Search results for: performance metrics.
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 5886

Search results for: performance metrics.

5796 A Novel Security Framework for the Web System

Authors: J. P. Dubois, P. G. Jreije

Abstract:

In this paper, a framework is presented trying to make the most secure web system out of the available generic and web security technology which can be used as a guideline for organizations building their web sites. The framework is designed to provide necessary security services, to address the known security threats, and to provide some cover to other security problems especially unknown threats. The requirements for the design are discussed which guided us to the design of secure web system. The designed security framework is then simulated and various quality of service (QoS) metrics are calculated to measure the performance of this system.

Keywords: Web Security, Internet Voting, Firewall, QoS, Latency, Utilization, Throughput.

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5795 Measuring the Influence of Functional Proximity on Environmental Urban Performance via Integrated Modification Methodology: Four Study Cases in Milan

Authors: M. Tadi, M. Hadi Mohammad Zadeh, Ozge Ogut

Abstract:

Although how cities’ forms are structured is studied, more efforts are needed on systemic comprehensions and evaluations of the urban morphology through quantitative metrics that are able to describe the performance of a city in relation to its formal properties. More research is required in this direction in order to better describe the urban form characteristics and their impact on the environmental performance of cities and to increase their sustainability stewardship. With the aim of developing a better understanding of the built environment’s systemic structure, the intention of this paper is to present a holistic methodology for studying the behavior of the built environment and investigate the methods for measuring the effect of urban structure to the environmental performance. This goal will be pursued through an inquiry into the morphological components of the urban systems and the complex relationships between them. Particularly, this paper focuses on proximity, referring to the proximity of different land-uses, is a concept with which Integrated Modification Methodology (IMM) explains how land-use allocation might affect the choice of mobility in neighborhoods, and especially, encourage or discourage non-motived mobility. This paper uses proximity to demonstrate that the structure attributes can quantifiably relate to the performing behavior in the city. The target is to devise a mathematical pattern from the structural elements and correlate it directly with urban performance indicators concerned with environmental sustainability. The paper presents some results of this rigorous investigation of urban proximity and its correlation with performance indicators in four different areas in the city of Milan, each of them characterized by different morphological features.

Keywords: Built environment, ecology, sustainable indicators, sustainability, urban morphology.

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5794 Application of Scientific Metrics to Evaluate Academic Reputation in Different Research Areas

Authors: Cristiano R. Cervi, Renata Galante, José Palazzo M. de Oliveira

Abstract:

In this paper, we address the problem of identifying academic reputation of researchers using scientific metrics in different research areas. Due to the characteristics of each area, researchers can present different behaviors. In previous work, we define Rep-Index that makes use of a profile template to individually identify the reputation of researchers. The Rep-Index is comprehensive and adaptive because involves hole trajectory of the researcher built throughout his career and can be used in different areas and in different contexts. Now, we compare our metric (Rep-Index) with the h-index and the g-index through experiments with researchers in the fields of Economics, Dentistry and Computer Science. We analyze the trajectory of 830 Brazilian researchers from the National Council of Technological and Scientific Development (CNPq), which receive grants research productivity. The grants are aimed at productivity researchers that stand out among their peers, enhancing their scientific normative criteria established by CNPq. Of the 830 researchers, 210 are in the area of Economics, 216 of Dentistry e 404 of Computer Science. The experiments show that our metric is strongly correlated with h-index, g-index and CNPq ranking. We also show good results for our hypothesis that our metric can be used to evaluate research in several areas. We apply our metric (Rep-Index) to compare the behavior of researchers in relation to their h-index and g-index through extensive experiments. The experiments showed that our metric is strongly correlated with h-index, g-index and CNPq ranking.

Keywords: Researcher reputation, profile model, scientific metrics.

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5793 Improved Computational Efficiency of Machine Learning Algorithms Based on Evaluation Metrics to Control the Spread of Coronavirus in the UK

Authors: Swathi Ganesan, Nalinda Somasiri, Rebecca Jeyavadhanam, Gayathri Karthick

Abstract:

The COVID-19 crisis presents a substantial and critical hazard to worldwide health. Since the occurrence of the disease in late January 2020 in the UK, the number of infected people confirmed to acquire the illness has increased tremendously across the country, and the number of individuals affected is undoubtedly considerably high. The purpose of this research is to figure out a predictive machine learning (ML) archetypal that could forecast the COVID-19 cases within the UK. This study concentrates on the statistical data collected from 31st January 2020 to 31st March 2021 in the United Kingdom. Information on total COVID-19 cases registered, new cases encountered on a daily basis, total death registered, and patients’ death per day due to Coronavirus is collected from World Health Organization (WHO). Data preprocessing is carried out to identify any missing values, outliers, or anomalies in the dataset. The data are split into 8:2 ratio for training and testing purposes to forecast future new COVID-19 cases. Support Vector Machine (SVM), Random Forest (RF), and linear regression (LR) algorithms are chosen to study the model performance in the prediction of new COVID-19 cases. From the evaluation metrics such as r-squared value and mean squared error, the statistical performance of the model in predicting the new COVID-19 cases is evaluated. RF outperformed the other two ML algorithms with a training accuracy of 99.47% and testing accuracy of 98.26% when n = 30. The mean square error obtained for RF is 4.05e11, which is lesser compared to the other predictive models used for this study. From the experimental analysis, RF algorithm can perform more effectively and efficiently in predicting the new COVID-19 cases, which could help the health sector to take relevant control measures for the spread of the virus.

Keywords: COVID-19, machine learning, supervised learning, unsupervised learning, linear regression, support vector machine, random forest.

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5792 eLearning Tools Evaluation based on Quality Concept Distance Computing. A Case Study

Authors: Mihai Caramihai, Irina Severin

Abstract:

Despite the extensive use of eLearning systems, there is no consensus on a standard framework for evaluating this kind of quality system. Hence, there is only a minimum set of tools that can supervise this judgment and gives information about the course content value. This paper presents two kinds of quality set evaluation indicators for eLearning courses based on the computational process of three known metrics, the Euclidian, Hamming and Levenshtein distances. The “distance" calculus is applied to standard evaluation templates (i.e. the European Commission Programme procedures vs. the AFNOR Z 76-001 Standard), determining a reference point in the evaluation of the e-learning course quality vs. the optimal concept(s). The case study, based on the results of project(s) developed in the framework of the European Programme “Leonardo da Vinci", with Romanian contractors, try to put into evidence the benefits of such a method.

Keywords: eLearning, European programme, metrics, quality evaluation

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5791 Impact of Node Density and Transmission Range on the Performance of OLSR and DSDV Routing Protocols in VANET City Scenarios

Authors: Yassine Meraihi, Dalila Acheli, Rabah Meraihi

Abstract:

Vehicular Ad hoc Network (VANET) is a special case of Mobile Ad hoc Network (MANET) used to establish communications and exchange information among nearby vehicles and between vehicles and nearby fixed infrastructure. VANET is seen as a promising technology used to provide safety, efficiency, assistance and comfort to the road users. Routing is an important issue in Vehicular Ad Hoc Network to find and maintain communication between vehicles due to the highly dynamic topology, frequently disconnected network and mobility constraints.

This paper evaluates the performance of two most popular proactive routing protocols OLSR and DSDV in real city traffic scenario on the basis of three metrics namely Packet delivery ratio, throughput and average end to end delay by varying vehicles density and transmission range.

Keywords: DSDV, OLSR, Quality of service, Routing protocols, VANET.

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5790 Key Frames Extraction for Sign Language Video Analysis and Recognition

Authors: Jaroslav Polec, Petra Heribanová, Tomáš Hirner

Abstract:

In this paper we proposed a method for finding video frames representing one sign in the finger alphabet. The method is based on determining hands location, segmentation and the use of standard video quality evaluation metrics. Metric calculation is performed only in regions of interest. Sliding mechanism for finding local extrema and adaptive threshold based on local averaging is used for key frames selection. The success rate is evaluated by recall, precision and F1 measure. The method effectiveness is compared with metrics applied to all frames. Proposed method is fast, effective and relatively easy to realize by simple input video preprocessing and subsequent use of tools designed for video quality measuring.

Keywords: Key frame, video, quality, metric, MSE, MSAD, SSIM, VQM, sign language, finger alphabet.

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5789 Cognitive Weighted Polymorphism Factor: A Comprehension Augmented Complexity Metric

Authors: T. Francis Thamburaj, A. Aloysius

Abstract:

Polymorphism is one of the main pillars of objectoriented paradigm. It induces hidden forms of class dependencies which may impact software quality, resulting in higher cost factor for comprehending, debugging, testing, and maintaining the software. In this paper, a new cognitive complexity metric called Cognitive Weighted Polymorphism Factor (CWPF) is proposed. Apart from the software structural complexity, it includes the cognitive complexity on the basis of type. The cognitive weights are calibrated based on 27 empirical studies with 120 persons. A case study and experimentation of the new software metric shows positive results. Further, a comparative study is made and the correlation test has proved that CWPF complexity metric is a better, more comprehensive, and more realistic indicator of the software complexity than Abreu’s Polymorphism Factor (PF) complexity metric.

Keywords: Cognitive complexity metric, cognitive weighted polymorphism factor, object-oriented metrics, polymorphism factor, software metrics.

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5788 Evaluating Portfolio Performance by Highlighting Network Property and the Sharpe Ratio in the Stock Market

Authors: Zahra Hatami, Hesham Ali, David Volkman

Abstract:

Selecting a portfolio for investing is a crucial decision for individuals and legal entities. In the last two decades, with economic globalization, a stream of financial innovations has rushed to the aid of financial institutions. The importance of selecting stocks for the portfolio is always a challenging task for investors. This study aims to create a financial network to identify optimal portfolios using network centralities metrics. This research presents a community detection technique of superior stocks that can be described as an optimal stock portfolio to be used by investors. By using the advantages of a network and its property in extracted communities, a group of stocks was selected for each of the various time periods. The performance of the optimal portfolios was compared to the famous index. Their Sharpe ratio was calculated in a timely manner to evaluate their profit for making decisions. The analysis shows that the selected potential portfolio from stocks with low centrality measurement can outperform the market; however, they have a lower Sharpe ratio than stocks with high centrality scores. In other words, stocks with low centralities could outperform the S&P500 yet have a lower Sharpe ratio than high central stocks.

Keywords: Portfolio management performance, network analysis, centrality measurements, Sharpe ratio.

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5787 IKEv1 and IKEv2: A Quantitative Analyses

Authors: H.Soussi, M.Hussain, H.Afifi, D.Seret

Abstract:

Key management is a vital component in any modern security protocol. Due to scalability and practical implementation considerations automatic key management seems a natural choice in significantly large virtual private networks (VPNs). In this context IETF Internet Key Exchange (IKE) is the most promising protocol under permanent review. We have made a humble effort to pinpoint IKEv2 net gain over IKEv1 due to recent modifications in its original structure, along with a brief overview of salient improvements between the two versions. We have used US National Institute of Technology NIIST VPN simulator to get some comparisons of important performance metrics.

Keywords: Quantitative Analyses, IKEv1, IKEv2, NIIST.

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5786 CSR of top Portuguese Companies: Relation between Social Performance and Economic Performance

Authors: Afonso, S. C., Fernandes, P. O., Monte, A. P.

Abstract:

Modern times call organizations to have an active role in the social arena, through Corporate Social Responsibility (CSR). The objective of this research was to test the hypothesis that there is a positive relation between social performance and economic performance, and if there is a positive correlation between social performance and financial-economic performance. To test these theories a measure of social performance, based on the Green Book of Commission of the European Community, was used in a group of nineteen Portuguese top companies, listed on the PSI 20 index, through a period of five years, since 2005 to 2009. A clusters analysis was applied to group companies by their social performance and to compare and correlate their economic performance. Results indicate that companies that had a better social performance are not the ones who had a better economic performance, and suggest that the middle path might provide a good relation CSR-Economic performance, as a basis to a sustainable development.

Keywords: Corporate Social Responsibility, Economic Performance, Win-Win relationship

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5785 Study of Qualitative and Quantitative Metric for Pixel Factor Mapping and Extended Pixel Mapping Method

Authors: Indradip Banerjee, Souvik Bhattacharyya, Gautam Sanyal

Abstract:

In this paper, an approach is presented to investigate the performance of Pixel Factor Mapping (PFM) and Extended PMM (Pixel Mapping Method) through the qualitative and quantitative approach. These methods are tested against a number of well-known image similarity metrics and statistical distribution techniques. The PFM has been performed in spatial domain as well as frequency domain and the Extended PMM has also been performed in spatial domain through large set of images available in the internet.

Keywords: Qualitative, quantitative, PFM, EXTENDED PMM.

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5784 Performance Modeling for Web based J2EE and .NET Applications

Authors: Shankar Kambhampaty, Venkata Srinivas Modali

Abstract:

When architecting an application, key nonfunctional requirements such as performance, scalability, availability and security, which influence the architecture of the system, are some times not adequately addressed. Performance of the application may not be looked at until there is a concern. There are several problems with this reactive approach. If the system does not meet its performance objectives, the application is unlikely to be accepted by the stakeholders. This paper suggests an approach for performance modeling for web based J2EE and .Net applications to address performance issues early in the development life cycle. It also includes a Performance Modeling Case Study, with Proof-of-Concept (PoC) and implementation details for .NET and J2EE platforms.

Keywords: Performance Measures, Performance Modeling, Performance Testing, Resource Utilization, Response Time, Throughput.

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5783 Design, Development by Functional Analysis in UML and Static Test of a Multimedia Voice and Video Communication Platform on IP for a Use Adapted to the Context of Local Businesses in Lubumbashi

Authors: Blaise Fyama, Elie Museng, Grace Mukoma

Abstract:

In this article we present a java implementation of video telephony using the SIP protocol (Session Initiation Protocol). After a functional analysis of the SIP protocol, we relied on the work of Italian researchers of University of Parma-Italy to acquire adequate libraries for the development of our own communication tool. In order to optimize the code and improve the prototype, we used, in an incremental approach, test techniques based on a static analysis based on the evaluation of the complexity of the software with the application of metrics and the number cyclomatic of Mccabe. The objective is to promote the emergence of local start-ups producing IP video in a well understood local context. We have arrived at the creation of a video telephony tool whose code is optimized.

Keywords: Static analysis, coding, complexity, mccabe metrics, Sip, uml.

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5782 A Framework for Review Spam Detection Research

Authors: Mohammadali Tavakoli, Atefeh Heydari, Zuriati Ismail, Naomie Salim

Abstract:

With the increasing number of people reviewing products online in recent years, opinion sharing websites has become the most important source of customers’ opinions. Unfortunately, spammers generate and post fake reviews in order to promote or demote brands and mislead potential customers. These are notably destructive not only for potential customers, but also for business holders and manufacturers. However, research in this area is not adequate, and many critical problems related to spam detection have not been solved to date. To provide green researchers in the domain with a great aid, in this paper, we have attempted to create a highquality framework to make a clear vision on review spam-detection methods. In addition, this report contains a comprehensive collection of detection metrics used in proposed spam-detection approaches. These metrics are extremely applicable for developing novel detection methods.

Keywords: Fake reviews, Feature collection, Opinion spam, Spam detection.

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5781 Towards an AS Level Network Performance Model

Authors: Huan Xiong, Ming Chen

Abstract:

In order to research Internet quantificationally and better model the performance of network, this paper proposes a novel AS level network performance model (MNPM), it takes autonomous system (AS) as basic modeling unit, measures E2E performance between any two outdegrees of an AS and organizes measurement results into matrix form which called performance matrix (PM). Inter-AS performance calculation is defined according to performance information stored in PM. Simulation has been implemented to verify the correctness of MNPM and a practical application of MNPM (network congestion detection) is given.

Keywords: AS, network performance, model, metric, congestion.

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5780 A Subtractive Clustering Based Approach for Early Prediction of Fault Proneness in Software Modules

Authors: Ramandeep S. Sidhu, Sunil Khullar, Parvinder S. Sandhu, R. P. S. Bedi, Kiranbir Kaur

Abstract:

In this paper, subtractive clustering based fuzzy inference system approach is used for early detection of faults in the function oriented software systems. This approach has been tested with real time defect datasets of NASA software projects named as PC1 and CM1. Both the code based model and joined model (combination of the requirement and code based metrics) of the datasets are used for training and testing of the proposed approach. The performance of the models is recorded in terms of Accuracy, MAE and RMSE values. The performance of the proposed approach is better in case of Joined Model. As evidenced from the results obtained it can be concluded that Clustering and fuzzy logic together provide a simple yet powerful means to model the earlier detection of faults in the function oriented software systems.

Keywords: Subtractive clustering, fuzzy inference system, fault proneness.

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5779 Benchmarking: Performance on ALPS and Formosa Clusters

Authors: Chih-Wei Hsieh, Chau-Yi Chou, Sheng-HsiuKuo, Tsung-Che Tsai, I-Chen Wu

Abstract:

This paper presents the benchmarking results and performance evaluation of differentclustersbuilt atthe National Center for High-Performance Computingin Taiwan. Performance of processor, memory subsystem andinterconnect is a critical factor in the overall performance of high performance computing platforms. The evaluation compares different system architecture and software platforms. Most supercomputer used HPL to benchmark their system performance, in accordance with the requirement of the TOP500 List. In this paper we consider system memory access factors that affect benchmark performance, such as processor and memory performance.We hope these works will provide useful information for future development and construct cluster system.

Keywords: Performance Evaluation, Benchmarking and High-Performance Computing

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5778 A Mathematical Representation for Mechanical Model Assessment: Numerical Model Qualification Method

Authors: Keny Ordaz-Hernandez, Xavier Fischer, Fouad Bennis

Abstract:

This article illustrates a model selection management approach for virtual prototypes in interactive simulations. In those numerical simulations, the virtual prototype and its environment are modelled as a multiagent system, where every entity (prototype,human, etc.) is modelled as an agent. In particular, virtual prototyp ingagents that provide mathematical models of mechanical behaviour inform of computational methods are considered. This work argues that selection of an appropriate model in a changing environment,supported by models? characteristics, can be managed by the deter-mination a priori of specific exploitation and performance measures of virtual prototype models. As different models exist to represent a single phenomenon, it is not always possible to select the best one under all possible circumstances of the environment. Instead the most appropriate shall be selecting according to the use case. The proposed approach consists in identifying relevant metrics or indicators for each group of models (e.g. entity models, global model), formulate their qualification, analyse the performance, and apply the qualification criteria. Then, a model can be selected based on the performance prediction obtained from its qualification. The authors hope that this approach will not only help to inform engineers and researchers about another approach for selecting virtual prototype models, but also assist virtual prototype engineers in the systematic or automatic model selection.

Keywords: Virtual prototype models, domain, qualification criterion, model qualification, model assessment, environmental modelling.

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5777 Demystifying Full-Stack Observability: Mastering Visibility, Insight, and Action in the Modern Digital Landscape

Authors: Ashly Joseph

Abstract:

In the era of digital transformation, full-stack observability has emerged as a crucial aspect of administering modern application stacks. This research paper presents the concept of full-stack observability, its significance in the context of contemporary application stacks, and the challenges posed by swiftly evolving digital environments. In addition, it describes how full-stack observability intends to provide complete visibility and actionable insights by correlating telemetry across multiple domains.

Keywords: Actionable insights, digital transformation, full-stack observability, performance metrics.

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5776 MinRoot and CMesh: Interconnection Architectures for Network-on-Chip Systems

Authors: Mohammad Ali Jabraeil Jamali, Ahmad Khademzadeh

Abstract:

The success of an electronic system in a System-on- Chip is highly dependent on the efficiency of its interconnection network, which is constructed from routers and channels (the routers move data across the channels between nodes). Since neither classical bus based nor point to point architectures can provide scalable solutions and satisfy the tight power and performance requirements of future applications, the Network-on-Chip (NoC) approach has recently been proposed as a promising solution. Indeed, in contrast to the traditional solutions, the NoC approach can provide large bandwidth with moderate area overhead. The selected topology of the components interconnects plays prime rule in the performance of NoC architecture as well as routing and switching techniques that can be used. In this paper, we present two generic NoC architectures that can be customized to the specific communication needs of an application in order to reduce the area with minimal degradation of the latency of the system. An experimental study is performed to compare these structures with basic NoC topologies represented by 2D mesh, Butterfly-Fat Tree (BFT) and SPIN. It is shown that Cluster mesh (CMesh) and MinRoot schemes achieves significant improvements in network latency and energy consumption with only negligible area overhead and complexity over existing architectures. In fact, in the case of basic NoC topologies, CMesh and MinRoot schemes provides substantial savings in area as well, because they requires fewer routers. The simulation results show that CMesh and MinRoot networks outperforms MESH, BFT and SPIN in main performance metrics.

Keywords: MinRoot, CMesh, NoC, Topology, Performance Evaluation

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5775 Social Media Idea Ontology: A Concept for Semantic Search of Product Ideas in Customer Knowledge through User-Centered Metrics and Natural Language Processing

Authors: Martin H¨ausl, Maximilian Auch, Johannes Forster, Peter Mandl, Alexander Schill

Abstract:

In order to survive on the market, companies must constantly develop improved and new products. These products are designed to serve the needs of their customers in the best possible way. The creation of new products is also called innovation and is primarily driven by a company’s internal research and development department. However, a new approach has been taking place for some years now, involving external knowledge in the innovation process. This approach is called open innovation and identifies customer knowledge as the most important source in the innovation process. This paper presents a concept of using social media posts as an external source to support the open innovation approach in its initial phase, the Ideation phase. For this purpose, the social media posts are semantically structured with the help of an ontology and the authors are evaluated using graph-theoretical metrics such as density. For the structuring and evaluation of relevant social media posts, we also use the findings of Natural Language Processing, e. g. Named Entity Recognition, specific dictionaries, Triple Tagger and Part-of-Speech-Tagger. The selection and evaluation of the tools used are discussed in this paper. Using our ontology and metrics to structure social media posts enables users to semantically search these posts for new product ideas and thus gain an improved insight into the external sources such as customer needs.

Keywords: Idea ontology, innovation management, open innovation, semantic search.

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5774 A Testbed for the Experiments Performed in Missing Value Treatments

Authors: Dias de J. C. Lilian, Lobato M. F. Fábio, de Santana L. Ádamo

Abstract:

The occurrence of missing values in database is a serious problem for Data Mining tasks, responsible for degrading data quality and accuracy of analyses. In this context, the area has shown a lack of standardization for experiments to treat missing values, introducing difficulties to the evaluation process among different researches due to the absence in the use of common parameters. This paper proposes a testbed intended to facilitate the experiments implementation and provide unbiased parameters using available datasets and suited performance metrics in order to optimize the evaluation and comparison between the state of art missing values treatments.

Keywords: Data imputation, data mining, missing values treatment, testbed.

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5773 Semantic Spatial Objects Data Structure for Spatial Access Method

Authors: Kalum Priyanath Udagepola, Zuo Decheng, Wu Zhibo, Yang Xiaozong

Abstract:

Modern spatial database management systems require a unique Spatial Access Method (SAM) in order solve complex spatial quires efficiently. In this case the spatial data structure takes a prominent place in the SAM. Inadequate data structure leads forming poor algorithmic choices and forging deficient understandings of algorithm behavior on the spatial database. A key step in developing a better semantic spatial object data structure is to quantify the performance effects of semantic and outlier detections that are not reflected in the previous tree structures (R-Tree and its variants). This paper explores a novel SSRO-Tree on SAM to the Topo-Semantic approach. The paper shows how to identify and handle the semantic spatial objects with outlier objects during page overflow/underflow, using gain/loss metrics. We introduce a new SSRO-Tree algorithm which facilitates the achievement of better performance in practice over algorithms that are superior in the R*-Tree and RO-Tree by considering selection queries.

Keywords: Outlier, semantic spatial object, spatial objects, SSRO-Tree, topo-semantic.

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5772 A Similarity Function for Global Quality Assessment of Retinal Vessel Segmentations

Authors: Arturo Aquino, Manuel Emilio Gegundez, Jose Manuel Bravo, Diego Marin

Abstract:

Retinal vascularity assessment plays an important role in diagnosis of ophthalmic pathologies. The employment of digital images for this purpose makes possible a computerized approach and has motivated development of many methods for automated vascular tree segmentation. Metrics based on contingency tables for binary classification have been widely used for evaluating performance of these algorithms and, concretely, the accuracy has been mostly used as measure of global performance in this topic. However, this metric shows very poor matching with human perception as well as other notable deficiencies. Here, a new similarity function for measuring quality of retinal vessel segmentations is proposed. This similarity function is based on characterizing the vascular tree as a connected structure with a measurable area and length. Tests made indicate that this new approach shows better behaviour than the current one does. Generalizing, this concept of measuring descriptive properties may be used for designing functions for measuring more successfully segmentation quality of other complex structures.

Keywords: Retinal vessel segmentation, quality assessment, performanceevaluation, similarity function.

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5771 Routing Medical Images with Tabu Search and Simulated Annealing: A Study on Quality of Service

Authors: Mejía M. Paula, Ramírez L. Leonardo, Puerta A. Gabriel

Abstract:

In telemedicine, the image repository service is important to increase the accuracy of diagnostic support of medical personnel. This study makes comparison between two routing algorithms regarding the quality of service (QoS), to be able to analyze the optimal performance at the time of loading and/or downloading of medical images. This study focused on comparing the performance of Tabu Search with other heuristic and metaheuristic algorithms that improve QoS in telemedicine services in Colombia. For this, Tabu Search and Simulated Annealing heuristic algorithms are chosen for their high usability in this type of applications; the QoS is measured taking into account the following metrics: Delay, Throughput, Jitter and Latency. In addition, routing tests were carried out on ten images in digital image and communication in medicine (DICOM) format of 40 MB. These tests were carried out for ten minutes with different traffic conditions, reaching a total of 25 tests, from a server of Universidad Militar Nueva Granada (UMNG) in Bogotá-Colombia to a remote user in Universidad de Santiago de Chile (USACH) - Chile. The results show that Tabu search presents a better QoS performance compared to Simulated Annealing, managing to optimize the routing of medical images, a basic requirement to offer diagnostic images services in telemedicine.

Keywords: Medical image, QoS, simulated annealing, Tabu search, telemedicine.

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5770 An Approach to Physical Performance Analysis for Judo

Authors: Stefano Frassinelli, Alessandro Niccolai, Riccardo E. Zich

Abstract:

Sport performance analysis is a technique that is becoming every year more important for athletes of every level. Many techniques have been developed to measure and analyse efficiently the performance of athletes in some sports, but in combat sports these techniques found in many times their limits, due to the high interaction between the two opponents during the competition. In this paper the problem will be framed. Moreover the physical performance measurement problem will be analysed and three different techniques to manage it will be presented. All the techniques have been used to analyse the performance of 22 high level Judo athletes.

Keywords: Sport performance, physical performance, judo, performance coefficients.

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5769 Subjective Versus Objective Assessment for Magnetic Resonance Images

Authors: Heshalini Rajagopal, Li Sze Chow, Raveendran Paramesran

Abstract:

Magnetic Resonance Imaging (MRI) is one of the most important medical imaging modality. Subjective assessment of the image quality is regarded as the gold standard to evaluate MR images. In this study, a database of 210 MR images which contains ten reference images and 200 distorted images is presented. The reference images were distorted with four types of distortions: Rician Noise, Gaussian White Noise, Gaussian Blur and DCT compression. The 210 images were assessed by ten subjects. The subjective scores were presented in Difference Mean Opinion Score (DMOS). The DMOS values were compared with four FR-IQA metrics. We have used Pearson Linear Coefficient (PLCC) and Spearman Rank Order Correlation Coefficient (SROCC) to validate the DMOS values. The high correlation values of PLCC and SROCC shows that the DMOS values are close to the objective FR-IQA metrics.

Keywords: Medical Resonance (MR) images, Difference Mean Opinion Score (DMOS), Full Reference Image Quality Assessment (FR-IQA).

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5768 Talent Management through Integration of Talent Value Chain and Human Capital Analytics Approaches

Authors: Wuttigrai Ngamsirijit

Abstract:

Talent management in today’s modern organizations has become data-driven due to a demand for objective human resource decision making and development of analytics technologies. HR managers have been faced with some obstacles in exploiting data and information to obtain their effective talent management decisions. These include process-based data and records; insufficient human capital-related measures and metrics; lack of capabilities in data modeling in strategic manners; and, time consuming to add up numbers and make decisions. This paper proposes a framework of talent management through integration of talent value chain and human capital analytics approaches. It encompasses key data, measures, and metrics regarding strategic talent management decisions along the organizational and talent value chain. Moreover, specific predictive and prescriptive models incorporating these data and information are recommended to help managers in understanding the state of talent, gaps in managing talent and the organization, and the ways to develop optimized talent strategies.    

Keywords: Decision making, human capital analytics, talent management, talent value chain.

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5767 Explanatory of Relationship between Learning Motivation and Learning Performance

Authors: Chih Chin Yang

Abstract:

In this paper, the relationship between learning motivation and learning performance is explored by using exchange theory. The relationship is concluded that external performance can raise learning motivation and then increase learning performance. The internal performance should be not completely neglected and the external performance should be not attached important excessively. The parents need self-study and must be also reeducated. The existing education must be improved in raise of internal performance. The incorrect learning thinking will mislead the students, parents, and educators of next generation, when the students obtain good learning performance in the learning environment with excess stimulants. Over operation of external performance will result abnormal learning thinking and violating learning goal. Learning is not only to obtain performance. Learning quality and learning performance will be limited as without learning motivation. The best learning motivation is, the best learning performance is. The learning for reward is not good for learning performance. Strategies of promoting life-long learning are including the encouraging for learner, establishment of good interaction learning environment, and the advertisement of the merit and the importance of life-long learning, which can let the learner with the correct learning motivation.

Keywords: exchange theory, learning motivation, learning performance, learning quality

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