Search results for: Optimizing Web Performance

Authors: Qiuyu Dai, Haochong Zhang, Xiangrong Liu

Abstract:

Efficient matrix-vector multiplication with diagonal sparse matrices is pivotal in a multitude of computational domains, ranging from scientific simulations to machine learning workloads. When encoded in the conventional Diagonal (DIA) format, these matrices often induce computational overheads due to extensive zero-padding and non-linear memory accesses, which can hamper the computational throughput, and elevate the usage of precious compute and memory resources beyond necessity. The ’DIA-Adaptive’ approach, a methodological enhancement introduced in this paper, confronts these challenges head-on by leveraging the advanced parallel instruction sets embedded within Machine Learning Units (MLUs). This research presents a thorough analysis of the DIA-Adaptive scheme’s efficacy in optimizing Sparse Matrix-Vector Multiplication (SpMV) operations. The scope of the evaluation extends to a variety of hardware architectures, examining the repercussions of distinct thread allocation strategies and cluster configurations across multiple storage formats. A dedicated computational kernel, intrinsic to the DIA-Adaptive approach, has been meticulously developed to synchronize with the nuanced performance characteristics of MLUs. Empirical results, derived from rigorous experimentation, reveal that the DIA-Adaptive methodology not only diminishes the performance bottlenecks associated with the DIA format but also exhibits pronounced enhancements in execution speed and resource utilization. The analysis delineates a marked improvement in parallelism, showcasing the DIA-Adaptive scheme’s ability to adeptly manage the interplay between storage formats, hardware capabilities, and algorithmic design. The findings suggest that this approach could set a precedent for accelerating SpMV tasks, thereby contributing significantly to the broader domain of high-performance computing and data-intensive applications.

Keywords: Adaptive method, DIA, diagonal sparse matrices, MLU, sparse matrix-vector multiplication.

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Authors: F. Apaydın

Abstract:

In this empirical research, how marketing managers evaluate their firms- performances and decide to make innovation is examined. They use some standards which are past performance of the firm, target performance of the firm, competitor performance, and average performance of the industry to compare and evaluate the firms- performances. It is hypothesized that marketing managers and owners of the firm compare the firms- current performance with these four standards at the same time to decide when to make innovation relating to any aspects of the firm, either management style or products. Relationship between the comparison of the firm-s performance with these standards and innovation are searched in the same regression model. The results of the regression analysis are discussed and some recommendations are made for future studies and applicants.

Keywords: Innovation, performance evaluation standards

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Authors: M. Derakhshanfar, B. Minaei-Bidgoli

Abstract:

Spatial trends are one of the valuable patterns in geo databases. They play an important role in data analysis and knowledge discovery from spatial data. A spatial trend is a regular change of one or more non spatial attributes when spatially moving away from a start object. Spatial trend detection is a graph search problem therefore heuristic methods can be good solution. Artificial immune system (AIS) is a special method for searching and optimizing. AIS is a novel evolutionary paradigm inspired by the biological immune system. The models based on immune system principles, such as the clonal selection theory, the immune network model or the negative selection algorithm, have been finding increasing applications in fields of science and engineering. In this paper, we develop a novel immunological algorithm based on clonal selection algorithm (CSA) for spatial trend detection. We are created neighborhood graph and neighborhood path, then select spatial trends that their affinity is high for antibody. In an evolutionary process with artificial immune algorithm, affinity of low trends is increased with mutation until stop condition is satisfied.

Keywords: Spatial Data Mining, Spatial Trend Detection, Heuristic Methods, Artificial Immune System, Clonal Selection Algorithm (CSA)

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Authors: Xu LiYun, Briand Florent, Fan GuoLiang

Abstract:

The loop-layout design problem (LLDP) aims at optimizing the sequence of positioning of the machines around the cyclic production line. Traffic congestion is the usual criteria to minimize in this type of problem, i.e. the number of additional cycles spent by each part in the network until the completion of its required routing sequence of machines. This paper aims at applying several improvements mechanisms such as a positioned-based crossover operator for the Genetic Algorithm (GA) called a Two Points Crossover (TPC) and an offspring selection process. The performance of the improved GA is measured using well-known examples from literature and compared to other evolutionary algorithms. Good results show that GA can still be competitive for this type of problem against more recent evolutionary algorithms.

Keywords: Crossover, genetic algorithm, layout design problem, loop-layout, manufacturing optimization.

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Authors: Saptiadi Nugroho, A. Nur Muhamad Afif

Abstract:

Understanding factors that influence employee performance is very important. By finding the significant factors, organization could intervene to improve the employee performance that simultaneously will affect organization itself. In this research, four aspects consist of PCCD training, education level, corrective action, and work location were tested to identify their influence on employee performance. By using correlation analysis and T-Test, it was found that employee performance significantly influenced by PCCD training, work location, and corrective action. Meanwhile the education level did not influence employee performance.

Keywords: Training, employee development, performance management system.

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Authors: G. Kumaravelan, R. Sivakumar

Abstract:

Modeling the behavior of the dialogue management in the design of a spoken dialogue system using statistical methodologies is currently a growing research area. This paper presents a work on developing an adaptive learning approach to optimize dialogue strategy. At the core of our system is a method formalizing dialogue management as a sequential decision making under uncertainty whose underlying probabilistic structure has a Markov Chain. Researchers have mostly focused on model-free algorithms for automating the design of dialogue management using machine learning techniques such as reinforcement learning. But in model-free algorithms there exist a dilemma in engaging the type of exploration versus exploitation. Hence we present a model-based online policy learning algorithm using interconnected learning automata for optimizing dialogue strategy. The proposed algorithm is capable of deriving an optimal policy that prescribes what action should be taken in various states of conversation so as to maximize the expected total reward to attain the goal and incorporates good exploration and exploitation in its updates to improve the naturalness of humancomputer interaction. We test the proposed approach using the most sophisticated evaluation framework PARADISE for accessing to the railway information system.

Keywords: Dialogue management, Learning automata, Reinforcement learning, Spoken dialogue system

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Authors: Liv Gingnell, Evelina Ericsson, Joakim Lilliesköld, Robert Langerström

Abstract:

In recent years, an increased competition and lower profit margins have necessitated a focus on improving the performance of the product development process, an area that traditionally have been excluded from detailed steering and evaluation. A systematic improvement requires a good understanding of the current performance, wherefore the interest for product development performance measurement has increased dramatically. This paper presents a case study that evaluates the performance of the product development performance measurement system used in a Swedish company that is a part of a global corporate group. The study is based on internal documentation and eighteen in-depth interviews with stakeholders involved in the product development process. The results from the case study includes a description of what metrics that are in use, how these are employed, and its affect on the quality of the performance measurement system. Especially, the importance of having a well-defined process proved to have a major impact on the quality of the performance measurement system in this particular case.

Keywords: Outcome metric, Performance driver, Performance measurement, Product development process.

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Authors: Ahmed Aljudaya, Derek Ingham, Lin Ma, Kevin Hughes, Mohammed Pourkashanian

Abstract:

Researchers, power companies, and state politicians have given concentrated solar power (CSP) much attention due to its capacity to generate large amounts of electricity whereas overcoming the intermittent nature of solar resources. The Linear Fresnel Reflector (LFR) is a well-known CSP technology type for being inexpensive, having a low land use factor, and suffering from low optical efficiency. The LFR was considered a cost-effective alternative option to the Parabolic Trough Collector (PTC) because of its simplistic design, and this often outweighs its lower efficiency. The LFR power plants commercially generate steam directly and indirectly in order to produce electricity with high technical efficiency and lower its costs. The purpose of this important analysis is to compare the annual performance of the Direct Steam Generation (DSG) and Indirect Steam Generation (ISG) of LFR power plants using molten salt and other different Heat Transfer Fluids (HTF) to investigate their technical and economic effects. A 50 MWe solar-only system is examined as a case study for both steam production methods in extreme weather conditions. In addition, a parametric analysis is carried out to determine the optimal solar field size that provides the lowest Levelized Cost of Electricity (LCOE) while achieving the highest technical performance. As a result of optimizing the optimum solar field size, the solar multiple (SM) is found to be between 1.2 – 1.5 in order to achieve as low as 9 Cent/KWh for the DSG of the LFR. In addition, the power plant is capable of producing around 141 GWh annually and up to 36% of the capacity factor, whereas the ISG produces less energy at a higher cost. The optimization results show that the DSG’s performance overcomes the ISG in producing around 3% more annual energy, 2% lower LCOE, and 28% less capital cost.

Keywords: Concentrated Solar Power, Levelized cost of electricity, Linear Fresnel reflectors, Steam generation.

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Authors: A. Hadi-Vencheh, N. Shayesteh Moghadam

Abstract:

Data envelopment analysis (DEA) has gained great popularity in environmental performance measurement because it can provide a synthetic standardized environmental performance index when pollutants are suitably incorporated into the traditional DEA framework. Since some of the environmental performance indicators cannot be controlled by companies managers, it is necessary to develop the model in a way that it could be applied when discretionary and/or non-discretionary factors were involved. In this paper, we present a semi-radial DEA approach to measuring environmental performance, which consists of non-discretionary factors. The model, then, has been applied on a real case.

Keywords: Environmental performance, efficiency, non-discretionary variables, data envelopment analysis.

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Authors: Mohsen Soori, Fooad Karimi Ghaleh Jough

Abstract:

The integration of Artificial Intelligence (AI) techniques in the optimization of steel moment frame structures represents a transformative approach to enhance the design, analysis, and performance of these critical engineering systems. The review encompasses a wide spectrum of AI methods, including machine learning algorithms, evolutionary algorithms, neural networks, and optimization techniques, applied to address various challenges in the field. The synthesis of research findings highlights the interdisciplinary nature of AI applications in structural engineering, emphasizing the synergy between domain expertise and advanced computational methodologies. This synthesis aims to serve as a valuable resource for researchers, practitioners, and policymakers seeking a comprehensive understanding of the state-of-the-art in AI-driven optimization for steel moment frame structures. The paper commences with an overview of the fundamental principles governing steel moment frame structures and identifies the key optimization objectives, such as efficiency of structures. Subsequently, it delves into the application of AI in the conceptual design phase, where algorithms aid in generating innovative structural configurations and optimizing material utilization. The review also explores the use of AI for real-time structural health monitoring and predictive maintenance, contributing to the long-term sustainability and reliability of steel moment frame structures. Furthermore, the paper investigates how AI-driven algorithms facilitate the calibration of structural models, enabling accurate prediction of dynamic responses and seismic performance. Thus, by reviewing and analyzing the recent achievements in applications artificial intelligent in optimization of steel moment frame structures, the process of designing, analysis, and performance of the structures can be analyzed and modified.

Keywords: Artificial Intelligent, optimization process, steel moment frame, structural engineering.

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Authors: David Wiese

Abstract:

In order to maximize efficiency of an information management platform and to assist in decision making, the collection, storage and analysis of performance-relevant data has become of fundamental importance. This paper addresses the merits and drawbacks provided by the OLAP paradigm for efficiently navigating large volumes of performance measurement data hierarchically. The system managers or database administrators navigate through adequately (re)structured measurement data aiming to detect performance bottlenecks, identify causes for performance problems or assessing the impact of configuration changes on the system and its representative metrics. Of particular importance is finding the root cause of an imminent problem, threatening availability and performance of an information system. Leveraging OLAP techniques, in contrast to traditional static reporting, this is supposed to be accomplished within moderate amount of time and little processing complexity. It is shown how OLAP techniques can help improve understandability and manageability of measurement data and, hence, improve the whole Performance Analysis process.

Keywords: Data Warehousing, OLAP, Multidimensional Navigation, Performance Diagnosis, Performance Management, Performance Tuning.

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Authors: Khairul Jauhari, Achmad Widodo, Ismoyo Haryanto

Abstract:

In this article, the radial displacement error correction capability of a high precision spindle grinding caused by unbalance force was investigated. The spindle shaft is considered as a flexible rotor mounted on two sets of angular contact ball bearing. Finite element methods (FEM) have been adopted for obtaining the equation of motion of the spindle. In this paper, firstly, natural frequencies, critical frequencies, and amplitude of the unbalance response caused by residual unbalance are determined in order to investigate the spindle behaviors. Furthermore, an optimization design algorithm is employed to minimize radial displacement of the spindle which considers dimension of the spindle shaft, the dynamic characteristics of the bearings, critical frequencies and amplitude of the unbalance response, and computes optimum spindle diameters and stiffness and damping of the bearings. Numerical simulation results show that by optimizing the spindle diameters, and stiffness and damping in the bearings, radial displacement of the spindle can be reduced. A spindle about 4 μm radial displacement error can be compensated with 2 μm accuracy. This certainly can improve the accuracy of the product of machining.

Keywords: Error correction, High precision grinding, Optimization, Radial displacement, Spindle.

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Authors: Dawit Mengistu, Lars Lundberg, Paul Davidsson

Abstract:

A major requirement for Grid application developers is ensuring performance and scalability of their applications. Predicting the performance of an application demands understanding its specific features. This paper discusses performance modeling and prediction of multi-agent based simulation (MABS) applications on the Grid. An experiment conducted using a synthetic MABS workload explains the key features to be included in the performance model. The results obtained from the experiment show that the prediction model developed for the synthetic workload can be used as a guideline to understand to estimate the performance characteristics of real world simulation applications.

Keywords: Grid computing, Performance modeling, Performance prediction, Multi-agent simulation.

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Authors: Mubarak S. Mohsen, Rosni Abdullah, Yong M. Teo

Abstract:

Advances in processors architecture, such as multicore, increase the size of complexity of parallel computer systems. With multi-core architecture there are different parallel languages that can be used to run parallel programs. One of these languages is OpenMP which embedded in C/Cµ or FORTRAN. Because of this new architecture and the complexity, it is very important to evaluate the performance of OpenMP constructs, kernels, and application program on multi-core systems. Performance is the activity of collecting the information about the execution characteristics of a program. Performance tools consists of at least three interfacing software layers, including instrumentation, measurement, and analysis. The instrumentation layer defines the measured performance events. The measurement layer determines what performance event is actually captured and how it is measured by the tool. The analysis layer processes the performance data and summarizes it into a form that can be displayed in performance tools. In this paper, a number of OpenMP performance tools are surveyed, explaining how each is used to collect, analyse, and display data collection.

Keywords: Parallel performance tools, OpenMP, multi-core.

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Authors: Kailash, Rajeev Kumar Saha, Sanjeev Goyal

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Each and every manufacturing industry has a goal that describes its purpose and destination. The goal of any industry may be achieved by team work and managerial skills of all departments. However, achieving goals and objectives is not enough to improve the internal supply chain management performance of manufacturing industries therefore proper identification of performance indicators for benchmarking of internal supply chain management is essential for the growth of manufacturing industry. The identification of benchmarking performance indicators and their impact on internal supply chain management performance is vital for productivity and performance improvement. This study identifies the benchmarking performance indicators to improve internal supply chain performance of Indian manufacturing industries through literature review.

Keywords: Benchmarking, Internal supply chain management, performance indicators, scenario of Indian manufacturing industries.

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Authors: C. Noi-Okwei

Abstract:

In this study, participants with adjustment disorder with depressed mood (aged 18-54 years) with mild depression (N=18), severe depression (N=12) were compared with healthy controls (N=20) on the Multidimensional Aptitude Battery (MAB) a cognitive performance test. Using One Way Analysis of Variance and Matched Sample t-test. The results of the analysis shows that severely depressed participants performed poorly on the cognitive performance test relative to controls, however there were no significant differences on the cognitive performance test scores between the severely depressed and the mildly depressed. In addition, performance on the non-verbal performance subtest was poorer than that of the verbal subtest, suggesting that depression affects the executive functions of the person.

Keywords: adjustment disorder, cognitive performance test, Depression,

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Authors: Jian Du, Shui Hong Hong, Lu Meng, Qing Wei Meng

Abstract:

This work addresses the problem of optimizing completely batch water-using network with multiple contaminants where the flow change caused by mass transfer is taken into consideration for the first time. A mathematical technique for optimizing water-using network is proposed based on source-tank-sink superstructure. The task is to obtain the freshwater usage, recycle assignments among water-using units, wastewater discharge and a steady water-using network configuration by following steps. Firstly, operating sequences of water-using units are determined by time constraints. Next, superstructure is simplified by eliminating the reuse and recycle from water-using units with maximum concentration of key contaminants. Then, the non-linear programming model is solved by GAMS (General Algebra Model System) for minimum freshwater usage, maximum water recycle and minimum wastewater discharge. Finally, numbers of operating periods are calculated to acquire the steady network configuration. A case study is solved to illustrate the applicability of the proposed approach.

Keywords: Completely batch process, flow change, multiple contaminants, water-using network.

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Authors: Saad Al-Baddai, Karema Al-Subari, Elmar Lang, Bernd Ludwig

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Empirical mode decomposition (EMD), a new data-driven of time-series decomposition, has the advantage of supposing that a time series is non-linear or non-stationary, as is implicitly achieved in Fourier decomposition. However, the EMD suffers of mode mixing problem in some cases. The aim of this paper is to present a solution for a common type of signals causing of EMD mode mixing problem, in case a signal suffers of an intermittency. By an artificial example, the solution shows superior performance in terms of cope EMD mode mixing problem comparing with the conventional EMD and Ensemble Empirical Mode decomposition (EEMD). Furthermore, the over-sifting problem is also completely avoided; and computation load is reduced roughly six times compared with EEMD, an ensemble number of 50.

Keywords: Empirical mode decomposition, mode mixing, sifting process, over-sifting.

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Authors: K. S. Jasmine, R. Vasantha

Abstract:

Component-Based software engineering provides an opportunity for better quality and increased productivity in software development by using reusable software components [10]. One of the most critical aspects of the quality of a software system is its performance. The systematic application of software performance engineering techniques throughout the development process can help to identify design alternatives that preserve desirable qualities such as extensibility and reusability while meeting performance objectives [1]. In the present scenario, software engineering methodologies strongly focus on the functionality of the system, while applying a “fix- it-later" approach to software performance aspects [3]. As a result, lengthy fine-tunings, expensive extra hard ware, or even redesigns are necessary for the system to meet the performance requirements. In this paper, we propose design based, implementation independent, performance prediction approach to reduce the overhead associated in the later phases while developing a performance guaranteed software product with the help of Unified Modeling Language (UML).

Keywords: Software Reuse, Component-based development, Unified Modeling Language, Software performance, Software components, Performance engineering, Software engineering.

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Authors: Hadi Gholizadeh, Ali Tajdin

Abstract:

To have effective production planning, it is necessary to control the quality of processes. This paper aims at improving the performance of the disposable essentials process using statistical quality control and goal programming in a vague environment. That is expressed uncertainty because there is always a measurement error in the real world. Therefore, in this study, the conditions are examined in a vague environment that is a distance-based environment. The disposable essentials process in Kach Company was studied. Statistical control tools were used to characterize the existing process for four factor responses including the average of disposable glasses’ weights, heights, crater diameters, and volumes. Goal programming was then utilized to find the combination of optimal factors setting in a vague environment which is measured to apply uncertainty of the initial information when some of the parameters of the models are vague; also, the fuzzy regression model is used to predict the responses of the four described factors. Optimization results show that the process capability index values for disposable glasses’ average of weights, heights, crater diameters and volumes were improved. Such increasing the quality of the products and reducing the waste, which will reduce the cost of the finished product, and ultimately will bring customer satisfaction, and this satisfaction, will mean increased sales.

Keywords: Goal programming, quality control, vague environment, disposable glasses’ optimization, fuzzy regression.

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Authors: Moch. Agus Choiron, Yoshihiro Kurata, Shigeyuki Haruyama, Ken Kaminishi

Abstract:

The contact width is important design parameter for optimizing the design of new metal gasket for asbestos substitution gasket. The contact width is found have relationship with the helium leak quantity. In the increasing of axial load value, the helium leak quantity is decreasing and the contact width is increasing. This study provides validity method using simulation analysis and the result is compared to experimental using pressure sensitive paper. The results denote similar trend data between simulation and experimental result. Final evaluation is determined by helium leak quantity to check leakage performance of gasket design. Considering the phenomena of position change on the convex contact, it can be developed the optimization of gasket design by increasing contact width.

Keywords: contact width, simulation, pressure sensitive paper.

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Authors: P. Brinks, O. Kornadt, R. Oly

Abstract:

This research focuses on the optimization of glazed surfaces and the assessment of possible solar gains in industrial buildings. Existing window rating methods for single windows were evaluated and a new method for a simple analysis of energy gains and losses by single windows was introduced. Furthermore extensive transient building simulations were carried out to appraise the performance of low cost polycarbonate multi-cell sheets in interaction with typical buildings for industrial applications. Mainly energy saving potential was determined by optimizing the orientation and area of such glazing systems in dependency on their thermal qualities. Moreover the impact on critical aspects such as summer overheating and daylight illumination was considered to ensure the user comfort and avoid additional energy demand for lighting or cooling. Hereby the simulated heating demand could be reduced by up to 1/3 compared to traditional architecture of industrial halls using mainly skylights.

Keywords: Solar Architecture, Passive Solar Building Design, Glazing, Low-Energy Buildings, Industrial Buildings.

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Authors: A. Bakhtiar, B. Purwanggono, N. Metasari

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PT XYZ is a bottled drinking water company. To preserve production resources owned by the company so that the resources could be utilized well, it has implemented maintenance management system, which has important role in company's profitability, and is one of the factors influenced overall company's performance. Yet, up to now the company has never measured maintenance activities' contribution to company's performance. Performance evaluation is done according to adapted Balanced Scorecard model fitted to maintenance function context. This model includes six perspectives: innovation and growth, production, maintenance, environment, costumer, and finance. Actual performance measurement is done through Analytic Hierarchy Process and Objective Matrix. From the research done, we can conclude that the company's maintenance function is categorized in moderate performance. But, there are some indicators which has high priority but low performance, which are: costumers' complain rate, work lateness rate, and Return on Investment.

Keywords: Maintenance, performance, balanced scorecard, objective matrix.

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Authors: Mariayee Doraisamy, Suhaimi Bin Ibrahim, Mohd Naz’ri Mahrin

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There are several methods to monitor software projects and the objective for monitoring is to ensure that the software projects are developed and delivered successfully. A performance measurement is a method that is closely associated with monitoring and it can be scrutinized by looking at two important attributes which are efficiency and effectiveness both of which are factors that are important for the success of a software project. Consequently, a successful steering is achieved by monitoring and controlling a software project via the performance measurement criteria and metrics. Hence, this paper is aimed at identifying the performance measurement criteria and the metrics for monitoring the performance of a software project by using the Goal Question Metrics (GQM) approach. The GQM approach is utilized to ensure that the identified metrics are reliable and useful. These identified metrics are useful guidelines for project managers to monitor the performance of their software projects.

Keywords: Software project performance, Goal Question Metrics, Performance Measurement Criteria, Metrics.

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Authors: T. Maruyama, T. Saida, S. Naritsuka, S. Iijima

Abstract:

Single-walled carbon nanotubes (SWCNTs) are generally synthesized by chemical vapor deposition (CVD) using Fe, Co, and Ni as catalysts. However, due to the Ostwald ripening of metal catalysts, the diameter distribution of the grown SWCNTs is considerably wide (>2 nm), which is not suitable for electronics applications. In addition, reduction in the growth temperature is desirable for fabricating SWCNT devices compatible with the LSI process. Herein, we performed SWCNT growth by alcohol catalytic CVD using platinum-group metal catalysts (Pt, Rh, and Pd) because these metals have high melting points, and the reduction in the Ostwald ripening of catalyst particles is expected. Our results revealed that web-like SWCNTs were obtained from Pt and Rh catalysts at growth temperature between 500 °C and 600 °C by optimizing the ethanol pressure. The SWCNT yield from Pd catalysts was considerably low. By decreasing the growth temperature, the diameter and chirality distribution of SWCNTs from Pt and Rh catalysts became small and narrow. In particular, the diameters of most SWCNTs grown using Pt catalysts were below 1 nm and their diameter distribution was considerably narrow. On the contrary, SWCNTs can grow from Rh catalysts even at 300 °C by optimizing the growth condition, which is the lowest temperature recorded for SWCNT growth. Our results demonstrated that platinum-group metals are useful for the growth of small-diameter SWCNTs and facilitate low-temperature growth.

Keywords: Carbon nanotube, chemical vapor deposition, catalyst, Pt, Rh, Pd.

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Authors: Melek Oktay, Ayşe Betül Gülbağcı, Mustafa Sarıöz

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Enterprise applications are complex systems that are hard to develop and deploy in organizations. Although software application development tools, frameworks, methodologies and patterns are rapidly developing; many projects fail by causing big costs. There are challenging issues that programmers and designers face with while working on enterprise applications. In this paper, we present the three of the significant issues: Architectural, technological and performance. The important subjects in each issue are pointed out and recommendations are given. In architectural issues the lifecycle, meta-architecture, guidelines are pointed out. .NET and Java EE platforms are presented in technological issues. The importance of performance, measuring performance and profilers are explained in performance issues.

Keywords: Enterprise Applications, Architecture, Technology, Performance.

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Authors: Dhinu Johnson, Gurdip Singh

Abstract:

Sensor network applications are often data centric and involve collecting data from a set of sensor nodes to be delivered to various consumers. Typically, nodes in a sensor network are resource-constrained, and hence the algorithms operating in these networks must be efficient. There may be several algorithms available implementing the same service, and efficient considerations may require a sensor application to choose the best suited algorithm. In this paper, we present a systematic evaluation of a set of algorithms implementing the data gathering service. We propose a modular infrastructure for implementing such algorithms in TOSSIM with separate configurable modules for various tasks such as interest propagation, data propagation, aggregation, and path maintenance. By appropriately configuring these modules, we propose a number of data gathering algorithms, each of which incorporates a different set of heuristics for optimizing performance. We have performed comprehensive experiments to evaluate the effectiveness of these heuristics, and we present results from our experimentation efforts.

Keywords: Data Centric Protocols, Shortest Paths, Sensor networks, Message passing systems.

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Authors: Dixit Garg, S. Luthra, A. Haleem

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During recent years, the natural environment has become a challenging topic that business organizations must consider due to the economic and ecological impacts and increasing awareness of environment protection among society. Organizations are trying to achieve the goals of improvement in environment, low cost, high quality, flexibility and more customer satisfaction. Performance measurement frameworks are very useful to monitor the performance of any organization. The basic goal of this paper is to identify performance measures and ranking of these performance measures of GSCM performance measurement towards sustainability framework. Five perspectives (Environment, Economic, Social, Operational and Cost performances) and nineteen performance measures of GSCM performance towards sustainability have been have been identified from extensive literature review. Analytical Hierarchy Process (AHP) technique has been utilized for ranking of these performance perspectives and measures. All pair comparisons in AHP have been made on the basis on the experts’ opinions (selected from academia and industry). Ranking of these performance perspectives and measures will help to understand the importance of environmental, economic, social, operational performances and cost performances in the supply chain.

Keywords: Analytical Hierarchy Process (AHP), Green Supply Chain Management, Performance Measures (PM), Sustainability.

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Authors: Amira A. A. Abdallah, Amir A. Beltagi

Abstract:

Background: Core stability training has recently attracted attention for improving muscle balance and optimizing performance in healthy and unhealthy individuals. Purpose: This study investigated the effect of beginner’s core stability exercises on trunk flexors’/extensors’ peak torque ratio and trunk flexors’ and extensors’ peak torques. Methods: Thirty five healthy individuals participated in the study. They were randomly assigned to two groups; experimental “group I, n=20” and control “group II, n=15”. Their mean age, weight and height were 20.7±2.4 vs. 20.3±0.61 years, 66.5±12.1 vs. 68.57±12.2 kg and 166.7±7.8 vs. 164.28 ±7.59 cm. for group I vs. group II. Data were collected using the Biodex Isokinetic system. The participants were tested twice; before and after a 6-week period during which group I performed a core stability training program. Results: The 2x2 Mixed Design ANOVA revealed that there were no significant differences (p>0.025) in the trunk flexors’/extensors’ peak torque ratio between the pre-test and post-test conditions for either group. Moreover, there were no significant differences (p>0.025) in the trunk flexion/extension ratios between both groups at either condition. However, the 2x2 Mixed Design MANOVA revealed significant increases (p<0.025) in the trunk flexors’ and extensors’ peak torques in the post-test condition compared with the pre-test in group I with no significant differences (p>0.025) in group II. Moreover, there was a significant increase (p<0.025) in the trunk flexors’ peak torque only in group I compared with group II in the post-test condition with no significant differences in the other conditions. Interpretation/Conclusion: The improvement in muscle performance indicated by the increase in the trunk flexors’ and extensors’ peak torques in the experimental group recommends including core stability training in the exercise programs that aim to improve muscle performance.

Keywords: Core Stability, Isokinetic, Trunk Muscles.

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Authors: Qing Lyu, Hang Zhu

Abstract:

Various flows in the network require to go through different types of middlebox. The improper placement of network middlebox and path assignment for flows could greatly increase the network latency and also decrease the performance of network. Minimizing the total end to end latency of all the ows requires to assign path for the incoming flows. In this paper, the flow path assignment problem in regard to the placement of various kinds of middlebox is studied. The flow path assignment problem is formulated to a linear programming problem, which is very time consuming. On the other hand, a naive greedy algorithm is studied. Which is very fast but causes much more latency than the linear programming algorithm. At last, the paper presents a heuristic algorithm named FPA, which takes bottleneck link information and estimated bandwidth occupancy into consideration, and achieves near optimal latency in much less time. Evaluation results validate the effectiveness of the proposed algorithm.

Keywords: Latency, Fast path assignment, Bottleneck link.

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