Search results for: fuzzy multiple objective programming

Authors: C. Babu Rao, Pandian Chelliah

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Owing to their reliability, a number of fluorescent spectra based fiber optic sensors have been developed for detection and identification of hazardous chemicals such as explosives, narcotics etc. In High security regions, such as airports, it is important to monitor simultaneously multiple locations. This calls for deployment of a portable sensor at each location. However, the selectivity and sensitivity of these techniques depends on the spectral resolution of the spectral analyzer. The better the resolution the larger the repertoire of chemicals that can be detected. A portable unit will have limitations in meeting these requirements. Optical fibers can be employed for collecting and transmitting spectral signal from the portable sensor head to a sensitive central spectral analyzer (CSA). For multipoint sensing, optical multiplexing of multiple sensor heads with CSA has to be adopted. However with multiplexing, when one sensor head is connected to CSA, the rest may remain unconnected for the turn-around period. The larger the number of sensor heads the larger this turn-around time will be. To circumvent this imitation, we propose in this paper, an optical encoding methodology to use multiple portable sensor heads connected to a single CSA. Each portable sensor head is assigned an unique address. Spectra of every chemical detected through this sensor head, are encoded by its unique address and can be identified at the CSA end. The methodology proposed is demonstrated through a simulation using Matlab SIMULINK.

Keywords: optical encoding, fluorescence, multipoint sensing

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Authors: Aderet Pantierer, Shmuel Pantierer, Atif Saeed, Amir Elzawawy

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In recent years, air travel has seen volatile growth. Due to this growth, the maximization of efficiency and space utilization has been a major issue for aircraft manufacturers. Elongation of the wingspan of aircraft has resulted in increased lift; and, thereby, efficiency. However, increasing the wingspan of aircraft has been detrimental to the manufacturing process and has led to airport congestion and required airport reconfiguration to accommodate the extended wingspans of aircraft. This project outlines differing wing configurations of a commercial aircraft and the effects on the aerodynamic loads produced. Multiple wing configurations are analyzed using Finite Element Models. These models are then validated by testing one wing configuration in a wind tunnel under laminar flow and turbulent flow conditions. The wing configurations to be tested include high and low wing aircraft, as well as various combinations of the two, including a unique model hereon referred to as an infinity wing. The infinity wing configuration consists of both a high and low wing, with the two wings connected by a vertical airfoil. This project seeks to determine if a wing configuration consisting of multiple airfoils produces more lift than the standard wing configurations and is able to provide a solution to manufacturing limitations as well as airport congestion. If the analysis confirms the hypothesis, a trade study will be performed to determine if and when an arrangement of multiple wings would be cost-effective.

Keywords: aerodynamics, aircraft design, aircraft efficiency, wing configuration, wing design

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Authors: Revoti Prasad Bora, Nikita Katyal

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Promotion is a key element in the retail business. Thus, analysis of promotions to quantify their effectiveness in terms of Revenue and/or Margin is an essential activity in the retail industry. However, measuring the sales/revenue uplift is based on estimations, as the actual sales/revenue without the promotion is not present. Further, the presence of Halo and Cannibalization in a multiple parallel promotions’ scenario complicates the problem. Calculating Baseline by considering inter-brand/competitor items or using Halo and Cannibalization's impact on Revenue calculations by considering Baseline as an interpretation of items’ unit sales in neighboring nonpromotional weeks individually may not capture the overall Revenue uplift in the case of multiple parallel promotions. Hence, this paper proposes a Machine Learning based method for calculating the Revenue uplift by considering the Halo and Cannibalization impact on the Baseline and the Revenue. In the first section of the proposed methodology, Baseline of an item is calculated by incorporating the impact of the promotions on its related items. In the later section, the Revenue of an item is calculated by considering both Halo and Cannibalization impacts. Hence, this methodology enables correct calculation of the overall Revenue uplift due a given promotion.

Keywords: Halo, Cannibalization, promotion, Baseline, temporary price reduction, retail, elasticity, cross price elasticity, machine learning, random forest, linear regression

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Authors: Ng Liang Shen, Hau Yuan Wen

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Arrhythmia analysis of ECG signal plays a major role in diagnosing most of the cardiac diseases. Therefore, a single arrhythmia detection of an electrocardiographic (ECG) record can determine multiple pattern of various algorithms and match accordingly each ECG beats based on Machine Learning supervised learning. These researchers used different features and classification methods to classify different arrhythmia types. A major problem in these studies is the fact that the symptoms of the disease do not show all the time in the ECG record. Hence, a successful diagnosis might require the manual investigation of several hours of ECG records. The point of this paper presents investigations cardiovascular ailment in Electrocardiogram (ECG) Signals for Cardiac Arrhythmia utilizing examination of ECG irregular wave frames via heart beat as correspond arrhythmia which with Machine Learning Pattern Recognition.

Keywords: electrocardiogram, ECG, classification, machine learning, pattern recognition, detection, QRS

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Authors: Garadi Ahmed, Boubakar S. Bouazza

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The Zero Cross-Correlation (C, w) code is a family of binary sequences of length C and constant Hamming-weight, the cross correlation between any two sequences equal zero. In this paper, we evaluate the performance of ZCC code based on Balanced Incomplete Block Design (BIBD) for Spectral Amplitude Coding Optical Code Division Multiple Access (SAC-OCDMA) system using direct detection. The BER obtained is better than 10-9 for five simultaneous users.

Keywords: spectral amplitude coding-optical code-division-multiple-access (SAC-OCDMA), phase induced intensity noise (PIIN), balanced incomplete block design (BIBD), zero cross-correlation (ZCC)

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Authors: A. Asgharzadeh, M. Maroufi

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5G mobile communication system has drawn more and more attention. The 5G system needs to provide three different types of services, including enhanced Mobile BroadBand (eMBB), massive machine-type communication (mMTC), and ultra-reliable and low-latency communication (URLLC). Universal Filtered Multi-Carrier (UFMC), Filter Bank Multicarrier (FBMC), and Filtered Orthogonal Frequency Division Multiplexing (f-OFDM) are suggested as a well-known candidate waveform for the coming 5G system. Themachine-to-machine (M2M) communications are one of the essential applications in 5G, and it involves exchanging of concise messages with a very short latency. However, in UFMC systems, the subcarriers are grouped into subbands but f-OFDM only one subband covers the entire band. Furthermore, in FBMC, a subband includes only one subcarrier, and the number of subbands is the same as the number of subcarriers. This paper mainly discusses the performance of UFMC with different parameters for the UFMC system. Also, paper shows that UFMC is the best choice outperforming OFDM in any case and FBMC in case of very short packets while performing similarly for long sequences with channel estimation techniques for Interleave Division Multiple Access (IDMA) systems.

Keywords: universal filtered multi-carrier technique, UFMC, interleave division multiple access, IDMA, fifth-generation, subband

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Authors: Y. Smirlis, G. Koronakos, S. Plitsos

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Shipbrokers assist the ship companies in chartering or selling and buying vessels, acting as intermediates between them and the market. They facilitate deals, providing their expertise, negotiating skills, and knowledge about ship market bargains. Their role is very important as it affects the profitability and market position of a shipping company. Due to their significant contribution, the shipping companies have to employ systematic procedures to evaluate the shipbrokers’ services in order to select the best and, consequently, to achieve the best deals. Towards this, in this paper, we consider shipbrokers as financial service providers, and we formulate the problem of evaluating and selecting shipbrokers’ services as a multi-criteria decision making (MCDM) procedure. The proposed methodology comprises a first normalization step to adjust different scales and orientations of the criteria and a second step that includes the mathematical model to evaluate the performance of the shipbrokers’ services involved in the assessment. The criteria along which the shipbrokers are assessed may refer to their size and reputation, the potential efficiency of the services, the terms and conditions imposed, the expenses (e.g., commission – brokerage), the expected time to accomplish a chartering or selling/buying task, etc. and according to our modelling approach these criteria may be assigned different importance. The mathematical programming model performs a comparative assessment and estimates for the shipbrokers involved in the evaluation, a relative score that ranks the shipbrokers in terms of their potential performance. To illustrate the proposed methodology, we present a case study in which a shipping company evaluates and selects the most suitable among a number of sale and purchase (S&P) brokers. Acknowledgment: This study is supported by the OptiShip project, implemented within the framework of the National Recovery Plan and Resilience “Greece 2.0” and funded by the European Union – NextGenerationEU programme.

Keywords: shipbrokers, multi-criteria decision making, mathematical programming, service-provider selection

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Authors: Asma Alzahrani, Elizabeth Stojanovski

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This study investigated factors that influence mathematics achievement based on a sample of ninth-grade students (N  =  21,444) from the High School Longitudinal Study of 2009 (HSLS09). Key aspects studied included efficacy in mathematics, interest and enjoyment of mathematics, identity with mathematics and future utility beliefs and how these influence mathematics achievement. The predictability of mathematics achievement based on these factors was assessed using correlation coefficients and multiple linear regression. Spearman rank correlations and multiple regression analyses indicated positive and statistically significant relationships between the explanatory variables: mathematics efficacy, identity with mathematics, interest in and future utility beliefs with the response variable, achievement in mathematics.

Keywords: Mathematics achievement, math efficacy, mathematics interest, factors influence

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Authors: Nicoly Coelho, Eduardo Vieira Vilas Boas, Paulo Orestes Formigoni

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Faced with the remarkable developments in the various segments of modern engineering, provided by the increasing technological development, professionals of all educational areas need to overcome the difficulties generated due to the good understanding of those who are starting their academic journey. Aiming to overcome these difficulties, this article aims at an introduction to the basic study of numerical methods applied to fluid mechanics and thermodynamics, demonstrating the modeling and simulations with its substance, and a detailed explanation of the fundamental numerical solution for the use of finite difference method, using SCILAB, a free software easily accessible as it is free and can be used for any research center or university, anywhere, both in developed and developing countries. It is known that the Computational Fluid Dynamics (CFD) is a necessary tool for engineers and professionals who study fluid mechanics, however, the teaching of this area of knowledge in undergraduate programs faced some difficulties due to software costs and the degree of difficulty of mathematical problems involved in this way the matter is treated only in postgraduate courses. This work aims to bring the use of DFC low cost in teaching Transport Phenomena for graduation analyzing a small classic case of fundamental thermodynamics with Scilab® program. The study starts from the basic theory involving the equation the partial differential equation governing heat transfer problem, implies the need for mastery of students, discretization processes that include the basic principles of series expansion Taylor responsible for generating a system capable of convergence check equations using the concepts of Sassenfeld, finally coming to be solved by Gauss-Seidel method. In this work we demonstrated processes involving both simple problems solved manually, as well as the complex problems that required computer implementation, for which we use a small algorithm with less than 200 lines in Scilab® in heat transfer study of a heated plate in rectangular shape on four sides with different temperatures on either side, producing a two-dimensional transport with colored graphic simulation. With the spread of computer technology, numerous programs have emerged requiring great researcher programming skills. Thinking that this ability to program DFC is the main problem to be overcome, both by students and by researchers, we present in this article a hint of use of programs with less complex interface, thus enabling less difficulty in producing graphical modeling and simulation for DFC with an extension of the programming area of experience for undergraduates.

Keywords: numerical methods, finite difference method, heat transfer, Scilab

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Authors: Othmane Touri, Sanaa El Filali, El Habib Benlahmar

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Natural Language Processing (NLP) has gained significant attention lately. It has proved its ability to analyze and extract insights from unstructured text data in various languages. It is found that one of the most popular NLP applications is sentiment analysis which aims to identify the sentiment expressed in a piece of text, such as positive, negative, or neutral, in multiple languages. While there are several multilingual NLP models available for sentiment analysis, there is a need to investigate their effectiveness in different contexts and applications. In this study, we aim to investigate the effectiveness of different multilingual NLP models for sentiment analysis on a dataset of online product reviews in multiple languages. The performance of several NLP models, including Google Cloud Natural Language API, Microsoft Azure Cognitive Services, Amazon Comprehend, Stanford CoreNLP, spaCy, and Hugging Face Transformers are being compared. The models based on several metrics, including accuracy, precision, recall, and F1 score, are being evaluated and compared to their performance across different categories of product reviews. In order to run the study, preprocessing of the dataset has been performed by cleaning and tokenizing the text data in multiple languages. Then training and testing each model has been applied using a cross-validation approach where randomly dividing the dataset into training and testing sets and repeating the process multiple times has been used. A grid search approach to optimize the hyperparameters of each model and select the best-performing model for each category of product reviews and language has been applied. The findings of this study provide insights into the effectiveness of different multilingual NLP models for Multilingual Sentiment Analysis and their suitability for different languages and applications. The strengths and limitations of each model were identified, and recommendations for selecting the most performant model based on the specific requirements of a project were provided. This study contributes to the advancement of research methods in multilingual NLP and provides a practical guide for researchers and practitioners in the field.

Keywords: NLP, multilingual, sentiment analysis, texts

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Authors: Mohd Izzat Md. Nor, Norfazlina Jaffar, Noor Zaitulakma Md. Zain, Nur Izyanti Mohd Suppian, Subhashini Balakrishnan, Geetha Kandavello

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During the Coronavirus (COVID-19) pandemic, Malaysia has been focusing on building herd immunity by introducing vaccination programs into the community. Hospital Standard Operating Procedures (SOP) were developed to prevent inpatient transmission. Objective: In this study, we focus on the positivity rate of inpatient Person Under Surveillance (PUS) becoming COVID-19 positive and compare this to the National rate in order to see the outcomes of the patient who becomes COVID-19 positive in relation to their vaccination status. Methodology: This is a retrospective observational study carried out from 1 January until 30 March 2022 in Institut Jantung Negara (IJN). There were 5,255 patients admitted during the time of this study. Pre-admission Polymerase Chain Reaction (PCR) swab was done for all patients. Patients with positive PCR on pre-admission screening were excluded. The patient who had exposure to COVID-19-positive staff or patients during hospitalization was defined as PUS and were quarantined and monitored for potential COVID-19 infection. Their frequency and risk of exposure (WHO definition) were recorded. A repeat PCR swab was done for PUS patients that have clinical deterioration with or without COVID symptoms and on their last day of quarantine. The severity of COVID-19 infection was defined as category 1-5A. All patients' vaccination status was recorded, and they were divided into three groups: fully immunised, partially immunised, and unvaccinated. We analyzed the positivity rate of PUS patients becoming COVID-positive, outcomes, and correlation with the vaccination status. Result: Total inpatient PUS to patients and staff was 492; only 13 became positive, giving a positivity rate of 2.6%. Eight (62%) had multiple exposures. The majority, 8/13(72.7%), had a high-risk exposure, and the remaining 5 had medium-risk exposure. Four (30.8%) were boostered, 7(53.8%) were fully vaccinated, and 2(15.4%) were partial/unvaccinated. Eight patients were in categories 1-2, whilst 38% were in categories 3-5. Vaccination status did not correlate with COVID-19 Category (P=0.641). One (7.7%) patient died due to COVID-19 complications and sepsis. Conclusion: Within the first quarter of 2022, our institution's positivity rate (2.6%) is significantly lower than the country's (14.4%). High-risk exposure and multiple exposures to positive COVID-19 cases increased the risk of PUS becoming COVID-19 positive despite their underlying vaccination status.

Keywords: COVID-19, boostered, high risk, Malaysia, quarantine, vaccination status

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Authors: Mohammedi Ferhate

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This work presents details of the study of the entire flow inside the facility where the exothermic chemical reaction process in the chemical laser cavity is analyzed. In our paper we will describe the principles of chemical lasers where flow reversal is produced by chemical reactions. We explain the device for converting chemical potential energy laser energy. We see that the phenomenon thus has an explosive trend. Finally, the feasibility and effectiveness of the proposed method is demonstrated by computer simulation

Keywords: genetic, lasers, nozzle, programming

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Authors: M. Tahir Demirsel, Mustafa Atsan

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Many elements of the environment in which businesses operate today leave them faced with unexpected threats and opportunities. One of the major threats is business crisis. The crisis is a state of affairs in a business wherein the executives must take urgent and unprecedented action to try to save the business from failure. In order to survive in the business environment, organizations should be prepared for the potential crises. Technological developments, uncertainty in the market and the intense competition increase the probability of encountering a crisis for organizations. Therefore, by acting proactively to predict crisis, to detect signals of crisis and be prepared for a crisis by taking necessary precautions accordingly, is of great importance for businesses. In this context, the objective of this study is to reveal that how much organizations are proactive and can predict the future crises and investigate whether they are prepared for possible crises or not. The research was conducted on 222 business executives in one of the major industrial zones of Turkey, Konya Organized Industrial Zone (KOS). The findings are analyzed through descriptive statistics and multiple regression analysis. According to the results, it has been observed that organizations cannot predict the crisis signals and are not prepared for potential crises.

Keywords: crisis preparedness, crisis signals, industrial organizations, proactivity

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Authors: Fiona Lord

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This paper presents research on strengthening urban governance and planning practices for sustainable and regenerative city transformations looking at urban governance in Cambodia as a case study. Transformations to urban sustainability and regeneration require systemic and long-term transformation processes, across multiple levels of society and inclusive of multiple urban actors. This paper presents the emerging findings of a qualitative case study comparing the urban governance and planning practices in two of Cambodia's secondary cities - Battambang and Sihanoukville. The lessons learned have broader implications for how governance and planning can be strengthened to initiate and sustain urban sustainability transformations in other developing country cities of Cambodia and the Southeast Asia region.

Keywords: Cambodia, planning practices, urban governance, urban sustainability transformations

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Authors: Lucille Alonso, Florent Renard

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The characterizations of urban heat island (UHI) and their interactions with climate change and urban climates are the main research and public health issue, due to the increasing urbanization of the population. These solutions require a better knowledge of the UHI and micro-climate in urban areas, by combining measurements and modelling. This study is part of this topic by evaluating microclimatic conditions in dense urban areas in the Lyon Metropolitan Area (France) using a combination of data traditionally used such as topography, but also from LiDAR (Light Detection And Ranging) data, Landsat 8 satellite observation and Sentinel and ground measurements by bike. These bicycle-dependent weather data collections are used to build the database of the variable to be modelled, the air temperature, over Lyon’s hyper-center. This study aims to model the air temperature, measured during 6 mobile campaigns in Lyon in clear weather, using multiple linear regressions based on 33 explanatory variables. They are of various categories such as meteorological parameters from remote sensing, topographic variables, vegetation indices, the presence of water, humidity, bare soil, buildings, radiation, urban morphology or proximity and density to various land uses (water surfaces, vegetation, bare soil, etc.). The acquisition sources are multiple and come from the Landsat 8 and Sentinel satellites, LiDAR points, and cartographic products downloaded from an open data platform in Greater Lyon. Regarding the presence of low, medium, and high vegetation, the presence of buildings and ground, several buffers close to these factors were tested (5, 10, 20, 25, 50, 100, 200 and 500m). The buffers with the best linear correlations with air temperature for ground are 5m around the measurement points, for low and medium vegetation, and for building 50m and for high vegetation is 100m. The explanatory model of the dependent variable is obtained by multiple linear regression of the remaining explanatory variables (Pearson correlation matrix with a |r| < 0.7 and VIF with < 5) by integrating a stepwise sorting algorithm. Moreover, holdout cross-validation is performed, due to its ability to detect over-fitting of multiple regression, although multiple regression provides internal validation and randomization (80% training, 20% testing). Multiple linear regression explained, on average, 72% of the variance for the study days, with an average RMSE of only 0.20°C. The impact on the model of surface temperature in the estimation of air temperature is the most important variable. Other variables are recurrent such as distance to subway stations, distance to water areas, NDVI, digital elevation model, sky view factor, average vegetation density, or building density. Changing urban morphology influences the city's thermal patterns. The thermal atmosphere in dense urban areas can only be analysed on a microscale to be able to consider the local impact of trees, streets, and buildings. There is currently no network of fixed weather stations sufficiently deployed in central Lyon and most major urban areas. Therefore, it is necessary to use mobile measurements, followed by modelling to characterize the city's multiple thermal environments.

Keywords: air temperature, LIDAR, multiple linear regression, surface temperature, urban heat island

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Authors: Donglan Zha, Jiansong Si

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Because of its flexibility, CES attracts much interest in economic growth and programming models, and the macroeconomics or micro-macro models. This paper focuses on the development, estimating methods of CES production function considering energy as an input. We leave for future research work of relaxing the assumption of constant returns to scale, the introduction of potential input factors, and the generalization method of the optimal nested form of multi-factor production functions.

Keywords: bias of technical change, CES production function, elasticity of substitution, energy input

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Authors: Seyedmirsajad Mokhtarimousavi, Danial Talebi, Hamidreza Asgari

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Gate Assignment Problem (GAP) is one of the most substantial issues in airport operation. In principle, GAP intends to maintain the maximum capacity of the airport through the best possible allocation of the resources (gates) in order to reach the optimum outcome. The problem involves a wide range of dependent and independent resources and their limitations, which add to the complexity of GAP from both theoretical and practical perspective. In this study, GAP was mathematically formulated as a three-objective problem. The preliminary goal of multi-objective formulation was to address a higher number of objectives that can be simultaneously optimized and therefore increase the practical efficiency of the final solution. The problem is solved by applying the second version of Non-dominated Sorting Genetic Algorithm (NSGA-II). Results showed that the proposed mathematical model could address most of major criteria in the decision-making process in airport management in terms of minimizing both airport/airline cost and passenger walking distance time. Moreover, the proposed approach could properly find acceptable possible answers.

Keywords: airport management, gate assignment problem, mathematical modeling, genetic algorithm, NSGA-II

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Authors: Marina Franulovic, Robert Basan, Bozidar Krizan

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Constitutive modelling of material behaviour is becoming increasingly important in prediction of possible failures in highly loaded engineering components, and consequently, optimization of their design. In order to account for large number of phenomena that occur in the material during operation, such as kinematic hardening effect in low cycle fatigue behaviour of steels, complex nonlinear material models are used ever more frequently, despite of the complexity of determination of their parameters. As a method for the determination of these parameters, genetic algorithm is good choice because of its capability to provide very good approximation of the solution in systems with large number of unknown variables. For the application of genetic algorithm to parameter identification, inverse analysis must be primarily defined. It is used as a tool to fine-tune calculated stress-strain values with experimental ones. In order to choose proper objective function for inverse analysis among already existent and newly developed functions, the research is performed to investigate its influence on material behaviour modelling.

Keywords: genetic algorithm, kinematic hardening, material model, objective function

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Authors: A. M. John-Otumu, M. M. Rahman, O. C. Nwokonkwo, M. C. Onuoha

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Online social media networks have long served as a primary arena for group conversations, gossip, text-based information sharing and distribution. The use of natural language processing techniques for text classification and unbiased decision-making has not been far-fetched. Proper classification of this textual information in a given context has also been very difficult. As a result, we decided to conduct a systematic review of previous literature on sentiment classification and AI-based techniques that have been used in order to gain a better understanding of the process of designing and developing a robust and more accurate sentiment classifier that can correctly classify social media textual information of a given context between hate speech and inverted compliments with a high level of accuracy by assessing different artificial intelligence techniques. We evaluated over 250 articles from digital sources like ScienceDirect, ACM, Google Scholar, and IEEE Xplore and whittled down the number of research to 31. Findings revealed that Deep learning approaches such as CNN, RNN, BERT, and LSTM outperformed various machine learning techniques in terms of performance accuracy. A large dataset is also necessary for developing a robust sentiment classifier and can be obtained from places like Twitter, movie reviews, Kaggle, SST, and SemEval Task4. Hybrid Deep Learning techniques like CNN+LSTM, CNN+GRU, CNN+BERT outperformed single Deep Learning techniques and machine learning techniques. Python programming language outperformed Java programming language in terms of sentiment analyzer development due to its simplicity and AI-based library functionalities. Based on some of the important findings from this study, we made a recommendation for future research.

Keywords: artificial intelligence, natural language processing, sentiment analysis, social network, text

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Authors: Shereen Ismail Fawaz, Shin-Ichi Izumi, Nouran Mohamed Salah, Heba G. Saber, Ibrahim Mohamed Roushdi

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Background: Multiple sclerosis (MS) is a chronic, inflammatory, mainly demyelinating disease of the central nervous system, more common in young adults. Cerebellar involvement is one of the most disabling lesions in MS and is usually a sign of disease progression. It plays a major role in the planning, initiation, and organization of movement via its influence on the motor cortex and corticospinal outputs. Therefore, it contributes to controlling movement, motor adaptation, and motor learning, in addition to its vast connections with other major pathways controlling balance, such as the cerebellopropriospinal pathways and cerebellovestibular pathways. Hence, trying to stimulate the cerebellum by facilitatory protocols will add to our motor control and balance function. Non-invasive brain stimulation, both repetitive transcranial magnetic stimulation (rTMS) and transcranial direct current stimulation (tDCS), has recently emerged as effective neuromodulators to influence motor and nonmotor functions of the brain. Anodal tDCS has been shown to improve motor skill learning and motor performance beyond the training period. Similarly, rTMS, when used at high frequency (>5 Hz), has a facilitatory effect on the motor cortex. Objective: Our aim was to determine the effect of high-frequency rTMS over the cerebellum in improving balance and functional ambulation of multiple sclerosis patients with Ataxia. Patients and methods: This was a randomized single-blinded placebo-controlled prospective trial on 40 patients. The active group (N=20) received real rTMS sessions, and the control group (N=20) received Sham rTMS using a placebo program designed for this treatment. Both groups received 12 sessions of high-frequency rTMS over the cerebellum, followed by an intensive exercise training program. Sessions were given three times per week for four weeks. The active group protocol had a frequency of 10 Hz rTMS over the cerebellar vermis, work period 5S, number of trains 25, and intertrain interval 25s. The total number of pulses was 1250 pulses per session. The control group received Sham rTMS using a placebo program designed for this treatment. Both groups of patients received an intensive exercise program, which included generalized strengthening exercises, endurance and aerobic training, trunk abdominal exercises, generalized balance training exercises, and task-oriented training such as Boxing. As a primary outcome measure the Modified ICARS was used. Static Posturography was done with: Patients were tested both with open and closed eyes. Secondary outcome measures included the expanded Disability Status Scale (EDSS) and 8 Meter walk test (8MWT). Results: The active group showed significant improvements in all the functional scales, modified ICARS, EDSS, and 8-meter walk test, in addition to significant differences in static Posturography with open eyes, while the control group did not show such differences. Conclusion: Cerebellar high-frequency rTMS could be effective in the functional improvement of balance in MS patients with ataxia.

Keywords: brain neuromodulation, high frequency rTMS, cerebellar stimulation, multiple sclerosis, balance rehabilitation

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Authors: Yichen Lin, Hsiao-Han Chen, Chi-Chen Jan

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Since 1990, the research area of Integrated Marketing Communications (IMC) has been presented from a different perspective. With advances in information technology and the rise of consumer consciousness, businesses are in a competitive environment. There is an urgent need to adopt more profitable and effective integrated marketing strategies to increase core competitiveness. The goal of the company's sustainable management is to increase consumers' willingness to purchase and to maximize profits. This research uses six aspects of IMC, which includes awareness integration, unified image, database integration, customer-based integration, stakeholders-based integration, and evaluation integration to examine the role of marketing strategies in the strengths and weaknesses of the six components of integrated marketing communications, their effectiveness, the most important components and the most important components that need improvement. At the same time, social media such as FaceBook, Instagram, Youtube, Line, or even TikTok have become marketing tools which firms adopt them more and more frequently in the marketing strategy. In the end of 2019, the outbreak of COVID-19 did really affect the global industries. Lockdown policies also accelerated closure of brick-mentor stores worldwide. Online purchases rose dramatically. Hence, the effectiveness of online marketing will be essential to maintain the business. This study uses multiple-case studies to extend the effects of social media and IMC. Moreover, the study would also explore the differences of social media and IMC during COVID-19. Through literature review and multiple-case studies, it is found that using social media combined with IMC did really help companies expand their business and make good connections with stakeholders. One of previous studies also used system theory to explore the interrelationship among Integrated Marketing Communication, collaborative marketing, and global brand building. Even during pandemic, firms could still maintain the operation and connect with their customers more tightly.

Keywords: integration marketing communications, multiple-case studies, social media, system theory

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Authors: Adham M. Salah, Tariq A. Nagem, Raed A. Abd-Alhameed, James M. Noras

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Recently, the demand for wireless communications systems to cover more than one frequency band (multi-band) with high data rate has been increased for both fixed and mobile services. Multiple Input Multiple Output (MIMO) technology is one of the significant solutions for attaining these requirements and to achieve the maximum channel capacity of the wireless communications systems. The main issue associated with MIMO antennas especially in portable devices is the compact space between the radiating elements which leads to limit the physical separation between them. This issue exacerbates the performance of the MIMO antennas by increasing the mutual coupling between the radiating elements. In other words, the mutual coupling will be stronger if the radiating elements of the MIMO antenna are closer. This paper presents a low–profile dual-band (2×1) MIMO antenna that works at 2.4GHz, 5.3GHz and 5.8GHz for wireless local area networks (WLAN) applications. A neutralization line (NL) technique for enhancing the isolation has been used by introducing a strip line with a length of λg/4 at the isolation frequency (2.4GHz) between the radiating elements. The overall dimensions of the antenna are 33.5 x 36 x 1.6 mm³. The fabricated prototype shows a good agreement between the simulated and measured results. The antenna impedance bandwidths are 2.38–2.75 GHz and 4.4–6 GHz for the lower and upper band respectively; the reflection coefficient and mutual coupling are better than -25 dB in both lower and higher bands. The MIMO antenna performance characteristics are reported in terms of the scattering parameters, envelope correlation coefficient (ECC), total active reflection coefficient, capacity loss, antenna gain, and radiation patterns. Analysis of these characteristics indicates that the design is appropriate for the WLAN terminal applications.

Keywords: ECC, neutralization line, MIMO antenna, multi-band, mutual coupling, WLAN

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Authors: Murat Erkoc, Kadir Ertogral

Abstract:

Maintenance, repair and overhauling (MRO) of high cost equipment used in many industries such as transportation, military and construction are typically subject to regulations set by local governments or international agencies. Aircrafts are prime examples for this kind of equipment. Such equipment must be overhauled at certain intervals for continuing permission of use. As such, the overhaul must be completed by strict deadlines, which often times cannot be exceeded. Due to the fact that the overhaul is typically a long process, MRO companies carry so called rotable inventory for exchange of expensive modules in the overhaul process of the equipment so that the equipment continue its services with minimal interruption. The extracted module is overhauled and returned back to the inventory for future exchange, hence the name rotable inventory. However, since the rotable inventory and overhaul capacity are limited, it may be necessary to carry out some of the exchanges earlier than their deadlines in order to produce a feasible overhaul schedule. An early exchange results with a decrease in the equipment’s cycle time in between overhauls and as such, is not desired by the equipment operators. This study introduces an integer programming model for the optimal overhaul and exchange scheduling. We assume that there is certain number of rotables at hand at the beginning of the planning horizon for a single type module and there are multiple demands with known deadlines for the exchange of the modules. We consider an MRO system with identical parallel processing lines. The model minimizes total earliness by generating optimal overhaul start times for rotables on parallel processing lines and exchange timetables for orders. We develop a fast exact solution algorithm for the model. The algorithm employs full-delay scheduling approach with backward allocation and can easily be used for overhaul scheduling problems in various MRO settings with modular rotable items. The proposed procedure is demonstrated by a case study from the aerospace industry.

Keywords: rotable inventory, full-delay scheduling, maintenance, overhaul, total earliness

Procedia PDF Downloads 545

Authors: M. V. Manoj Kumar, Likewin Thomas, Annappa

Abstract:

Process mining research discipline bridges the gap between data mining and business process modeling and analysis, it offers the process-centric and end-to-end methods/techniques for analyzing information of real-world process detailed in operational event-logs. In this paper, we have proposed a notation called trace logo for graphically representing control-flow perspective (order of execution of activities) of process. A trace logo consists of a stack of activity names at each position, sizes of the activity name indicates their frequency in the traces and the total height of the activity depicts the information content of the position. A trace logo created from a set of aligned traces generated using Multiple Trace Alignment technique.

Keywords: consensus trace, process mining, multiple trace alignment, trace logo

Procedia PDF Downloads 350

Authors: K. R. Sultana, K. Pope, Y. S. Muzychka

Abstract:

In recent years, the research of heat transfer or phase change phenomena of liquid water droplets experiences a growing interest in aircraft icing, power transmission line icing, marine icing and wind turbine icing applications. This growing interest speeding up the research from single to multiple droplet phenomena. Impingements of multiple droplets and the resulting solidification phenomena after impact on a very cold surface is computationally studied in this paper. The model used in the current study solves the flow equation, composed of energy balance and the volume fraction equations. The main aim of the study is to investigate the effects of several thermo-physical properties (density, thermal conductivity and specific heat) on droplets freezing. The outcome is examined by various important factors, for instance, liquid fraction, total freezing time, droplet temperature and total heat transfer rate in the interface region. The liquid fraction helps to understand the complete phase change phenomena during solidification. Temperature distribution and heat transfer rate help to demonstrate the overall thermal exchange behaviors between the droplets and substrate surface. Findings of this research provide an important technical achievement for ice modeling and prediction studies.

Keywords: droplets, CFD, thermos-physical properties, solidification

Procedia PDF Downloads 244

Authors: Mohamed Barbary, Mohamed H. Abd El-Azeem

Abstract:

Maneuvering extended object tracking (M-EOT) using high-resolution inverse synthetic aperture radar (ISAR) observations has been gaining momentum recently. This work presents a new robust implementation of the multiple models (MM) multi-Bernoulli (MB) filter for M-EOT, where the M-EOT’s ISAR observations are characterized using a skewed (SK) non-symmetrically normal distribution. To cope with the possible abrupt change of kinematic state, extension, and observation distribution over an extended object when a target maneuvers, a multiple model technique is represented based on MB-track-before-detect (TBD) filter supported by SK-sub-random matrix model (RMM) or sub-ellipses framework. Simulation results demonstrate this remarkable impact.

Keywords: maneuvering extended objects, ISAR, skewed normal distribution, sub-RMM, MM-MB-TBD filter

Procedia PDF Downloads 77

Authors: Victoria Molina, Wendy Franco, Sergio Benavides, José M. Troncoso, Ricardo Luna, Jose R. PéRez-Correa

Abstract:

Emamectin Benzoate (EB) is a crystal antiparasitic that belongs to the avermectin family. It is one of the most common treatments used in Chile to control Caligus rogercresseyi in Atlantic salmon. However, the sea lice acquired resistance to EB when it is exposed at sublethal EB doses. The low solubility rate of EB and its degradation at the acidic pH in the fish digestive tract are the causes of the slow absorption of EB in the intestine. To protect EB from degradation and enhance its absorption, specific microencapsulation technologies must be developed. Amorphous Solid Dispersion techniques such as Spray Drying (SD) and Ionic Gelation (IG) seem adequate for this purpose. Recently, Soluplus® (SOL) has been used to increase the solubility rate of several drugs with similar characteristics than EB. In addition, alginate (ALG) is a widely used polymer in IG for biomedical applications. Regardless of the encapsulation technique, the quality of the obtained microparticles is evaluated with the following responses, yield (Y%), encapsulation efficiency (EE%) and loading capacity (LC%). In addition, it is important to know the percentage of EB released from the microparticles in gastric (GD%) and intestinal (ID%) digestions. In this work, we microencapsulated EB with SOL (EB-SD) and with ALG (EB-IG) using SD and IG, respectively. Quality microencapsulation responses and in vitro gastric and intestinal digestions at pH 3.35 and 7.8, respectively, were obtained. A central composite design was used to find the optimum microencapsulation variables (amount of EB, amount of polymer and feed flow). In each formulation, the behavior of these variables was predicted with statistical models. Then, the response surface methodology was used to find the best combination of the factors that allowed a lower EB release in gastric conditions, while permitting a major release at intestinal digestion. Two approaches were used to determine this. The desirability approach (DA) and multi-objective optimization (MOO) with multi-criteria decision making (MCDM). Both microencapsulation techniques allowed to maintain the integrity of EB in acid pH, given the small amount of EB released in gastric medium, while EB-IG microparticles showed greater EB release at intestinal digestion. For EB-SD, optimal conditions obtained with MOO plus MCDM yielded a good compromise among the microencapsulation responses. In addition, using these conditions, it is possible to reduce microparticles costs due to the reduction of 60% of BE regard the optimal BE proposed by (DA). For EB-GI, the optimization techniques used (DA and MOO) yielded solutions with different advantages and limitations. Applying DA costs can be reduced 21%, while Y, GD and ID showed 9.5%, 84.8% and 2.6% lower values than the best condition. In turn, MOO yielded better microencapsulation responses, but at a higher cost. Overall, EB-SD with operating conditions selected by MOO seems the best option, since a good compromise between costs and encapsulation responses was obtained.

Keywords: microencapsulation, multiple decision-making criteria, multi-objective optimization, Soluplus®

Procedia PDF Downloads 131

Authors: Daniel Hristov

Abstract:

The paper describes the principle of operation, simulation and physical validation of method for simultaneous acquisition of gain and phase states of multiple antenna elements and the corresponding feed lines across a Phased Array Antenna (PAA). The derived values for gain and phase are used for PAA-calibration. The method utilizes the Rotating-Element Electric- Field Vector (REV) principle currently used for gain and phase state estimation of single antenna element across an active antenna aperture. A significant reduction of procedure execution time is achieved with simultaneous setting of different phase delays to multiple phase shifters, followed by a single power measurement. The initial gain and phase states are calculated using spectral and correlation analysis of the measured power series.

Keywords: antenna, antenna arrays, calibration, phase measurement, power measurement

Procedia PDF Downloads 138

Authors: Wendy Ampadu, Ray Diezmos, Hassan Malik, Jeremy Hyslob

Abstract:

There are several technologies out there for use as high-level switches as part of a system for shutting down flow to a vessel. Given that the asphalt truck loading poses issues such as poor visibility, coating, condensation, and fumes, a solution that is robust enough to last in these conditions is often needed in industries. Furthermore, the design of the loading arm, rack, and process equipment should allow for the safety of workers. The objective of this report includes the redesign of structures for use at loading facilities and selecting an overflow technology protection from hot bitumen. The report is based on loading facilities at a Canadian bitumen production company. The engineering design approach was used to create multiple redesign concepts for the loading dock system. Research on overfill systems was also completed by surveying the existing market for technologies and securing quotes from over 20 Canadian and United States instrumentation companies. A final loading dock redesign and level transmitter for overfill protection solution were chosen.

Keywords: bitumen, reliability engineering, safety system, process safety management, asphalt, loading docks, tanker trucks

Procedia PDF Downloads 158

Authors: Jaswinder Singh

Abstract:

In this paper, comparative analysis is carried out to study the performance of wavelength/time/space optical CDMA codes using two well-known formats; those are CSRZ and DPSK-RZ using RSoft’s OptSIM. The analysis is carried out under the real-like scenario considering the presence of various non-linear effects such as XPM, SPM, SRS, SBS and FWM. Fiber dispersion and the multiple access interference are also considered. The codes used in this analysis are 3-D wavelength/time/space codes. These are converted into 2-D wavelength-time codes so that their requirement of space couplers and fiber ribbons is eliminated. Under the conditions simulated, this is found that CSRZ performs better than DPSK-RZ for fiber-optic CDMA applications.

Keywords: Optical CDMA, Multiple access interference (MAI), CSRZ, DPSK-RZ

Procedia PDF Downloads 647