Search results for: Energy performance
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 7890

Search results for: Energy performance

2040 Fabrication of Autonomous Wheeled Mobile Robot for Industrial Applications Using Appropriate Technology

Authors: M. M. Islam, Rajib K. Saha, Abdullah A. Amin, M. Z. Haq

Abstract:

The autonomous mobile robot was designed and implemented which was capable of navigating in the industrial environments and did a job of picking objects from variable height and delivering it to another location following a predefined trajectory. In developing country like Bangladesh industrial robotics is not very prevalent yet, due to the high installation cost. The objective of this project was to develop an autonomous mobile robot for industrial application using the available resources in the local market at lower manufacturing cost. The mechanical system of the robot was comprised of locomotion, gripping and elevation system. Grippers were designed to grip objects of a predefined shape. Cartesian elevation system was designed for vertical movement of the gripper. PIC18F452 microcontroller was the brain of the control system. The prototype autonomous robot was fabricated for relatively lower load than the industry and the performance was tested in a virtual industrial environment created within the laboratory to realize the effectiveness.

Keywords: Industrial application, autonomous mobile robot, appropriate technology.

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2039 Shot Transition Detection with Minimal Decoding of MPEG Video Streams

Authors: Mona A. Fouad, Fatma M. Bayoumi, Hoda M. Onsi, Mohamed G. Darwish

Abstract:

Digital libraries become more and more necessary in order to support users with powerful and easy-to-use tools for searching, browsing and retrieving media information. The starting point for these tasks is the segmentation of video content into shots. To segment MPEG video streams into shots, a fully automatic procedure to detect both abrupt and gradual transitions (dissolve and fade-groups) with minimal decoding in real time is developed in this study. Each was explored through two phases: macro-block type's analysis in B-frames, and on-demand intensity information analysis. The experimental results show remarkable performance in detecting gradual transitions of some kinds of input data and comparable results of the rest of the examined video streams. Almost all abrupt transitions could be detected with very few false positive alarms.

Keywords: Adaptive threshold, abrupt transitions, gradual transitions, MPEG video streams.

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2038 Enhanced Nutrients Removal in Conventional Anaerobic Digestion Processes

Authors: M. Z. Othman, S. Uludag-Demirer, G. N. Demirer

Abstract:

One of the main challenges for one phase anaerobic digestion processes is the high concentration of NH4+ and PO4 3- ions  in the digested sludge supernatant. This project focuses on enhancing the removal of nutrients during the anaerobic digestion process through fixing both NH4+ and PO4 3- ions in the form of struvite (magnesium ammonium phosphate, MAP, MgNH4PO4.6H2O) within the anaerobic sludge. Batch anaerobic digestion tests showed that Mg2+ concentration in the range 279 – 812 mg/L had insignificant effect on CGP but incurred a slight increase in COD removal. The reactor that had soluble Mg2+:NH4+:PO43- at a molar ratio of 1.28:1:00:1:00 achieved the best performance enhancement of 8% increase in COD removal and 32% reduction in NH4+ in the reactor supernatant. Overall, the results show that there is a potential to optimise conventional anaerobic digestion such that supernatant lean in P and N, and sludge rich in nutrients are obtained. 

Keywords: Anaerobic Digestion, Nutrients, Struvite, Waste Activated Sludge (WAS)

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2037 An Innovative Wireless Sensor Network Protocol Implementation using a Hybrid FPGA Technology

Authors: Danielle Reichel, Antoine Druilhe, Tuan Dang

Abstract:

Traditional development of wireless sensor network mote is generally based on SoC1 platform. Such method of development faces three main drawbacks: lack of flexibility in terms of development due to low resource and rigid architecture of SoC; low capability of evolution and portability versus performance if specific micro-controller architecture features are used; and the rapid obsolescence of micro-controller comparing to the long lifetime of power plants or any industrial installations. To overcome these drawbacks, we have explored a new approach of development of wireless sensor network mote using a hybrid FPGA technology. The application of such approach is illustrated through the implementation of an innovative wireless sensor network protocol called OCARI.

Keywords: Hybrid FPGA, Embedded system, Mote, flexibility, durability, OCARI protocol, SoC, Wireless Sensor Network

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2036 The Different Roles between Sodium and Potassium Ions in Ion Exchange of WO3/SiO2 Catalysts

Authors: K. Pipitthapan, S. Maksasithorn, P. Praserthdam, J. Panpranot, K. Suriye, S. Kunjara Na Ayudhya

Abstract:

WO3/SiO2 catalysts were modified by an ion exchange method with sodium hydroxide or potassium hydroxide solution. The performance of the modified catalysts was tested in the metathesis of ethylene and trans-2-butene to propylene. During ion exchange, sodium and potassium ions played different roles. Sodium modified catalysts revealed constant trans-2-butene conversion and propylene selectivity when the concentrations of sodium in the solution were varied. In contrast, potassium modified catalysts showed reduction of the conversion and increase of the selectivity. From these results, potassium hydroxide may affect the transformation of tungsten oxide active species, resulting in the decrease in conversion whereas sodium hydroxide did not. Moreover, the modification of catalysts by this method improved the catalyst stability by lowering the amount of coke deposited on the catalyst surface.

Keywords: Acid sites, alkali metals, isomerization, metathesis.

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2035 Mining of Interesting Prediction Rules with Uniform Two-Level Genetic Algorithm

Authors: Bilal Alatas, Ahmet Arslan

Abstract:

The main goal of data mining is to extract accurate, comprehensible and interesting knowledge from databases that may be considered as large search spaces. In this paper, a new, efficient type of Genetic Algorithm (GA) called uniform two-level GA is proposed as a search strategy to discover truly interesting, high-level prediction rules, a difficult problem and relatively little researched, rather than discovering classification knowledge as usual in the literatures. The proposed method uses the advantage of uniform population method and addresses the task of generalized rule induction that can be regarded as a generalization of the task of classification. Although the task of generalized rule induction requires a lot of computations, which is usually not satisfied with the normal algorithms, it was demonstrated that this method increased the performance of GAs and rapidly found interesting rules.

Keywords: Classification rule mining, data mining, genetic algorithms.

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2034 A Distributed Approach to Extract High Utility Itemsets from XML Data

Authors: S. Kannimuthu, K. Premalatha

Abstract:

This paper investigates a new data mining capability that entails mining of High Utility Itemsets (HUI) in a distributed environment. Existing research in data mining deals with only presence or absence of an items and do not consider the semantic measures like weight or cost of the items. Thus, HUI mining algorithm has evolved. HUI mining is the one kind of utility mining concept, aims to identify itemsets whose utility satisfies a given threshold. Although, the approach of mining HUIs in a distributed environment and mining of the same from XML data have not explored yet. In this work, a novel approach is proposed to mine HUIs from the XML based data in a distributed environment. This work utilizes Service Oriented Computing (SOC) paradigm which provides Knowledge as a Service (KaaS). The interesting patterns are provided via the web services with the help of knowledge server to answer the queries of the consumers. The performance of the approach is evaluated on various databases using execution time and memory consumption.

Keywords: Data mining, Knowledge as a Service, service oriented computing, utility mining.

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2033 Cold Spray Deposition of SS316L Powders on Al5052 Substrates and Their Potential Using for Biomedical Applications

Authors: B. Dikici, I. Ozdemir, M. Topuz

Abstract:

The corrosion behaviour of 316L stainless steel coatings obtained by cold spray method was investigated in this study. 316L powders were deposited onto Al5052 aluminum substrates. The coatings were produced using nitrogen (N2) process gas. In order to further improve the corrosion and mechanical properties of the coatings, heat treatment was applied at 250 and 750 °C. The corrosion performances of the coatings were compared using the potentiodynamic scanning (PDS) technique under in-vitro conditions (in Ringer’s solution at 37 °C). In addition, the hardness and porosity tests were carried out on the coatings. Microstructural characterization of the coatings was carried out by using scanning electron microscopy attached with energy dispersive spectrometer (SEM-EDS) and X-ray diffraction (XRD) technique. It was found that clean surfaces and a good adhesion were achieved for particle/substrate bonding. The heat treatment process provided both elimination of the anisotropy in the coating and resulting in healing-up of the incomplete interfaces between the deposited particles. It was found that the corrosion potential of the annealed coatings at 750 °C was higher than that of commercially 316 L stainless steel. Moreover, the microstructural investigations after the corrosion tests revealed that corrosion preferentially starts at inter-splat boundaries.

Keywords: 316L, biomaterials, cold spray, heat treatment.

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2032 Native Language Identification with Cross-Corpus Evaluation Using Social Media Data: 'Reddit'

Authors: Yasmeen Bassas, Sandra Kuebler, Allen Riddell

Abstract:

Native Language Identification is one of the growing subfields in Natural Language Processing (NLP). The task of Native Language Identification (NLI) is mainly concerned with predicting the native language of an author’s writing in a second language. In this paper, we investigate the performance of two types of features; content-based features vs. content independent features when they are evaluated on a different corpus (using social media data “Reddit”). In this NLI task, the predefined models are trained on one corpus (TOEFL) and then the trained models are evaluated on a different data using an external corpus (Reddit). Three classifiers are used in this task; the baseline, linear SVM, and Logistic Regression. Results show that content-based features are more accurate and robust than content independent ones when tested within corpus and across corpus.

Keywords: NLI, NLP, content-based features, content independent features, social media corpus, ML.

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2031 Horizontal and Vertical Illuminance Correlations in a Case Study for Shaded South Facing Surfaces

Authors: S. Matour, M. Mahdavinejad, R. Fayaz

Abstract:

Daylight utilization is a key factor in achieving visual and thermal comfort, and energy savings in integrated building design. However, lack of measured data related to this topic has become a major challenge with the increasing need for integrating lighting concepts and simulations in the early stages of design procedures. The current paper deals with the values of daylight illuminance on horizontal and south facing vertical surfaces; the data are estimated using IESNA model and measured values of the horizontal and vertical illuminance, and a regression model with an acceptable linear correlation is obtained. The resultant illuminance frequency curves are useful for estimating daylight availability on south facing surfaces in Tehran. In addition, the relationship between indirect vertical illuminance and the corresponding global horizontal illuminance is analyzed. A simple parametric equation is proposed in order to predict the vertical illumination on a shaded south facing surface. The equation correlates the ratio between the vertical and horizontal illuminance to the solar altitude and is used with another relationship for prediction of the vertical illuminance. Both equations show good agreement, which allows for calculation of indirect vertical illuminance on a south facing surface at any time throughout the year.

Keywords: Tehran daylight availability, horizontal illuminance, vertical illuminance, diffuse illuminance.

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2030 Malt Bagasse Waste as Biosorbent for Malachite Green: An Ecofriendly Approach for Dye Removal from Aqueous Solution

Authors: H. C. O. Reis, A. S. Cossolin, B. A. P. Santos, K. C. Castro, G. M. Pereira, V. C. Silva, P. T. Sousa Jr, E. L. Dall’Oglio, L. G. Vasconcelos, E. B. Morais

Abstract:

In this study, malt bagasse, a low-cost waste biomass, was tested as a biosorbent to remove the cationic dye Malachite green (MG) from aqueous solution. Batch biosorption experiments were investigated as functions of different experimental parameters such as initial pH, salt (NaCl) concentration, contact time, temperature and initial dye concentration. Higher removal rates of MG were obtained at pH 8 and 10. The equilibrium and kinetic studies suggest that the biosorption follows Langmuir isotherm and the pseudo-second-order model. The maximum monolayer adsorption capacity was estimated at 117.65 mg/g (at 45 °C). According to Dubinin–Radushkevich (D-R) isotherm model, biosorption of MG onto malt bagasse occurs physically. The thermodynamic parameters such as Gibbs free energy, enthalpy and entropy indicated that the MG biosorption onto malt bagasse is spontaneous and endothermic. The results of the ionic strength effect indicated that the biosorption process under study had a strong tolerance under high salt concentrations. It can be concluded that malt bagasse waste has potential for application as biosorbent for removal of MG from aqueous solution.

Keywords: Color removal, kinetic and isotherm studies, thermodynamic parameters, FTIR.

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2029 Comparison of Inter Cell Interference Coordination Approaches

Authors: Selma Sbit, Mohamed Bechir Dadi, Belgacem Chibani Rhaimi

Abstract:

This work aims to compare various techniques used in order to mitigate Inter-Cell Interference (ICI) in Long Term Evolution (LTE) and LTE-Advanced systems. For that, we will evaluate the performance of each one. In mobile communication networks, systems are limited by ICI particularly caused by deployment of small cells in conventional cell’s implementation. Therefore, various mitigation techniques, named Inter-Cell Interference Coordination techniques (ICIC), enhanced Inter-Cell Interference Coordination (eICIC) techniques and Coordinated Multi-Point transmission and reception (CoMP) are proposed. This paper presents a comparative study of these strategies. It can be concluded that CoMP techniques can ameliorate SINR and capacity system compared to ICIC and eICIC. In fact, SINR value reaches 15 dB for a distance of 0.5 km between user equipment and servant base station if we use CoMP technology whereas it cannot exceed 12 dB and 9 dB for eICIC and ICIC approaches respectively as reflected in simulations.

Keywords: 4th generation, interference, coordination, ICIC.

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2028 Optimal Based Damping Controllers of Unified Power Flow Controller Using Adaptive Tabu Search

Authors: Rungnapa Taithai, Anant Oonsivilai

Abstract:

This paper presents optimal based damping controllers of Unified Power Flow Controller (UPFC) for improving the damping power system oscillations. The design problem of UPFC damping controller and system configurations is formulated as an optimization with time domain-based objective function by means of Adaptive Tabu Search (ATS) technique. The UPFC is installed in Single Machine Infinite Bus (SMIB) for the performance analysis of the power system and simulated using MATLAB-s simulink. The simulation results of these studies showed that designed controller has an tremendous capability in damping power system oscillations.

Keywords: Adaptive Tabu Search (ATS), damping controller, Single Machine Infinite Bus (SMIB), Unified Power Flow Controller (UPFC).

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2027 Motion Control of a Ball Throwing Robot with a Flexible Robotic Arm

Authors: Yizhi Gai, Yukinori Kobayashi, Yohei Hoshino, Takanori Emaru

Abstract:

Motion control of flexible arms is more difficult than that of rigid arms, however utilizing its dynamics enables improved performance such as a fast motion in short operation time. This paper investigates a ball throwing robot with one rigid link and one flexible link. This robot throws a ball at a set speed with a proper control torque. A mathematical model of this ball throwing robot is derived through Hamilton’s principle. Several patterns of torque input are designed and tested through the proposed simulation models. The parameters of each torque input pattern is optimized and determined by chaos embedded vector evaluated particle swarm optimization (CEVEPSO). Then, the residual vibration of the manipulator after throwing is suppressed with input shaping technique. Finally, a real experiment is set up for the model checking.

Keywords: Motion control, flexible robotic arm, CEVEPSO, ball throwing robot.

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2026 Study on Crater Detection Using FLDA

Authors: Yoshiaki Takeda, Norifumi Aoyama, Takahiro Tanaami, Syouhei Honda, Kenta Tabata, Hiroyuki Kamata

Abstract:

In this paper, we validate crater detection in moon surface image using FLDA. This proposal assumes that it is applied to SLIM (Smart Lander for Investigating Moon) project aiming at the pin-point landing to the moon surface. The point where the lander should land is judged by the position relations of the craters obtained via camera, so the real-time image processing becomes important element. Besides, in the SLIM project, 400kg-class lander is assumed, therefore, high-performance computers for image processing cannot be equipped. We are studying various crater detection methods such as Haar-Like features, LBP, and PCA. And we think these methods are appropriate to the project, however, to identify the unlearned images obtained by actual is insufficient. In this paper, we examine the crater detection using FLDA, and compare with the conventional methods.

Keywords: Crater Detection, Fisher Linear Discriminant Analysis , Haar-Like Feature, Image Processing.

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2025 Mining Frequent Patterns with Functional Programming

Authors: Nittaya Kerdprasop, Kittisak Kerdprasop

Abstract:

Frequent patterns are patterns such as sets of features or items that appear in data frequently. Finding such frequent patterns has become an important data mining task because it reveals associations, correlations, and many other interesting relationships hidden in a dataset. Most of the proposed frequent pattern mining algorithms have been implemented with imperative programming languages such as C, Cµ, Java. The imperative paradigm is significantly inefficient when itemset is large and the frequent pattern is long. We suggest a high-level declarative style of programming using a functional language. Our supposition is that the problem of frequent pattern discovery can be efficiently and concisely implemented via a functional paradigm since pattern matching is a fundamental feature supported by most functional languages. Our frequent pattern mining implementation using the Haskell language confirms our hypothesis about conciseness of the program. The performance studies on speed and memory usage support our intuition on efficiency of functional language.

Keywords: Association, frequent pattern mining, functionalprogramming, pattern matching.

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2024 A Canadian Leaf Shaped Triple Band Patch Antenna with DGS for X and C-Band Applications

Authors: R. Kiruthika, T. Shanmuganantham

Abstract:

A shaped single feed microstrip antenna is realized for C-Band and X-Band applications. The frequency range of C-band and X-band varies from 4 to 8 Gigahertz and 8 to 12 Gigahertz. The antenna operates under three frequency bands, one under C band and two under X-band applications. Defect on the ground called DGS (Defected Ground Structure) is made to enhance the distinctiveness of the antenna parameters. The design consists of DGS provided to improve the antenna performance. The substrate material used is of the Flame Retardant grade-4 (FR4) epoxy having high mechanical and electrical strength. The design and analysis was done using the FEM (Finite Element Method) based Ansoft HFSS (High Frequency Structural Simulator) Version 12. For the resonant frequencies of 5.21, 9.17 and 10.45, a value of reflection coefficient obtained is of -39.0, -16.0 and -30.7 dB respectively. Other constraints of antenna such as bandwidth, gain, directivity and Voltage Standing Wave Ratio (VSWR) are also conferred.

Keywords: Flame retardant-4 epoxy, finite element method, return loss, directivity.

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2023 Renewable Energy Potential of Diluted Poultry Manure during Ambient Anaerobic Stabilisation

Authors: Cigdem Yangin-Gomec, Aigerim Jaxybayeva, Orhan Ince

Abstract:

In this study, the anaerobic treatability of chicken manure diluted with tap water (with an influent feed ratio of 1 kg of fresh chicken manure to 6 liter of tap water) was investigated in a lab-scale anaerobic sludge bed (ASB) reactor inoculated with the granular sludge already adapted to chicken manure. The raw waste digested in this study was the manure from laying-hens having average total solids (TS) of about 30% with ca. 60% volatile content. The ASB reactor was fed semi-continuously at ambient operating temperature range (17-23C) at a HRT of 13 and 26 days for about 6 months, respectively. The respective average total and soluble chemical oxygen demand (COD) removals were ca. 90% and 75%, whereas average biomethane production rate was calculated ca. 180 lt per kg of CODremoved from the ASB reactor at an average HRT of 13 days. Moreover, total suspended solids (TSS) and volatile suspended solids (VSS) in the influent were reduced more than 97%. Hence, high removals of the organic compounds with respective biogas production made anaerobic stabilization of the diluted chicken manure by ASB reactor at ambient operating temperatures viable. By this way, external heating up to 35C (i.e. anaerobic processes have been traditionally operated at mesophilic conditions) could be avoided in the scope of this study.

Keywords: Ambient anaerobic digestion, biogas recovery, poultry manure.

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2022 A Comparison between Hybrid and Experimental Extended Polars for the Numerical Prediction of Vertical-Axis Wind Turbine Performance using Blade Element-Momentum Algorithm

Authors: Gabriele Bedon, Marco Raciti Castelli, Ernesto Benini

Abstract:

A dynamic stall-corrected Blade Element-Momentum algorithm based on a hybrid polar is validated through the comparison with Sandia experimental measurements on a 5-m diameter wind turbine of Troposkien shape. Different dynamic stall models are evaluated. The numerical predictions obtained using the extended aerodynamic coefficients provided by both Sheldal and Klimas and Raciti Castelli et al. are compared to experimental data, determining the potential of the hybrid database for the numerical prediction of vertical-axis wind turbine performances.

Keywords: Darrieus wind turbine, Blade Element-Momentum Theory, extended airfoil database, hybrid database, Sandia 5-m wind turbine.

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2021 Optimal Linear Quadratic Digital Tracker for the Discrete-Time Proper System with an Unknown Disturbance

Authors: Jason Sheng-Hong Tsai, Faezeh Ebrahimzadeh, Min-Ching Chung, Shu-Mei Guo, Leang-San Shieh, Tzong-Jiy Tsai, Li Wang

Abstract:

In this paper, we first construct a new state and disturbance estimator using discrete-time proportional plus integral observer to estimate the system state and the unknown external disturbance for the discrete-time system with an input-to-output direct-feedthrough term. Then, the generalized optimal linear quadratic digital tracker design is applied to construct a proportional plus integral observer-based tracker for the system with an unknown external disturbance to have a desired tracking performance. Finally, a numerical simulation is given to demonstrate the effectiveness of the new application of our proposed approach.

Keywords: Optimal linear quadratic tracker, proportional plus integral observer, state estimator, disturbance estimator.

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2020 Single-Camera Basketball Tracker through Pose and Semantic Feature Fusion

Authors: Adrià Arbués-Sangüesa, Coloma Ballester, Gloria Haro

Abstract:

Tracking sports players is a widely challenging scenario, specially in single-feed videos recorded in tight courts, where cluttering and occlusions cannot be avoided. This paper presents an analysis of several geometric and semantic visual features to detect and track basketball players. An ablation study is carried out and then used to remark that a robust tracker can be built with Deep Learning features, without the need of extracting contextual ones, such as proximity or color similarity, nor applying camera stabilization techniques. The presented tracker consists of: (1) a detection step, which uses a pretrained deep learning model to estimate the players pose, followed by (2) a tracking step, which leverages pose and semantic information from the output of a convolutional layer in a VGG network. Its performance is analyzed in terms of MOTA over a basketball dataset with more than 10k instances.

Keywords: Basketball, deep learning, feature extraction, single-camera, tracking.

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2019 Connectionist Approach to Generic Text Summarization

Authors: Rajesh S.Prasad, U. V. Kulkarni, Jayashree.R.Prasad

Abstract:

As the enormous amount of on-line text grows on the World-Wide Web, the development of methods for automatically summarizing this text becomes more important. The primary goal of this research is to create an efficient tool that is able to summarize large documents automatically. We propose an Evolving connectionist System that is adaptive, incremental learning and knowledge representation system that evolves its structure and functionality. In this paper, we propose a novel approach for Part of Speech disambiguation using a recurrent neural network, a paradigm capable of dealing with sequential data. We observed that connectionist approach to text summarization has a natural way of learning grammatical structures through experience. Experimental results show that our approach achieves acceptable performance.

Keywords: Artificial Neural Networks (ANN); Computational Intelligence (CI); Connectionist Text Summarizer ECTS (ECTS); Evolving Connectionist systems; Evolving systems; Fuzzy systems (FS); Part of Speech (POS) disambiguation.

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2018 Spark Breakdown Voltage and Surface Degradation of Multiwalled Carbon Nanotube Electrode Surfaces

Authors: M. G. Rostedt, M. J. Hall, L. Shi, R. D. Matthews

Abstract:

Silicon substrates coated with multiwalled carbon nanotubes (MWCNTs) were experimentally investigated to determine spark breakdown voltages relative to uncoated surfaces, the degree of surface degradation associated with the spark discharge, and techniques to minimize the surface degradation. The results may be applicable to instruments or processes that use MWCNT as a means of increasing local electric field strength and where spark breakdown is a possibility that might affect the devices’ performance or longevity. MWCNTs were shown to reduce the breakdown voltage of a 1mm gap in air by 30-50%. The relative decrease in breakdown voltage was maintained over gap distances of 0.5 to 2mm and gauge pressures of 0 to 4 bar. Degradation of the MWCNT coated surfaces was observed. Several techniques to improve durability were investigated. These included: chromium and gold-palladium coatings, tube annealing, and embedding clusters of MWCNT in a ceramic matrix.

Keywords: Ionization sensor, spark, nanotubes, electrode, breakdown.

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2017 Empirical Study on the Student Satisfaction in Higher Education: Importance-Satisfaction Analysis

Authors: Silva, Fátima, Fernandes, Paula Odete

Abstract:

The future of Higher Education Institutions (HEI) depend on their ability to attract and retain students, increase recognition and prestige. In order to respond to the 'customers' increasingly demanding, HEI need to identify the key factors that influence the satisfaction of a 'customers', thereby creating competitive advantages. These determinants of satisfaction are important elements that guide the strategy of an institution and allow the successful achievement of strategic plans, both teaching and administrative, to offer their ‘costumers’ services and products with higher quality. Following this way of thinking, the purpose of this study was to evaluate the satisfaction with the service quality of the School of Technology and Management of Bragança (ESTiG), of the Polytechnic Institute of Bragança, identifying, thus, the dimensions related to the quality of services that might influence students' satisfaction. The results showed that, in general, the students are satisfied with the performance of ESTiG.

Keywords: Customer Satisfaction, Higher Education Institutions, Importance-Satisfaction Model.

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2016 An Anonymity-Based Secure On-Demand Routing for Mobile Ad Hoc Networks

Authors: M. Gunasekaran, K. Premalatha

Abstract:

Privacy and Security have emerged as an important research issue in Mobile Ad Hoc Networks (MANET) due to its unique nature such as scarce of resources and absence of centralized authority. There are number of protocols have been proposed to provide privacy and security for data communication in an adverse environment, but those protocols are compromised in many ways by the attackers. The concept of anonymity (in terms of unlinkability and unobservability) and pseudonymity has been introduced in this paper to ensure privacy and security. In this paper, a Secure Onion Throat (SOT) protocol is proposed to provide complete anonymity in an adverse environment. The SOT protocol is designed based on the combination of group signature and onion routing with ID-based encryption for route discovery. The security analysis demonstrates the performance of SOT protocol against all categories of attacks. The simulation results ensure the necessity and importance of the proposed SOT protocol in achieving such anonymity.

Keywords: Routing, anonymity, privacy, security and MANET.

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2015 A Hybrid Genetic Algorithm for the Sequence Dependent Flow-Shop Scheduling Problem

Authors: Mohammad Mirabi

Abstract:

Flow-shop scheduling problem (FSP) deals with the scheduling of a set of jobs that visit a set of machines in the same order. The FSP is NP-hard, which means that an efficient algorithm for solving the problem to optimality is unavailable. To meet the requirements on time and to minimize the make-span performance of large permutation flow-shop scheduling problems in which there are sequence dependent setup times on each machine, this paper develops one hybrid genetic algorithms (HGA). Proposed HGA apply a modified approach to generate population of initial chromosomes and also use an improved heuristic called the iterated swap procedure to improve initial solutions. Also the author uses three genetic operators to make good new offspring. The results are compared to some recently developed heuristics and computational experimental results show that the proposed HGA performs very competitively with respect to accuracy and efficiency of solution.

Keywords: Hybrid genetic algorithm, Scheduling, Permutationflow-shop, Sequence dependent

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2014 Comparison of Artificial Neural Network Architectures in the Task of Tourism Time Series Forecast

Authors: João Paulo Teixeira, Paula Odete Fernandes

Abstract:

The authors have been developing several models based on artificial neural networks, linear regression models, Box- Jenkins methodology and ARIMA models to predict the time series of tourism. The time series consist in the “Monthly Number of Guest Nights in the Hotels" of one region. Several comparisons between the different type models have been experimented as well as the features used at the entrance of the models. The Artificial Neural Network (ANN) models have always had their performance at the top of the best models. Usually the feed-forward architecture was used due to their huge application and results. In this paper the author made a comparison between different architectures of the ANNs using simply the same input. Therefore, the traditional feed-forward architecture, the cascade forwards, a recurrent Elman architecture and a radial based architecture were discussed and compared based on the task of predicting the mentioned time series.

Keywords: Artificial Neural Network Architectures, time series forecast, tourism.

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2013 Modelling of Composite Steel and Concrete Beam with the Lightweight Concrete Slab

Authors: V. Přivřelová

Abstract:

Well-designed composite steel and concrete structures highlight the good material properties and lower the deficiencies of steel and concrete, in particular they make use of high tensile strength of steel and high stiffness of concrete. The most common composite steel and concrete structure is a simply supported beam, which concrete slab transferring the slab load to a beam is connected to the steel cross-section. The aim of this paper is to find the most adequate numerical model of a simply supported composite beam with the cross-sectional and material parameters based on the results of a processed parametric study and numerical analysis. The paper also evaluates the suitability of using compact concrete with the lightweight aggregates for composite steel and concrete beams. The most adequate numerical model will be used in the resent future to compare the results of laboratory tests.

Keywords: Composite beams, high-performance concrete, highstrength steel, lightweight concrete slab, modeling.

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2012 Examining of Tool Wear in Cryogenic Machining of Cobalt-Based Haynes 25 Superalloy

Authors: Murat Sarıkaya, Abdulkadir Güllü

Abstract:

Haynes 25 alloy (also known as L-605 alloy) is cobalt based super alloy which has widely applications such as aerospace industry, turbine and furnace parts, power generators and heat exchangers and petroleum refining components due to its excellent characteristics. However, the workability of this alloy is more difficult compared to normal steels or even stainless. In present work, an experimental investigation was performed under cryogenic cooling to determine cutting tool wear patterns and obtain optimal cutting parameters in turning of cobalt based superalloy Haynes 25. In experiments, uncoated carbide tool was used and cutting speed (V) and feed rate (f) were considered as test parameters. Tool wear (VBmax) were measured for process performance indicators. Analysis of variance (ANOVA) was performed to determine the importance of machining parameters.

Keywords: Cryogenic machining, difficult-to-cut alloy, tool wear, turning.

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2011 Block Based Imperial Competitive Algorithm with Greedy Search for Traveling Salesman Problem

Authors: Meng-Hui Chen, Chiao-Wei Yu, Pei-Chann Chang

Abstract:

Imperial competitive algorithm (ICA) simulates a multi-agent algorithm. Each agent is like a kingdom has its country, and the strongest country in each agent is called imperialist, others are colony. Countries are competitive with imperialist which in the same kingdom by evolving. So this country will move in the search space to find better solutions with higher fitness to be a new imperialist. The main idea in this paper is using the peculiarity of ICA to explore the search space to solve the kinds of combinational problems. Otherwise, we also study to use the greed search to increase the local search ability. To verify the proposed algorithm in this paper, the experimental results of traveling salesman problem (TSP) is according to the traveling salesman problem library (TSPLIB). The results show that the proposed algorithm has higher performance than the other known methods.

Keywords: Traveling Salesman Problem, Artificial Chromosomes, Greedy Search, Imperial Competitive Algorithm.

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