Search results for: hybrid PSO-GA algorithm and mutual information

Authors: Mahdi Fakoor, Seyed Mohammad Navid Ghoreishi

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Composite patching is a common way for reinforcing the cracked pipes and cylinders. The effects of composite patch reinforcement on fracture parameters of a cracked pipe depend on a variety of parameters such as number of layers, angle, thickness, and material of each layer. Therefore, stacking sequence optimization of composite patch becomes crucial for the applications of cracked pipes. In this study, in order to obtain the optimal stacking sequence for a composite patch that has minimum weight and maximum resistance in propagation of cracks, a coupled Multi-Objective Genetic Algorithm (MOGA) and Finite Element Method (FEM) process is proposed. This optimization process has done for longitudinal and transverse semi-elliptical cracks and optimal stacking sequences and Pareto’s front for each kind of cracks are presented. The proposed algorithm is validated against collected results from the existing literature.

Keywords: multi objective optimization, pareto front, composite patch, cracked pipe

Procedia PDF Downloads 312

Authors: K. Thiagarajan, K. Saranya, A. Veeraiah, B. Sudha

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This paper presents a novel algorithm for secure, reliable and flexible transmission of big data in two hop wireless networks using cooperative jamming scheme. Two hop wireless networks consist of source, relay and destination nodes. Big data has to transmit from source to relay and from relay to destination by deploying security in physical layer. Cooperative jamming scheme determines transmission of big data in more secure manner by protecting it from eavesdroppers and malicious nodes of unknown location. The novel algorithm that ensures secure and energy balance transmission of big data, includes selection of data transmitting region, segmenting the selected region, determining probability ratio for each node (capture node, non-capture and eavesdropper node) in every segment, evaluating the probability using binary based evaluation. If it is secure transmission resume with the two- hop transmission of big data, otherwise prevent the attackers by cooperative jamming scheme and transmit the data in two-hop transmission.

Keywords: big data, two-hop transmission, physical layer wireless security, cooperative jamming, energy balance

Procedia PDF Downloads 490

Authors: Xiuying Wang, Changliang Li, Bo Xu

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A fixed-length feature vector is required for many machine learning algorithms in NLP field. Word embeddings have been very successful at learning lexical information. However, they cannot capture the compositional meaning of sentences, which prevents them from a deeper understanding of language. In this paper, we introduce a novel hierarchical tree long short-term memory (HTLSTM) model that learns vector representations for sentences of arbitrary syntactic type and length. We propose to split one sentence into three hierarchies: short phrase, long phrase and full sentence level. The HTLSTM model gives our algorithm the potential to fully consider the hierarchical information and long-term dependencies of language. We design the experiments on both English and Chinese corpus to evaluate our model on sentiment analysis task. And the results show that our model outperforms several existing state of the art approaches significantly.

Keywords: deep learning, hierarchical tree long short-term memory, sentence representation, sentiment analysis

Procedia PDF Downloads 349

Authors: Amir Mohtarami, Hadi Kandjani

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The amount of business-critical information in enterprises is growing at an extraordinary rate, and the ability to catalog that information and properly protect it using traditional security mechanisms is not keeping pace. Alongside the Information Technology (IT), information security needs a holistic view in enterprise. In other words, a comprehensive architectural approach is required, focusing on the information itself, understanding what the data are, who owns it, and which business and regulatory policies should be applied to the information. Enterprise Architecture Frameworks provide useful tools to grasp different dimensions of IT in organizations. Usually this is done by the layered views on IT architecture, but not requisite security attention has been held in this frameworks. In this paper, after a brief look at the Enterprise Architecture (EA), we discuss the issue of security in the overall enterprise IT architecture. Due to the increasing importance of security, a rigorous EA program in an enterprise should be able to consider security architecture as an integral part of its processes and gives a visible roadmap and blueprint for this aim.

Keywords: enterprise architecture, architecture framework, security architecture, information systems

Procedia PDF Downloads 704

Authors: Misrak Assefa

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The Amharic language is the second most widely spoken Semitic language in the world. There are several new overloaded on the web. Searching some useful documents from the web on a specific topic, which is written in the Amharic language, is a challenging task. Hence, document categorization is required for managing and filtering important information. In the classification of Amharic text news, there is still a gap in the domain of information that needs to be launch. This study attempts to design an automatic Amharic news classification using a supervised learning mechanism on four un-touch classes. To achieve this research, 4,182 news articles were used. Naive Bayes (NB) and Decision tree (j48) algorithms were used to classify the given Amharic dataset. In this paper, k-fold cross-validation is used to estimate the accuracy of the classifier. As a result, it shows those algorithms can be applicable in Amharic news categorization. The best average accuracy result is achieved by j48 decision tree and naïve Bayes is 95.2345 %, and 94.6245 % respectively using three categories. This research indicated that a typical decision tree algorithm is more applicable to Amharic news categorization.

Keywords: text categorization, supervised machine learning, naive Bayes, decision tree

Procedia PDF Downloads 210

Authors: Seongsoo Lee

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IP reuse is an effective design methodology for modern SoC design to reduce effort and time. However, description and modeling methods of IP interfaces are different due to different IP designers. In this paper, standardized description and modeling methods of IP interfaces are proposed. It consists of 11 items such as IP information, model provision, data type, description level, interface information, port information, signal information, protocol information, modeling level, modeling information, and source file. The proposed description and modeling methods enables easy understanding, simulation, verification, and modification in IP reuse.

Keywords: interface, standardization, description, modeling, semiconductor IP

Procedia PDF Downloads 502

Authors: Pogula Rakesh, T. Kishore Kumar

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Speech enhancement is a long standing problem with numerous applications like teleconferencing, VoIP, hearing aids, and speech recognition. The motivation behind this research work is to obtain a clean speech signal of higher quality by applying the optimal noise cancellation technique. Real-time adaptive filtering algorithms seem to be the best candidate among all categories of the speech enhancement methods. In this paper, we propose a speech enhancement method based on Recursive Least Squares (RLS) adaptive filter of speech signals. Experiments were performed on noisy data which was prepared by adding AWGN, Babble and Pink noise to clean speech samples at -5dB, 0dB, 5dB, and 10dB SNR levels. We then compare the noise cancellation performance of proposed RLS algorithm with existing NLMS algorithm in terms of Mean Squared Error (MSE), Signal to Noise ratio (SNR), and SNR loss. Based on the performance evaluation, the proposed RLS algorithm was found to be a better optimal noise cancellation technique for speech signals.

Keywords: adaptive filter, adaptive noise canceller, mean squared error, noise reduction, NLMS, RLS, SNR, SNR loss

Procedia PDF Downloads 481

Authors: Avantika Vats, Kushal Thakur

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This paper displays the point at issue, improvement, and utilization of a Monarch Butterfly Optimization (MBO) rather than a Genetic Algorithm (GA) in cognitive radio for the channel portion. This approach offers a satisfactory approach to get the accessible range of both the users, i.e., primary users (PUs) and secondary users (SUs). The proposed enhancement procedure depends on a nature-inspired metaheuristic algorithm. In MBO, all the monarch butterfly individuals are located in two distinct lands, viz. Southern Canada and the northern USA (land 1), and Mexico (Land 2). The positions of the monarch butterflies are modernizing in two ways. At first, the offsprings are generated (position updating) by the migration operator and can be adjusted by the migration ratio. It is trailed by tuning the positions for different butterflies by the methods for the butterfly adjusting operator. To keep the population unaltered and minimize fitness evaluations, the aggregate of the recently produced butterflies in these two ways stays equivalent to the first population. The outcomes obviously display the capacity of the MBO technique towards finding the upgraded work values on issues regarding the genetic algorithm.

Keywords: cognitive radio, channel allocation, monarch butterfly optimization, evolutionary, computation

Procedia PDF Downloads 73

Authors: Zhi Liu, Hui Jiang, Jin Li, Kunhao Chen, Langfang Zhang

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Fast acquisition of the seismic information and accurate assessment of the earthquake disaster is the key problem for emergency rescue after a destructive earthquake. In order to meet the requirements of the earthquake emergency response and rescue for the cities and counties, a quasi real-time comprehensive evaluation system for earthquake disaster is developed. Based on monitoring data of Micro-Electro-Mechanical Systems (MEMS) strong motion network, structure database of a county area and the real-time disaster information by the mobile terminal after an earthquake, fragility analysis method and dynamic correction algorithm are synthetically obtained in the developed system. Real-time evaluation of the seismic disaster in the county region is finally realized to provide scientific basis for seismic emergency command, rescue and assistant decision.

Keywords: quasi real-time, earthquake disaster data collection, MEMS accelerometer, dynamic correction, comprehensive evaluation

Procedia PDF Downloads 213

Authors: Gizem Arslan Özgen, Kutay Yücetürk, Metin Tanoğlu, Engin Aktaş

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Power transmitted from the engine to the final drive where useful work is applied through a system consisting of a gearbox, clutch, drive shaft and a differential in the rear-wheel-drive automobiles. It is well-known that the steel drive shaft is usually manufactured in two pieces to increase the fundamental bending natural frequency to ensure safe operation conditions. In this work, hybrid one-piece propeller shafts composed of carbon/epoxy and glass/epoxy composites have been designed for a rear wheel drive automobile satisfying three design specifications, such as static torque transmission capability, torsional buckling and the fundamental natural bending frequency. Hybridization of carbon and glass fibers is being studied to optimize the cost/performance requirements. Composites shaft materials with various fiber orientation angles and stacking sequences are being fabricated and analyzed using finite element analysis (FEA).

Keywords: composite propeller shaft, hybridization, epoxy matrix, static torque transmission capability, torsional buckling strength, fundamental natural bending frequency.

Procedia PDF Downloads 270

Authors: P. V. Krupakara

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This paper deals with the high corrosion resistance developed by the hybrid metal matrix composites when compared with that of matrix alloy. Matrix selected is Al6061. Reinforcements selected are graphite and red mud particulates. The composites are prepared using liquid melt metallurgy technique using vortex method. Metal matrix composites containing 2 percent graphite and 2 percent red mud, 2 percent graphite and 4 percent red mud, 2 percent graphite and 6 percent of red mud are prepared. Bar castings are cut into cylindrical discs of 20mm diameter and 20mm thickness. Corrosion tests were conducted at room temperature (230 °C) using conventional weight loss method according to ASTM G69-80. The corrodents used for the test were hydrochloric acid solution of different concentrations. Specimens were tested for every 24 hours interval up to 96 hours. Four specimens for each condition and time were immersed in corrodent. In each case the corrosion rate decreases with increase in exposure time for matrix and metal matrix composites whatever may be the concentration of hydrochloric acid. This may be due to aluminium, which may induce passivation due to development of non-porous layer. As red mud content increases the composites become corrosion resistant due to insulating nature of ceramic material red mud and less exposure of matrix alloy in those metal matrix composites.

Keywords: Al6061, graphite, passivation, red mud, vortex

Procedia PDF Downloads 542

Authors: Ehsan Saghehei, Mahdi Eghbali

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The maximal covering location problem (MCLP) was originally developed to determine a set of facility locations which would maximize the total customers' demand serviced by the facilities within a predetermined critical service criterion. However, on some problems that differences between the demand nodes are covered or the number of nodes each node is large, the method of solving MCLP may ignore these differences. In this paper, Heuristic solution based on the ranking of demands in each node and the number of nodes covered by each node according to a predetermined critical value is proposed. The output of this method is to maximize total demands of nodes and number of covered nodes, simultaneously. Furthermore, by providing an example, the solution algorithm is described and its results are compared with Greedy and Lagrange algorithms. Also, the results of the algorithm to solve the larger problem sizes that compared with other methods are provided. A summary and future works conclude the paper.

Keywords: heuristic solution, maximal covering location problem, ranking, set covering

Procedia PDF Downloads 573

Authors: Khuram Shahzad, Omar Usman Khan

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Quantum bit string comparators (QBSC) operate on two sequences of n-qubits, enabling the determination of their relationships, such as equality, greater than, or less than. This is analogous to the way conditional statements are used in programming languages. Consequently, QBSCs play a crucial role in various algorithms that can be executed or adapted for quantum computers. The development of efficient and generalized comparators for any n-qubit length has long posed a challenge, as they have a high-cost footprint and lead to quantum delays. Comparators that are efficient are associated with inputs of fixed length. As a result, comparators without a generalized circuit cannot be employed at a higher level, though they are well-suited for problems with limited size requirements. In this paper, we introduce a generalized design for the comparison of two n-qubit logic states using just two ancillary bits. The design is examined on the basis of qubit requirements, ancillary bit usage, quantum cost, quantum delay, gate operations, and circuit complexity and is tested comprehensively on various input lengths. The work allows for sufficient flexibility in the design of quantum algorithms, which can accelerate quantum algorithm development.

Keywords: quantum comparator, quantum algorithm, space-efficient comparator, comparator

Procedia PDF Downloads 15

Authors: Aya Al Masri, Naima Oubenali, Safoin Aktaou, Thibault Julien, Malorie Martin, Fouad Maaloul

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Introduction: The increased number of performed 'Computed Tomography (CT)' examinations raise public concerns regarding associated stochastic risk to patients. In its Publication 102, the ‘International Commission on Radiological Protection (ICRP)’ emphasized the importance of managing patient dose, particularly from repeated or multiple examinations. We developed a Dose Archiving and Communication System that gives multiple dose indexes (organ dose, effective dose, and skin-dose mapping) for patients undergoing radiological imaging exams. The aim of this study is to compare the organ dose values given by our software for patients undergoing CT exams with those of another software named "VirtualDose". Materials and methods: Our software uses Monte Carlo simulations to calculate organ doses for patients undergoing computed tomography examinations. The general calculation principle consists to simulate: (1) the scanner machine with all its technical specifications and associated irradiation cases (kVp, field collimation, mAs, pitch ...) (2) detailed geometric and compositional information of dozens of well identified organs of computational hybrid phantoms that contain the necessary anatomical data. The mass as well as the elemental composition of the tissues and organs that constitute our phantoms correspond to the recommendations of the international organizations (namely the ICRP and the ICRU). Their body dimensions correspond to reference data developed in the United States. Simulated data was verified by clinical measurement. To perform the comparison, 270 adult patients and 150 pediatric patients were used, whose data corresponds to exams carried out in France hospital centers. The comparison dataset of adult patients includes adult males and females for three different scanner machines and three different acquisition protocols (Head, Chest, and Chest-Abdomen-Pelvis). The comparison sample of pediatric patients includes the exams of thirty patients for each of the following age groups: new born, 1-2 years, 3-7 years, 8-12 years, and 13-16 years. The comparison for pediatric patients were performed on the “Head” protocol. The percentage of the dose difference were calculated for organs receiving a significant dose according to the acquisition protocol (80% of the maximal dose). Results: Adult patients: for organs that are completely covered by the scan range, the maximum percentage of dose difference between the two software is 27 %. However, there are three organs situated at the edges of the scan range that show a slightly higher dose difference. Pediatric patients: the percentage of dose difference between the two software does not exceed 30%. These dose differences may be due to the use of two different generations of hybrid phantoms by the two software. Conclusion: This study shows that our software provides a reliable dosimetric information for patients undergoing Computed Tomography exams.

Keywords: adult and pediatric patients, computed tomography, organ dose calculation, software comparison

Procedia PDF Downloads 162

Authors: Chih-Hsiang Chang, Pei-Shan Kao

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This paper discusses the reaction of investors in the Taiwan stock market to the most probable unknown earnings-related information and the most probable known earnings-related information. As compared with the previous literature regarding the effect of an official announcement of earnings forecast revision, this paper further analyzes investors’ cognitive bias toward the unknown and known earnings-related information, and the role of media during the investors' reactions to the foresaid information shocks. The empirical results show that both the unknown and known earnings-related information provides useful information content for a stock market. In addition, cognitive bias and disposition effect are the behavioral pitfalls that commonly occur in the process of the investors' reactions to the earnings-related information. Finally, media coverage has a remarkable influence upon the investors' trading decisions.

Keywords: cognitive bias, role of media, disposition effect, earnings-related information, behavioral pitfall

Procedia PDF Downloads 224

Authors: O. Adjoul, A. Feugier, K. Benfriha, A. Aoussat

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In general, issues related to design and maintenance are considered in an independent manner. However, the decisions made in these two sets influence each other. The design for maintenance is considered an opportunity to optimize the life cycle cost of a product, particularly in the nuclear or aeronautical field, where maintenance expenses represent more than 60% of life cycle costs. The design of large-scale systems starts with product architecture, a choice of components in terms of cost, reliability, weight and other attributes, corresponding to the specifications. On the other hand, the design must take into account maintenance by improving, in particular, real-time monitoring of equipment through the integration of new technologies such as connected sensors and intelligent actuators. We noticed that different approaches used in the Design For Maintenance (DFM) methods are limited to the simultaneous characterization of the reliability and maintainability of a multi-component system. This article proposes a method of DFM that assists designers to propose dynamic maintenance for multi-component industrial systems. The term "dynamic" refers to the ability to integrate available monitoring data to adapt the maintenance decision in real time. The goal is to maximize the availability of the system at a given life cycle cost. This paper presents an approach for simultaneous optimization of the design and maintenance of multi-component systems. Here the design is characterized by four decision variables for each component (reliability level, maintainability level, redundancy level, and level of monitoring data). The maintenance is characterized by two decision variables (the dates of the maintenance stops and the maintenance operations to be performed on the system during these stops). The DFM model helps the designers choose technical solutions for the large-scale industrial products. Large-scale refers to the complex multi-component industrial systems and long life-cycle, such as trains, aircraft, etc. The method is based on a two-level hybrid algorithm for simultaneous optimization of design and maintenance, using genetic algorithms. The first level is to select a design solution for a given system that considers the life cycle cost and the reliability. The second level consists of determining a dynamic and optimal maintenance plan to be deployed for a design solution. This level is based on the Maintenance Free Operating Period (MFOP) concept, which takes into account the decision criteria such as, total reliability, maintenance cost and maintenance time. Depending on the life cycle duration, the desired availability, and the desired business model (sales or rental), this tool provides visibility of overall costs and optimal product architecture.

Keywords: availability, design for maintenance (DFM), dynamic maintenance, life cycle cost (LCC), maintenance free operating period (MFOP), simultaneous optimization

Procedia PDF Downloads 118

Authors: Ajish Sreedharan

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Security in transmission and storage of digital images has its importance in today’s image communications and confidential video conferencing. Due to the increasing use of images in industrial process, it is essential to protect the confidential image data from unauthorized access. Advanced Encryption Standard (AES) is a well known block cipher that has several advantages in data encryption. However, it is not suitable for real-time applications. This paper presents modifications to the Advanced Encryption Standard to reflect a high level security and better image encryption. The modifications are done by adjusting the ShiftRow Transformation and using On Dynamic chaotic S-BOX. In AES the Substitute bytes, Shift row and Mix columns by themselves would provide no security because they do not use the key. In Dynamic chaotic S-BOX Based AES the Substitute bytes provide security because the S-Box is constructed from the key. Experimental results verify and prove that the proposed modification to image cryptosystem is highly secure from the cryptographic viewpoint. The results also prove that with a comparison to original AES encryption algorithm the modified algorithm gives better encryption results in terms of security against statistical attacks.

Keywords: advanced encryption standard (AES), on dynamic chaotic S-BOX, image encryption, security analysis, ShiftRow transformation

Procedia PDF Downloads 437

Authors: Hoyeon Park, Yunhwan Keon, Kyoung-Jae Kim

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Location Based Social Network services (LBSNs) is a new term that combines location based service and social network service (SNS). Unlike traditional SNS, LBSNs emphasizes empirical elements in the user's actual physical location. Point-of-Interest (POI) is the most important factor to implement LBSNs recommendation system. POI information is the most popular spot in the area. In this study, we would like to recommend POI to users in a specific area through recommendation system using collaborative filtering. The process is as follows: first, we will use different data sets based on Seoul and New York to find interesting results on human behavior. Secondly, based on the location-based activity information obtained from the personalized LBSNs, we have devised a new rating that defines the user's preference for the area. Finally, we have developed an automated rating algorithm from massive raw data using distributed systems to reduce advertising costs of LBSNs.

Keywords: location-based social network services, point-of-interest, recommender systems, business analytics

Procedia PDF Downloads 229

Authors: L. Major, J. M. Lackner, M. Dyner, B. Major

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Development of new generation bio- tribological, multilayer coatings, opens an avenue for fabrication of future high- tech functional surfaces. In the presented work, nano- composite, Cr/CrN+[Cr/ a-C:H implanted by metallic nanocrystals] multilayer coatings have been developed for surface protection of medical tools. Thin films were fabricated by a hybrid Pulsed Laser Deposition technique. Complex microstructure analysis of nano- multilayer coatings, subjected to mechanical and biological tests, were performed by means of transmission electron microscopy (TEM). Microstructure characterization revealed the layered arrangement of Cr23C6 nanoparticles in multilayer structure. Influence of deposition conditions on bio- tribological properties of the coatings were studied. The bio-tests were used as a screening tool for the analyzed nano- multilayer coatings before they could be deposited on medical tools. Bio- medical tests were done using fibroblasts. The mechanical properties of the coatings were investigated by means of a ball-on-disc mechanical test. The microhardness was done using Berkovich indenter. The scratch adhesion test was done using Rockwell indenter. From the bio- tribological point of view, the optimal properties had the C106_1 material.

Keywords: bio- tribological coatings, cell- material interaction, hybrid PLD, tribology

Procedia PDF Downloads 380

Authors: Shaharuddin Salleh, Sara Marouf, Hosein Mohammadi

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Directional sensor networks (DSNs) have recently attracted a great deal of attention due to their extensive applications in a wide range of situations. One of the most important problems associated with DSNs is covering a set of targets in a given area and, at the same time, maximizing the network lifetime. This is due to limitation in sensing angle and battery power of the directional sensors. This problem gets more complicated by the possibility that targets may have different coverage requirements. In the present study, this problem is referred to as priority-based target coverage (PTC). As sensors are often densely deployed, organizing the sensors into several cover sets and then activating these cover sets successively is a promising solution to this problem. In this paper, we propose a learning automata-based algorithm to organize the directional sensors into several cover sets in such a way that each cover set could satisfy coverage requirements of all the targets. Several experiments are conducted to evaluate the performance of the proposed algorithm. The results demonstrated that the algorithms were able to contribute to solving the problem.

Keywords: directional sensor networks, target coverage problem, cover set formation, learning automata

Procedia PDF Downloads 414

Authors: Jyoti Bharti, M. K. Gupta, Astha Jain

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This paper proposes a new improved approach for false positives filtering of detected face images on OpenCV’s Viola Jones Algorithm In this approach, for Filtering of False Positives, Skin Detection in two colour spaces i.e. HSV (Hue, Saturation and Value) and YCrCb (Y is luma component and Cr- red difference, Cb- Blue difference) is used. As a result, it is found that false detection has been reduced. Our proposed method reaches the accuracy of about 98.7%. Thus, a better recognition rate is achieved.

Keywords: face detection, Viola Jones, false positives, OpenCV

Procedia PDF Downloads 407

Authors: Imen Elleuch, Wael Ouarda, Gargouri Bilel

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We proposes in this paper a Deep Learning based approach to classify text in order to enrich an Arabic ontology based on the objects classes of Gaston Gross. Those object classes are defined by taking into account the syntactic and semantic features of the treated language. Thus, our proposed approach is a hybrid one. In fact, it is based on the one hand on the object classes that represents a knowledge based-approach on classification of text and in the other hand it uses the deep learning approach that use the word embedding-based-approach to classify text. We have applied our proposed approach on a corpus constructed from an Arabic dictionary. The obtained semantic classification of text will enrich the Arabic objects classes ontology. In fact, new classes can be added to the ontology or an expansion of the features that characterizes each object class can be updated. The obtained results are compared to a similar work that treats the same object with a classical linguistic approach for the semantic classification of text. This comparison highlight our hybrid proposed approach that can be ameliorated by broaden the dataset used in the deep learning process.

Keywords: deep-learning approach, object-classes, semantic classification, Arabic

Procedia PDF Downloads 88

Authors: Y. Mehdipour, S. Ebrahimi, A. Jahanpour, F. Seyedzaei, B. Sabayan, A. Karimi, H. Amirifard

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Ischemic stroke is one of the common reasons for disability and mortality. The fourth leading cause of death in the world and the third in some other sources. Only 1/3 of the patients with ischemic stroke fully recover, 1/3 of them end in permanent disability and 1/3 face death. Thus, the use of predictive models to predict stroke has a vital role in reducing the complications and costs related to this disease. Thus, the aim of this study was to specify the effective factors and predict ischemic stroke with the help of DM methods. The present study was a descriptive-analytic study. The population was 213 cases from among patients referring to Ali ibn Abi Talib (AS) Hospital in Zahedan. Data collection tool was a checklist with the validity and reliability confirmed. This study used DM algorithms of decision tree for modeling. Data analysis was performed using SPSS-19 and SPSS Modeler 14.2. The results of the comparison of algorithms showed that CHAID algorithm with 95.7% accuracy has the best performance. Moreover, based on the model created, factors such as anemia, diabetes mellitus, hyperlipidemia, transient ischemic attacks, coronary artery disease, and atherosclerosis are the most effective factors in stroke. Decision tree algorithms, especially CHAID algorithm, have acceptable precision and predictive ability to determine the factors affecting ischemic stroke. Thus, by creating predictive models through this algorithm, will play a significant role in decreasing the mortality and disability caused by ischemic stroke.

Keywords: data mining, ischemic stroke, decision tree, Bayesian network

Procedia PDF Downloads 174

Authors: Sadegh Sadeghi, Negar Shabani

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From a thermal point of view, zeotropic mixtures are likely to be more efficient than azeotropic fluids in low-temperature thermodynamic cycles due to their suitable boiling characteristics. In this study, performance of a low-temperature Kalina cycle with R717/water working fluid used in different existing power plants is mathematically investigated. To analyze the behavior of the cycle, mass conservation, energy conservation, and exergy balance equations are presented. With regard to the similarity in molar mass of R717 (17.03 gr/mol) and water (18.01 gr/mol), there is no need to alter the size of Kalina system components such as turbine and pump. To optimize the cycle energy and exergy efficiencies simultaneously, a constrained multi-objective optimization is carried out applying an Artificial Bee Colony algorithm. The main motivation behind using this algorithm lies on its robustness, reliability, remarkable precision and high–speed convergence rate in dealing with complicated constrained multi-objective problems. Convergence rates of the algorithm for calculating the optimal energy and exergy efficiencies are presented. Subsequently, due to the importance of exergy concept in Kalina cycles, exergy destructions occurring in the components are computed. Finally, the impacts of pressure, temperature, mass fraction and mass flow rate on the energy and exergy efficiencies are elaborately studied.

Keywords: artificial bee colony algorithm, binary zeotropic mixture, constrained multi-objective optimization, energy efficiency, exergy efficiency, Kalina cycle

Procedia PDF Downloads 153

Authors: David Tresner-Kirsch

Abstract:

Reconciling patient medication lists from multiple sources is a critical task supporting the safe delivery of patient care. Manual reconciliation is a time-consuming and error-prone process, and recently attempts have been made to develop efficiency- and safety-oriented automated support for professionals performing the task. An important capability of any such support system is automated alignment – finding which medications from a list correspond to which medications from a different source, regardless of misspellings, naming differences (e.g. brand name vs. generic), or changes in treatment (e.g. switching a patient from one antidepressant class to another). This work describes a new algorithmic solution to this alignment task, using a greedy matching approach based on string similarity, edit distances, concept extraction and normalization, and synonym search derived from the RxNorm nomenclature. The accuracy of this algorithm was evaluated against a gold-standard corpus of 681 medication records; this evaluation found that the algorithm predicted alignments with 99% precision and 91% recall. This performance is sufficient to support decision support applications for medication reconciliation.

Keywords: clinical decision support, medication reconciliation, natural language processing, RxNorm

Procedia PDF Downloads 285

Authors: Ariq Bani Hardi

Abstract:

Empowerment of smartphone technology is growing very rapidly in various fields of science. One of the mobile operating systems that dominate the smartphone market today is Android by Google. Unfortunately, the expansion of mobile technology is misused by criminals to hide the information that they store or exchange with each other. It makes law enforcement more difficult to prove crimes committed in the judicial process (anti-forensic). One of technique that used to hide the information is encryption, such as the usages of SMS encryption applications. A Mobile Forensic Examiner or an investigator should prepare a countermeasure technique if he finds such things during the investigation process. This paper will discuss an extension procedure if the investigator found unreadable SMS in android evidence because of encryption. To define the extended procedure, we create and analyzing a dataset of android SMS encryption application. The dataset was grouped by application characteristics related to communication permissions, as well as the availability of source code and the documentation of encryption scheme. Permissions indicate the possibility of how applications exchange the data and keys. Availability of the source code and the encryption scheme documentation can show what the cryptographic algorithm specification is used, how long the key length, how the process of key generation, key exchanges, encryption/decryption is done, and other related information. The output of this paper is an extended or alternative procedure for examination and analysis process of android digital forensic. It can be used to help the investigators while they got a confused cause of SMS encryption during examining and analyzing. What steps should the investigator take, so they still have a chance to discover the encrypted SMS in android evidence?

Keywords: anti-forensic countermeasure, SMS encryption android, examination and analysis, digital forensic

Procedia PDF Downloads 127

Authors: Heramb Somthankar, Anujoy Chakraborty

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This paper presents a classification study on yield prediction in semiconductor production using machine learning approaches. A complicated semiconductor production process is generally monitored continuously by signals acquired from sensors and measurement sites. A monitoring system contains a variety of signals, all of which contain useful information, irrelevant information, and noise. In the case of each signal being considered a feature, "Feature Selection" is used to find the most relevant signals. The open-source UCI SECOM Dataset provides 1567 such samples, out of which 104 fail in quality assurance. Feature extraction and selection are performed on the dataset, and useful signals were considered for further study. Afterward, common machine learning algorithms were employed to predict whether the signal yields pass or fail. The most relevant algorithm is selected for prediction based on the accuracy and loss of the ML model.

Keywords: deep learning, feature extraction, feature selection, machine learning classification algorithms, semiconductor production monitoring, signal processing, time-series analysis

Procedia PDF Downloads 109

Authors: Yury S. Shpanskiy, Boris V. Kuteev

Abstract:

Development of a fusion-fission hybrid facility based on superconducting conventional tokamak DEMO-FNS runs in Russia since 2013. The main design goal is to reach the technical feasibility and outline prospects of industrial hybrid technologies providing the production of neutrons, fuel nuclides, tritium, high-temperature heat, electricity and subcritical transmutation in Fusion-Fission Hybrid Systems. The facility should operate in a steady-state mode at the fusion power of 40 MW and fission reactions of 400 MW. Major tokamak parameters are the following: major radius R=3.2 m, minor radius a=1.0 m, elongation 2.1, triangularity 0.5. The design provides the neutron wall loading of ~0.2 MW/m², the lifetime neutron fluence of ~2 MWa/m², with the surface area of the active cores and tritium breeding blanket ~100 m². Core plasma modelling showed that the neutron yield ~10¹⁹ n/s is maximal if the tritium/deuterium density ratio is 1.5-2.3. The design of the electromagnetic system (EMS) defined its basic parameters, accounting for the coils strength and stability, and identified the most problematic nodes in the toroidal field coils and the central solenoid. The EMS generates toroidal, poloidal and correcting magnetic fields necessary for the plasma shaping and confinement inside the vacuum vessel. EMC consists of eighteen superconducting toroidal field coils, eight poloidal field coils, five sections of a central solenoid, correction coils, in-vessel coils for vertical plasma control. Supporting structures, the thermal shield, and the cryostat maintain its operation. EMS operates with the pulse duration of up to 5000 hours at the plasma current up to 5 MA. The vacuum vessel (VV) is an all-welded two-layer toroidal shell placed inside the EMS. The free space between the vessel shells is filled with water and boron steel plates, which form the neutron protection of the EMS. The VV-volume is 265 m³, its mass with manifolds is 1800 tons. The nuclear blanket of DEMO-FNS facility was designed to provide functions of minor actinides transmutation, tritium production and enrichment of spent nuclear fuel. The vertical overloading of the subcritical active cores with MA was chosen as prospective. Analysis of the device neutronics and the hybrid blanket thermal-hydraulic characteristics has been performed for the system with functions covering transmutation of minor actinides, production of tritium and enrichment of spent nuclear fuel. A study of FNS facilities role in the Russian closed nuclear fuel cycle was performed. It showed that during ~100 years of operation three FNS facilities with fission power of 3 GW controlled by fusion neutron source with power of 40 MW can burn 98 tons of minor actinides and 198 tons of Pu-239 can be produced for startup loading of 20 fast reactors. Instead of Pu-239, up to 25 kg of tritium per year may be produced for startup of fusion reactors using blocks with lithium orthosilicate instead of fissile breeder blankets.

Keywords: fusion-fission hybrid system, conventional tokamak, superconducting electromagnetic system, two-layer vacuum vessel, subcritical active cores, nuclear fuel cycle

Procedia PDF Downloads 147

Authors: Dora Triki, Irena Vida, Claude Obadia

Abstract:

Social networks such as e-Forums or dating sites often face the reluctance of key members to participate. Relying on the conation theory, this study investigates this phenomenon and proposes solutions to mitigate the issue. We show that highly experienced e-Forum members refuse to share business information in a peer to peer information exchange forums. However, forums managers can mitigate this behavior by developing a sentiment of belongingness to the network. Furthermore, by selecting only elite forum participants with ample experience, they can reduce the reluctance of key information providers to engage in information exchange. Our hypotheses are tested with PLS structural equations modeling using survey data from members of a French e-Forum dedicated to the exchange of business information about exporting.

Keywords: conation, e-Forum, information exchange, members participation

Procedia PDF Downloads 158

Authors: Ayubi Wirara, Ardya Suryadinata

Abstract:

Improper application of the RSA algorithm scheme can cause vulnerability to attacks. The attack utilizes the relationship between broadcast messages sent to the user with some fixed polynomial functions that belong to each user. Scheme attacks carried out by applying the Chinese Remainder Theorem to obtain a general polynomial equation with the same modulus. The formation of the general polynomial becomes a first step to get back the original message. Furthermore, to solve these equations can use Coppersmith's theorem.

Keywords: RSA algorithm, broadcast message, Chinese Remainder Theorem, Coppersmith’s theorem

Procedia PDF Downloads 341