Search results for: search techniques

Authors: Ahmad H. Abdelgwad, Galal E. Nadim, Tarek M. Said, Amr M. Gody

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The prime objective of this manuscript is to provide intensive review of the techniques used for permittivity measurements. The measurement techniques, relevant for any desired application, rely on the nature of the measured dielectric material, both electrically and physically, the degree of accuracy required, and the frequency of interest. Regardless of the way that distinctive sorts of instruments can be utilized, measuring devices that provide reliable determinations of the required electrical properties including the obscure material in the frequency range of interest can be considered. The challenge in making precise dielectric property or permittivity measurements is in designing of the material specimen holder for those measurements (RF and MW frequency ranges) and adequately modeling the circuit for reliable computation of the permittivity from the electrical measurements. If the RF circuit parameters such as the impedance or admittance are estimated appropriately at a certain frequency, the material’s permittivity at this frequency can be estimated by the equations which relate the way in which the dielectric properties of the material affect on the parameters of the circuit.

Keywords: dielectric permittivity, free space measurement, waveguide techniques, coaxial probe, cavity resonator

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Authors: Gertrude Nkechi Okenwa

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Higher institutions, especially the universities that are saddled with the responsibilities of teaching, learning, research, publications and social services for the production of graduates that are worthy in learning and character, and the creation of up-to-date knowledge and innovations for the total socio-economic and even political development of a given nation. Therefore, the purpose of the study was to identify the teaching, learning techniques used in the Enugu State University of Science and Technology to ensure or ascertain students’ perception on these techniques. To guide the study, survey research method was used. The population for the study was made up of second and final year students which summed up to one hundred and twenty-six students in the faculty of education. Stratified random sampling technique was adopted. A sample size of sixty (60) students was drawn for the study. The instrument used for data collection was questionnaire. To analyze the data, mean and standard deviation were used to answers the research questions. The findings revealed that direct instruction and construction techniques are used in the university. On the whole, it was observed that the students perceived constructivist techniques to be more useful and effective than direct instruction technique. Based on the findings recommendations were made to include diversification of teaching techniques among others.

Keywords: Strategies, Teaching and Learning, Constructive Technique, Direct Instructional Technique

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Authors: Leszek Chybowski, Artur Bejger, Katarzyna Gawdzińska

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Subversion analysis is a tool used in the TRIZ (Theory of Inventive Problem Solving) methodology. This article introduces the history and describes the process of subversion analysis, as well as function analysis and analysis of the resources, used at the design stage when generating possible undesirable situations. The article charts the course of subversion analysis when applied to a fuel injection nozzle of a marine engine. The work describes the fuel injector nozzle as a technological system and presents principles of analysis for the causes of a cracked tip of the nozzle body. The system is modelled with functional analysis. A search for potential causes of the damage is undertaken and a cause-and-effect analysis for various hypotheses concerning the damage is drawn up. The importance of particular hypotheses is evaluated and the most likely causes of damage identified.

Keywords: complex technical system, fuel injector, function analysis, importance analysis, resource analysis, sabotage analysis, subversion analysis, TRIZ (Theory of Inventive Problem Solving)

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Authors: Railly Hugo, Igor Aguilar-Alonso

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Software visualization is a powerful tool for understanding complex software systems. However, current visualization tools often lack features or are difficult to use, limiting their effectiveness. In this paper, we present next-viz, a proposed web-based visualization tool that addresses these challenges. We provide a literature review of existing software visualization techniques and tools and describe the architecture of next-viz in detail. Our proposed tool incorporates state-of-the-art visualization techniques and is designed to be user-friendly and intuitive. We believe next-viz has the potential to advance the field of software visualization significantly.

Keywords: software visualization, literature review, tool proposal, next-viz, web-based, architecture, visualization techniques, user-friendly, intuitive

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Authors: Manisha Mukherjee, Diptarka Saha

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Reliable forecasts of univariate time series data are often necessary for several contexts. ARIMA models are quite popular among practitioners in this regard. Hence, choosing correct parameter values for ARIMA is a challenging yet imperative task. Thus, a stepwise algorithm is introduced to provide automatic and robust estimates for parameters (p; d; q)(P; D; Q) used in seasonal ARIMA models. This process is focused on improvising the overall quality of the estimates, and it alleviates the problems induced due to the unidimensional nature of the methods that are currently used such as auto.arima. The fast and automated search of parameter space also ensures reliable estimates of the parameters that possess several desirable qualities, consequently, resulting in higher test accuracy especially in the cases of noisy data. After vigorous testing on real as well as simulated data, the algorithm doesn’t only perform better than current state-of-the-art methods, it also completely obviates the need for human intervention due to its automated nature.

Keywords: time series, ARIMA, auto.arima, ARIMA parameters, forecast, R function

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Authors: Abdulaziz Alsadhan, Naveed Khan

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In recent years intrusions on computer network are the major security threat. Hence, it is important to impede such intrusions. The hindrance of such intrusions entirely relies on its detection, which is primary concern of any security tool like Intrusion Detection System (IDS). Therefore, it is imperative to accurately detect network attack. Numerous intrusion detection techniques are available but the main issue is their performance. The performance of IDS can be improved by increasing the accurate detection rate and reducing false positive. The existing intrusion detection techniques have the limitation of usage of raw data set for classification. The classifier may get jumble due to redundancy, which results incorrect classification. To minimize this problem, Principle Component Analysis (PCA), Linear Discriminant Analysis (LDA), and Local Binary Pattern (LBP) can be applied to transform raw features into principle features space and select the features based on their sensitivity. Eigen values can be used to determine the sensitivity. To further classify, the selected features greedy search, back elimination, and Particle Swarm Optimization (PSO) can be used to obtain a subset of features with optimal sensitivity and highest discriminatory power. These optimal feature subset used to perform classification. For classification purpose, Support Vector Machine (SVM) and Multilayer Perceptron (MLP) used due to its proven ability in classification. The Knowledge Discovery and Data mining (KDD’99) cup dataset was considered as a benchmark for evaluating security detection mechanisms. The proposed approach can provide an optimal intrusion detection mechanism that outperforms the existing approaches and has the capability to minimize the number of features and maximize the detection rates.

Keywords: Particle Swarm Optimization (PSO), Principle Component Analysis (PCA), Linear Discriminant Analysis (LDA), Local Binary Pattern (LBP), Support Vector Machine (SVM), Multilayer Perceptron (MLP)

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Authors: M. S. Gaafar, S. Y. Marzouk, I. S. Mahmoud, S. Al-Zobaidi

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Makishima and Mackenzie model was used to simulation of acoustic properties (longitudinal and shear ultrasonic wave velocities, elastic moduli theoretically for many tellurite and borate glasses. The model was proposed mainly depending on the values of the experimentally measured density, which are obtained before. In this search work, we are trying to obtain the values of densities of amorphous glasses (as the density depends on the geometry of the network structure of these glasses). In addition, the problem of simulating the slope of linear regression between the experimentally determined bulk modulus and the product of packing density and experimental Young's modulus, were solved in this search work. The results showed good agreement between the experimentally measured values of densities and both ultrasonic wave velocities, and those theoretically determined.

Keywords: glasses, ultrasonic wave velocities, elastic modulus, Makishima & Mackenzie Model

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Authors: Martin H¨ausl, Maximilian Auch, Johannes Forster, Peter Mandl, Alexander Schill

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In order to survive on the market, companies must constantly develop improved and new products. These products are designed to serve the needs of their customers in the best possible way. The creation of new products is also called innovation and is primarily driven by a company’s internal research and development department. However, a new approach has been taking place for some years now, involving external knowledge in the innovation process. This approach is called open innovation and identifies customer knowledge as the most important source in the innovation process. This paper presents a concept of using social media posts as an external source to support the open innovation approach in its initial phase, the Ideation phase. For this purpose, the social media posts are semantically structured with the help of an ontology and the authors are evaluated using graph-theoretical metrics such as density. For the structuring and evaluation of relevant social media posts, we also use the findings of Natural Language Processing, e. g. Named Entity Recognition, specific dictionaries, Triple Tagger and Part-of-Speech-Tagger. The selection and evaluation of the tools used are discussed in this paper. Using our ontology and metrics to structure social media posts enables users to semantically search these posts for new product ideas and thus gain an improved insight into the external sources such as customer needs.

Keywords: idea ontology, innovation management, semantic search, open information extraction

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Authors: Shahul Hamid Khan, S. Santhosh, Abhinav Kumar Sharma

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Environmental performance along with social performance is becoming vital factors for industries to achieve global standards. With a good environmental policy global industries are differentiating them from their competitors. This paper concentrates on multi stage, multi product and multi period manufacturing network. Bi-objective mathematical models for total cost and total emission for the entire forward supply chain are considered. Here five different problems are considered by varying the number of suppliers, manufacturers, and environmental levels, for illustrating the taken mathematical model. GA, and Random search are used for finding the optimal solution. The input parameters of the optimal solution are used to find the tradeoff between the initial investment by the industry and the long term benefit of the environment.

Keywords: closed loop supply chain, genetic algorithm, random search, green supply chain

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Authors: Alaa Allakany, Koji Okamura

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Multicast technology is an efficient and scalable technology for data distribution in order to optimize network resources. However, in the IP network, the responsibility for management of multicast groups is distributed among network routers, which causes some limitations such as delays in processing group events, high bandwidth consumption and redundant tree calculation. Software Defined Networking (SDN) represented by OpenFlow presented as a solution for many problems, in SDN the control plane and data plane are separated by shifting the control and management to a remote centralized controller, and the routers are used as a forwarder only. In this paper we will proposed fast switching mechanism for solving the problem of link failure in multicast tree based on Tabu Search heuristic algorithm and modifying the functions of OpenFlow switch to fasts switch to the pack up sub tree rather than sending to the controller. In this work we will implement multicasting OpenFlow controller, this centralized controller is a core part in our multicasting approach, which is responsible for 1- constructing the multicast tree, 2- handling the multicast group events and multicast state maintenance. And finally modifying OpenFlow switch functions for fasts switch to pack up paths. Forwarders, forward the multicast packet based on multicast routing entries which were generated by the centralized controller. Tabu search will be used as heuristic algorithm for construction near optimum multicast tree and maintain multicast tree to still near optimum in case of join or leave any members from multicast group (group events).

Keywords: multicast tree, software define networks, tabu search, OpenFlow

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Authors: Santosh Kumar Suman, Vinod Kumar Giri

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The goal of this paper is to outline a speed controller of a DC motor by choice of a PID parameters utilizing genetic algorithms (GAs), the DC motor is extensively utilized as a part of numerous applications such as steel plants, electric trains, cranes and a great deal more. DC motor could be represented by a nonlinear model when nonlinearities such as attractive dissemination are considered. To provide effective control, nonlinearities and uncertainties in the model must be taken into account in the control design. The DC motor is considered as third order system. Objective of this paper three type of tuning techniques for PID parameter. In this paper, an independently energized DC motor utilizing MATLAB displaying, has been outlined whose velocity might be examined utilizing the Proportional, Integral, Derivative (KP, KI , KD) addition of the PID controller. Since, established controllers PID are neglecting to control the drive when weight parameters be likewise changed. The principle point of this paper is to dissect the execution of optimization techniques viz. The Genetic Algorithm (GA) for improve PID controllers parameters for velocity control of DC motor and list their points of interest over the traditional tuning strategies. The outcomes got from GA calculations were contrasted and that got from traditional technique. It was found that the optimization techniques beat customary tuning practices of ordinary PID controllers.

Keywords: DC motor, PID controller, optimization techniques, genetic algorithm (GA), objective function, IAE

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Authors: S. H. Borghei, E. Teymourian, M. Mobin, G. M. Komaki, S. Sheikh

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Imperialist competitive algorithm (ICA) is a recent meta-heuristic method that is inspired by the social evolutions for solving NP-Hard problems. The ICA is a population based algorithm which has achieved a great performance in comparison to other meta-heuristics. This study is about developing enhanced ICA approach to solve the cell formation problem (CFP) using sequence data. In addition to the conventional ICA, an enhanced version of ICA, namely EICA, applies local search techniques to add more intensification aptitude and embed the features of exploration and intensification more successfully. Suitable performance measures are used to compare the proposed algorithms with some other powerful solution approaches in the literature. In the same way, for checking the proficiency of algorithms, forty test problems are presented. Five benchmark problems have sequence data, and other ones are based on 0-1 matrices modified to sequence based problems. Computational results elucidate the efficiency of the EICA in solving CFP problems.

Keywords: cell formation problem, group technology, imperialist competitive algorithm, sequence data

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Authors: Benalia Nadia, Zerzouri Nora, Ben Si Ali Nadia

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Abstract: Among the many different modern heuristic optimization methods, genetic algorithms (GA) and the particle swarm optimization (PSO) technique have been attracting a lot of interest. The GA has gained popularity in academia and business mostly because to its simplicity, ability to solve highly nonlinear mixed integer optimization problems that are typical of complex engineering systems, and intuitiveness. The mechanics of the PSO methodology, a relatively recent heuristic search tool, are modeled after the swarming or cooperative behavior of biological groups. It is suitable to compare the performance of the two techniques since they both aim to solve a particular objective function but make use of distinct computing methods. In this article, PSO and GA optimization approaches are used for the parameter tuning of the power system stabilizer and Proportional integral derivative regulator. Load angle and rotor speed variations in the single machine infinite bus bar system is used to measure the performance of the suggested solution.

Keywords: SMIB, genetic algorithm, PSO, transient stability, power system stabilizer, PID

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Authors: Mohsin Talib Mohammed, Zahid A. Khan, Arshad N. Siddiquee

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The wide use of titanium (Ti) materials in medicine gives impetus to a search for development new techniques with elevated properties such as strength, corrosion resistance and Young's modulus close to that of bone tissue. This article presents the most recent state of the art on the use of equal channel angular pressing (ECAP) technique in evolving mechanical characteristics of the ultrafine-grained bio-grade Ti materials. Over past few decades, research activities in this area have grown enormously and have produced interesting results, including achieving the combination of conflicting properties that are desirable for biomedical applications by severe plastic deformation (SPD) processing. A comprehensive review of the most recent work in this area is systematically presented. The challenges in processing ultrafine-grained Ti materials are identified and discussed. An overview of the biomedical Ti alloys processed with ECAP technique is given in this review, along with a summary of their effect on the important mechanical properties that can be achieved by SPD processing. The paper also offers insights in the mechanisms underlying SPD.

Keywords: mechanical properties, ECAP, titanium, biomedical applications

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Authors: R. W. Walker, J. M. Lynch, K. Anderson, R. G. Middleton

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Hip and knee arthritis are two of the commonest conditions that result in elective orthopaedic outpatient referral. At clinic appointments advice given regarding lifestyle modifications or treatment options may not be fully understood by patients. The majority of patients now use the internet to research their condition and use this to inform their decision about treatments. This study assessed the quality of patient information regarding hip and knee arthritis. To assess the quality of patient information regarding knee and hip arthritis available on the internet. Two internet searches were carried out one month apart using the search terms “knee arthritis” and “hip arthritis” on Google, a search engine that accounts for over 90% or internet searches in the UK. Sites were evaluated using the DISCERN instrument, a validated tool for measuring the quality of consumer health information. The first 50 results for each search were analysed by two different observers and discrepancies in scores were reviewed by both observers together and a score was agreed upon. In total 200 search result websites were assessed, of which 84 fulfilled the inclusion criteria. 53% (n=44) were funded directly by commercial healthcare businesses and of these, 70% (n=31) were funded by a surgeon/hospital promoting end-user purchase of surgical intervention. Overall 35% (n=29) websites were “for-profit” information websites where funding was from advertising revenues from pharmaceutical and prosthesis companies. 81% (n=67) offered information about surgical treatments however only 43% (n=36) mentioned the risk of complications of surgery. 67% (n=56) did not have any reference to sources for the information they detailed and 57% (n=47) had no apparent date for the production of the information they offered. Overall 17% (n=14) of websites were judged as being of high quality, with 29% (n=24) being of moderate quality and 54% (n=45) being of low quality. The quality of health information regarding hip and knee arthritis on the internet is highly variable and the majority of websites assessed were of poor quality. A preponderance of websites were funded by a commercial surgical service offering athroplasty at consumer cost, with a further third being funded indirectly via advertising revenues from commercial businesses. The vast majority of websites only mentioned surgery as a treatment and nearly half of all websites did not mention the risks or complications of surgical intervention at all. This has implications for the consent process. As such, Clinicians should be aware of the heterogeneous nature of patient information on the internet and be prepared to advise their patients about good quality websites where further reliable information can be sought.

Keywords: hip osteoarthritis, informed consent, knee osteoarthritis, patient information

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Authors: R. N. Jay A. Ablog, M. N. Dyanne R. Del Carmen, Roma Rose A. Dela Cruz, Joselle Dara M. Estrada, Luke Clifferson M. Gagarin, Florence T. Lang-ay, Ma. Dayanara O. Mariñas, Maria Christina S. Nepa, Jahraine Chyle B. Ocampo, Mark Reynie Renz V. Silva, Jenny Lyn L. Soriano, Loreal Cloe M. Suva, Jackelyn R. Torres

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Background: To date, there is dearth of literature as to the effect of relaxation techniques in lowering the stress level of mothers of children with autism spectrum disorder (ASD). Aim: To investigate the effectiveness of 4-week relaxation techniques in stress level reduction of mothers of children with ASD. Methods: Quasi experimental design. It included 25 mothers (10-experimental, 15-control) who were chosen via purposive sampling. The mothers were recruited in the different SPED centers in Baguio City and La Trinidad and in the community. Statistics used were T-test and Related T-Test. Results: The overall weighted mean score after 4-week training is 2.3, indicating that the relaxation techniques introduced were moderately effective in lowering stress level. Statistical analysis (T-test; CV=4.51>TV=2.26) shown a significant difference in the stress level reduction of mothers in the experimental group pre and post interventions. There is also a significant difference in the stress level reduction in the control and the experimental group (Related T-test; CV=2.08 >TV=2.07). The relaxation techniques introduced were favorable, cost-effective, and easy to perform interventions to decrease stress level.

Keywords: relaxation techniques, mindful eating, progressive muscle relaxation, breathing exercise, autism spectrum disorder

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Authors: Patricia Helena Dos Santos Martins, Mateus Atique, Lucas Oliveira Gomes Ferreira

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There is a growing body of literature that recognizes the importance of bibliometric analysis through the evolutionary nuances of a specific field while shedding light on the emerging areas in that field. Surprisingly, its application in the manufacturing research of vitiviniculture is relatively new and, in many instances, underdeveloped. The aim of this study is to present an overview of the bibliometric methodology, with a particular focus on the Meta-Analytical Approach Theory model – TEMAC, while offering step-by-step results on the available techniques and procedures for carrying out studies about the elements associated with vitiviniculture. Where TEMAC is a method that uses metadata to generate heat maps, graphs of keyword relationships and others, with the aim of revealing relationships between authors, articles and mainly to understand how the topic has evolved over the period study and thus reveal which subthemes were worked on, main techniques and applications, helping to understand that topic under study and guide researchers in generating new research. From the studies carried out using TEMAC, it is possible to raise which are the techniques within the statistical control of processes that are most used within the wine industry and thus assist professionals in the area in the application of the best techniques. It is expected that this paper will be a useful resource for gaining insights into the available techniques and procedures for carrying out studies about vitiviniculture, the cultivation of vineyards, the production of wine, and all the ethnography connected with it.

Keywords: TEMAC, vitiviniculture, statical control of process, quality

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Authors: Christofas Stergianos, Jason Atkin, Herve Morvan

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As air traffic increases, more airports are interested in utilizing optimization methods. Many processes happen in parallel at an airport, and complex models are needed in order to have a reliable solution that can be implemented for ground movement operations. The ground movement for aircraft in an airport, allocating a path to each aircraft to follow in order to reach their destination (e.g. runway or gate), is one process that could be optimized. The Quickest Path Problem with Time Windows (QPPTW) algorithm has been developed to provide a conflict-free routing of vehicles and has been applied to routing aircraft around an airport. It was subsequently modified to increase the accuracy for airport applications. These modifications take into consideration specific characteristics of the problem, such as: the pushback process, which considers the extra time that is needed for pushing back an aircraft and turning its engines on; stand holding where any waiting should be allocated to the stand; and runway sequencing, where the sequence of the aircraft that take off is optimized and has to be respected. QPPTW involves searching for the quickest path by expanding the search in all directions, similarly to Dijkstra’s algorithm. Finding a way to direct the expansion can potentially assist the search and achieve a better performance. We have further modified the QPPTW algorithm to use a heuristic approach in order to guide the search. This new algorithm is based on the A-star search method but estimates the remaining time (instead of distance) in order to assess how far the target is. It is important to consider the remaining time that it is needed to reach the target, so that delays that are caused by other aircraft can be part of the optimization method. All of the other characteristics are still considered and time windows are still used in order to route multiple aircraft rather than a single aircraft. In this way the quickest path is found for each aircraft while taking into account the movements of the previously routed aircraft. After running experiments using a week of real aircraft data from Zurich Airport, the new algorithm (A-star QPPTW) was found to route aircraft much more quickly, being especially fast in routing the departing aircraft where pushback delays are significant. On average A-star QPPTW could route a full day (755 to 837 aircraft movements) 56% faster than the original algorithm. In total the routing of a full week of aircraft took only 12 seconds with the new algorithm, 15 seconds faster than the original algorithm. For real time application, the algorithm needs to be very fast, and this speed increase will allow us to add additional features and complexity, allowing further integration with other processes in airports and leading to more optimized and environmentally friendly airports.

Keywords: a-star search, airport operations, ground movement optimization, routing and scheduling

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Authors: Lavanya Madhuri Bollipo, K. V. Kadambari

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Objective: To discuss key issues in the diagnosis of Parkinson disease (PD), To discuss features influencing PD progression, To discuss importance of brain SPECT data in PD diagnosis, and To discuss the essentiality of machine learning techniques in early diagnosis of PD. An accurate and early diagnosis of PD is nowadays a challenge as clinical symptoms in PD arise only when there is more than 60% loss of dopaminergic neurons. So far there are no laboratory tests for the diagnosis of PD, causing a high rate of misdiagnosis especially when the disease is in the early stages. Recent neuroimaging studies with brain SPECT using 123I-Ioflupane (DaTSCAN) as radiotracer shown to be widely used to assist the diagnosis of PD even in its early stages. Machine learning techniques can be used in combination with image analysis procedures to develop computer-aided diagnosis (CAD) systems for PD. This paper addressed recent studies involving diagnosis of PD in its early stages using brain SPECT data with Machine Learning Techniques.

Keywords: Parkinson disease (PD), dopamine transporter, single-photon emission computed tomography (SPECT), support vector machine (SVM)

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Authors: Mustafa Jahanara

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The present research was carried out in order to investigate the relationship between meaning in life and hope with depression, anxiety and stress in Afghan Refugees in Alborz province in Iran. In this research, method of study is a descriptive correlation type. One hundred and fifty-eight Afghan refugees (64 male, 94 female) participated in this study. All participants completed the Meaning in Life Questionnaires (MLQ), Hope Scale (HS), and The Depression Anxiety Stress Scales (DASS-21). The results revealed that Meaning in Life was positively associated with hope, presence of meaning, search of meaning, and negatively associated with depression and anxiety. Hope was positively associated with presence of meaning and search of meaning, and hope was negatively associated with depression, anxiety, and stress. Depression, anxiety, and stress were positively correlated with each other. Meaning in life and hope could influence on mental health.

Keywords: Afghan refugees, meaning of life, hope, depression, anxiety and stress

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Authors: Tung-Hui Hsu, Wen-Yuh Jywe

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Five-axis computer numerical control (CNC) machine tools (three linear and two rotary axes) are ideally suited to the fabrication of complex work pieces, such as dies, turbo blades, and cams. The locations of the axis average line and centerline of the rotary axes strongly influence the performance of these machines; however, techniques to compensate for eccentric error in the rotary axes remain weak. This paper proposes optical (Non-Bar) techniques capable of calibrating five-axis CNC machine tools and compensating for eccentric error in the rotary axes. This approach employs the measurement path in ISO/CD 10791-6 to determine the eccentric error in two rotary axes, for which compensatory measures can be implemented. Experimental results demonstrate that the proposed techniques can improve the performance of various five-axis CNC machine tools by more than 90%. Finally, a result of the cutting test using a B-type five-axis CNC machine tool confirmed to the usefulness of this proposed compensation technique.

Keywords: calibration, compensation, rotary axis, five-axis computer numerical control (CNC) machine tools, eccentric error, optical calibration system, ISO/CD 10791-6

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Authors: Weiying Wang, Qi Li, Huiwen Deng, Weirong Chen

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The abrupt light change and uneven illumination will make the PV system get rid of constant output power, which will affect the efficiency of the grid connected inverter as well as the stability of the system. To solve this problem, this paper presents a strategy to control the stability of photovoltaic power system under the condition of partial shading of PV array, leading to constant power output, improving the capacity of resisting interferences. Firstly, a photovoltaic cell model considering the partial shading is established, and the backtracking search algorithm is used as the maximum power point to track algorithm under complex illumination. Then, the energy storage system based on the constant power control strategy is used to achieve constant power output. Finally, the effectiveness and correctness of the proposed control method are verified by the joint simulation of MATLAB/Simulink and RTLAB simulation platform.

Keywords: backtracking search algorithm, constant power control, hybrid system, partial shading, stability

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Authors: Siddarth Kannan

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Objectives: Deep Brain Stimulation (DBS) and Motor Cortex stimulation (MCS) are innovative interventions in order to treat various neuropathic pain disorders such as post-stroke pain. While each treatment has a varying degree of success in managing pain, comparative analysis has not yet been performed, and the success rates of these techniques using validated, objective pain scores have not been synthesised. The aim of this study was to compare the effect of pain relief offered by MCS and DBS on patients with post-stroke pain and to assess if either of these procedures offered better results. Methods: A systematic review and meta-analysis were conducted in accordance with PRISMA guidelines (PROSPEROID CRD42021277542). Three databases were searched, and articles published from 2000 to June 2023 were included (last search date 25 June 2023). Meta-analysis was performed using random effects models. We evaluated the performance of DBS or MCS by assessing studies that reported pain relief using the Visual Analogue Scale (VAS). Data analysis of descriptive statistics was performed using SPSS (Version 27; IBM; Armonk; NY; USA). R statistics (Rstudio Version 4.0.1) was used to perform meta-analysis. Results: Of the 478 articles identified, 27 were included in the analysis (232 patients- 117 DBS & 115 MCS). The pooled number of patients who improved after DBS was 0.68 (95% CI, 0.57-0.77, I2=36%). The pooled number of patients who improved after MCS was 0.72 (95% CI, 0.62-0.80, I2=59%). Further sensitivity analysis was done to include only studies with a minimum of 5 patients in order to assess if there was any impact on the overall results. Nine studies each for DBS and MCS met these criteria. There seemed to be no significant difference in results. Conclusions: The use of surgical interventions such as DBS and MCS is an upcoming field for the treatment of post-stroke pain, with limited studies exploring and comparing these two techniques. While our study shows that MCS might be a slightly better treatment option, further research would need to be done in order to determine the appropriate surgical intervention for post-stroke pain.

Keywords: post-stroke pain, deep brain stimulation, motor cortex stimulation, pain relief

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Authors: Lee Jeong Min, Lee Mi Hee, Eo Yang Dam

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Geospatial feature extraction is a very important issue in the remote sensing research. In the meantime, the image classification based on statistical techniques, but, in recent years, data mining and machine learning techniques for automated image processing technology is being applied to remote sensing it has focused on improved results generated possibility. In this study, artificial neural network and decision tree technique is applied to classify the high-resolution satellite images, as compared to the MLC processing result is a statistical technique and an analysis of the pros and cons between each of the techniques.

Keywords: remote sensing, artificial neural network, decision tree, maximum likelihood classification

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Authors: Eyibo Ebengeobong Eddie

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Taking advantage of the sun's position to design buildings to ensure human comfort has always been an important aspect in an architectural design. Using cheap and less expensive methods and systems for gaining solar energy, heating and cooling has always been a great advantage to users and occupants of a building. As the years run by, daily techniques and methods have been created and more are being discovered to help reduce the energy demands of any building. Architects have made effective use of a buildings orientation, building materials and elements to achieve less energy demand. This paper talks about the various techniques used in solar heating and passive cooling of buildings and through water techniques and concepts to achieve thermal comfort.

Keywords: comfort, passive, solar, water

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Authors: Rui Brito

Abstract:

This contribution regards a literature review of inventory management that is a relevant topic for the firms, due to its important use of capital with implications in firm’s profitability within the complexity of a more competitive and globalized world. Firms look for small inventories in order to reduce holding costs, namely opportunity cost, warehousing and handling costs, deterioration and being out of style, but larger inventories are required by some reasons, such as customer service, ordering cost, transportation cost, supplier’s payment to reduce unit costs or to take advantage of price increase in the near future, and equipment setup cost. Thus, management shall address a trade-off between small inventories and larger inventories. This literature review concerns three types of inventory (spare parts, safety stock, and vendor) whose management usually is beyond the scope of logistics. The applied methodology consisted of an online search of databases regarding scientific documents in English, namely Elsevier, Springer, Emerald, Wiley, and Taylor & Francis, but excluding books except if edited, using search engines, such as Google Scholar and B-on. The search was based on three keywords/strings (themes) which had to be included just as in the article title, suggesting themes were very relevant to the researchers. The whole search period was between 2009 and 2018 with the aim of collecting between twenty and forty studies considered relevant within each of the key words/strings specified. Documents were sorted by relevance and to prevent the exclusion of the more recent articles, based on lower quantity of citations partially due to less time to be cited in new research articles, the search period was divided into two sub-periods (2009-2015 and 2016-2018). The number of surveyed articles by theme showed a variation from 40 to 200 and the number of citations of those articles showed a wider variation from 3 to 216. Selected articles from the three themes were analyzed and the first seven of the first sub-period and the first three of the second sub-period with more citations were read in full to make a synopsis of each article. Overall, the findings show that the majority of article types were models, namely mathematical, although with different sub-types for each theme. Almost all articles suggest further studies, with some mentioning it for their own author(s), which widen the diversity of the previous research. Identified research gaps concern the use of surveys to know which are the models more used by firms, the reasons for not using the models with more performance and accuracy, and which are the satisfaction levels with the outcomes of the inventories management and its effect on the improvement of the firm’s overall performance. The review ends with the limitations and contributions of the study.

Keywords: inventory management, safety stock, spare parts inventory, vendor managed inventory

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Authors: Muhammad Usman

Abstract:

Pattern extraction has been done in past to extract hidden and interesting patterns from large datasets. Recently, advancements are being made in these techniques by providing the ability of multi-level mining, effective dimension reduction, advanced evaluation and visualization support. This paper focuses on reviewing the current techniques in literature on the basis of these parameters. Literature review suggests that most of the techniques which provide multi-level mining and dimension reduction, do not handle mixed-type data during the process. Patterns are not extracted using advanced algorithms for large datasets. Moreover, the evaluation of patterns is not done using advanced measures which are suited for high-dimensional data. Techniques which provide visualization support are unable to handle a large number of rules in a small space. We present a theoretical model to handle these issues. The implementation of the model is beyond the scope of this paper.

Keywords: association rule mining, data mining, data warehouses, visualization of association rules

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Authors: Aftab Hameed Memon, Shadab Noor, Muhammad Akram Akhund

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Lean construction is a philosophy adopted in the construction industry to increase the value of a project by reducing waste and improving construction productivity. Lean emphasizes on maximizing the value of a project with less expenditure. Globally, lean philosophy has received wider popularity in construction sector. Lean construction has supported the practitioners with several tools and techniques to implement at various stages of a construction project. Following the global trends, this study has investigated the lean practice in Pakistan. The level of implementation of different lean tools and techniques altogether with potential benefits experienced by its implementation in construction projects of Pakistan is analyzed. To achieve the targets, the opinion was sought by the practitioners involved in handling construction projects representing four stakeholders that are a client, consultant, contractors and material suppliers through a structured questionnaire. A total of 34 completed questionnaires were collected and then statistically analyzed. The findings of the analysis have highlighted that pull approach, work standardization, just in time, increase visualization tools, integrated project delivery method and fail-safe for quality are common lean techniques implemented in the local construction industry. While reduction in waste, client’s satisfaction, improved communication, visual control and proper task management are major benefits of the lean construction application.

Keywords: lean construction, lean tools and techniques, lean benefits, waste reduction, Pakistan

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Authors: Jakob Renko, Deja Praprotnik, Kristina Martinovič, Igor Karnjuš

Abstract:

Introduction: Catheter-related bloodstream infections are a major burden for healthcare and patients. Although infections of this type cannot be completely avoided, they can be reduced by taking preventive measures. The aim of this study is to review and analyze the existing literature on preventive interventions to prevent central venous catheters (CVC) infections. Methods: A systematic literature review was carried out. The international databases CINAHL, Medline, PubMed, and Web of Science were searched using the search strategy: "catheter-related infections" AND "intensive care units" AND "prevention" AND "central venous catheter." Articles that met the inclusion and exclusion criteria were included in the study. The literature search flow is illustrated by the PRISMA diagram. The descriptive research method was used to analyze the data. Results: Out of 554 search results, 22 surveys were included in the final analysis. We identified seven relevant preventive measures to prevent CVC infections: washing the whole body with chlorhexidine gluconate (CHG) solution, disinfecting the CVC entry site with CHG solution, use of CHG or silver dressings, alcohol protective caps, CVC care education, selecting appropriate catheter and multicomponent care bundles. Discussion and conclusions: Both single interventions and multicomponent care bundles have been shown to be currently effective measures to prevent CVC infections in adult patients in the ICU. None of the measures identified stood out in terms of their effectiveness. Prevention work to reduce CVC infections in the ICU is a complex process that requires the simultaneous consideration of several factors.

Keywords: central venous access, critically ill patients, hospital-acquired complications, prevention

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Authors: Yena Lee, Vassilis M. Charitopoulos, Karthik Thyagarajan, Ian Morris, Jose M. Pinto, Lazaros G. Papageorgiou

Abstract:

With globalisation, the need to have better coordination of production and distribution decisions has become increasingly important for industrial gas companies in order to remain competitive in the marketplace. In this work, we investigate a problem that integrates production, inventory, and routing decisions in a liquid oxygen supply chain. The oxygen supply chain consists of production facilities, external third-party suppliers, and multiple customers, including hospitals and industrial customers. The product produced by the plants or sourced from the competitors, i.e., third-party suppliers, is distributed by a fleet of heterogenous vehicles to satisfy customer demands. The objective is to minimise the total operating cost involving production, third-party, and transportation costs. The key decisions for production include production and inventory levels and product amount from third-party suppliers. In contrast, the distribution decisions involve customer allocation, delivery timing, delivery amount, and vehicle routing. The optimisation of the coordinated production, inventory, and routing decisions is a challenging problem, especially when dealing with large-size problems. Thus, we present a two-stage procedure to solve the integrated problem efficiently. First, the problem is formulated as a mixed-integer linear programming (MILP) model by simplifying the routing component. The solution from the first-stage MILP model yields the optimal customer allocation, production and inventory levels, and delivery timing and amount. Then, we fix the previous decisions and solve a detailed routing. In the second stage, we propose a column generation scheme to address the computational complexity of the resulting detailed routing problem. A case study considering a real-life oxygen supply chain in the UK is presented to illustrate the capability of the proposed models and solution method. Furthermore, a comparison of the solutions from the proposed approach with the corresponding solutions provided by existing metaheuristic techniques (e.g., guided local search and tabu search algorithms) is presented to evaluate the efficiency.

Keywords: production planning, inventory routing, column generation, mixed-integer linear programming

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