, an application of meta-analysis will be made with reference to two of the main steps towards the development of an empirically-tested theory: testing the adequacy of the measurement of variables and testing the linkages between the variables.

Keywords: FMS (flexible manufacturing system), HPM (highperformance manufacturing), reconfigurability, RMS (reconfigurablemanufacturing system), responsiveness

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Authors: A. Ashjaran, A. Rashidi, R. Ghazi-Saeidi

Abstract:

Protective clothing limits heat transfer and hampers task performance due to the increased weight. Militarism protective clothing enables humans to operate in adverse environments. In the selection and evaluation of militarism protective clothing attention should be given to heat strain, ergonomic and fit issues next to the actual protection it offers. Fifty Male healthy subjects participated in the study. The subjects were dressed in shorts, T-shirts, socks, sneakers and four deferent kinds of militarism protective clothing such as CS, CSB, CS with NBC protection and CS with NBC- protection added. Ergonomically and psychological strains of every four cloths were investigated on subjects by walking on a treadmill (7km/hour) with a 19.7 kg backpack. As a result of these tests were showed that, the highest heart rate was found wearing the NBC-protection added outfit, the highest temperatures were observed wearing NBCprotection added, followed by respectively CS with NBC protection, CSB and CS and the highest value for thermal comfort (implying worst thermal comfort) was observed wearing NBC-protection added.

Keywords: Militarist protective clothing, Ergonomic, Heat strain, Thermal comfort

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Authors: Kwangho Cha, Hyeyoung Cho, Sungho Kim

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As many scientific applications require large data processing, the importance of parallel I/O has been increasingly recognized. Collective I/O is one of the considerable features of parallel I/O and enables application programmers to easily handle their large data volume. In this paper we measured and analyzed the performance of original collective I/O and the subgroup method, the way of using collective I/O of MPI effectively. From the experimental results, we found that the subgroup method showed good performance with small data size.

Keywords: Collective I/O, MPI, parallel file system.

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Authors: Ahmed Ashraf Khamis, Sherif A. Ibrahim, Mahmoud ElKhatieb, Mohamed A. Barakat

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Parametric design deemed to be one of icons of the modern architectural trends that facilitates taking complex design decisions counting on altering various design parameters. Double skin façades are one of the parametric applications that are used in parametric designs. This paper opts to enhance different daylight parameters of a selected case study office building in Cairo using a parametric double skin façade. First, the design and optimization process was executed utilizing Grasshopper parametric design software package, in which the daylighting performance of the base case building model was compared with the one used in the double façade showing an enhancement in task plane illuminance by 180%. Second, execution drawings are made for the optimized design using Revit software. Finally, computerized digital fabrication stages of the designed model with various scales are demonstrated to reach the final design decisions using Simplify 3D for mock-up digital fabrication.

Keywords: Parametric design, Double skin façades, Digital Fabrication, Grasshopper, Simplify 3D.

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Authors: Erh-Wen Hu, Cyril S. Ku, Andrew T. Russo, Bogong Su, Jian Wang

Abstract:

Unlike general-purpose processors, digital signal processors (DSP processors) are strongly application-dependent. To meet the needs for diverse applications, a wide variety of DSP processors based on different architectures ranging from the traditional to VLIW have been introduced to the market over the years. The functionality, performance, and cost of these processors vary over a wide range. In order to select a processor that meets the design criteria for an application, processor performance is usually the major concern for digital signal processing (DSP) application developers. Performance data are also essential for the designers of DSP processors to improve their design. Consequently, several DSP performance benchmarks have been proposed over the past decade or so. However, none of these benchmarks seem to have included recent new DSP applications. In this paper, we use a new benchmark that we recently developed to compare the performance of popular DSP processors from Texas Instruments and StarCore. The new benchmark is based on the Selectable Mode Vocoder (SMV), a speech-coding program from the recent third generation (3G) wireless voice applications. All benchmark kernels are compiled by the compilers of the respective DSP processors and run on their simulators. Weighted arithmetic mean of clock cycles and arithmetic mean of code size are used to compare the performance of five DSP processors. In addition, we studied how the performance of a processor is affected by code structure, features of processor architecture and optimization of compiler. The extensive experimental data gathered, analyzed, and presented in this paper should be helpful for DSP processor and compiler designers to meet their specific design goals.

Keywords: digital signal processors, DSP benchmark, instruction level parallelism, modified cyclomatic complexity, performance analysis.

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Authors: Kati Kõrbe Kaare, Ott Koppel

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Transport and logistics are the lifeblood of societies. There is a strong correlation between overall growth in economic activity and growth of transport. The movement of people and goods has the potential for creating wealth and prosperity, therefore the state of transportation infrastructure and especially the condition of road networks is often a governmental priority. The design, building and maintenance of national roads constitute a substantial share of government budgets. Taking into account the magnitude and importance of these investments, the expedience, efficiency and sustainability of these projects are of great public interest. This paper provides an overview of supply chain management principles applied to road construction. In addition, road construction performance measurement systems and ICT solutions are discussed. Road construction in Estonia is analyzed. The authors propose the development of a national performance measurement system for road construction.

Keywords: ICT in road construction, key performance indicators, quality performance measurement, road construction supply chain.

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Authors: Waqar Haque, Pai Qi

Abstract:

The speculative locking (SL) protocol extends the twophase locking (2PL) protocol to allow for parallelism among conflicting transactions. The adaptive speculative locking (ASL) protocol provided further enhancements and outperformed SL protocols under most conditions. Neither of these protocols consider the impact of network latency on the performance of the distributed database systems. We have studied the performance of ASL protocol taking into account the communication overhead. The results indicate that though system load can counter network latency, it can still become a bottleneck in many situations. The impact of latency on performance depends on many factors including the system resources. A flexible discrete event simulator was used as the testbed for this study.

Keywords: concurrency control, distributed database systems, speculative locking

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Authors: R. Matousek, S. Lang, P. Minar, P. Pivonka

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In the control theory one attempts to find a controller that provides the best possible performance with respect to some given measures of performance. There are many sorts of controllers e.g. a typical PID controller, LQR controller, Fuzzy controller etc. In the paper will be introduced polynomial controller with novel tuning method which is based on the special pole placement encoding scheme and optimization by Genetic Algorithms (GA). The examples will show the performance of the novel designed polynomial controller with comparison to common PID controller.

Keywords: Evolutionary design, Genetic algorithms, PID controller, Pole placement, Polynomial controller

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Authors: T. Teo, S. W. Lye, Y. F. Li, Z. Zakaria

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Wearable devices such as Electroencephalography (EEG) hold immense potential in the monitoring and assessment of a person’s task engagement. This is especially so in remote or online sites. Research into its use in measuring an individual's cognitive state while performing task activities is therefore expected to increase. Despite the growing number of EEG research into brain functioning activities of a person, key challenges remain in adopting EEG for real-time operations. These include limited portability, long preparation time, high number of channel dimensionality, intrusiveness, as well as level of accuracy in acquiring neurological data. This paper proposes an approach using a 4-6 EEG channels to determine the cognitive states of a subject when undertaking a set of passive and active monitoring tasks of a subject. Air traffic controller (ATC) dynamic-tasks are used as a proxy. The work found that using a developed channel reduction and identifier algorithm, good trend adherence of 89.1% can be obtained between a commercially available brain computer interface (BCI) 14 channel Emotiv EPOC+ EEG headset and that of a carefully selected set of reduced 4-6 channels. The approach can also identify different levels of engagement activities ranging from general monitoring, ad hoc and repeated active monitoring activities involving information search, extraction, and memory activities.

Keywords: Neurophysiology, monitoring, EEG, outliers, electroencephalography.

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Authors: S. Falkenberg, L. Overmeyer

Abstract:

The “conveyor belt" as a product represents a complex high performance component with a wide range of different applications. Further development of these highly complex components demands an integration of new technologies and new enhanced materials. In this context nanostructured fillers appear to have a more promising effect on the performance of the conveyor belt composite than conventional micro-scaled fillers. Within the project “DotTrans" nanostructured fillers, for example silicon dioxide, are used to optimize performance parameters of conveyor belt systems. The objective of the project includes operating parameters like energy consumption or friction characteristics as well as adaptive parameters like cut or wear resistance.

Keywords: Conveyor belt, nanostructured fillers, wear resistance, friction characteristics.

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Authors: F. Lazzeri, I. Reiter

Abstract:

Energy production optimization has been traditionally very important for utilities in order to improve resource consumption. However, load forecasting is a challenging task, as there are a large number of relevant variables that must be considered, and several strategies have been used to deal with this complex problem. This is especially true also in microgrids where many elements have to adjust their performance depending on the future generation and consumption conditions. The goal of this paper is to present a solution for short-term load forecasting in microgrids, based on three machine learning experiments developed in R and web services built and deployed with different components of Cortana Intelligence Suite: Azure Machine Learning, a fully managed cloud service that enables to easily build, deploy, and share predictive analytics solutions; SQL database, a Microsoft database service for app developers; and PowerBI, a suite of business analytics tools to analyze data and share insights. Our results show that Boosted Decision Tree and Fast Forest Quantile regression methods can be very useful to predict hourly short-term consumption in microgrids; moreover, we found that for these types of forecasting models, weather data (temperature, wind, humidity and dew point) can play a crucial role in improving the accuracy of the forecasting solution. Data cleaning and feature engineering methods performed in R and different types of machine learning algorithms (Boosted Decision Tree, Fast Forest Quantile and ARIMA) will be presented, and results and performance metrics discussed.

Keywords: Time-series, features engineering methods for forecasting, energy demand forecasting, Azure machine learning.

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Authors: Petia Georgieva, Sebastião Feyo de Azevedo

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This paper is focused on issues of nonlinear dynamic process modeling and model-based predictive control of a fed-batch sugar crystallization process applying the concept of artificial neural networks as computational tools. The control objective is to force the operation into following optimal supersaturation trajectory. It is achieved by manipulating the feed flow rate of sugar liquor/syrup, considered as the control input. A feed forward neural network (FFNN) model of the process is first built as part of the controller structure to predict the process response over a specified (prediction) horizon. The predictions are supplied to an optimization procedure to determine the values of the control action over a specified (control) horizon that minimizes a predefined performance index. The control task is rather challenging due to the strong nonlinearity of the process dynamics and variations in the crystallization kinetics. However, the simulation results demonstrated smooth behavior of the control actions and satisfactory reference tracking.

Keywords: Feed forward neural network, process modelling, model predictive control, crystallization process.

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Authors: Mahmoud Miri, Morteza Naghipour, Amir Kashiryfar

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The unanticipated destruct of more of the steel moment frames in Northridge earthquake, altered class of regard to the beamto- column connections in moment frames. Panel zone is one the significant part of joints which, it-s stiffness and rigidity has an important effect on the behavior and ductility of the frame. Specifically that behavior of panel zone has a very significant effect on the special moment frames. In this paper , meanwhile the relations for modeling of panel zone in frames are expressed , special moment frames with different spans and stories were studied in the way of performance-based design. The frames designed in according with Iranian steel building code. The effect of panel zone is also considered and in the case of non-existence of performance level, by changing in intimacies and parameter of panel zone, performance level is considered.

Keywords: steel moment frame, panel zone, performance based design

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Authors: E. Ahvar, M. Fathy

Abstract:

Ad hoc networks are characterized by multihop wireless connectivity, frequently changing network topology and the need for efficient dynamic routing protocols. We compare the performance of three routing protocols for mobile ad hoc networks: Dynamic Source Routing (DSR), Ad Hoc On-Demand Distance Vector Routing (AODV), location-aided routing (LAR1).Our evaluation is based on energy consumption in mobile ad hoc networks. The performance differentials are analyzed using varying network load, mobility, and network size. We simulate protocols with GLOMOSIM simulator. Based on the observations, we make recommendations about when the performance of either protocol can be best.

Keywords: Ad hoc Network, energy consumption, Glomosim, routing protocols.

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Authors: E. A. Tkachenko, E. M. Rogova, V. V. Klimov

Abstract:

One of the basic issues of development management is connected with performance measurement as a prerequisite for identifying the achievement of development objectives. The aim of our research is to develop an improved model of assessing a company’s development results. The model should take into account the cyclical nature of development and the high degree of uncertainty in dealing with numerous management tasks. Our hypotheses may be formulated as follows: Hypothesis 1. The cycle of a company’s development may be studied from the standpoint of a project cycle. To do that, methods and tools of project analysis are to be used. Hypothesis 2. The problem of the uncertainty when justifying managerial decisions within the framework of a company’s development cycle can be solved through the use of the mathematical apparatus of fuzzy logic. The reasoned justification of the validity of the hypotheses made is given in the suggested article. The fuzzy logic toolkit applies to the case of technology shift within an enterprise. It is proven that some restrictions in performance measurement that are incurred to conventional methods could be eliminated by implementation of the fuzzy logic apparatus in performance measurement models.

Keywords: Fuzzy logic, fuzzy sets, performance measurement, project analysis.

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Authors: Daya Weerasinghe

Abstract:

Parental expectations often differ to that of their children and the influence and involvement of parents, at home, may affect the student performance in the classroom. This paper presents results from a survey of Asian and European background secondary school mathematics students (N=128) in Melbourne, Australia. Student responses to survey questions were analysed using confirmatory factor analysis, followed by t-tests and ANOVA. The aim of the analysis was to identify similarities and differences in parental expectations in relation to ethnicity, gender, and the year level of the students. The notable findings from the analysis showed no significant difference (at 0.05 level) in parental expectations and student performance, in relation to ethnicity or gender. Conversely, there was a significant difference in both parental expectations and student performance between year 7 and year 12 students. Further, whilst there was a significant difference in parental expectations between year 7 and year 11 students, the students’ performances were not significantly different. The results suggest further research may be needed to understand the parental expectations and student performance between the lower and upper secondary school mathematics students.

Keywords: Ethnic background, gender, parental expectations, student performance, year level.

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Authors: Fabrício José Piacente, Vanessa de Cillos Silva, Thigo Luiz Mello Melato

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The construction industry has been demonstrating increased growth and importance in Brazil’s national economic development. This study aims to evaluate the financial performance of the leading companies in the construction sector in Brazil in the period from 2009 to 2012. An analysis is made of the capital structure, liquidity, and profitability of the six largest companies in the construction sector in Brazil: Brookfield, Cyrela, Gafisa, MRV, PDG and Rossi. The results are then compared with standard industry ratios. It was found that among the companies analyzed, MRV and Cyrela showed the best relative performance in the period under consideration.

Keywords: Accounting ratios, construction, financial performance.

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Authors: Cheng Fang, Lingwei Quan, Cunyue Lu

Abstract:

Human pose estimation and tracking are to accurately identify and locate the positions of human joints in the video. It is a computer vision task which is of great significance for human motion recognition, behavior understanding and scene analysis. There has been remarkable progress on human pose estimation in recent years. However, more researches are needed for human pose tracking especially for online tracking. In this paper, a framework, called PoseSRPN, is proposed for online single-person pose estimation and tracking. We use Siamese network attaching a pose estimation branch to incorporate Single-person Pose Tracking (SPT) and Visual Object Tracking (VOT) into one framework. The pose estimation branch has a simple network structure that replaces the complex upsampling and convolution network structure with deconvolution. By augmenting the loss of fully convolutional Siamese network with the pose estimation task, pose estimation and tracking can be trained in one stage. Once trained, PoseSRPN only relies on a single bounding box initialization and producing human joints location. The experimental results show that while maintaining the good accuracy of pose estimation on COCO and PoseTrack datasets, the proposed method achieves a speed of 59 frame/s, which is superior to other pose tracking frameworks.

Keywords: Computer vision, Siamese network, pose estimation, pose tracking.

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Authors: K. Biswas, U. H. Armin, S. M. J. Prodhan, J. A. Prithul, S. Sarker, F. Afrin

Abstract:

Alzheimer’s disease (AD) (a progressive neurodegenerative disorder) is mostly predominant cause of dementia in the elderly. Prolonging the function of acetylcholine by inhibiting both acetylcholinesterase and butyrylcholinesterase is most effective treatment therapy of AD. Traditionally Pterocarpus santalinus L. is widely known for its medicinal use. In this study, in vitro acetylcholinesterase inhibitory activity was investigated and methanolic extract of the plant showed significant activity. To confirm this activity (in vivo), learning and memory enhancing effects were tested in mice. For the test, memory impairment was induced by scopolamine (cholinergic muscarinic receptor antagonist). Anti-amnesic effect of the extract was investigated by the passive avoidance task in mice. The study also includes brain acetylcholinesterase activity. Results proved that scopolamine induced cognitive dysfunction was significantly decreased by administration of the extract solution, in the passive avoidance task and inhibited brain acetylcholinesterase activity. These results suggest that bark extract of Pterocarpus santalinus can be better option for further studies on AD via their acetylcholinesterase inhibitory actions.

Keywords: Pterocarpus santalinus, cholinesterase inhibitor, passive avoidance, Alzheimer’s disease.

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Authors: V. Eramo, L. Piazzo, M. Listanti, A. Germoni, A Cianfrani

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The performance of the Optical Code Division Multiplexing/ Wavelength Division Multiplexing (WDM/OCDM) technique for Optical Packet Switch is investigated. The impact on the performance of the impairment due to both Multiple Access Interference and Beat noise is studied. The Packet Loss Probability due to output packet contentions is evaluated as a function of the main switch and traffic parameters when Gold coherent optical codes are adopted. The Packet Loss Probability of the OCDM/WDM switch can reach 10-9 when M=16 wavelengths, Gold code of length L=511 and only 24 wavelength converters are used in the switch.

Keywords: Optical code division multiplexing, bufferless optical packet switch, performance evaluation.

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Authors: Radosveta Sokullu, Engin Karatepe

Abstract:

In the last couple of years Bluetooth has gained a large share in the market of home and personal appliances. It is now a well established technology a short range supplement to the wireless world of 802.11. The two main trends of research that have sprung from these developments are directed towards the coexistence and performance issues of Bluetooth and 802.11 as well as the co-existence in the very short range of multiple Bluetooth devices. Our work aims at thoroughly investigating different aspects of co-channel interference and effects of transmission power, distance and 802.11 interference on Bluetooth connections.

Keywords: Bluetooth, co-channel interference, 802.11, performance analysis

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Authors: H. Soleimanjahi, M. J. Nategh, S. Falahi

Abstract:

Deciding the numerous parameters involved in designing a competent artificial neural network is a complicated task. The existence of several options for selecting an appropriate architecture for neural network adds to this complexity, especially when different applications of heterogeneous natures are concerned. Two completely different applications in engineering and medical science were selected in the present study including prediction of workpiece's surface roughness in ultrasonic-vibration assisted turning and papilloma viruses oncogenicity. Several neural network architectures with different parameters were developed for each application and the results were compared. It was illustrated in this paper that some applications such as the first one mentioned above are apt to be modeled by a single network with sufficient accuracy, whereas others such as the second application can be best modeled by different expert networks for different ranges of output. Development of knowledge about the essentials of neural networks for different applications is regarded as the cornerstone of multidisciplinary network design programs to be developed as a means of reducing inconsistencies and the burden of the user intervention.

Keywords: Artificial Neural Network, Malignancy Diagnosis, Papilloma Viruses Oncogenicity, Surface Roughness, UltrasonicVibration-Assisted Turning.

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Authors: Tal Ben-Zvi, Donald N. Lombardi

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This study uses a simulation to establish a realistic environment for laboratory research on Accountable Care Organizations. We study network attributes in order to gain insights regarding healthcare providers- conduct and performance. Our findings indicate how network structure creates significant differences in organizational performance. We demonstrate how healthcare providers positioning themselves at the central, pivotal point of the network while maintaining their alliances with their partners produce better outcomes.

Keywords: Social Networks, Decision-Making, Accountable Care Organizations, Performance

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Authors: Shivakumar, G. S. Vijay, P. Srinivas Pai, B. R. Shrinivasa Rao

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In the present study, RBF neural networks were used for predicting the performance and emission parameters of a biodiesel engine. Engine experiments were carried out in a 4 stroke diesel engine using blends of diesel and Honge methyl ester as the fuel. Performance parameters like BTE, BSEC, Tex and emissions from the engine were measured. These experimental results were used for ANN modeling. RBF center initialization was done by random selection and by using Clustered techniques. Network was trained by using fixed and varying widths for the RBF units. It was observed that RBF results were having a good agreement with the experimental results. Networks trained by using clustering technique gave better results than using random selection of centers in terms of reduced MRE and increased prediction accuracy. The average MRE for the performance parameters was 3.25% with the prediction accuracy of 98% and for emissions it was 10.4% with a prediction accuracy of 80%.

Keywords: Radial Basis Function networks, emissions, Performance parameters, Fuzzy c means.

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Authors: Salwa Aftab, Sehrish Riaz

Abstract:

The objective of this study was to check the impact of grade sensitivity on learning motivation and academic performance of students and to remove the degree of difference that exists among students regarding the cause of their learning motivation and also to gain knowledge about this matter since it has not been adequately researched. Data collection was primarily done through the academic sector of Pakistan and was depended upon the responses given by students solely. A sample size of 208 university students was selected. Both paper and online surveys were used to collect data from respondents. The results of the study revealed that grade sensitivity has a positive relationship with the learning motivation of students and their academic performance. These findings were carried out through systematic correlation and regression analysis.

Keywords: Academic performance, correlation, grade sensitivity, learning motivation, regression.

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Authors: Na Li, Samuel Simon Araya, Søren Knudsen Kær

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This study investigates the effects of operating parameters of different current density, temperature and pressure on the performance of a proton exchange membrane (PEM) water electrolysis stack. A 7-cell PEM water electrolysis stack was assembled and tested under different operation modules. The voltage change and polarization curves under different test conditions, namely current density, temperature and pressure, were recorded. Results show that higher temperature has positive effect on overall stack performance, where temperature of 80 ℃ improved the cell performance greatly. However, the cathode pressure and current density has little effect on stack performance.

Keywords: PEM electrolysis stack, current density, temperature, pressure.

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Authors: Dim En Nyaung, Thin Lai Lai Thein

Abstract:

Due to the rapid increase of Internet, web opinion sources dynamically emerge which is useful for both potential customers and product manufacturers for prediction and decision purposes. These are the user generated contents written in natural languages and are unstructured-free-texts scheme. Therefore, opinion mining techniques become popular to automatically process customer reviews for extracting product features and user opinions expressed over them. Since customer reviews may contain both opinionated and factual sentences, a supervised machine learning technique applies for subjectivity classification to improve the mining performance. In this paper, we dedicate our work is the task of opinion summarization. Therefore, product feature and opinion extraction is critical to opinion summarization, because its effectiveness significantly affects the identification of semantic relationships. The polarity and numeric score of all the features are determined by Senti-WordNet Lexicon. The problem of opinion summarization refers how to relate the opinion words with respect to a certain feature. Probabilistic based model of supervised learning will improve the result that is more flexible and effective.

Keywords: Opinion Mining, Opinion Summarization, Sentiment Analysis, Text Mining.

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Authors: Patricia M. Boechler, Heather M. Gautreau

Abstract:

In this research study, postsecondary students completed an information learning task in an avatar-based 3D virtual learning environment. Three factors were of interest in relation to learning; 1) the influence of collaborative vs. independent conditions, 2) the influence of the spatial arrangement of the virtual environment (linear, random and clustered), and 3) the relationship of individual differences such as spatial skill, general computer experience and video game experience to learning. Students completed pretest measures of prior computer experience and prior spatial skill. Following the premeasure administration, students were given instruction to move through the virtual environment and study all the material within 10 information stations. In the collaborative condition, students proceeded in randomly assigned pairs, while in the independent condition they proceeded alone. After this learning phase, all students individually completed a multiple choice test to determine information retention. The overall results indicated that students in pairs did not perform any better or worse than independent students. As far as individual differences, only spatial ability predicted the performance of students. General computer experience and video game experience did not. Taking a closer look at the pairs and spatial ability, comparisons were made on pairs high/matched spatial ability, pairs low/matched spatial ability and pairs that were mismatched on spatial ability. The results showed that both high/matched pairs and mismatched pairs outperformed low/matched pairs. That is, if a pair had even one individual with strong spatial ability they would perform better than pairs with only low spatial ability individuals. This suggests that, in virtual environments, the specific individuals that are paired together are important for performance outcomes. The paper also includes a discussion of trends within the data that have implications for virtual environment education.

Keywords: Avatar-based, virtual environment, paired learning, individual differences.

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