Search results for: response surface model

Authors: Roman J. Jedrzejczyk, Damian K. Chlebda, Anna Dziedzicka, Rafal Wazny, Agnieszka Domka, Maciej Sitarz, Przemyslaw J. Jodlowski

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The aim of this study was to obtain antimicrobial material based on thin zirconium dioxide coatings on structured reactors doped with metal nanoparticles using the sonochemical sol-gel method. As a result, dense, uniform zirconium dioxide films were obtained on the kanthal sheets which can be used as support materials in antimicrobial converters with sophisticated shapes. The material was characterised by physicochemical methods, such as AFM, SEM, EDX, XRF, XRD, XPS and in situ Raman and DRIFT spectroscopy. In terms of antimicrobial activity, the material was tested by ATP/AMP method using model microbes isolated from the real systems. The results show that the material can be potentially used in the market as a good candidate for active package and as active bulkheads of climatic systems. The mechanical tests showed that the developed method is an efficient way to obtain durable converters with high antimicrobial activity against fungi and bacteria.

Keywords: antimicrobial properties, kanthal steel, nanocomposite, zirconium oxide

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Authors: C. A. Barros, Ana P. Barroso

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Any industrial company needs to determine the amount of variation that exists within its measurement process and guarantee the reliability of their data, studying the performance of their measurement system, in terms of linearity, bias, repeatability and reproducibility and stability. This issue is critical for automotive industry suppliers, who are required to be certified by the 16949:2016 standard (replaces the ISO/TS 16949) of International Automotive Task Force, defining the requirements of a quality management system for companies in the automotive industry. Measurement System Analysis (MSA) is one of the mandatory tools. Frequently, the measurement system in companies is not connected to the equipment and do not incorporate the methods proposed by the Automotive Industry Action Group (AIAG). To address these constraints, an R&D project is in progress, whose objective is to develop a web and cloud-based MSA tool. This MSA tool incorporates Industry 4.0 concepts, such as, Internet of Things (IoT) protocols to assure the connection with the measuring equipment, cloud computing, artificial intelligence, statistical tools, and advanced mathematical algorithms. This paper presents the preliminary findings of the project. The web and cloud-based MSA tool is innovative because it implements all statistical tests proposed in the MSA-4 reference manual from AIAG as well as other emerging methods and techniques. As it is integrated with the measuring devices, it reduces the manual input of data and therefore the errors. The tool ensures traceability of all performed tests and can be used in quality laboratories and in the production lines. Besides, it monitors MSAs over time, allowing both the analysis of deviations from the variation of the measurements performed and the management of measurement equipment and calibrations. To develop the MSA tool a ten-step approach was implemented. Firstly, it was performed a benchmarking analysis of the current competitors and commercial solutions linked to MSA, concerning Industry 4.0 paradigm. Next, an analysis of the size of the target market for the MSA tool was done. Afterwards, data flow and traceability requirements were analysed in order to implement an IoT data network that interconnects with the equipment, preferably via wireless. The MSA web solution was designed under UI/UX principles and an API in python language was developed to perform the algorithms and the statistical analysis. Continuous validation of the tool by companies is being performed to assure real time management of the ‘big data’. The main results of this R&D project are: MSA Tool, web and cloud-based; Python API; New Algorithms to the market; and Style Guide of UI/UX of the tool. The MSA tool proposed adds value to the state of the art as it ensures an effective response to the new challenges of measurement systems, which are increasingly critical in production processes. Although the automotive industry has triggered the development of this innovative MSA tool, other industries would also benefit from it. Currently, companies from molds and plastics, chemical and food industry are already validating it.

Keywords: automotive Industry, industry 4.0, Internet of Things, IATF 16949:2016, measurement system analysis

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Authors: Rosyidah Muhamad

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Democracies are premised on the idea that citizens can hold their leaders accountable for their actions by voting for or against them in regular elections. However, in order this ideal to be realized, citizens must possess a minimum amount of information about their leaders’ performance. Citizens should be made aware of the performance of their elected representatives. This study seeks to analyse this critical information with special reference to Malaysian Parliamentarians (MPs). We adopted several existence Parliamentary Performance model with special reference to their performance inside the parliament. Among indicators used by the Scholastic for analysing this performance are the number of bills proposed by parliamentarian, the number of proposals that would benefit their constituency, the number of speeches made by the parliamentarian during plenary and the percentage of laws passed among the proposals made by certain parliamentary. The broad goals of the study include the analysis of the capacity of a representative body to accommodate the diverse claims and demands that are made on it. We find that overall performances of MPs are average. This is due to not only the background characteristic of individuals MPs but also the limitation of the mechanism provides in the Parliament itself.

Keywords: member of parliament, democracy, evaluation, Malaysia

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Authors: Martha Ndeley, John Ikome

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In this paper, we expand the scope of constraint-directed techniques to deal with the case of transportation schedule with capacity restrictions where the scheduling problem includes alternative activities. That is, not only does the scheduling problem consist of determining when an activity is to be executed, but also determining which set of alternative activities is to be executed at all level of transportation from input to output. Such problems encompass both alternative resource problems and alternative process plan problems. We formulate a constraint-based representation of alternative activities to model problems containing such choices. We then extend existing constraint-directed scheduling heuristic commitment techniques and propagators to reason directly about the fact that an activity does not necessarily have to exist in a final transportation schedule without being completed. Tentative results show that an algorithm using a novel texture-based heuristic commitment technique propagators achieves the best overall performance of the techniques tested.

Keywords: production, transportation, scheduling, integrated

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Authors: Sadegh Torfi

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Realization of anticipated energy efficiency from recuperative run-around energy recovery (RER) systems requires identification of the system components influential parameters. Because simulation modeling is considered as an integral part of the design and economic evaluation of RER systems, it is essential to calibrate the developed models and validate the performance predictions by means of comparison with data from experimental measurements. Several theoretical and numerical analyses on RER systems by researchers have been done, but generally the effect of distance between hot and cold flow is ignored. The objective of this study is to develop a thermohydroulic model for a typical RER system that accounts for energy loss from the interconnecting piping and effects of interconnecting pipes length performance of run-around energy recovery systems. Numerical simulation shows that energy loss from the interconnecting piping is change linear with pipes length and if pipes are properly isolated, maximum reduction of effectiveness of RER systems is 2% in typical piping systems.

Keywords: combined heat and power, heat recovery, effectiveness, CGS

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Authors: M. Moharami Gargari, S. Javdani Zamani, A. Mohammadnejad, S. Abuali

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As maritime container transport is developing fast, the need arises for efficient operations at container terminals. One of the most important determinants of container handling efficiency is the productivity of quay cranes and internal transportation vehicles, which are responsible transporting of containers for unloading and loading operations for container vessels. For this reason, this paper presents an integrated mathematical model formulation for discrete berths with quay cranes and internal transportations vehicles. The problems have received increasing attention in the literature and the present paper deals with the integration of these interrelated problems. A new mixed integer linear formulation is developed for the Berth Allocation Problem (BAP), Quay Crane Assignment and Scheduling Problem (QCASP) and Internal Transportation Scheduling (ITS), which accounts for cranes and trucks positioning conditions.

Keywords: discrete berths, container terminal, truck scheduling, dynamic vessel arrival

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Authors: Muhammad Umair, Syed Qasim Gilani

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A technique using Independent Component Analysis (ICA) for blind receiver signal processing is investigated. The problem of the receiver signal processing is viewed as of signal equalization and implementation imperfections compensation. Based on this, a model similar to a general ICA problem is developed for the received signal. Then, the use of ICA technique for blind signal equalization in the time domain is presented. The equalization is regarded as a signal separation problem, since the desired signal is separated from interference terms. This problem is addressed in the paper by over-sampling of the received signal. By using ICA for equalization, besides channel equalization, other transmission imperfections such as Direct current (DC) bias offset, carrier phase and In phase Quadrature phase imbalance will also be corrected. Simulation results for a system using 16-Quadraure Amplitude Modulation(QAM) are presented to show the performance of the proposed scheme.

Keywords: blind equalization, blind signal separation, equalization, independent component analysis, transmission impairments, QAM receiver

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Authors: Farzaneh Rajabighamchi, Stan van Hoesel, Christof Defryn

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The generalized traveling salesman problem (GTSP) is an extension of the traveling salesman problem (TSP) where the set of nodes is partitioned into clusters, and the salesman must visit exactly one node per cluster. In this research, we apply the definition of the GTSP to an order picker routing problem with multiple locations per product. As such, each product represents a cluster and its corresponding nodes are the locations at which the product can be retrieved. To pick a certain product item from the warehouse, the picker needs to visit one of these locations during its pick tour. As all products are scattered throughout the warehouse, the product clusters not separated geographically. We propose an exact LP model as well as heuristic and meta-heuristic solution algorithms for the order picking problem with multiple product locations.

Keywords: warehouse optimization, order picking problem, generalised travelling salesman problem, heuristic algorithm

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Authors: Nicholas Milburn, Yu Liang, Dalei Wu

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Athlete performance scoring within the climbing do-main presents interesting challenges as the sport does not have an objective way to assign skill. Assessing skill levels within any sport is valuable as it can be used to mark progress while training, and it can help an athlete choose appropriate climbs to attempt. Machine learning-based methods are popular for complex problems like this. The dataset available was composed of dynamic force data recorded during climbing; however, this dataset came with challenges such as data scarcity, imbalance, and it was temporally heterogeneous. Investigated solutions to these challenges include data augmentation, temporal normalization, conversion of time series to the spectral domain, and cross validation strategies. The investigated solutions to the classification problem included light weight machine classifiers KNN and SVM as well as the deep learning with CNN. The best performing model had an 80% accuracy. In conclusion, there seems to be enough information within climbing force data to accurately categorize climbers by skill.

Keywords: classification, climbing, data imbalance, data scarcity, machine learning, time sequence

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Authors: Johannes Günther

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Time Sensitive Networking (TSN), standardized in the IEEE 802.1 standard, has been lent increasing attention in the context of mission critical systems. Such mission critical systems, e.g., in the automotive domain, aviation, industrial, and smart factory domain, are responsible for coordinating complex functionalities in real time. In many of these contexts, a reliable data exchange fulfilling hard time constraints and quality of service (QoS) conditions is of critical importance. TSN standards are able to provide guarantees for deterministic communication behaviour, which is in contrast to common best-effort approaches. Therefore, the superior QoS guarantees of TSN may aid in the development of new technologies, which rely on low latencies and specific bandwidth demands being fulfilled. TSN extends existing Ethernet protocols with numerous standards, providing means for synchronization, management, and overall real-time focussed capabilities. These additional QoS guarantees, as well as management mechanisms, lead to an increased attack surface for potential malicious attackers. As TSN guarantees certain deadlines for priority traffic, an attacker may degrade the QoS by delaying a packet beyond its deadline or even execute a denial of service (DoS) attack if the delays lead to packets being dropped. However, thus far, security concerns have not played a major role in the design of such standards. Thus, while TSN does provide valuable additional characteristics to existing common Ethernet protocols, it leads to new attack vectors on networks and allows for a range of potential attacks. One answer to these security risks is to deploy defense mechanisms according to a moving target defense (MTD) strategy. The core idea relies on the reduction of the attackers' knowledge about the network. Typically, mission-critical systems suffer from an asymmetric disadvantage. DoS or QoS-degradation attacks may be preceded by long periods of reconnaissance, during which the attacker may learn about the network topology, its characteristics, traffic patterns, priorities, bandwidth demands, periodic characteristics on links and switches, and so on. Here, we implemented and tested several MTD-like defense strategies against different attacker models of varying capabilities and budgets, as well as collaborative attacks of multiple attackers within a network, all within the context of TSN networks. We modelled the networks and tested our defense strategies on an OMNET++ testbench, with networks of different sizes and topologies, ranging from a couple dozen hosts and switches to significantly larger set-ups.

Keywords: network security, time sensitive networking, moving target defense, cyber security

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Authors: Katerina Zaharieva, Vicente Rives, Martin Tsvetkov, Raquel Trujillano, Boris Kunev, Ivan Mitov, Maria Milanova, Zara Cherkezova-Zheleva

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The nanostructured cobalt ferrite-type materials Sample A - Co0.25Fe2.75O4, Sample B - Co0.5Fe2.5O4, and Sample C - CoFe2O4 were prepared by co-precipitation in our previous investigations. The co-precipitated Sample B and Sample C were mechanochemically activated in order to produce Sample D - Co0.5Fe2.5O4 and Sample E- CoFe2O4. The PXRD, Moessbauer and FTIR spectroscopies, specific surface area determination by the BET method, thermal analysis, element chemical analysis and temperature-programmed reduction were used to investigate the prepared nano-sized samples. The changes of the Malachite green dye concentration during reaction of the photocatalytic decolorization using nanostructured cobalt ferrite-type catalysts with different chemical composition are included. The photocatalytic results show that the increase in the degree of incorporation of cobalt ions in the magnetite host structure for co-precipitated cobalt ferrite-type samples results in an increase of the photocatalytic activity: Sample A (4 х10-3 min-1) < Sample B (5 х10-3 min-1) < Sample C (7 х10-3 min-1). Mechanochemically activated photocatalysts showed a higher activity than the co-precipitated ferrite materials: Sample D (16 х10-3 min-1) > Sample E (14 х10-3 min-1) > Sample C (7 х10-3 min-1) > Sample B (5 х10-3 min-1) > Sample A (4 х10-3 min-1). On decreasing the degree of substitution of iron ions by cobalt ones a higher sorption ability of the dye after the dark period for the co-precipitated cobalt ferrite materials was observed: Sample C (72 %) < Sample B (78 %) < Sample A (80 %). Mechanochemically treated ferrite catalysts and co-precipitated Sample B possess similar sorption capacities, Sample D (78 %) ~ Sample E (78 %) ~ Sample B (78 %). The prepared nano-sized cobalt ferrite-type materials demonstrate good photocatalytic and sorption properties. Mechanochemically activated Sample D - Co0.5Fe2.5O4 (16х10-3 min-1) and Sample E-CoFe2O4 (14х10-3 min-1) possess higher photocatalytic activity than that of the most common used UV-light catalyst Degussa P25 (12х10-3 min-1). The dependence of the photo-catalytic activity and sorption properties on the preparation method and different degree of substitution of iron ions by cobalt ions in synthesized cobalt ferrite samples is established. The mechanochemical activation leads to formation of nano-structured cobalt ferrite-type catalysts (Sample D and Sample E) with higher rate constants than those of the ferrite materials (Sample A, Sample B, and Sample C) prepared by the co-precipitation procedure. The increase in the degree of substitution of iron ions by cobalt ones leads to improved photocatalytic properties and lower sorption capacities of the co-precipitated ferrite samples. The good sorption properties between 72 and 80% of the prepared ferrite-type materials show that they could be used as potential cheap absorbents for purification of polluted waters.

Keywords: nanodimensional cobalt ferrites, photocatalyst, synthesis, mechanochemical activation

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Authors: Hamdy Ahmed Ashour

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This paper studies the parallel operation of rotary frequency converters which can be used within a ship micro-grid system and also to supply ships and equipment in a harbour during off-sail and maintenance periods with their suitable voltage and frequency requirements in order to overcome the possible associated problems of overloading on a single converter. The paper theoretically and experimentally investigated the operation of 3-ph induction motor / 3-ph synchronous generator based rotary converters set. Concept of operation and merits of such converters has been discussed. Overall dynamic simulation model of two parallel operated rotary converters has been developed. Active and reactive load sharing of the two converters has been analyzed. Experimental setup has been implemented for proof of concept and practical validation. Simulation and experimental results have been obtained and well correlated; showing how the rotary converters based setup can be manipulated to achieve different requirements of operating conditions.

Keywords: experimental, frequency-converters, load-sharing, marine-applications, simulation, synchronization

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Authors: Leena Wanganoo

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In this digital age with the mushrooming of online companies across the globe has led to an unprecedented new business model. The frequency of online purchasing varies across the globe, but trend shows a steep upward movement. From Generation X to the Millennial the consumer not only wants to order the product with the click of mouse but also very demanding service quality during pre to post-transaction stage. The existing research examines the impact of website quality on the on behavioral intentions in e-services customers and has not adequately recognized the quality of e-commerce logistics perceived by the customer.In order to address this gap, this study examines the relationship among the logistics service quality, satisfaction, and loyalty. Drawing upon a sample of 350 millennial customers from various regions of UAE will work within the framework of structural equation modeling (SEM). Finally, the study would use Importance-Performance analysis (IPA) to discuss the relations of the level of customers’ expected logistics service quality and level of customers’ perceived logistics serviced quality.

Keywords: logistics service quality, customer satisfaction, loyalty, electronic commerce

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Authors: Belkacem Laimouche

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With the field of artificial intelligence (AI) experiencing exponential growth, fueled by technological advancements that pave the way for increasingly innovative and promising applications, there is an escalating need to develop rigorous methods for assessing their performance in pursuit of transparency and equity. This article proposes a metrology-inspired statistical framework for evaluating bias and explainability in AI systems. Drawing from the principles of metrology, we propose a pioneering approach, using a concrete example, to evaluate the accuracy and precision of AI models, as well as to quantify the sources of measurement uncertainty that can lead to bias in their predictions. Furthermore, we explore a statistical approach for evaluating the explainability of AI systems based on their ability to provide interpretable and transparent explanations of their predictions.

Keywords: artificial intelligence, metrology, measurement uncertainty, prediction error, bias, machine learning algorithms, probabilistic models, interlaboratory comparison, data analysis, data reliability, measurement of bias impact on predictions, improvement of model accuracy and reliability

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Authors: Salim Ahmed

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In many countries, water pollution from industrial effluents is a real problem. It may have a negative impact on the environment. To minimize the adverse effects of these contaminants, various methods are used to improve effluent purification, including physico-chemical processes such as adsorption.The present study focuses on applying a naturally biodegradable adsorbent based on argan (southern Morocco) in a physico-chemical adsorption process to reduce the harmful effects of pollutants on the environment. Tests were carried out with the cationic dye methylene blue (MB) and revealed that removal is significantly higher within the first 15 minutes. The parameters studied in this study are adsorbent mass and concentration. The Freundlich model provides an excellent example of the adsorption phenomenon of BMs over argan powder. The results of this study show that argan kernels are a highly beneficial alternative for local communities, as they help to achieve a triple objective: pollution reduction, waste recovery and water recycling.

Keywords: environmental protection, activated carbon, water treatment, adsorption

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Authors: Reza Safari, Ali Rajabzadeh Ghatari, Raheleh Hossseinzadeh Mahabadi

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In the present world, there are different pressures on firms such as competition, legislations, social etc. these pressures force the firms to follow “survival” as their primary goal and then growth. One of the main factors that helps firms to reach their goals is proper financial performance. To find out about the financial performance, a firm should monitors its financial performance. Financial performance affected by many factors. This research seeks to clear which financial performance indicators are most important according to Environmental situation of a firm and what are their priorities. To do so, environmental indicators specified as presented on OECD Key Environmental Indicators 2008 and so the financial performance indicators such as Profitability, Liquidity, Gearing, Investor ratios, and etc. At this stage, the affections questioned through questionnaires. After gaining the results, data analyzed using Promethee technique. By using decision matrixes extracted from those techniques an expert system designed. This expert system suggests the suitable financial performance indicators and their ranking by receiving the environment situation given environment indicators weight.

Keywords: environment indicators, financial performance indicators, promethee, expert system

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Authors: M. Khalfa, H. Khachai, F. Chiker, K. Bougherara, R. Khenata, G. Murtaza, M. Harmel

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A theoretical study of structural, elastic, electronic and thermodynamic properties of Fe2VX, (with X = Al and Ga), were studied by means of the full-relativistic version of the full-potential augmented plane wave plus local orbitals method. For exchange and correlation potential we used both generalized-gradient approximation (GGA) and local-density approximation (LDA). Our calculated ground state properties like as lattice constants, bulk modulus and elastic constants appear more accurate when we employed the GGA rather than the LDA approximation, and these results agree very well with the available experimental and theoretical data. Further, prediction of the thermal effects on some macroscopic properties of Fe2VAl and Fe2VGa are given in this paper using the quasi-harmonic Debye model in which the lattice vibrations are taken into account. We have obtained successfully the variations of the primitive cell volume, volume expansion coefficient, heat capacities and Debye temperature with pressure and temperature in the ranges of 0–40 GPa and 0–1500 K.

Keywords: full Heusler, FP-LAPW, electronic properties, thermal properties

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Authors: Jayson G. Balansag

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An integrated biology and chemistry (iBC) course for freshmen college students was developed in University of Delaware. This course will prepare students to (1) become interdisciplinary thinkers in the field of biology and (2) collaboratively work with others from multiple disciplines in the future. This paper documents and describes the implementation of the course. The information gathered from reading literature, classroom observations, and interviews were used to carry out the purpose of this paper. The major goal of the iBC course is to align the concepts between Biology and Chemistry, so that students can draw science concepts from both disciplines which they can apply in their interdisciplinary researches. This course is offered every fall and spring semesters of each school year. Students enrolled in Biology are also enrolled in Chemistry during the same semester. The iBC is composed of lectures, laboratories, studio sessions, and workshops and is taught by the faculty from the biology and chemistry departments. In addition, the preceptors, graduate teaching assistants, and studio fellows facilitate the laboratory and studio sessions. These roles are interdependent with each other. The iBC can be used as a model for higher education institutions who wish to implement an integrated biology course.

Keywords: integrated biology and chemistry, integration, interdisciplinary research, new biology, undergraduate science education

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Authors: Surita Maini, Sanjay Dhanka

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Machine learning (ML) involves developing algorithms and statistical models that enable computers to learn and make predictions or decisions based on data without being explicitly programmed. Because of its unlimited abilities ML is gaining popularity in medical sectors; Medical Imaging, Electronic Health Records, Genomic Data Analysis, Wearable Devices, Disease Outbreak Prediction, Disease Diagnosis, etc. In the last few decades, many researchers have tried to diagnose Breast Cancer (BC) using ML, because early detection of any disease can save millions of lives. Working in this direction, the authors have proposed a hybrid ML technique RBF SVM, to predict the BC in earlier the stage. The proposed method is implemented on the Breast Cancer UCI ML dataset with 569 instances and 32 attributes. The authors recorded performance metrics of the proposed model i.e., Accuracy 98.24%, Sensitivity 98.67%, Specificity 97.43%, F1 Score 98.67%, Precision 98.67%, and run time 0.044769 seconds. The proposed method is validated by K-Fold cross-validation.

Keywords: breast cancer, support vector classifier, machine learning, hyper parameter tunning

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Authors: Talebi Aliasghar, Ebrahimpour Komeleh Hooman, Maghsoudi Ali Akbar

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In reinforced concrete (RC) structures, beam-column connection region has a considerable effect on the behavior of structures. Using fiber reinforcement polymer (FRP) for the strengthening of connections in RC structures can be one of the solutions to retrofitting this zone which result in the enhanced behavior of structure. In this paper, these changes in behavior by using FRP for high strength concrete beam-column connection have been studied by finite element modeling. The concrete damage plasticity (CDP) model has been used to analyze the RC. The results illustrated a considerable development in load-bearing capacity but also a noticeable reduction in ductility. The study also assesses these qualities for several modes of strengthening and suggests the most effective mode of strengthening. Using FRP in flexural zone and FRP with 45-degree oriented fibers in shear zone of joint showed the most significant change in behavior.

Keywords: HSC, beam-column connection, Fiber Reinforcement Polymer, FRP, Finite Element Modeling, FEM

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Authors: Wataru Nakamura, Tomoaki Hashimoto, Liang-Kuang Chen

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This paper provides a state estimation method for automatic control systems of nonlinear vehicle dynamics. A nonlinear tire model is employed to represent the realistic behavior of a vehicle. In general, all the state variables of control systems are not precisedly known, because those variables are observed through output sensors and limited parts of them might be only measurable. Hence, automatic control systems must incorporate some type of state estimation. It is needed to establish a state estimation method for nonlinear vehicle dynamics with restricted measurable state variables. For this purpose, unscented Kalman filter method is applied in this study for estimating the state variables of nonlinear vehicle dynamics. The objective of this paper is to propose a state estimation method using unscented Kalman filter for nonlinear vehicle dynamics. The effectiveness of the proposed method is verified by numerical simulations.

Keywords: state estimation, control systems, observer systems, nonlinear systems

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Authors: Qi Peng

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The Chinese sport sector is currently undergoing a dramatic institutional change. A sport system that was heavily dominated by the government is starting to shift towards one that is driven by the market. During the past sixty years, the Chinese Football Association (CFA), although ostensibly a ‘non-governmental organization’, has been in fact operated under the close supervision and control of the government. The double-identity of CFA has taken most of the blame for the poor performance of the Chinese football team, especially the men’s team. In 2015, a policy initiated by the Chinese government introduced a potentially radical change to the institutional structure of CFA by delegating the power of government agency – the General Administration of Sport of China - to the organization (CFA) itself. Against such background, an overarching research question was brought up- will an organization remained institutionalized within the system change in response to the external (policy) jolt? To answer this question, three principal data collection methods were employed: document review, participant observation and semi-structured interviews. Document review provides the mapping of the structural and cultural framework in which the CFA functions during the change process. The author have had the chance to interact closely with the organization as participant observer in the organization for a period of time, long enough to collect the data, but never too long to get biased view of the situation. This stage enables the author to gain an in-depth understanding of how CFA managed to restructure the governance and legitimacy. Conducting semi-structured interviews with staff within the CFA and from staff within selected stakeholders of CFA also provided a crucial step to gain an insight into the factors for change as well as the implications of the change. A wide range of interviewees that have been and to be interviewed include: CFA members (senior officials and staff); local football associations members; senior Chinese Super League football club managers; CFA Super League Co., LTD (senior officials and staff); CSL broadcasters; Chinese Olympic Committee members. The preliminary research data shows that the CFA is currently undergoing two levels of change: although the settings of CFA has been gradually restructured (organizational framework), the organizational values and beliefs remain almost the same as the CFA before the reform. This means that the plan of shifting from a governmental agency to an autonomous association is an going process, and that organizational core beliefs and values are more difficult to change than its structural framework. This is due to the inertia of the organizational history and the effect of institutionalization. The change of Chinese Football Association is looked at as a pioneering sport organization in China to undertake the “decoupling” road. It is believed that many other sport organizations, especially sport governing bodies will follow the step of CFA in the near future. Therefore, the experience of CFA change is worthy of studying.

Keywords: Chinese Football Association, Organizational Change, Organizational Culture, Structural Framework

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Authors: Oussama Derdous, Lakhdar Djemili, Hamza Bouchahed

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The consequences of a dam breach can be devastating; both in terms of lives lost and damaged infrastructure and property. Hydraulic modeling provides a clear picture of the possible consequences of partial or complete failure of a dam, which is the key to carry out emergency planning and conduct reliable risk assessments. In this paper, the MIKE11 model developed by the Danish Hydrologic Institute (DHI) was used to simulate the flood wave propagation associated with a potential failure analysis failure of Zardezas dam located in the city of Skikda in the North East of Algeria. MIKE11 results including inundation maps and the representative channel/valley cross-sections depicting flow depth and maximal flow velocities showed that Zardezas reservoir presents a significant risk to downstream areas in the event of a dam failure. These results can be used as the basis of the development of an Emergency Action Plan (EAP).The main objective of this plan is to predict the appropriate steps to avoid or at least decrease the consequences of unexpected failure of Zardezas dam.

Keywords: MIKE11, dam break, inundation maps, emergency action plan

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Authors: Solanki Ravirajsinh

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In the software testing life cycle, failing to conduct thorough performance testing can result in significant losses for an organization due to application crashes and improper behavior under high user loads in production. Simulating large volumes of requests, such as 5 million within 5-10 minutes, is challenging without a scalable performance testing framework. Leveraging cloud services to implement a performance testing framework makes it feasible to handle 5-10 million requests in just 5-10 minutes, helping organizations ensure their applications perform reliably under peak conditions. Implementing a scalable performance testing framework using cloud services and tools like JMeter, EC2 instances (Virtual machine), cloud logs (Monitor errors and logs), EFS (File storage system), and security groups offers several key benefits for organizations. Creating performance test framework using this approach helps optimize resource utilization, effective benchmarking, increased reliability, cost savings by resolving performance issues before the application is released. In performance testing, a master-slave framework facilitates distributed testing across multiple EC2 instances to emulate many concurrent users and efficiently handle high loads. The master node orchestrates the test execution by coordinating with multiple slave nodes to distribute the workload. Slave nodes execute the test scripts provided by the master node, with each node handling a portion of the overall user load and generating requests to the target application or service. By leveraging JMeter's master-slave framework in conjunction with cloud services like EC2 instances, EFS, CloudWatch logs, security groups, and command-line tools, organizations can achieve superior scalability and flexibility in their performance testing efforts. In this master-slave framework, JMeter must be installed on both the master and each slave EC2 instance. The master EC2 instance functions as the "brain," while the slave instances operate as the "body parts." The master directs each slave to execute a specified number of requests. Upon completion of the execution, the slave instances transmit their results back to the master. The master then consolidates these results into a comprehensive report detailing metrics such as the number of requests sent, encountered errors, network latency, response times, server capacity, throughput, and bandwidth. Leveraging cloud services, the framework benefits from automatic scaling based on the volume of requests. Notably, integrating cloud services allows organizations to handle more than 5-10 million requests within 5 minutes, depending on the server capacity of the hosted website or application.

Keywords: identify crashes of application under heavy load, JMeter with cloud Services, Scalable performance testing, JMeter master and slave using cloud Services

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Authors: Antoni Ivanov, Nikolay Dandanov, Nicole Christoff, Vladimir Poulkov

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Spectrum underutilization has made cognitive radio a promising technology both for current and future telecommunications. This is due to the ability to exploit the unused spectrum in the bands dedicated to other wireless communication systems, and thus, increase their occupancy. The essential function, which allows the cognitive radio device to perceive the occupancy of the spectrum, is spectrum sensing. In this paper, the performance of modern adaptations of the four most widely used spectrum sensing techniques namely, energy detection (ED), cyclostationary feature detection (CSFD), matched filter (MF) and eigenvalues-based detection (EBD) is compared. The implementation has been accomplished through the PlutoSDR hardware platform and the GNU Radio software package in very low Signal-to-Noise Ratio (SNR) conditions. The optimal detection performance of the examined methods in a realistic implementation-oriented model is found for the common relevant parameters (number of observed samples, sensing time and required probability of false alarm).

Keywords: cognitive radio, dynamic spectrum access, GNU Radio, spectrum sensing

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Authors: Radoslav Židek, Veronika Šidlová, Radovan Kasarda, Birgit Fuerst-Waltl

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Machine learning represents a set of topics dealing with the creation and evaluation of algorithms that facilitate pattern recognition, classification, and prediction, based on models derived from existing data. The data can present identification patterns which are used to classify into groups. The result of the analysis is the pattern which can be used for identification of data set without the need to obtain input data used for creation of this pattern. An important requirement in this process is careful data preparation validation of model used and its suitable interpretation. For breeders, it is important to know the origin of animals from the point of the genetic diversity. In case of missing pedigree information, other methods can be used for traceability of animal´s origin. Genetic diversity written in genetic data is holding relatively useful information to identify animals originated from individual countries. We can conclude that the application of data mining for molecular genetic data using supervised learning is an appropriate tool for hypothesis testing and identifying an individual.

Keywords: genetic data, Pinzgau cattle, supervised learning, machine learning

Procedia PDF Downloads 549

Authors: Anna Wolowicz, Katarzyna Staszak, Zbigniew Hubicki

Abstract:

Nowadays heavy metal ions as well as surfactants are widely used throughout the world due to their useful properties. The consequence of such widespread use is their significant production. On the other hand, the increasing demand for surfactants and heavy metal ions results in production of large amounts of wastewaters which are discharged to the environment from mining, metal plating, pharmaceutical, cosmetic, fertilizer, paper, pesticide and electronic industries, pigments producing, petroleum refining and from autocatalyst, fibers, food, polymer industries etc. Heavy metal ions are non-biodegradable in the environment, cable of accumulation in living organisms and organs, toxic and carcinogenic. On the other hand, not only heavy metal ions but also surfactants affect the purity of water and soils. Some of surfactants are also toxic, harmful and dangerous because they are able to penetrate into surface waters causing foaming, blocked diffusion of oxygen from the atmosphere and act as emulsifiers of hydrophobic substances and increase solubility of many the dangerous pollutants. Among surfactants the anionic ones dominate and their share in the global production of surfactants is around 50 ÷ 60%. Due to the negative impact of heavy metals and surfactants on aquatic ecosystems and living organisms, removal and monitoring of their concentration in the environment is extremely important. Surfactants and heavy metal ions removal can be achieved by different biological and physicochemical methods. The adsorption as well as the ion-exchange methods play here a significant role. The aim of this study was heavy metal ions removal from aqueous solutions using different types of ion exchangers in the presence of anionic surfactants. Preliminary studies of copper(II), nickel(II), zinc(II) and cobalt(II) removal from acidic solutions using ion exchangers (Lewatit MonoPlus TP 220, Lewatit MonoPlus SR 7, Purolite A 400 TL, Purolite A 830, Purolite S 984, Dowex PSR 2, Dowex PSR3, Lewatit AF-5) allowed to select the most effective ones for the above mentioned sorbates and then to checking their removal efficiency in the presence of anionic surfactants. As it was found out Lewatit MonoPlus TP 220 of the chelating type, show the highest sorption capacities for copper(II) ions in comparison with the other ion exchangers under discussion, e.g. 9.98 mg/g (0.1 M HCl); 9.12 mg/g (6 M HCl). Moreover, cobalt(II) removal efficiency was the highest in 0.1 M HCl using also Lewatit MonoPlus TP 220 (6.9 mg/g) similar to zinc(II) (9.1 mg/g) and nickiel(II) (6.2 mg/g). As the anionic surfactant sodium dodecyl sulphate (SDS) was used and surfactant parameters such as viscosity (η), density (ρ) and critical micelle concentration (CMC) were obtained: η = 1.13 ± 0,01 mPa·s; ρ = 999.76 mg/cm3; CMC = 2.26 g/cm3. The studies of copper(II) removal from acidic solutions in the presence of SDS of different concentration show negligible effects on copper(II) removal efficiency. The sorption capacity of Cu(II) from 0.1 M acidic solution of 500 mg/L initial concentration was equal to 46.8 mg/g whereas in the presence of SDS 45.3 mg/g (0.1 mg SDS/L), 47.1 mg/g (0.5 mg SDS/L), 46.6 mg/g (1 mg SDS/L).

Keywords: anionic surfactant, heavy metal ions, ion exchanger, removal

Procedia PDF Downloads 140

Authors: A. Ejah Umraeni Salam, M. Tola, M. Selintung, F. Maricar

Abstract:

Clean water is an essential and fundamental human need. Therefore, its supply must be assured by maintaining the quality, quantity and water pressure. However the fact is, on its distribution system, leakage happens and becomes a common world issue. One of the technical causes of the leakage is a leaking pipe. The purpose of the research is how to use the Radial Basis Function Neural (RBFNN) model to detect the location and the magnitude of the pipeline leakage rapidly and efficiently. In this study the RBFNN are trained and tested on data from EPANET hydraulic modeling system. Method of Radial Basis Function Neural Network is proved capable to detect location and magnitude of pipeline leakage with of the accuracy of the prediction results based on the value of RMSE (Root Meant Square Error), comparison prediction and actual measurement approaches 0.000049 for the whole pipeline system.

Keywords: radial basis function neural network, leakage pipeline, EPANET, RMSE

Procedia PDF Downloads 356

Authors: Fatemeh Rahmani, Navid Nadimi, Vahid Khalifeh

Abstract:

In the near future, cities with medium populations will face traffic congestion, air pollution, high fuel consumption, and noise pollution. It is possible to improve the sustainability of cities by utilizing public transportation. A study of the factors that influence citizens' bus usage in medium-sized cities is presented in this paper. For this purpose, Kerman's citizens were surveyed online. The model was based on a binary logistic regression. A descriptive analysis revealed that simple measures like renewing the fleet, upgrading the stations, establishing a schedule program, and cleaning the buses could improve passenger satisfaction. In addition, the modeling results showed that future traffic congestion can be prevented by implementing road and parking lot pricing plans. Further, as the number and length of trips increases, the probability of citizens taking the bus increases. In conclusion, Kerman's bus system is both secure and fast, but these two characteristics can be improved to increase bus ridership.

Keywords: sustainability, transportation, bus, congestion, satisfaction

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Authors: Rosidah Rosidah

Abstract:

The paper aims to identify and examine the effectiveness of social marketing as an approach for conducting anti-corruption campaign. Social marketing has been widely used to promote social change for the benefit of individual and society; such as for promoting healthy foods consumption, encouraging breastfeeding, reducing smoking, solving alcohol problem and drunk driving. Therefore, it is believed that this approach can be promising to be used in anti-corruption campaign. It is because social marketing can be useful of prompting people to act in accordance to the existing norms that denounce corruption, or help to establish new norms that more averse to corruption. It has established into evidence and insight based approaches to social campaign that focus on changing people’s behavior. Qualitative approach will be used in this study, with the using of literature review and secondary data analysis as the research methods. This paper is still on preliminary stage, which its results is expected to provide fundamental basis for designing model of intervention (anti-corruption campaign) using social marketing approaches.

Keywords: anti-corruption campaign, behavioral change, social influence, social marketing

Procedia PDF Downloads 331