Search results for: decision support filters

Authors: Alexandru George Floares

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Chronic hepatitis B can evolve to cirrhosis and liver cancer. Interferon is the only effective treatment, for carefully selected patients, but it is very expensive. Some of the selection criteria are based on liver biopsy, an invasive, costly and painful medical procedure. Therefore, developing efficient non-invasive selection systems, could be in the patients benefit and also save money. We investigated the possibility to create intelligent systems to assist the Interferon therapeutical decision, mainly by predicting with acceptable accuracy the results of the biopsy. We used a knowledge discovery in integrated medical data - imaging, clinical, and laboratory data. The resulted intelligent systems, tested on 500 patients with chronic hepatitis B, based on C5.0 decision trees and boosting, predict with 100% accuracy the results of the liver biopsy. Also, by integrating the other patients selection criteria, they offer a non-invasive support for the correct Interferon therapeutic decision. To our best knowledge, these decision systems outperformed all similar systems published in the literature, and offer a realistic opportunity to replace liver biopsy in this medical context.

Keywords: Interferon, chronic hepatitis B, intelligent virtualbiopsy.

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Authors: Qiang Yang, Ping-An Du

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Group decision making with multiple attribute has attracted intensive concern in the decision analysis area. This paper assumes that the contributions of all the decision makers (DMs) are not equal to the decision process based on different knowledge and experience in group setting. The aim of this paper is to develop a novel approach to determine weights of DMs in the group decision making problems. In this paper, the weights of DMs are determined in the group decision environment via angle cosine and projection method. First of all, the average decision of all individual decisions is defined as the ideal decision. After that, we define the weight of each decision maker (DM) by aggregating the angle cosine and projection between individual decision and ideal decision with associated direction indicator μ. By using the weights of DMs, all individual decisions are aggregated into a collective decision. Further, the preference order of alternatives is ranked in accordance with the overall row value of collective decision. Finally, an example in a chemical company is provided to illustrate the developed approach.

Keywords: Angel cosine, ideal decision, projection method, weights of decision makers.

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Authors: M. Challal, F. Labu, M. Dehmas, A. Azrar

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In this paper, three types of defected ground structure (DGS) units which are triangular-head (TH), rectangular-head (RH) and U-shape (US) are investigated. They are further used to low-pass and band-pass filters designs (LPF and BPF) and the obtained performances are examined. The LPF employing RH-DGS geometry presents the advantages of compact size, low-insertion loss and wide stopband compared to the other filters. It provides cutoff frequency of 2.5 GHz, largest rejection band width of 20 dB from 2.98 to 8.76 GHz, smallest transition region and smallest sharpness of the cutoff frequency. The BPF based on RH-DGS has the highest bandwidth (BW) of about 0.74 GHz and the lowest center frequency of 3.24 GHz, whereas the other BPFs have BWs less than 0.7 GHz.

Keywords: Defected ground structure (DGS), triangular-head(TH) DGS, rectangular-head (RH) DGS, U-shape (US) DGS, lowpassfilter (LPF) and band-pass filter (BPF).

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Authors: R. Tur, A. Yardımcı

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Imperfect knowledge cannot be avoided all the time. Imperfections may have several forms; uncertainties, imprecision and incompleteness. When we look to classification of methods for the management of imperfect knowledge we see fuzzy set-based techniques. The choice of a method to process data is linked to the choice of knowledge representation, which can be numerical, symbolic, logical or semantic and it depends on the nature of the problem to be solved for example decision support, which will be mentioned in our study. Fuzzy Logic is used for its ability to manage imprecise knowledge, but it can take advantage of the ability of neural networks to learn coefficients or functions. Such an association of methods is typical of so-called soft computing. In this study a new method was used for the management of imprecision for collected knowledge which related to economic analysis of construction industry in Turkey. Because of sudden changes occurring in economic factors decrease competition strength of construction companies. The better evaluation of these changes in economical factors in view of construction industry will made positive influence on company-s decisions which are dealing construction.

Keywords: Fuzzy logic, decision support systems, construction industry.

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Authors: Jun-Ho Park, Kwang-Woo Nam, Seung-Mo Hong, Tae-Heon Moon, Sang-Ho Lee, Youn-Taik Leem

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The aim of this study was to build ‘Ubi-Net’, a decision-making support system for systematic establishment in U-City planning. We have experienced various urban problems caused by high-density development and population concentrations in established urban areas. To address these problems, a U-Service contributes to the alleviation of urban problems by providing real-time information to citizens through network connections and related information. However, technology, devices, and information for consumers are required for systematic U-Service planning in towns and cities where there are many difficulties in this regard, and a lack of reference systems. Thus, this study suggests methods to support the establishment of sustainable planning by providing comprehensive information including IT technology, devices, news, and social networking services (SNS) to U-City planners through intelligent searches. In this study, we targeted Smart U-Parking Planning to solve parking problems in an ‘old’ city. Through this study, we sought to contribute to supporting advances in U-Space and the alleviation of urban problems.

Keywords: Design and decision support system, smart U-parking planning, social network analysis.

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Authors: Elham Serkani, Hossein Gharaee Garakani, Naser Mohammadzadeh, Elaheh Vaezpour

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Intrusion detection systems (IDS) are the main components of network security. These systems analyze the network events for intrusion detection. The design of an IDS is through the training of normal traffic data or attack. The methods of machine learning are the best ways to design IDSs. In the method presented in this article, the pruning algorithm of C5.0 decision tree is being used to reduce the features of traffic data used and training IDS by the least square vector algorithm (LS-SVM). Then, the remaining features are arranged according to the predictor importance criterion. The least important features are eliminated in the order. The remaining features of this stage, which have created the highest level of accuracy in LS-SVM, are selected as the final features. The features obtained, compared to other similar articles which have examined the selected features in the least squared support vector machine model, are better in the accuracy, true positive rate, and false positive. The results are tested by the UNSW-NB15 dataset.

Keywords: Intrusion detection system, decision tree, support vector machine, feature selection.

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Authors: Pejman Hosseinioun, Hasan Shakeri, Ghasem Ghorbanirostam

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

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

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Authors: R. Monib, C. I. Goodier, A. Gibb

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The aim of this paper is to investigate the key drivers in planning the construction phase for infrastructure projects to reduce project delays. To achieve this aim, the research conducted three case studies using semi-structured and unstructured interviews (n = 59). The results conclude that a lack of modularization awareness is among the key factors attributed to project delays. The current emotive and ill-informed approach to decision-making, coupled with the lack of knowledge regarding appropriate construction method selection, prevents the potential benefits of modularization being fully realized. To assist with decision-making for the best construction method, the research presents project management tools to help decision makers to choose the most appropriate construction approach through optimizing the use of modularization in engineering and construction (EC). A decision-making checklist is presented in this paper. This checklist tool assists the project team in determining the best construction method, taking into consideration the module type.

Keywords: Infrastructure, modularization, decision support, planning.

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Authors: Faten A. Dawood, Rahmita W. Rahmat, Suhaini B. Kadiman, Lili N. Abdullah, Mohd D. Zamrin

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Echocardiography imaging is one of the most common diagnostic tests that are widely used for assessing the abnormalities of the regional heart ventricle function. The main goal of the image enhancement task in 2D-echocardiography (2DE) is to solve two major anatomical structure problems; speckle noise and low quality. Therefore, speckle noise reduction is one of the important steps that used as a pre-processing to reduce the distortion effects in 2DE image segmentation. In this paper, we present the common filters that based on some form of low-pass spatial smoothing filters such as Mean, Gaussian, and Median. The Laplacian filter was used as a high-pass sharpening filter. A comparative analysis was presented to test the effectiveness of these filters after being applied to original 2DE images of 4-chamber and 2-chamber views. Three statistical quantity measures: root mean square error (RMSE), peak signal-to-ratio (PSNR) and signal-tonoise ratio (SNR) are used to evaluate the filter performance quantitatively on the output enhanced image.

Keywords: Gaussian operator, median filter, speckle texture, peak signal-to-ratio

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Authors: Ganesan V.

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Application of Expert System in the area of agriculture would take the form of Integrated Crop Management decision aids and would encompass water management, fertilizer management, crop protection systems and identification of implements. In order to remain competitive, the modern farmer often relies on agricultural specialists and advisors to provide information for decision-making. An expert system normally composed of a knowledge base (information, heuristics, etc.), inference engine (analyzes knowledge base), and end user interface (accepting inputs, generating outputs). Software named 'CROP-9-DSS' incorporating all modern features like, graphics, photos, video clippings etc. has been developed. This package will aid as a decision support system for identification of pest and diseases with control measures, fertilizer recommendation system, water management system and identification of farm implements for leading crops of Kerala (India) namely Coconut, Rice, Cashew, Pepper, Banana, four vegetables like Amaranthus, Bhindi, Brinjal and Cucurbits. 'CROP-9-DSS' will act as an expert system to agricultural officers, scientists in the field of agriculture and extension workers for decision-making and help them in suggesting suitable recommendations.

Keywords: Diagnostic, inference engine, knowledge base and user interface.

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Authors: Paul O'Leary, Matthew Harker

Abstract:

This paper presents unified theory for local (Savitzky- Golay) and global polynomial smoothing. The algebraic framework can represent any polynomial approximation and is seamless from low degree local, to high degree global approximations. The representation of the smoothing operator as a projection onto orthonormal basis functions enables the computation of: the covariance matrix for noise propagation through the filter; the noise gain and; the frequency response of the polynomial filters. A virtually perfect Gram polynomial basis is synthesized, whereby polynomials of degree d = 1000 can be synthesized without significant errors. The perfect basis ensures that the filters are strictly polynomial preserving. Given n points and a support length ls = 2m + 1 then the smoothing operator is strictly linear phase for the points xi, i = m+1. . . n-m. The method is demonstrated on geometric surfaces data lying on an invariant 2D lattice.

Keywords: Gram polynomials, Savitzky-Golay Smoothing, Discrete Polynomial Moments

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Authors: Chandrika M.J., Lariyah M.S., Alicia Y.C. Tang

Abstract:

Ontology is widely being used as a tool for organizing information, creating the relation between the subjects within the defined knowledge domain area. Various fields such as Civil, Biology, and Management have successful integrated ontology in decision support systems for managing domain knowledge and to assist their decision makers. Gross pollutant traps (GPT) are devices used in trapping and preventing large items or hazardous particles in polluting and entering our waterways. However choosing and determining GPT is a challenge in Malaysia as there are inadequate GPT data repositories being captured and shared. Hence ontology is needed to capture, organize and represent this knowledge into meaningful information which can be contributed to the efficiency of GPT selection in Malaysia urbanization. A GPT Ontology framework is therefore built as the first step to capture GPT knowledge which will then be integrated into the decision support system. This paper will provide several examples of the GPT ontology, and explain how it is constructed by using the Protégé tool.

Keywords: Gross pollutant Trap, Ontology, Protégé.

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Authors: Kamalendu Pal

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This paper describes the main features of a knowledge-based system evaluation method. System evaluation is placed in the context of a hybrid legal decision-support system, Advisory Support for Home Settlement in Divorce (ASHSD). Legal knowledge for ASHSD is represented in two forms, as rules and previously decided cases. Besides distinguishing the two different forms of knowledge representation, the paper outlines the actual use of these forms in a computational framework that is designed to generate a plausible solution for a given case, by using rule-based reasoning (RBR) and case-based reasoning (CBR) in an integrated environment. The nature of suitability assessment of a solution has been considered as a multiple criteria decision-making process in ASHAD evaluation. The evaluation was performed by a combination of discussions and questionnaires with different user groups. The answers to questionnaires used in this evaluations method have been measured as a fuzzy linguistic term. The finding suggests that fuzzy linguistic evaluation is practical and meaningful in knowledge-based system development purpose. 

Keywords: Case-based reasoning, decision-support system, fuzzy linguistic term, rule-based reasoning, system evaluation.

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Authors: Rawan A. Abdelrazeq, Ahmed M. Khalafallah, Nabil A. Kartam

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Selection of competent contractors for construction projects is usually accomplished through competitive bidding or negotiated contracting in which the contract bid price is the basic criterion for selection. The evaluation of contractor’s safety performance is still not a typical criterion in the selection process, despite the existence of various safety prequalification procedures. There is a critical need for practical and automated systems that enable owners and decision makers to evaluate contractor safety performance, among other important contractor selection criteria. These systems should ultimately favor safety-conscious contractors to be selected by the virtue of their past good safety records and current safety programs. This paper presents an exploratory sequential mixed-methods approach to develop a framework for an automated decision support system that evaluates contractor safety performance based on a multitude of indicators and metrics that have been identified through a comprehensive review of construction safety research, and a survey distributed to domain experts. The framework is developed in three phases: (1) determining the indicators that depict contractor current and past safety performance; (2) soliciting input from construction safety experts regarding the identified indicators, their metrics, and relative significance; and (3) designing a decision support system using relational database models to integrate the identified indicators and metrics into a system that assesses and rates the safety performance of contractors. The proposed automated system is expected to hold several advantages including: (1) reducing the likelihood of selecting contractors with poor safety records; (2) enhancing the odds of completing the project safely; and (3) encouraging contractors to exert more efforts to improve their safety performance and practices in order to increase their bid winning opportunities which can lead to significant safety improvements in the construction industry. This should prove useful to decision makers and researchers, alike, and should help improve the safety record of the construction industry.

Keywords: Construction safety, contractor selection, decision support system, relational database.

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Authors: Jinn-Yi Yeh, Tai-Hsi Wu

Abstract:

Hemodialysis patients might suffer from unhealthy care behaviors or long-term dialysis treatments. Ultimately they need to be hospitalized. If the hospitalization rate of a hemodialysis center is high, its quality of service would be low. Therefore, how to decrease hospitalization rate is a crucial problem for health care. In this study we combined temporal abstraction with data mining techniques for analyzing the dialysis patients' biochemical data to develop a decision support system. The mined temporal patterns are helpful for clinicians to predict hospitalization of hemodialysis patients and to suggest them some treatments immediately to avoid hospitalization.

Keywords: Hemodialysis, Temporal abstract, Data mining, Healthcare quality.

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Authors: Aliaksei Patsekha, Michael Hohenberger, Harald Raupenstrauch

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An effective emergency response to accidents with chemical, biological, radiological, nuclear, or explosive materials (CBRNE) that represent highly dynamic situations needs immediate actions within limited time, information and resources. The aim of the study is to provide the foundation for division of unsafe area into risk zones according to the impact of hazardous parameters (heat radiation, thermal dose, overpressure, chemical concentrations). A decision on the boundary values for three risk zones is based on the vulnerability analysis that covered a variety of accident scenarios containing the release of a toxic or flammable substance which either evaporates, ignites and/or explodes. Critical values are selected for the boundary definition of the Red, Orange and Yellow risk zones upon the examination of harmful effects that are likely to cause injuries of varying severity to people and different levels of damage to structures. The obtained results provide the basis for creating a comprehensive real-time risk map for a decision support at CBRNE operations.

Keywords: Boundary values, CBRNE threats, decision making process, hazardous effects, vulnerability analysis, risk zones.

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Authors: Jun Gil Ahn, Jong Kang Park, Jong Tae Kim

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In this paper, we analyze major components of activity recognition (AR) in wearable device with 9-axis sensors and sensor fusion filters. 9-axis sensors commonly include 3-axis accelerometer, 3-axis gyroscope and 3-axis magnetometer. We chose sensor fusion filters as Kalman filter and Direction Cosine Matrix (DCM) filter. We also construct sensor fusion data from each activity sensor data and perform classification by accuracy of AR using Naïve Bayes and SVM. According to the classification results, we observed that the DCM filter and the specific combination of the sensing axes are more effective for AR in wearable devices while classifying walking, running, ascending and descending.

Keywords: Accelerometer, activity recognition, directional cosine matrix filter, gyroscope, Kalman filter, magnetometer.

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Authors: Tristan O’Neill, Trina Myers, Jarrod Trevathan

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The Tropical Data Hub (TDH) is a virtual research environment that provides researchers with an e-research infrastructure to congregate significant tropical data sets for data reuse, integration, searching, and correlation. However, researchers often require data and metadata synthesis across disciplines for cross-domain analyses and knowledge discovery. A triplestore offers a semantic layer to achieve a more intelligent method of search to support the synthesis requirements by automating latent linkages in the data and metadata. Presently, the benchmarks to aid the decision of which triplestore is best suited for use in an application environment like the TDH are limited to performance. This paper describes a new evaluation tool developed to analyze both features and performance. The tool comprises a weighted decision matrix to evaluate the interoperability, functionality, performance, and support availability of a range of integrated and native triplestores to rank them according to requirements of the TDH.

Keywords: Virtual research environment, Semantic Web, performance analysis, tropical data hub.

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Authors: A. Diet, M. Villegas, G. Baudoin

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This work concerns the measurements of a Bulk Acoustic Waves (BAW) emission filter S parameters and compare with prototypes simulated types. Thanks to HP-ADS, a co-simulation of filters- characteristics in a digital radio-communication chain is performed. Four cases of modulation schemes are studied in order to illustrate the impact of the spectral occupation of the modulated signal. Results of simulations and co-simulation are given in terms of Error Vector Measurements to be useful for a general sensibility analysis of 4th/3rd Generation (G.) emitters (wideband QAM and OFDM signals)

Keywords: RF architectures, BAW filters.

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Authors: Christiono Utomo, Arazi Idrus, Madzlan Napiah, Mohd. Faris Khamidi

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This paper presents a conceptual model of agreement options for negotiation support in multi-person decision on optimizing high-rise building columns. The decision is complicated since many parties involved in choosing a single alternative from a set of solutions. There are different concern caused by differing preferences, experiences, and background. Such building columns as alternatives are referred to as agreement options which are determined by identifying the possible decision maker group, followed by determining the optimal solution for each group. The group in this paper is based on three-decision makers preferences that are designer, programmer, and construction manager. Decision techniques applied to determine the relative value of the alternative solutions for performing the function. Analytical Hierarchy Process (AHP) was applied for decision process and game theory based agent system for coalition formation. An n-person cooperative game is represented by the set of all players. The proposed coalition formation model enables each agent to select individually its allies or coalition. It further emphasizes the importance of performance evaluation in the design process and value-based decision.

Keywords: Agreement options, coalition, group choice, game theory, building columns selection.

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Authors: Ferdi Sönmez, Nihal Yorulmaz

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Decision making on the true planning of the public transportation systems to serve potential users is a must for metropolitan areas. To take attraction of travelers to projected modes of transport, adequately fair overall travel times should be provided. In this fashion, other benefits such as lower traffic congestion, road safety and lower noise and atmospheric pollution may be earned. The congestion which comes with increasing demand of public transportation is becoming a part of our lives and making residents’ life difficult. Hence, regulations should be done to reduce this congestion. To provide a constructive and balanced regulation in public transportation systems, right stations should be located in right places. In this study, it is aimed to design and implement a Decision Support System (DSS) Application to determine the optimal bus stop places for public transport in Istanbul which is one of the biggest and oldest cities in the world. Required information is gathered from IETT (Istanbul Electricity, Tram and Tunnel) Enterprises which manages all public transportation services in Istanbul Metropolitan Area. By using the most real-like values, cost assignments are made. The cost is calculated with the help of equations produced by bi-level optimization model. For this study, 300 buses, 300 drivers, 10 lines and 110 stops are used. The user cost of each station and the operator cost taken place in lines are calculated. Some components like cost, security and noise pollution are considered as significant factors affecting the solution of set covering problem which is mentioned for identifying and locating the minimum number of possible bus stops. Preliminary research and model development for this study refers to previously published article of the corresponding author. Model results are represented with the intent of decision support to the specialists on locating stops effectively.

Keywords: User cost, bi-level optimization model, decision support, operator cost, transportation.

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Authors: Ferenc Peter Pach, Janos Abonyi

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This paper focuses on the data-driven generation of fuzzy IF...THEN rules. The resulted fuzzy rule base can be applied to build a classifier, a model used for prediction, or it can be applied to form a decision support system. Among the wide range of possible approaches, the decision tree and the association rule based algorithms are overviewed, and two new approaches are presented based on the a priori fuzzy clustering based partitioning of the continuous input variables. An application study is also presented, where the developed methods are tested on the well known Wisconsin Breast Cancer classification problem.

Keywords:

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Authors: Krzysztof Walczak

Abstract:

Fractional delay FIR filters design method based on the differential evolution algorithm is presented. Differential evolution is an evolutionary algorithm for solving a global optimization problems in the continuous search space. In the proposed approach, an evolutionary algorithm is used to determine the coefficients of a fractional delay FIR filter based on the Farrow structure. Basic differential evolution is enhanced with a restricted mating technique, which improves the algorithm performance in terms of convergence speed and obtained solution. Evolutionary optimization is carried out by minimizing an objective function which is based on the amplitude response and phase delay errors. Experimental results show that the proposed algorithm leads to a reduction in the amplitude response and phase delay errors relative to those achieved with the Least-Squares method.

Keywords: Fractional Delay Filters, Farrow Structure, Evolutionary Computation, Differential Evolution

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Authors: Carmen E. Zapata, Juan Bautista, Olga Montoya, Claudia Moreno, Marisol Suarez, Alejandra Betancur, Duvan Nanclares, Natalia A. Cano

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This study aims to evaluate the diversity of microorganisms in filters PM2.5 and PM10; and determine the genotoxic and cytotoxic activity of the complex mixture present in PM2.5 filters used in the Aburrá Valley Air Quality Monitoring Network (Colombia). The research results indicate that particulate matter PM2.5 of different monitoring stations are bacteria; however, this study of detection of bacteria and their phylogenetic relationship is not complete evidence to connect the microorganisms with pathogenic or degrading activities of compounds present in the air. Additionally, it was demonstrated the damage induced by the particulate material in the cell membrane, lysosomal and endosomal membrane and in the mitochondrial metabolism; this damage was independent of the PM2.5 concentrations in almost all the cases.

Keywords: Cytotoxic, genotoxic, microbiological analysis, PM10, PM2.5.

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Authors: Xiaohua Liu, Juan F. Beltran, Nishant Mohanchandra, Godfried T. Toussaint

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Support vector machines (SVMs) are considered to be the best machine learning algorithms for minimizing the predictive probability of misclassification. However, their drawback is that for large data sets the computation of the optimal decision boundary is a time consuming function of the size of the training set. Hence several methods have been proposed to speed up the SVM algorithm. Here three methods used to speed up the computation of the SVM classifiers are compared experimentally using a musical genre classification problem. The simplest method pre-selects a random sample of the data before the application of the SVM algorithm. Two additional methods use proximity graphs to pre-select data that are near the decision boundary. One uses k-Nearest Neighbor graphs and the other Relative Neighborhood Graphs to accomplish the task.

Keywords: Machine learning, data mining, support vector machines, proximity graphs, relative-neighborhood graphs, k-nearestneighbor graphs, random sampling, training data condensation.

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Authors: S. Kamyabi, M. Salari, H. Shahabi

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One of the processes of slope that occurs every year in Iran and some parts of world and cause a lot of criminal and financial harms is called landslide. They are plenty of method to stability landslide in soil and rock slides. The use of the best method with the least cost and in the shortest time is important for researchers. In this research, determining the best method of stability is investigated by using of Decision Support systems. DSS is made for this purpose and was used (for Hasan Salaran area in Kurdistan). Field study data from topography, slope, geology, geometry of landslide and the related features was used. The related data entered decision making managements programs (DSS) (ALES).Analysis of mass stability indicated the instability potential at present. Research results show that surface and sub surface drainage the best method of stabilizing. Analysis of stability shows that acceptable increase in security coefficient is a consequence of drainage.

Keywords: Landslide, Decision Support systems, stability, Hasan Salaran landslide, Kurdistan province, Iran.

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Authors: Ismail Karaca, Ridvan Saracoglu, Omer Soner

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Fuzzy Logic, an advanced method to support decision-making, is used by various scientists in many disciplines. Fuzzy programming is a product of fuzzy logic, fuzzy rules, and implication. In marine science, fuzzy programming for ships is dramatically increasing together with autonomous ship studies. In this paper, a program to support the decision-making process for ship navigation has been designed. The program is produced in fuzzy logic and rules, by taking the marine accidents and expert opinions into account. After the program was designed, the program was tested by 46 ship accidents reported by the Transportation Safety Investigation Center of Turkey. Wind speed, sea condition, visibility, day/night ratio have been used as input data. They have been converted into a risk factor within the Fuzzy Logic Designer application and fuzzy rules set by marine experts. Finally, the expert's meteorological risk factor for each accident is compared with the program's risk factor, and the error rate was calculated. The main objective of this study is to improve the navigational safety of ships, by using the advance decision support model. According to the study result, fuzzy programming is a robust model that supports safe navigation.

Keywords: Calculation of risk factor, fuzzy logic, fuzzy programming for ship, safe navigation of ships.

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Authors: T. Alghamdi, G. Alaghband

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In this paper we develop a model that couples Two Concurrent Convolution Neural Network with different filters (TC*CNN) for face recognition and compare its performance to an existing sequential CNN (base model). We also test and compare the quality and performance of the models on three datasets with various levels of complexity (easy, moderate, and difficult) and show that for the most complex datasets, edges will produce the most accurate and efficient results. We further show that in such cases while Support Vector Machine (SVM) models are fast, they do not produce accurate results.

Keywords: Convolution neural network, edges, face recognition, support vector machine.

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Authors: H. Omrani, P. Gerber

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Success is a European project that will implement several clean transport offers in three European cities and evaluate the environmental impacts. The goal of these measures is to improve urban mobility or the displacement of residents inside cities. For e.g. park and ride, electric vehicles, hybrid bus and bike sharing etc. A list of 28 criteria and 60 measures has been established for evaluation of these transport projects. The evaluation criteria can be grouped into: Transport, environment, social, economic and fuel consumption. This article proposes a decision support system based that encapsulates a hybrid approach based on fuzzy logic, multicriteria analysis and belief theory for the evaluation of impacts of urban mobility solutions. A web-based tool called DeSSIA (Decision Support System for Impacts Assessment) has been developed that treats complex data. The tool has several functionalities starting from data integration (import of data), evaluation of projects and finishes by graphical display of results. The tool development is based on the concept of MVC (Model, View, and Controller). The MVC is a conception model adapted to the creation of software's which impose separation between data, their treatment and presentation. Effort is laid on the ergonomic aspects of the application. It has codes compatible with the latest norms (XHTML, CSS) and has been validated by W3C (World Wide Web Consortium). The main ergonomic aspect focuses on the usability of the application, ease of learning and adoption. By the usage of technologies such as AJAX (XML and Java Script asynchrones), the application is more rapid and convivial. The positive points of our approach are that it treats heterogeneous data (qualitative, quantitative) from various information sources (human experts, survey, sensors, model etc.).

Keywords: Decision support tool, hybrid approach, urban mobility.

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Authors: Iyad F. Jafar, Sandra J. Alrawashdeh, Ban K. Alhamayel

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High level synthesis (HLS) is a process which generates register-transfer level design for digital systems from behavioral description. There are many HLS algorithms and commercial tools. However, most of these algorithms consider a behavioral description for the system when a single token is presented to the system. This approach does not exploit extra hardware efficiently, especially in the design of digital filters where common operations may exist between successive tokens. In this paper, we modify the behavioral description to process multiple tokens in parallel. However, this approach is unlike the full processing that requires full hardware replication. It exploits the presence of common operations between successive tokens. The performance of the proposed approach is better than sequential processing and approaches that of full parallel processing as the hardware resources are increased.

Keywords: Digital filters, High level synthesis, Sub-token forwarding

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