Search results for: distributed model

Authors: Jinkoo Kim, Minsung Kim

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This study develops a hybrid seismic energy dissipation device composed of a viscoelastic damper and a steel slit damper connected in parallel. A cyclic loading test is conducted on a test specimen to validate the seismic performance of the hybrid damper. Then a moment-framed model structure is designed without seismic load so that it is retrofitted with the hybrid dampers. The model structure is transformed into an equivalent simplified system to find out optimum story-wise damper distribution pattern using genetic algorithm. The effectiveness of the hybrid damper is investigated by fragility analysis and the life cycle cost evaluation of the structure with and without the dampers. The analysis results show that the model structure has reduced probability of reaching damage states, especially the complete damage state, after seismic retrofit. The expected damage cost and consequently the life cycle cost of the retrofitted structure turn out to be significantly small compared with those of the original structure. Acknowledgement: This research was supported by the Ministry of Trade, Industry and Energy (MOTIE) and Korea Institute for Advancement of Technology (KIAT) through the International Cooperative R & D program (N043100016).

Keywords: seismic retrofit, slit dampers, friction dampers, hybrid dampers

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Authors: Halima Akhtar, Abhijeet Chandra

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The paper attempts to analyze the factors that influence the Consumer Behavior to purchase apparel through the internet. The intentions to buy apparels online were based on in terms of user style, orientation, size and reputation of the merchant, social influence, perceived information utility, perceived ease of use, perceived pleasure and attractiveness and perceived trust and risk. The basic framework used was Technology acceptance model to explain apparels acceptance. A survey was conducted to gather the data from 200 people. The measures and hypotheses were analyzed using Correlation testing and would be further validated by the Structural Equation Modelling. The implications of the findings for theory and practice could be used by marketers of online apparel websites. Based on the values obtained, we can conclude that the factors such as social influence, Perceived information utility, attractiveness and trust influence the decision for a user to buy apparels online. The major factors which are found to influence an online apparel buying decision are ease of use, attractiveness that a website can offer and the trust factor which a user shares with the website.

Keywords: E-tailers, consumer behaviour, technology acceptance model, structural modelling

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Authors: Azizah Hashim, Rohana Ngah

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Transformation of Economic Development is aimed to transform Malaysia to become a high-income developed nation with a knowledge-based economy by 2020. To achieve this national agenda, the country needs to further strengthen its economic development, growth and well-being. Therefore, this study aspires to examine the relationship between market orientation, human resource management and adoption of information communication technology and SMEs performance and cash management as a mediator. This study will employ quantitative approaches. Questionnaires will be distributed to managers and owners in service sectors. The data collected will be analyzed using SPSS and Structural Equation Modelling. Resource Based Theory (RBT) adopts as an integral part of management literature that explains the performance of organizations through building resources and implement of their strategies.

Keywords: small medium enterprises (SMEs), market orientation, human resource management, adoption of information communication technology

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Authors: Aleena Rena Onozuka, Patompong Satapornpong

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Introduction: In a Human Leukocyte Antigen (HLA)’s immune response, HLA alleles (HLA class I and class II) play a crucial role in fighting against pathogens. HLA-B*15:01 allele had a significant association with asymptomatic COVID-19 infection (p-value = 5.67 x 10-5 ; OR = 2.40 and 95% CI = 1.54 - 3.64). There was also a notable linkage between HLA-B*51:01 allele and critically ill patients with COVID-19 (p-value = 0.007 and OR = 3.38). This study has described the distribution of HLA marker alleles in Thais and sub-groups. Objective: We want to investigate the prevalence of HLA-B*15:01 and HLA-B*51:01 alleles in the Thai population. Materials and Methods: 200 healthy Thai population were included in this study from the College of Pharmacy, Rangsit University. HLA-B alleles were genotyped using the sequence-specific oligonucleotides process (PCR-SSOs). Results: We found out that HLA-B*46:01 (12.00%), HLA-B*15:02 (9.25%), HLA-B*40:01 (6.50%), HLA-B*13:01 (6.25%), and HLA-B* 38:02 (5.50%) alleles were more common than other alleles in Thai population. HLA-B*46:01 and HLA-B*15:02 were the most common allele found across four regions. Moreover, the frequency of HLA-B*15:01 and HLA-B*51:01 alleles were similarly distributed in Thai population (0.50, 5.25 %) and (p-value > 0.05), respectively. The frequencies of HLA-B*15:01 and HLA-B*51:01 alleles were not significantly different from other populations compared to the Thai population. Conclusions: We can screen for HLA-B*15:01 and HLA-B*51:01 alleles to determine the symptoms of COVID-19 since they are universal HLA-B markers. Importantly, the database of HLA markers indicates the association between HLA frequency and populations. However, we need further research on larger numbers of COVID-19 patients and in different populations.

Keywords: HLA-B*15:01, HLA-B*51:01, COVID-19, HLA-B alleles

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Authors: R. Simutis, V. Galvanauskas, D. Levisauskas, J. Repsyte, V. Grincas

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This paper deals with advanced state estimation algorithms for estimation of biomass concentration and specific growth rate in a typical fed-batch biotechnological process. This biotechnological process was represented by a nonlinear mass-balance based process model. Extended Kalman Filter (EKF) and Particle Filter (PF) was used to estimate the unmeasured state variables from oxygen uptake rate (OUR) and base consumption (BC) measurements. To obtain more general results, a simplified process model was involved in EKF and PF estimation algorithms. This model doesn’t require any special growth kinetic equations and could be applied for state estimation in various bioprocesses. The focus of this investigation was concentrated on the comparison of the estimation quality of the EKF and PF estimators by applying different measurement noises. The simulation results show that Particle Filter algorithm requires significantly more computation time for state estimation but gives lower estimation errors both for biomass concentration and specific growth rate. Also the tuning procedure for Particle Filter is simpler than for EKF. Consequently, Particle Filter should be preferred in real applications, especially for monitoring of industrial bioprocesses where the simplified implementation procedures are always desirable.

Keywords: biomass concentration, extended Kalman filter, particle filter, state estimation, specific growth rate

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Authors: Nadjah Chergui, Narhimene Boustia

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Intrusion Detection Systems are an essential tool for network security infrastructure. However, IDSs have a serious problem which is the generating of massive number of alerts, most of them are false positive ones which can hide true alerts and make the analyst confused to analyze the right alerts for report the true attacks. The purpose behind this paper is to present a formalism model to perform correlation engine by the reduction of false positive alerts basing on vulnerability contextual information. For that, we propose a formalism model based on non-monotonic JClassicδє description logic augmented with a default (δ) and an exception (є) operator that allows a dynamic inference according to contextual information.

Keywords: context, default, exception, vulnerability

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Authors: M. Mehani, N. Salhi, T. Valeria, S. Ladjel

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Red River Gum (Eucalyptus camaldulensis) is a tree of the genus Eucalyptus widely distributed in Algeria and in the world. The value of its aromatic secondary metabolites offers new perspectives in the pharmaceutical industry. This strategy can contribute to the sustainable development of our country. Preliminary tests performed on the essential oil of Eucalyptus camendulensis showed that this oil has antibacterial activity vis-à-vis the bacterial strains (Enterococcus feacalis, Enterobacter cloaceai, Proteus microsilis, Escherichia coli, Klebsiella pneumonia, and Pseudomonas aeruginosa) and antifungic (Fusarium sporotrichioide and Fusarium graminearum). The culture medium used was nutrient broth Muller Hinton. The interaction between the bacteria and the essential oil is expressed by a zone of inhibition with diameters of MIC indirectly expression of. And we used the PDA medium to determine the fungal activity. The extraction of the aromatic fraction (essentially oil- hydrolat) of the fresh aerian part of the Eucalyptus camendulensis was performed by hydrodistillation. The average essential oil yield is 0.99%. The antimicrobial and fungal study of the essential oil and hydrosol showed a high inhibitory effect on the growth of pathogens.

Keywords: essential oil, Eucalyptus camendulensis, bacteria and fungi, red river gum

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Authors: A. Brahma

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Drying is a phenomenon that accompanies the hardening of hydraulic materials. It can, if it is not prevented, lead to significant spontaneous dimensional variations, which the cracking is one of events. In this context, cracking promotes the transport of aggressive agents in the material, which can affect the durability of concrete structures. Drying shrinkage develops over a long period almost 30 years although most occurred during the first three years. Drying shrinkage stabilizes when the material is water balance with the external environment. The drying shrinkage of cementitious materials is due to the formation of capillary tensions in the pores of the material, which has the consequences of bringing the solid walls of each other. Knowledge of the shrinkage characteristics of concrete is a necessary starting point in the design of structures for crack control. Such knowledge will enable the designer to estimate the probable shrinkage movement in reinforced or prestressed concrete and the appropriate steps can be taken in design to accommodate this movement. This study is concerned the modelling of drying shrinkage of the hydraulic materials and the prediction of the rate of spontaneous deformations of hydraulic materials during hardening. The model developed takes in consideration the main factors affecting drying shrinkage. There was agreement between drying shrinkage predicted by the developed model and experimental results. In last we show that developed model describe the evolution of the drying shrinkage of high performances concretes correctly.

Keywords: drying, hydraulic concretes, shrinkage, modeling, prediction

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Authors: N. Marzban, J. K. Heydarzadeh M. Pourmohammadbagher, M. H. Hatami, A. Samia

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A nano-alumina-zirconia composite catalyst was synthesized by a simple aqueous sol-gel method using AlCl₃.6H₂O and ZrCl₄ as precursors. Thermal decomposition of the precursor and subsequent formation of γ-Al₂O₃ and t-Zr were investigated by thermal analysis. XRD analysis showed that γ-Al₂O₃ and t-ZrO₂ phases were formed at 700 °C. FT-IR analysis also indicated that the phase transition to γ-Al₂O₃ occurred in corroboration with X-ray studies. TEM analysis of the calcined powder revealed that spherical particles were in the range of 8-12 nm. The nano-alumina-zirconia composite particles were mesoporous and uniformly distributed in their crystalline phase. In order to measure the catalytic activity, esterification reaction was carried out. Biodiesel, as a renewable fuel, was formed in a continuous packed column reactor. Free fatty acid (FFA) was esterified with ethanol in a heterogeneous catalytic reactor. It was found that the synthesized γ-Al₂O₃/ZrO₂ composite had the potential to be used as a heterogeneous base catalyst for biodiesel production processes.

Keywords: nano alumina-zirconia, composite catalyst, thin film, biodiesel

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Authors: Amir Andria Gad Shehata

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Minimizing the inventory cost, optimizing the inventory quantities, and increasing system operational availability are the main motivations to enhance forecasting demand of spare parts in a major power utility company in Medina. This paper reports in an effort made to optimize the orders quantities of spare parts by improving the method of forecasting the demand. The study focuses on equipment that has frequent spare parts purchase orders with uncertain demand. The pattern of the demand considers a lumpy pattern which makes conventional forecasting methods less effective. A comparison was made by benchmarking various methods of forecasting based on experts’ criteria to select the most suitable method for the case study. Three actual data sets were used to make the forecast in this case study. Two neural networks (NN) approaches were utilized and compared, namely long short-term memory (LSTM) and multilayer perceptron (MLP). The results as expected, showed that the NN models gave better results than traditional forecasting method (judgmental method). In addition, the LSTM model had a higher predictive accuracy than the MLP model.

Keywords: spare part, spare part inventory, inventory model, optimization, maintenanceneural network, LSTM, MLP, forecasting demand, inventory management

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Authors: Jae-Yeong Choi, Gyu-Mok Jeon, Jong-Chun Park, Yong-Jin Cho, Seok-Tae Yoon

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When air flow is injected into water, bubbles are formed in various types inside the water pool along with the air flow rate. The bubbles are floated in equilibrium with forces such as buoyancy, surface tension and shear force. Single bubble generated at low flow rate maintains shape, but bubbles with high flow rate break up to make mixing and turbulence. In addition to this phenomenon, as the hot air bubbles are injected into the water, heat affects the interface of phases. Therefore, the main scope of the present work reveals how to proceed heat transfer between water and hot air bubbles injected into water. In the present study, a series of CFD simulation for the heat transfer of hot bubbles injected through a nozzle near the bottom in a cylindrical water column are performed using a commercial CFD software, STAR-CCM+. The governing equations for incompressible and viscous flow are the continuous and the RaNS (Reynolds- averaged Navier-Stokes) equations and discretized by the FVM (Finite Volume Method) manner. For solving multi-phase flow, the Eulerian multiphase model is employed and the interface is defined by VOF (Volume-of-Fluid) technique. As a turbulence model, the SST k-w model considering the buoyancy effects is introduced. For spatial differencing the 3th-order MUSCL scheme is adopted and the 2nd-order implicit scheme for time integration. As the results, the dynamic behavior of the rising hot bubbles with the flow rate injected and regarding heat transfer mechanism are discussed based on the simulation results.

Keywords: heat transfer, hot bubble injection, eulerian multiphase model, flow rate, CFD (Computational Fluid Dynamics)

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Authors: Gheyzer Villegas, Edgardo Cedeño, Veruska Mata, Edmundo Chauran

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One of the most significant changes that occurred in global commerce was the emergence of cryptocurrencies and blockchain technology. There is still much debate about the adoption of the economic model based on crypto assets, and myriad international projects and initiatives are being carried out to try and explore the potential that this new field offers. The Hive blockchain is a prime example of this, featuring two use cases: of how trade based on its native currencies can give successful results in the exchange of goods and services and in the financing of social impact projects. Its decentralized management model and visionary administration of its development fund have become a key part of its success.

Keywords: Hive, business, network, blockchain

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Authors: Fazilet Özlem Çekiç, Seyda Yılmaz

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Salinity and drought are important environmental problems in the world and have negative effects on plant metabolism. Gamma-aminobutyric acid (GABA), four-carbon non-protein amino acid, is a significant component of the free amino acid pool. GABA is widely distributed in prokaryotic and eukaryotic organisms. Environmental stress factors increase GABA accumulation in plants. Our aim was to evaluate the effect of gibberellic acid (GA) on GABA metabolism system during drought and salt stress factors in Phaseolus vulgaris L. plants. GABA, Glutamate dehydrogenase (GDH) activity, chlorophyll, and lipid peroxidation (MDA) analyses were determined. According to our results we can suggest that GA play a role in GABA metabolism during salt and drought stresses in bean plants. Also GABA shunt is an important metabolic pathway and key signaling allowing to adapt to drought and salt stresses.

Keywords: gibberellic acid, GABA, Phaseolus vulgaris L., salinity, drought

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Authors: Jihene Jlassi, Ahmed Frikha, Wazna Kortli

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The objectives of Nurse-Patient Assignment are the minimization of the overall hospital cost and the maximization of nurses ‘preferences. This paper aims to assess nurses' satisfaction related to the implementation of patient acuity tool-based assignments. So, we used an integer linear program that assigns patients to nurses while balancing nurse workloads. Then, the proposed model is applied to the Paediatrics Department at Kasserine Hospital Tunisia. Where patients need special acuities and high-level nursing skills and care. Hence, numerical results suggested that proposed nurse-patient assignment models can achieve a balanced assignment

Keywords: nurse-patient assignment, mathematical model, logistics, pediatrics department, balanced assignment

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Authors: Maria Ezziani, Rabie Zine, Amine Amar, Ilhame Kissani

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This paper introduces a predictive model for urban transportation engineering, which is vital for efficient traffic management. Utilizing comprehensive datasets and advanced statistical techniques, the model accurately forecasts travel times by considering temporal variations and traffic dynamics. Machine learning algorithms, including regression trees and neural networks, are employed to capture sequential dependencies. Results indicate significant improvements in predictive accuracy, particularly during peak hours and holidays, with the incorporation of traffic flow and speed variables. Future enhancements may integrate weather conditions and traffic incidents. The model's applications range from adaptive traffic management systems to route optimization algorithms, facilitating congestion reduction and enhancing journey reliability. Overall, this research extends beyond travel time estimation, offering insights into broader transportation planning and policy-making realms, empowering stakeholders to optimize infrastructure utilization and improve network efficiency.

Keywords: predictive analytics, traffic flow, travel time estimation, urban transportation, machine learning, traffic management

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Authors: Angela U. Makolo

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Protein-coding and Non-coding regions determine the biology of a sequenced transcriptome. Research advances have shown that Non-coding regions are important in disease progression and clinical diagnosis. Existing bioinformatics tools have been targeted towards Protein-coding regions alone. Therefore, there are challenges associated with gaining biological insights from transcriptome sequence data. These tools are also limited to computationally intensive sequence alignment, which is inadequate and less accurate to identify both Protein-coding and Non-coding regions. Alignment-free techniques can overcome the limitation of identifying both regions. Therefore, this study was designed to develop an efficient sequence alignment-free model for identifying both Protein-coding and Non-coding regions in sequenced transcriptomes. Feature grouping and randomization procedures were applied to the input transcriptomes (37,503 data points). Successive iterations were carried out to compute the gradient vector that converged the developed Protein-coding and Non-coding Region Identifier (PNRI) model to the approximate coefficient vector. The logistic regression algorithm was used with a sigmoid activation function. A parameter vector was estimated for every sample in 37,503 data points in a bid to reduce the generalization error and cost. Maximum Likelihood Estimation (MLE) was used for parameter estimation by taking the log-likelihood of six features and combining them into a summation function. Dynamic thresholding was used to classify the Protein-coding and Non-coding regions, and the Receiver Operating Characteristic (ROC) curve was determined. The generalization performance of PNRI was determined in terms of F1 score, accuracy, sensitivity, and specificity. The average generalization performance of PNRI was determined using a benchmark of multi-species organisms. The generalization error for identifying Protein-coding and Non-coding regions decreased from 0.514 to 0.508 and to 0.378, respectively, after three iterations. The cost (difference between the predicted and the actual outcome) also decreased from 1.446 to 0.842 and to 0.718, respectively, for the first, second and third iterations. The iterations terminated at the 390th epoch, having an error of 0.036 and a cost of 0.316. The computed elements of the parameter vector that maximized the objective function were 0.043, 0.519, 0.715, 0.878, 1.157, and 2.575. The PNRI gave an ROC of 0.97, indicating an improved predictive ability. The PNRI identified both Protein-coding and Non-coding regions with an F1 score of 0.970, accuracy (0.969), sensitivity (0.966), and specificity of 0.973. Using 13 non-human multi-species model organisms, the average generalization performance of the traditional method was 74.4%, while that of the developed model was 85.2%, thereby making the developed model better in the identification of Protein-coding and Non-coding regions in transcriptomes. The developed Protein-coding and Non-coding region identifier model efficiently identified the Protein-coding and Non-coding transcriptomic regions. It could be used in genome annotation and in the analysis of transcriptomes.

Keywords: sequence alignment-free model, dynamic thresholding classification, input randomization, genome annotation

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Authors: Thozama Kwinana-Mandindi

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The contribution made by wild edible plants to the livelihoods, food baskets and diets of the indigenous people, particularly among the rural dwellers is invaluable. These wild vegetables are among the non-conventional crops which are widely distributed throughout the wild regions in South Africa, indigenous communities have always exploited for micro-nutrient supply. They also supply significant complex, recently discovered compounds, naturally occurring phytonutrients. In order to protect and promote sustainable use of these plants for household food security, there is a need to better understand them through studies and innovations. Assessment of the wild edible plants’ safety is very key to the promotion as an agricultural product which can be utilised during dry seasons and periods of food scarcity to alleviate nutrient insecurity. Through the use of Scanning Electron Microscope (SEM) and energy dispersive X-ray spectroscopy (EDXS), the study is seen as the vital step in taking a holistic view of the value of the four most consumed wild vegetables in the Eastern Cape Province of South Africa as they were analysed for safety and appraised for components that can influence utilisation. Results indicate that they can be relied upon and cultivation be promoted.

Keywords: nature’s resource, wild vegetables, appraisal for safety, SEM

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Authors: Mohammed Alhawiti

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Assessment of Learning Management Systems has been of less importance than its due share. This paper investigates the evaluation of learning management systems (LMS) within educational setting as both an online learning system as well as a helpful tool for multidisciplinary learning environment. This study suggests a theoretical e-learning evaluation model, studying a multi-dimensional methods for evaluation through LMS system, service and content quality, learner`s perspective and attitudes of the instructor. A survey was conducted among 105 e-learners. The sample consisted of students at both undergraduate and master’s levels. Content validity, reliability were tested through the instrument, Findings suggested the suitability of the proposed model in evaluation for the satisfaction of learners through LMS. The results of this study would be valuable for both instructors and users of e-learning systems.

Keywords: e-learning, LMS, higher education, management systems

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Authors: Khaled M. Alhawiti

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This research study aims to present a retrospective study about speech recognition systems and artificial intelligence. Speech recognition has become one of the widely used technologies, as it offers great opportunity to interact and communicate with automated machines. Precisely, it can be affirmed that speech recognition facilitates its users and helps them to perform their daily routine tasks, in a more convenient and effective manner. This research intends to present the illustration of recent technological advancements, which are associated with artificial intelligence. Recent researches have revealed the fact that speech recognition is found to be the utmost issue, which affects the decoding of speech. In order to overcome these issues, different statistical models were developed by the researchers. Some of the most prominent statistical models include acoustic model (AM), language model (LM), lexicon model, and hidden Markov models (HMM). The research will help in understanding all of these statistical models of speech recognition. Researchers have also formulated different decoding methods, which are being utilized for realistic decoding tasks and constrained artificial languages. These decoding methods include pattern recognition, acoustic phonetic, and artificial intelligence. It has been recognized that artificial intelligence is the most efficient and reliable methods, which are being used in speech recognition.

Keywords: speech recognition, acoustic phonetic, artificial intelligence, hidden markov models (HMM), statistical models of speech recognition, human machine performance

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Authors: Jirarat Teeravaraprug, Tarathorn Podcharathitikull

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Nowadays, Ministry of Industry has given an attention to develop Eco-industrial towns in Thailand. Eco-industrial towns are a way of demonstrating the application of industrial ecology and are subjects of increased interest as government, business and society. This concept of Eco-industrial town is quite new in Thailand. It is used as a way of achieving more sustainable industrial development. However, many firms or organizations have misunderstood the concept and treated with suspicion. The planning and development of Eco-industrial towns is a significant challenge for the developers and public agencies. This research then gives an attempt to determine current problems of being Eco-Industrial towns and determine success factors for developing Eco-Industrial towns in Thailand. The research starts with giving knowledge about Eco-industrial towns to stakeholders and conducting public hearing in order to acquire the problems of being Eco-industrial towns. Then, factors effecting the development of Eco-Industrial town are collected. The obtained factors are analyzed by using the concept of IOC. Then, the remained factors are categorized and structured based on the concept of AHP. A questionnaire is constructed and distributed to the experts who are involved in the Eco-industrial town project. The result shows that the most significant success criterion is management teams of industrial parks or groups and the second most significant goes to governmental policies.

Keywords: AHP, Eco-Industrial town, success factors, Thailand

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Authors: Said Al Saifi

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This paper proposes a conceptual model for understanding the impact of organisational culture on knowledge management processes and their link with organisational performance. It is suggested that organisational culture should be assessed as a multi-level construct comprising artifacts, espoused beliefs and values, and underlying assumptions. A holistic view of organisational culture and knowledge management processes, and their link with organisational performance, is presented. A comprehensive review of previous literature was undertaken in the development of the conceptual model. Taken together, the literature and the proposed model reveal possible relationships between organisational culture, knowledge management processes, and organisational performance. Potential implications of organisational culture levels for the creation, sharing, and application of knowledge are elaborated. In addition, the paper offers possible new insight into the impact of organisational culture on various knowledge management processes and their link with organisational performance. A number of possible relationships between organisational culture factors, knowledge management processes, and their link with organisational performance were employed to examine such relationships. The research model highlights the multi-level components of organisational culture. These are: the artifacts, the espoused beliefs and values, and the underlying assumptions. Through a conceptualisation of the relationships between organisational culture, knowledge management processes, and organisational performance, the study provides practical guidance for practitioners during the implementation of knowledge management processes. The focus of previous research on knowledge management has been on understanding organisational culture from the limited perspective of promoting knowledge creation and sharing. This paper proposes a more comprehensive approach to understanding organisational culture in that it draws on artifacts, espoused beliefs and values, and underlying assumptions, and reveals their impact on the creation, sharing, and application of knowledge which can affect overall organisational performance.

Keywords: knowledge application, knowledge creation, knowledge management, knowledge sharing, organisational culture, organisational performance

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Authors: Mohammadamin Abbasnejad

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The analysis of expression and facial Action Units (AUs) detection are very important tasks in fields of computer vision and Human Computer Interaction (HCI) due to the wide range of applications in human life. Many works have been done during the past few years which has their own advantages and disadvantages. In this work, we present a new model based on Gaussian Conditional Random Field. We solve our objective problem using ADMM and we show how well the proposed model works. We train and test our work on two facial expression datasets, CK+, and RU-FACS. Experimental evaluation shows that our proposed approach outperform state of the art expression recognition.

Keywords: Gaussian Conditional Random Field, ADMM, convergence, gradient descent

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Authors: Saeed Al Amoudy

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During the last decade, the rapidly growing prestige of so-called Creative Cities has inspired many other cities seeking to enhance their attractiveness, creativity, and success. However, the concept of a creative city seems to be an elusive one because it reflects a set of distinct ideologies which apply distinct ideas of creativity to physical and economic urban development. The main aim of this study is to investigate the ways in which the theoretical concept of the creative city can be usefully and practically employed to develop the urban services and global identity of Makkah, Saudi Arabia. This is a challenging prospect since no research on creative cities in the Middle East has previously been conducted. The city of Makkah and its holy sites is known as the focus of religious devotion for one and half billion Muslims around the globe, with millions travelling there on annual pilgrimage. The ideas of three of the key authors who have addressed relevant aspects of the concept of the creative city, Landry, Howkins and Florida, were explored in depth for the purpose of identifying the model which would be best suited to Makkah’s identity as a sacred city. Of these, it was the approach of Landry and others whose work was originally focused on finding creative solutions to the problems faced by cities which proved most suitable for the context of Makkah. The development strategies of five case studies of Creative Cities situated in different parts of the world, namely Vancouver, Yokohama, Glasgow, Barcelona, and Sydney, were also examined. Inspired by their diverse experiences, a model, referred to by the acronym CREATIVE, was developed by bringing together the key elements which seemed to ,account for the success of these five creative cities: Concept, Resources, Events, Attractiveness, Technology, Involvement, Vision and Enthusiasm. Expert opinion was sought on the model by presenting this for discussion at five international conferences. This model was used to guide both the process of data collection via interviews, documentation and field notes, and for analysing this, revealing that Makkah has great potential to become a Creative City. The results suggested that implementation of the CREATIVE model in Makkah would help produce creative solutions to address the problems that the city currently faces due to the growing number of pilgrims every year.

Keywords: creative city, city imaging, Makkah, sacred city

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Authors: Qi Lu, Jian Deng, Daishun Huang, Chao Guo

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The lead cooled fast reactor is considered as one of the most potential Generation IV nuclear systems due to the low working pressure, the appreciable neutron economy, and the considerable passive characteristics. Meanwhile, the lead bismuth eutectic (LBE) has the related advantages of lead with the weaker corrosiveness, which has been paid much attention by recent decades. Moreover, the sub-channel code is a necessary analysis tool for the reactor thermal-hydraulic design and safety analysis, which has been developed combined with the accumulation of LBE experimental data and the understanding of physical phenomena. In this study, a sub-channel code available for LBE was developed, and the corresponding geometric characterization method of typical sub-channels was described in detail, especially for for the fuel assembly with wire spacer. As for this sub-channel code, the transversal thermal conduction through gap was taken into account. In addition, the physical properties, the heat transfer model, the flow resistance model and the turbulent mixing model were analyzed. Finally, the thermal-hydraulic experiments of LBE conducted on THEADES (THErmal-hydraulics and Ads DESign) were selected as the evaluation data of this sub-channel code, including 19 rods with wire spacer, and the calculated results were in good agreement with the experimental results.

Keywords: lead bismuth eutectic, sub-channel code, wire spacer, transversal thermal conduction

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Authors: Supakij Saisopon

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The process of economic development incurs spatial transformation. This spatial alternation also causes environmental impacts, leading to higher pollution. In the case of Thailand, there is still a lack of price-endogenous quantitative analysis incorporating relationships among economic growth, land-use change, and environmental impact. Therefore, this paper aimed at developing the Computable General Equilibrium (CGE) model with the capability of stimulating such mutual effects. The developed CGE model has also incorporated the nested constant elasticity of transformation (CET) structure that describes the spatial redistribution mechanism between agricultural land and urban area. The simulation results showed that the 1% decrease in the availability of agricultural land lowers the value-added of agricultural by 0.036%. Similarly, the 1% reduction of availability of urban areas can decrease the value-added of manufacturing and service sectors by 0.05% and 0.047%, respectively. Moreover, the outcomes indicate that the increasing farming and urban areas induce higher volumes of solid waste, wastewater, and air pollution. Specifically, the 1% increase in the urban area can increase pollution as follows: (1) the solid waste increase by 0.049%, (2) water pollution ̶ indicated by biochemical oxygen demand (BOD) value ̶ increase by 0.051% and (3) air pollution ̶ indicated by the volumes of CO₂, N₂O, NOₓ, CH₄, and SO₂ ̶ increase within the range of 0.045%–0.051%. With the simulation for exploring the sustainable development path, a 1% increase in agricultural land use efficiency leads to the shrinking demand for agricultural land. But this is not happening in urban, a 1% scale increase in urban utilization results in still increasing demand for land. Therefore, advanced clean production technology is necessary to align the increasing land-use efficiency with the lowered pollution density.

Keywords: CGE model, CET structure, environmental impact, land use

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Authors: Gong Zhilin, Jing Yang, Jian Yin

Abstract:

The purpose of this paper is to develop a novel system for credit card fraud detection based on sequential modeling of data using hybrid deep learning models. The projected model encapsulates five major phases are pre-processing, imbalance-data handling, feature extraction, optimal feature selection, and fraud detection with an ensemble classifier. The collected raw data (input) is pre-processed to enhance the quality of the data through alleviation of the missing data, noisy data as well as null values. The pre-processed data are class imbalanced in nature, and therefore they are handled effectively with the K-means clustering-based SMOTE model. From the balanced class data, the most relevant features like improved Principal Component Analysis (PCA), statistical features (mean, median, standard deviation) and higher-order statistical features (skewness and kurtosis). Among the extracted features, the most optimal features are selected with the Self-improved Arithmetic Optimization Algorithm (SI-AOA). This SI-AOA model is the conceptual improvement of the standard Arithmetic Optimization Algorithm. The deep learning models like Long Short-Term Memory (LSTM), Convolutional Neural Network (CNN), and optimized Quantum Deep Neural Network (QDNN). The LSTM and CNN are trained with the extracted optimal features. The outcomes from LSTM and CNN will enter as input to optimized QDNN that provides the final detection outcome. Since the QDNN is the ultimate detector, its weight function is fine-tuned with the Self-improved Arithmetic Optimization Algorithm (SI-AOA).

Keywords: credit card, data mining, fraud detection, money transactions

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Authors: Reza Salehi, Peter L. Dold, Yves Comeau

Abstract:

The aim of the present study was to investigate the effect of a total of 6 operating parameters including pH (X1), temperature (X2), stirring speed (X3), chemical oxygen demand (COD) (X4), volatile suspended solids (VSS) (X5) and time (X6) on anaerobic orthophosphate release from enhanced biological phosphorus removal (EBPR) sludge. An 8-run Plackett Burman design was applied and the statistical analysis of the experimental data was performed using Minitab16.2.4 software package. The Analysis of variance (ANOVA) results revealed that temperature, COD, VSS and time had a significant effect with p-values of less than 0.05 whereas pH and stirring speed were identified as non-significant parameters, but influenced orthophosphate release from the EBPR sludge. The mathematic expression obtained by the first-order multiple linear regression model between orthophosphate release from the EBPR sludge (Y) and the operating parameters (X1-X6) was Y=18.59+1.16X1-3.11X2-0.81X3+3.79X4+9.89X5+4.01X6. The model p-value and coefficient of determination (R2) value were 0.026 and of 99.87%, respectively, which indicates the model is significant and the predicted values of orthophosphate release from the EBPR sludge have been excellently correlated with the observed values.

Keywords: anaerobic, operating parameters, orthophosphate release, Plackett-Burman design

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Authors: Muhammed Auwal Umar, M. Saleh

Abstract:

The main purpose of this research is to examine the relationship between entrepreneurial orientation (innovativeness, risk-taking propensity, and proactiveness) and SME's growth in Bauchi metropolis. The study is quantitative in nature using a cross-sectional survey. The population of the study was 364 SMEs. Using simple random sampling, 183 questionnaires were personally distributed, out of which 165 (90%) were found valid for the analysis. Kregcie and Morgan (1970) table was used to determine the sample size. Pearson correlation was used to test the hypotheses. The analysis was conducted with the aid of IBM Statistical Package for Social Sciences (SPSS) version 20. The results established that innovativeness, risk-taking propensity, and proactiveness have significant positive relationship with SME's growth. It is therefore recommended that SMEs’ owners/managers should change their attitude by changing their product and mode of operation in line with customer demand, being proactive ahead of other competitors in trying a better way of doing things, and taking calculated risks in anticipation of high return in order for their businesses to survive and grow.

Keywords: SMEs growth, innovativeness, risk-taking propensity, proactiveness

Procedia PDF Downloads 106

Authors: A. Bahmanpour, I. Eames, C. Klettner, A. Dimakopoulos

Abstract:

We develop a new set of diagnostic tools to analyze inundation into a model district using three-dimensional CFD simulations, with a view to generating a database against which to test simpler models. A three-dimensional model of Oregon city with different-sized groups of building next to the coastline is used to run calculations of the movement of a long period wave on the shore. The initial and boundary conditions of the off-shore water are set using a nonlinear inverse method based on Eulerian spatial information matching experimental Eulerian time series measurements of water height. The water movement is followed in time, and this enables the pressure distribution on every surface of each building to be followed in a temporal manner. The three-dimensional numerical data set is validated against published experimental work. In the first instance, we use the dataset as a basis to understand the success of reduced models - including 2D shallow water model and reduced 1D models - to predict water heights, flow velocity and forces. This is because models based on the shallow water equations are known to underestimate drag forces after the initial surge of water. The second component is to identify critical flow features, such as hydraulic jumps and choked states, which are flow regions where dissipation occurs and drag forces are large. Finally, we describe how future tsunami inundation models should be modified to account for the complex effects of buildings through drag and blocking.Financial support from UCL and HR Wallingford is greatly appreciated. The authors would like to thank Professor Daniel Cox and Dr. Hyoungsu Park for providing the data on the Seaside Oregon experiment.

Keywords: computational fluid dynamics, extreme events, loading, tsunami

Procedia PDF Downloads 103

Authors: Yan-Ting Lin, Wei-Nian Su

Abstract:

The purpose of this paper is to demonstrate the design of 5kW vertical axis wind turbine (VAWT) using DOE method. The NACA0015 airfoil was implemented for the design and 3D simulation. The critical design parameters are chord length, tip speed ratio (TSR), aspect ratio (AR) and pitch angle in this investigation. The RNG k-ε turbulent model and the sliding mesh method are adopted in the CFD simulation. The results show that the model with zero pitch, 0.3 m in chord length, TSR of 3, and AR of 10 demonstrated the optimum aerodynamic power under the uniform 10m/s inlet velocity. The aerodynamic power is 3.61kW and 3.89kW under TSR of 3 and 4 respectively. The aerodynamic power decreased dramatically while TSR increased to 5.

Keywords: vertical axis wind turbine, CFD, DOE, VAWT

Procedia PDF Downloads 425