Search results for: Java benchmark
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 343

Search results for: Java benchmark

283 Comparative Study of Evolutionary Model and Clustering Methods in Circuit Partitioning Pertaining to VLSI Design

Authors: K. A. Sumitra Devi, N. P. Banashree, Annamma Abraham

Abstract:

Partitioning is a critical area of VLSI CAD. In order to build complex digital logic circuits its often essential to sub-divide multi -million transistor design into manageable Pieces. This paper looks at the various partitioning techniques aspects of VLSI CAD, targeted at various applications. We proposed an evolutionary time-series model and a statistical glitch prediction system using a neural network with selection of global feature by making use of clustering method model, for partitioning a circuit. For evolutionary time-series model, we made use of genetic, memetic & neuro-memetic techniques. Our work focused in use of clustering methods - K-means & EM methodology. A comparative study is provided for all techniques to solve the problem of circuit partitioning pertaining to VLSI design. The performance of all approaches is compared using benchmark data provided by MCNC standard cell placement benchmark net lists. Analysis of the investigational results proved that the Neuro-memetic model achieves greater performance then other model in recognizing sub-circuits with minimum amount of interconnections between them.

Keywords: VLSI, circuit partitioning, memetic algorithm, genetic algorithm.

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282 An Advanced Nelder Mead Simplex Method for Clustering of Gene Expression Data

Authors: M. Pandi, K. Premalatha

Abstract:

The DNA microarray technology concurrently monitors the expression levels of thousands of genes during significant biological processes and across the related samples. The better understanding of functional genomics is obtained by extracting the patterns hidden in gene expression data. It is handled by clustering which reveals natural structures and identify interesting patterns in the underlying data. In the proposed work clustering gene expression data is done through an Advanced Nelder Mead (ANM) algorithm. Nelder Mead (NM) method is a method designed for optimization process. In Nelder Mead method, the vertices of a triangle are considered as the solutions. Many operations are performed on this triangle to obtain a better result. In the proposed work, the operations like reflection and expansion is eliminated and a new operation called spread-out is introduced. The spread-out operation will increase the global search area and thus provides a better result on optimization. The spread-out operation will give three points and the best among these three points will be used to replace the worst point. The experiment results are analyzed with optimization benchmark test functions and gene expression benchmark datasets. The results show that ANM outperforms NM in both benchmarks.

Keywords: Spread out, simplex, multi-minima, fitness function, optimization, search area, monocyte, solution, genomes.

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281 Benchmarking Cleaner Production Performance of Coal-fired Power Plants Using Two-stage Super-efficiency Data Envelopment Analysis

Authors: Shao-lun Zeng, Yu-long Ren

Abstract:

Benchmarking cleaner production performance is an effective way of pollution control and emission reduction in coal-fired power industry. A benchmarking method using two-stage super-efficiency data envelopment analysis for coal-fired power plants is proposed – firstly, to improve the cleaner production performance of DEA-inefficient or weakly DEA-efficient plants, then to select the benchmark from performance-improved power plants. An empirical study is carried out with the survey data of 24 coal-fired power plants. The result shows that in the first stage the performance of 16 plants is DEA-efficient and that of 8 plants is relatively inefficient. The target values for improving DEA-inefficient plants are acquired by projection analysis. The efficient performance of 24 power plants and the benchmarking plant is achieved in the second stage. The two-stage benchmarking method is practical to select the optimal benchmark in the cleaner production of coal-fired power industry and will continuously improve plants- cleaner production performance.

Keywords: benchmarking, cleaner production performance, coal-fired power plant, super-efficiency data envelopment analysis

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280 A Two-Stage Adaptation towards Automatic Speech Recognition System for Malay-Speaking Children

Authors: Mumtaz Begum Mustafa, Siti Salwah Salim, Feizal Dani Rahman

Abstract:

Recently, Automatic Speech Recognition (ASR) systems were used to assist children in language acquisition as it has the ability to detect human speech signal. Despite the benefits offered by the ASR system, there is a lack of ASR systems for Malay-speaking children. One of the contributing factors for this is the lack of continuous speech database for the target users. Though cross-lingual adaptation is a common solution for developing ASR systems for under-resourced language, it is not viable for children as there are very limited speech databases as a source model. In this research, we propose a two-stage adaptation for the development of ASR system for Malay-speaking children using a very limited database. The two stage adaptation comprises the cross-lingual adaptation (first stage) and cross-age adaptation. For the first stage, a well-known speech database that is phonetically rich and balanced, is adapted to the medium-sized Malay adults using supervised MLLR. The second stage adaptation uses the speech acoustic model generated from the first adaptation, and the target database is a small-sized database of the target users. We have measured the performance of the proposed technique using word error rate, and then compare them with the conventional benchmark adaptation. The two stage adaptation proposed in this research has better recognition accuracy as compared to the benchmark adaptation in recognizing children’s speech.

Keywords: Automatic speech recognition system, children speech, adaptation, Malay.

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279 LSGENSYS - An Integrated System for Pattern Recognition and Summarisation

Authors: Hema Nair

Abstract:

This paper presents a new system developed in Java® for pattern recognition and pattern summarisation in multi-band (RGB) satellite images. The system design is described in some detail. Results of testing the system to analyse and summarise patterns in SPOT MS images and LANDSAT images are also discussed.

Keywords: Pattern recognition, image analysis, feature extraction, blackboard component, linguistic summary.

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278 Verifying X.509 Certificates on Smart Cards

Authors: Olaf Henniger, Karim Lafou, Dirk Scheuermann, Bruno Struif

Abstract:

This paper presents a smart-card applet that is able to verify X.509 certificates and to use the public key contained in the certificate for verifying digital signatures that have been created using the corresponding private key, e.g. for the purpose of authenticating the certificate owner against the card. The approach has been implemented as an operating prototype on Java cards.

Keywords: Public key cryptographic applications, smart cards.

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277 Soybean Based Farming System Assessment in Pasuruan East Java Indonesia

Authors: Mohammad Saeri, Noor Rizkiyah, Kambang Vetrani Asie, Titin Apung Atikah

Abstract:

The study aims to assess efficient specific-location soybean farming technology assembly by assisting the farmers in applying the suggested technology. Superimposed trial was conducted to know NPK fertilizer effect toward soybean growth and yield and soybean improved variety test for the dissemination of improved variety. The assessment was conducted at the farmers group of Sumber Rejeki, Kepulungan Village, Gempol Sub-district, Pasuruan Regency as the soybean central at Pasuruan area. The number of farmers involved in the study was 38 people with 25 ha soybean area. This study was held from July to October 2012.  The recommended technology package agreed at the socialization time and used in this research were: using Argomulyo variety seeds of 40 kg/ha, planting by drilling, planting by distance of 40x10 cm, deciding the seeds amount of 2-3 seeds per hole, and giving fertilization based on recommendation of East Java AIAT of 50 kg Urea, 100 kg SP-36 and 50 kg KCl.  Farmers around the research location were used as control group. Assessment on soybean farming system was considered effective because it could increase the production up to 38%. The farming analysis showed that the result collaborator farmers gained were positively higher than non-collaborator farmers with RC ratio of 2.03 and 1.54, respectively. Argomulyo variety has the prospect to be developed due to the high yield of about 2 tons/ha and the larger seeds. The NPK fertilization test at the soybean plants showed that the fertilization had minor effect on the yield.

Keywords: Farming system, soybean, variety, location specific farming.

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276 Augmented Reality on Android

Authors: Chunghan Li, Chang-Shyh Peng, Daisy F. Sang

Abstract:

Augmented Reality is an application which combines a live view of real-world environment and computer-generated images. This paper studies and demonstrates an efficient Augmented Reality development in the mobile Android environment with the native Java language and Android SDK. Major components include Barcode Reader, File Loader, Marker Detector, Transform Matrix Generator, and a cloud database.

Keywords: Augmented Reality, Android.

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275 Application of Remote Sensing for Monitoring the Impact of Lapindo Mud Sedimentation for Mangrove Ecosystem: Case Study in Sidoarjo, East Java

Authors: Akbar Cahyadhi Pratama Putra, Tantri Utami Widhaningtyas, M. Randy Aswin

Abstract:

Indonesia, as an archipelagic nation, has a very long coastline with significant potential for marine resources, including mangrove ecosystems. The Lapindo mudflow disaster in Sidoarjo, East Java, resulted in mudflow being discharged into the sea through the Brantas and Porong rivers. The mud material transported by the river flow is feared to be dangerous because it contains harmful substances such as heavy metals. This study aims to map the mangrove ecosystem in terms of its density and assess the impact of the Lapindo mud disaster on the mangrove ecosystem, along with efforts to sustain its continuity. The mapping of the coastal mangrove conditions in Sidoarjo was carried out using remote sensing products, specifically Landsat 7 ETM+ images, taken during dry months in 2002, 2006, 2009, and 2014. The density of mangroves was determined using NDVI, which utilizes band 3 (the red channel) and band 4 (the near IR channel). Image processing to generate NDVI was performed using ENVI 5.1 software. The NDVI results were used to assess mangrove density on a scale from 0 to 1. The growth of mangrove ecosystems, both in terms of area and density, showed a significant increase from year to year. The development of mangrove ecosystems was influenced by the deposition of Lapindo mud in the estuaries of the Porong and Brantas rivers, where the silt provided a suitable medium for the growth of the mangrove ecosystem, leading to an increase in its density. The rise in density was supported by public awareness to mitigate heavy metal contamination, allowing for mangrove breeding near the affected areas.

Keywords: Archipelagic nation, Mangrove, Lapindo mudflow disaster, NDVI.

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274 Use XML Format like a Model of Data Backup

Authors: Souleymane Oumtanaga, Kadjo Tanon Lambert, Koné Tiémoman, Tety Pierre, Dowa N’sreke Florent

Abstract:

Nowadays data backup format doesn-t cease to appear raising so the anxiety on their accessibility and their perpetuity. XML is one of the most promising formats to guarantee the integrity of data. This article suggests while showing one thing man can do with XML. Indeed XML will help to create a data backup model. The main task will consist in defining an application in JAVA able to convert information of a database in XML format and restore them later.

Keywords: Backup, Proprietary format, parser, syntactic tree.

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273 Edge-end Pixel Extraction for Edge-based Image Segmentation

Authors: Mahinda P. Pathegama, Özdemir Göl

Abstract:

Extraction of edge-end-pixels is an important step for the edge linking process to achieve edge-based image segmentation. This paper presents an algorithm to extract edge-end pixels together with their directional sensitivities as an augmentation to the currently available mathematical models. The algorithm is implemented in the Java environment because of its inherent compatibility with web interfaces since its main use is envisaged to be for remote image analysis on a virtual instrumentation platform.

Keywords: edge-end pixels, image processing, imagesegmentation, pixel extraction

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272 Mining Sequential Patterns Using I-PrefixSpan

Authors: Dhany Saputra, Dayang R. A. Rambli, Oi Mean Foong

Abstract:

In this paper, we propose an improvement of pattern growth-based PrefixSpan algorithm, called I-PrefixSpan. The general idea of I-PrefixSpan is to use sufficient data structure for Seq-Tree framework and separator database to reduce the execution time and memory usage. Thus, with I-PrefixSpan there is no in-memory database stored after index set is constructed. The experimental result shows that using Java 2, this method improves the speed of PrefixSpan up to almost two orders of magnitude as well as the memory usage to more than one order of magnitude.

Keywords: ArrayList, ArrayIntList, minimum support, sequence database, sequential patterns.

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271 Comparative Survey of Object Serialization Techniques and the Programming Supports

Authors: Kazuaki Maeda

Abstract:

This paper compares six approaches of object serialization from qualitative and quantitative aspects. Those are object serialization in Java, IDL, XStream, Protocol Buffers, Apache Avro, and MessagePack. Using each approach, a common example is serialized to a file and the size of the file is measured. The qualitative comparison works are investigated in the way of checking whether schema definition is required or not, whether schema compiler is required or not, whether serialization is based on ascii or binary, and which programming languages are supported. It is clear that there is no best solution. Each solution makes good in the context it was developed.

Keywords: structured data, serialization, programming

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270 Network Based High Performance Computing

Authors: Karanjeet Singh Kahlon, Gurvinder Singh, Arjan Singh

Abstract:

In the past few years there is a change in the view of high performance applications and parallel computing. Initially such applications were targeted towards dedicated parallel machines. Recently trend is changing towards building meta-applications composed of several modules that exploit heterogeneous platforms and employ hybrid forms of parallelism. The aim of this paper is to propose a model of virtual parallel computing. Virtual parallel computing system provides a flexible object oriented software framework that makes it easy for programmers to write various parallel applications.

Keywords: Applet, Efficiency, Java, LAN

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269 Multiagent Systems Simulation

Authors: G. Balakayeva, A. Aktymbayeva

Abstract:

In this paper, we consider components of discrete event imitating model, implementing a simulation model by using JAVA and performing an input analysis of the data and an output analysis of the simulation results. Was lead development of imitating model of mass service system with n (n≥1) devices of service. On the basis of the developed process of a multithreading simulated the distributed processes with presence of synchronization. Was developed the algorithm of event-oriented simulation, was received results of system functioning with n devices of service.

Keywords: Imitating modeling, Mass service system, Multi agentsystem.

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268 Approximately Similarity Measurement of Web Sites Using Genetic Algorithms and Binary Trees

Authors: Doru Anastasiu Popescu, Dan Rădulescu

Abstract:

In this paper, we determine the similarity of two HTML web applications. We are going to use a genetic algorithm in order to determine the most significant web pages of each application (we are not going to use every web page of a site). Using these significant web pages, we will find the similarity value between the two applications. The algorithm is going to be efficient because we are going to use a reduced number of web pages for comparisons but it will return an approximate value of the similarity. The binary trees are used to keep the tags from the significant pages. The algorithm was implemented in Java language.

Keywords: Tag, HTML, web page, genetic algorithm, similarity value, binary tree.

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267 Numerical Simulation of a Conventional Heat Pipe

Authors: Shoeib Mahjoub, Ali Mahtabroshan

Abstract:

The steady incompressible flow has been solved in cylindrical coordinates in both vapour region and wick structure. The governing equations in vapour region are continuity, Navier-Stokes and energy equations. These equations have been solved using SIMPLE algorithm. For study of parameters variation on heat pipe operation, a benchmark has been chosen and the effect of changing one parameter has been analyzed when the others have been fixed.

Keywords: Vapour region, conventional heat pipe, numerical simulation.

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266 A Optimal Subclass Detection Method for Credit Scoring

Authors: Luciano Nieddu, Giuseppe Manfredi, Salvatore D'Acunto, Katia La Regina

Abstract:

In this paper a non-parametric statistical pattern recognition algorithm for the problem of credit scoring will be presented. The proposed algorithm is based on a clustering k- means algorithm and allows for the determination of subclasses of homogenous elements in the data. The algorithm will be tested on two benchmark datasets and its performance compared with other well known pattern recognition algorithm for credit scoring.

Keywords: Constrained clustering, Credit scoring, Statistical pattern recognition, Supervised classification.

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265 Dynamics and Control of Bouncing Ball

Authors: A. K. Kamath, N. M. Singh, R. Pasumarthy

Abstract:

This paper investigates the control of a bouncing ball using Model Predictive Control. Bouncing ball is a benchmark problem for various rhythmic tasks such as juggling, walking, hopping and running. Humans develop intentions which may be perceived as our reference trajectory and tries to track it. The human brain optimizes the control effort needed to track its reference; this forms the central theme for control of bouncing ball in our investigations.

Keywords: Bouncing Ball, impact dynamics, intermittent control, model predictive control.

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264 XML based Safe and Scalable Multi-Agent Development Framework

Authors: Rinkaj Goyal, Pravin Chandra, Yogesh Singh

Abstract:

In this paper we describe our efforts to design and implement an agent development framework that has the potential to scale to the size of any underlying network suitable for various ECommerce activities. The main novelty in our framework is it-s capability to allow the development of sophisticated, secured agents which are simple enough to be practical. We have adopted FIPA agent platform reference Model as backbone for implementation along with XML for agent Communication and Java Cryptographic Extension and architecture to realize the security of communication information between agents. The advantage of our architecture is its support of agents development in different languages and Communicating with each other using a more open standard i.e. XML

Keywords: Agent, Agent Development Framework, Agent Coordination, Security

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263 Intelligent Agent System Simulation Using Fear Emotion

Authors: Latifeh PourMohammadBagher

Abstract:

In this paper I have developed a system for evaluating the degree of fear emotion that the intelligent agent-based system may feel when it encounters to a persecuting event. In this paper I want to describe behaviors of emotional agents using human behavior in terms of the way their emotional states evolve over time. I have implemented a fuzzy inference system using Java environment. As the inputs of this system, I have considered three parameters related on human fear emotion. The system outputs can be used in agent decision making process or choosing a person for team working systems by combination the intensity of fear to other emotion intensities.

Keywords: Emotion simulation, Fear, Fuzzy intelligent agent

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262 A Novel Method for Live Debugging of Production Web Applications by Dynamic Resource Replacement

Authors: Khalid Al-Tahat, Khaled Zuhair Mahmoud, Ahmad Al-Mughrabi

Abstract:

This paper proposes a novel methodology for enabling debugging and tracing of production web applications without affecting its normal flow and functionality. This method of debugging enables developers and maintenance engineers to replace a set of existing resources such as images, server side scripts, cascading style sheets with another set of resources per web session. The new resources will only be active in the debug session and other sessions will not be affected. This methodology will help developers in tracing defects, especially those that appear only in production environments and in exploring the behaviour of the system. A realization of the proposed methodology has been implemented in Java.

Keywords: Live debugging, web application, web resources, inconsistent bugs, tracing.

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261 Combining Bagging and Additive Regression

Authors: Sotiris B. Kotsiantis

Abstract:

Bagging and boosting are among the most popular re-sampling ensemble methods that generate and combine a diversity of regression models using the same learning algorithm as base-learner. Boosting algorithms are considered stronger than bagging on noise-free data. However, there are strong empirical indications that bagging is much more robust than boosting in noisy settings. For this reason, in this work we built an ensemble using an averaging methodology of bagging and boosting ensembles with 10 sub-learners in each one. We performed a comparison with simple bagging and boosting ensembles with 25 sub-learners on standard benchmark datasets and the proposed ensemble gave better accuracy.

Keywords: Regressors, statistical learning.

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260 Statistical Genetic Algorithm

Authors: Mohammad Ali Tabarzad, Caro Lucas, Ali Hamzeh

Abstract:

Adaptive Genetic Algorithms extend the Standard Gas to use dynamic procedures to apply evolutionary operators such as crossover, mutation and selection. In this paper, we try to propose a new adaptive genetic algorithm, which is based on the statistical information of the population as a guideline to tune its crossover, selection and mutation operators. This algorithms is called Statistical Genetic Algorithm and is compared with traditional GA in some benchmark problems.

Keywords: Genetic Algorithms, Statistical Information ofthe Population, PAUX, SSO.

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259 B-VIS Service-oriented Middleware for RFID Sensor Network

Authors: Wiroon Sriborrirux, Sorakrai Kraipui, Nakorn Indra-Payoong

Abstract:

One of the most importance of intelligence in-car and roadside systems is the cooperative vehicle-infrastructure system. In Thailand, ITS technologies are rapidly growing and real-time vehicle information is considerably needed for ITS applications; for example, vehicle fleet tracking and control and road traffic monitoring systems. This paper defines the communication protocols and software design for middleware components of B-VIS (Burapha Vehicle-Infrastructure System). The proposed B-VIS middleware architecture serves the needs of a distributed RFID sensor network and simplifies some intricate details of several communication standards.

Keywords: Middleware, RFID sensor network, Cooperativevehicle-infrastructure system, Enterprise Java Bean.

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258 Linear Elasticity Problems Solved by Using the Fictitious Domain Method and Total - FETI Domain Decomposition

Authors: Lukas Mocek, Alexandros Markopoulos

Abstract:

The main goal of this paper is to show a possibility, how to solve numerically elliptic boundary value problems arising in 2D linear elasticity by using the fictitious domain method (FDM) and the Total-FETI domain decomposition method. We briefly mention the theoretical background of these methods and demonstrate their performance on a benchmark.

Keywords: Linear elasticity, fictitious domain method, Total-FETI, domain decomposition, saddle-point system.

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257 Architectural, Technological and Performance Issues in Enterprise Applications

Authors: Melek Oktay, Ayşe Betül Gülbağcı, Mustafa Sarıöz

Abstract:

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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256 A Dataset of Program Educational Objectives Mapped to ABET Outcomes: Data Cleansing, Exploratory Data Analysis and Modeling

Authors: Addin Osman, Anwar Ali Yahya, Mohammed Basit Kamal

Abstract:

Datasets or collections are becoming important assets by themselves and now they can be accepted as a primary intellectual output of a research. The quality and usage of the datasets depend mainly on the context under which they have been collected, processed, analyzed, validated, and interpreted. This paper aims to present a collection of program educational objectives mapped to student’s outcomes collected from self-study reports prepared by 32 engineering programs accredited by ABET. The manual mapping (classification) of this data is a notoriously tedious, time consuming process. In addition, it requires experts in the area, which are mostly not available. It has been shown the operational settings under which the collection has been produced. The collection has been cleansed, preprocessed, some features have been selected and preliminary exploratory data analysis has been performed so as to illustrate the properties and usefulness of the collection. At the end, the collection has been benchmarked using nine of the most widely used supervised multiclass classification techniques (Binary Relevance, Label Powerset, Classifier Chains, Pruned Sets, Random k-label sets, Ensemble of Classifier Chains, Ensemble of Pruned Sets, Multi-Label k-Nearest Neighbors and Back-Propagation Multi-Label Learning). The techniques have been compared to each other using five well-known measurements (Accuracy, Hamming Loss, Micro-F, Macro-F, and Macro-F). The Ensemble of Classifier Chains and Ensemble of Pruned Sets have achieved encouraging performance compared to other experimented multi-label classification methods. The Classifier Chains method has shown the worst performance. To recap, the benchmark has achieved promising results by utilizing preliminary exploratory data analysis performed on the collection, proposing new trends for research and providing a baseline for future studies.

Keywords: Benchmark collection, program educational objectives, student outcomes, ABET, Accreditation, machine learning, supervised multiclass classification, text mining.

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255 DJess A Knowledge-Sharing Middleware to Deploy Distributed Inference Systems

Authors: Federico Cabitza, Bernardo Dal Seno

Abstract:

In this paper DJess is presented, a novel distributed production system that provides an infrastructure for factual and procedural knowledge sharing. DJess is a Java package that provides programmers with a lightweight middleware by which inference systems implemented in Jess and running on different nodes of a network can communicate. Communication and coordination among inference systems (agents) is achieved through the ability of each agent to transparently and asynchronously reason on inferred knowledge (facts) that might be collected and asserted by other agents on the basis of inference code (rules) that might be either local or transmitted by any node to any other node.

Keywords: Knowledge-Based Systems, Expert Systems, Distributed Inference Systems, Parallel Production Systems, Ambient Intelligence, Mobile Agents.

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254 Combining Bagging and Boosting

Authors: S. B. Kotsiantis, P. E. Pintelas

Abstract:

Bagging and boosting are among the most popular resampling ensemble methods that generate and combine a diversity of classifiers using the same learning algorithm for the base-classifiers. Boosting algorithms are considered stronger than bagging on noisefree data. However, there are strong empirical indications that bagging is much more robust than boosting in noisy settings. For this reason, in this work we built an ensemble using a voting methodology of bagging and boosting ensembles with 10 subclassifiers in each one. We performed a comparison with simple bagging and boosting ensembles with 25 sub-classifiers, as well as other well known combining methods, on standard benchmark datasets and the proposed technique was the most accurate.

Keywords: data mining, machine learning, pattern recognition.

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