Search results for: genetic resource
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 4066

Search results for: genetic resource

3256 Improve Closed Loop Performance and Control Signal Using Evolutionary Algorithms Based PID Controller

Authors: Mehdi Shahbazian, Alireza Aarabi, Mohsen Hadiyan

Abstract:

Proportional-Integral-Derivative (PID) controllers are the most widely used controllers in industry because of its simplicity and robustness. Different values of PID parameters make different step response, so an increasing amount of literature is devoted to proper tuning of PID controllers. The problem merits further investigation as traditional tuning methods make large control signal that can damages the system but using evolutionary algorithms based tuning methods improve the control signal and closed loop performance. In this paper three tuning methods for PID controllers have been studied namely Ziegler and Nichols, which is traditional tuning method and evolutionary algorithms based tuning methods, that are, Genetic algorithm and particle swarm optimization. To examine the validity of PSO and GA tuning methods a comparative analysis of DC motor plant is studied. Simulation results reveal that evolutionary algorithms based tuning method have improved control signal amplitude and quality factors of the closed loop system such as rise time, integral absolute error (IAE) and maximum overshoot.

Keywords: evolutionary algorithm, genetic algorithm, particle swarm optimization, PID controller

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3255 Series Network-Structured Inverse Models of Data Envelopment Analysis: Pitfalls and Solutions

Authors: Zohreh Moghaddas, Morteza Yazdani, Farhad Hosseinzadeh

Abstract:

Nowadays, data envelopment analysis (DEA) models featuring network structures have gained widespread usage for evaluating the performance of production systems and activities (Decision-Making Units (DMUs)) across diverse fields. By examining the relationships between the internal stages of the network, these models offer valuable insights to managers and decision-makers regarding the performance of each stage and its impact on the overall network. To further empower system decision-makers, the inverse data envelopment analysis (IDEA) model has been introduced. This model allows the estimation of crucial information for estimating parameters while keeping the efficiency score unchanged or improved, enabling analysis of the sensitivity of system inputs or outputs according to managers' preferences. This empowers managers to apply their preferences and policies on resources, such as inputs and outputs, and analyze various aspects like production, resource allocation processes, and resource efficiency enhancement within the system. The results obtained can be instrumental in making informed decisions in the future. The top result of this study is an analysis of infeasibility and incorrect estimation that may arise in the theory and application of the inverse model of data envelopment analysis with network structures. By addressing these pitfalls, novel protocols are proposed to circumvent these shortcomings effectively. Subsequently, several theoretical and applied problems are examined and resolved through insightful case studies.

Keywords: inverse models of data envelopment analysis, series network, estimation of inputs and outputs, efficiency, resource allocation, sensitivity analysis, infeasibility

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3254 Solving Process Planning, Weighted Apparent Tardiness Cost Dispatching, and Weighted Processing plus Weight Due-Date Assignment Simultaneously Using a Hybrid Search

Authors: Halil Ibrahim Demir, Caner Erden, Abdullah Hulusi Kokcam, Mumtaz Ipek

Abstract:

Process planning, scheduling, and due date assignment are three important manufacturing functions which are studied independently in literature. There are hundreds of works on IPPS and SWDDA problems but a few works on IPPSDDA problem. Integrating these three functions is very crucial due to the high relationship between them. Since the scheduling problem is in the NP-Hard problem class without any integration, an integrated problem is even harder to solve. This study focuses on the integration of these functions. Sum of weighted tardiness, earliness, and due date related costs are used as a penalty function. Random search and hybrid metaheuristics are used to solve the integrated problem. Marginal improvement in random search is very high in the early iterations and reduces enormously in later iterations. At that point directed search contribute to marginal improvement more than random search. In this study, random and genetic search methods are combined to find better solutions. Results show that overall performance becomes better as the integration level increases.

Keywords: process planning, genetic algorithm, hybrid search, random search, weighted due-date assignment, weighted scheduling

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3253 Intelligent Control of Doubly Fed Induction Generator Wind Turbine for Smart Grid

Authors: Amal A. Hassan, Faten H. Fahmy, Abd El-Shafy A. Nafeh, Hosam K. M. Youssef

Abstract:

Due to the growing penetration of wind energy into the power grid, it is very important to study its interactions with the power system and to provide good control technique in order to deliver high quality power. In this paper, an intelligent control methodology is proposed for optimizing the controllers’ parameters of doubly fed induction generator (DFIG) based wind turbine generation system (WTGS). The genetic algorithm (GA) and particle swarm optimization (PSO) are employed and compared for the parameters adaptive tuning of the proposed proportional integral (PI) multiple controllers of the back to back converters of the DFIG based WTGS. For this purpose, the dynamic model of WTGS with DFIG and its associated controllers is presented. Furthermore, the simulation of the system is performed using MATLAB/SIMULINK and SIMPOWERSYSTEM toolbox to illustrate the performance of the optimized controllers. Finally, this work is validated to 33-bus test radial system to show the interaction between wind distributed generation (DG) systems and the distribution network.

Keywords: DFIG wind turine, intelligent control, distributed generation, particle swarm optimization, genetic algorithm

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3252 Genetically Informed Precision Drug Repurposing for Rheumatoid Arthritis

Authors: Sahar El Shair, Laura Greco, William Reay, Murray Cairns

Abstract:

Background: Rheumatoid arthritis (RA) is a chronic, systematic, inflammatory, autoimmune disease that involves damages to joints and erosions to the associated bones and cartilage, resulting in reduced physical function and disability. RA is a multifactorial disorder influenced by heterogenous genetic and environmental factors. Whilst different medications have proven successful in reducing inflammation associated with RA, they often come with significant side effects and limited efficacy. To address this, the novel pharmagenic enrichment score (PES) algorithm was tested in self-reported RA patients from the UK Biobank (UKBB), which is a cohort of predominantly European ancestry, and identified individuals with a high genetic risk in clinically actionable biological pathways to identify novel opportunities for precision interventions and drug repurposing to treat RA. Methods and materials: Genetic association data for rheumatoid arthritis was derived from publicly available genome-wide association studies (GWAS) summary statistics (N=97173). The PES framework exploits competitive gene set enrichment to identify pathways that are associated with RA to explore novel treatment opportunities. This data is then integrated into WebGestalt, Drug Interaction database (DGIdb) and DrugBank databases to identify existing compounds with existing use or potential for repurposed use. The PES for each of these candidates was then profiled in individuals with RA in the UKBB (Ncases = 3,719, Ncontrols = 333,160). Results A total of 209 pathways with known drug targets after multiple testing correction were identified. Several pathways, including interferon gamma signaling and TID pathway (which relates to a chaperone that modulates interferon signaling), were significantly associated with self-reported RA in the UKBB when adjusting for age, sex, assessment centre month and location, RA polygenic risk and 10 principal components. These pathways have a major role in RA pathogenesis, including autoimmune attacks against certain citrullinated proteins, synovial inflammation, and bone loss. Encouragingly, many also relate to the mechanism of action of existing RA medications. The analyses also revealed statistically significant association between RA polygenic scores and self-reported RA with individual PES scorings, highlighting the potential utility of the PES algorithm in uncovering additional genetic insights that could aid in the identification of individuals at risk for RA and provide opportunities for more targeted interventions. Conclusions In this study, pharmacologically annotated genetic risk was explored through the PES framework to overcome inter-individual heterogeneity and enable precision drug repurposing in RA. The results showed a statistically significant association between RA polygenic scores and self-reported RA and individual PES scorings for 3,719 RA patients. Interestingly, several enriched PES pathways were targeted by already approved RA drugs. In addition, the analysis revealed genetically supported drug repurposing opportunities for future treatment of RA with a relatively safe profile.

Keywords: rheumatoid arthritis, precision medicine, drug repurposing, system biology, bioinformatics

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3251 Managerial Encouragement, Organizational Encouragement, and Resource Sufficiency and Its Effect on Creativity as Perceived by Architects in Metro Manila

Authors: Ferdinand de la Paz

Abstract:

In highly creative environments such as in the business of architecture, business models exhibit more focus on the traditional practice of mainstream design consultancy services as mandated and constrained by existing legislation. Architectural design firms, as business units belonging to the creative industries, have long been provoked to innovate not only in terms of their creative outputs but, more significantly, in the way they create and capture value from what they do. In the Philippines, there is still a dearth of studies exploring organizational creativity within the context of architectural firm practice, let alone across other creative industries. The study sought to determine the effects, measure the extent, and assess the relationships of managerial encouragement, organizational encouragement, and resource sufficiency on creativity as perceived by architects. A survey questionnaire was used to gather data from 100 respondents. The analysis was done using descriptive statistics, correlational, and causal-explanatory methods. The findings reveal that there is a weak positive relationship between Managerial Encouragement (ME), Organizational Encouragement (OE), and Sufficient Resources (SR) toward Creativity (C). The study also revealed that while Organizational Creativity and Sufficient Resources have significant effects on Creativity, Managerial Encouragement does not. It is recommended that future studies with a larger sample size be pursued among architects holding top management positions in architectural design firms to further validate the findings of this research. It is also highly recommended that the other stimulant scales in the KEYS framework be considered in future studies covering other locales to generate a better understanding of the architecture business landscape in the Philippines.

Keywords: managerial encouragement, organizational encouragement, resource sufficiency, organizational creativity, architecture firm practice, creative industries

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3250 A Hybrid Data Mining Algorithm Based System for Intelligent Defence Mission Readiness and Maintenance Scheduling

Authors: Shivam Dwivedi, Sumit Prakash Gupta, Durga Toshniwal

Abstract:

It is a challenging task in today’s date to keep defence forces in the highest state of combat readiness with budgetary constraints. A huge amount of time and money is squandered in the unnecessary and expensive traditional maintenance activities. To overcome this limitation Defence Intelligent Mission Readiness and Maintenance Scheduling System has been proposed, which ameliorates the maintenance system by diagnosing the condition and predicting the maintenance requirements. Based on new data mining algorithms, this system intelligently optimises mission readiness for imminent operations and maintenance scheduling in repair echelons. With modified data mining algorithms such as Weighted Feature Ranking Genetic Algorithm and SVM-Random Forest Linear ensemble, it improves the reliability, availability and safety, alongside reducing maintenance cost and Equipment Out of Action (EOA) time. The results clearly conclude that the introduced algorithms have an edge over the conventional data mining algorithms. The system utilizing the intelligent condition-based maintenance approach improves the operational and maintenance decision strategy of the defence force.

Keywords: condition based maintenance, data mining, defence maintenance, ensemble, genetic algorithms, maintenance scheduling, mission capability

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3249 Dynamic Marketing Capabilities; From Marketing to Product Development and Technological Change: An Exploratory Study of Independent Companies of the Swiss Luxury Watchmaking Industry

Authors: Maria Bashutkina

Abstract:

In seeking to identify marketing factors that influence company’s performance, product management as well as new technology configuration, this study adopts resource based theory and applies it to the Swiss watchmaking companies. This paper presents results of qualitative research based on semi-structured interviews with CEO and marketing managers among watchmaking companies. This paper provides empirical evidences illustrating the link between the use of dynamic marketing capabilities and competitive advantage. We also present a set of propositions that outline how dynamic marketing capabilities could benefit product management and technological change in the Swiss independent watchmaking company, revealing competitive advantage in the highly competitive and turbulent market.

Keywords: dynamic marketing capabilities, luxury marketing, resource based theory, product management, Swiss watchmaking

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3248 A Genetic Identification of Candida Species Causing Intravenous Catheter-Associated Candidemia in Heart Failure Patients

Authors: Seyed Reza Aghili, Tahereh Shokohi, Shirin Sadat Hashemi Fesharaki, Mohammad Ali Boroumand, Bahar Salmanian

Abstract:

Introduction: Intravenous catheter-associated fungal infection as nosocomial infection continue to be a deep problem among hospitalized patients, decreasing quality of life and adding healthcare costs. The capacity of catheters in the spread of candidemia in heart failure patients is obvious. The aim of this study was to evaluate the prevalence and genetic identification of Candida species in heart disorder patients. Material and Methods: This study was conducted in Tehran Hospital of Cardiology Center (Tehran, Iran, 2014) during 1.5 years on the patients hospitalized for at least 7 days and who had central or peripheral vein catheter. Culture of catheters, blood and skin of the location of catheter insertion were applied for detecting Candida colonies in 223 patients. Identification of Candida species was made on the basis of a combination of various phenotypic methods and confirmed by sequencing the ITS1-5.8S-ITS2 region amplified from the genomic DNA using PCR and the NCBI BLAST. Results: Of the 223 patients samples tested, we identified totally 15 Candida isolates obtained from 9 (4.04%) catheter cultures, 3 (1.35%) blood cultures and 2 (0.90%) skin cultures of the catheter insertion areas. On the base of ITS region sequencing, out of nine Candida isolates from catheter, 5(55.6%) C. albicans, 2(22.2%) C. glabrata, 1(11.1%) C. membranifiaciens and 1 (11.1%) C. tropicalis were identified. Among three Candida isolates from blood culture, C. tropicalis, C. carpophila and C. membranifiaciens were identified. Non-candida yeast isolated from one blood culture was Cryptococcus albidus. One case of C. glabrata and one case of Candida albicans were isolated from skin culture of the catheter insertion areas in patients with positive catheter culture. In these patients, ITS region of rDNA sequence showed a similarity between Candida isolated from the skin and catheter. However, the blood samples of these patients were negative for fungal growth. We report two cases of catheter-related candidemia caused by C. membranifiaciens and C. tropicalis on the base of genetic similarity of species isolated from blood and catheter which were treated successfully with intravenous fluconazole and catheter removal. In phenotypic identification methods, we could only identify C. albicans and C. tropicalis and other yeast isolates were diagnosed as Candida sp. Discussion: Although more than 200 species of Candida have been identified, only a few cause diseases in humans. There is some evidence that non-albicans infections are increasing. Many risk factors, including prior antibiotic therapy, use of a central venous catheter, surgery, and parenteral nutrition are considered to be associated with candidemia in hospitalized heart failure patients. Identifying the route of infection in candidemia is difficult. Non-albicans candida as the cause of candidemia is increasing dramatically. By using conventional method, many non-albicans isolates remain unidentified. So, using more sensitive and specific molecular genetic sequencing to clarify the aspects of epidemiology of the unknown candida species infections is essential. The positive blood and catheter cultures for candida isolates and high percentage of similarity of their ITS region of rDNA sequence in these two patients confirmed the diagnosis of intravenous catheter-associated candidemia.

Keywords: catheter-associated infections, heart failure patient, molecular genetic sequencing, ITS region of rDNA, Candidemia

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3247 A Study on Employer Branding and Its Impacts on Employee’s

Authors: KVNKC Sharma, Soujanya Pasumarthi

Abstract:

Globalization, coupled with increase in competition is compelling organizations to adopt innovative strategies and identify core competencies in order to distinguish themselves from the competition. The capability of an organization is no longer determined by their products or services alone. The intellectual assets and quality of the human resource are fast emerging as key differentiators. Corporations are now positioning themselves as ‘brands’ not solely to market their products and services, but also to lure and to retain the best talent in the business. This paper identifies leadership as the ‘key element’ in developing an organization’s brand, which has a significant influence on the employee’s eventual perception of this external brand as portrayed by the organization. External branding incorporates innovation, consumer concern, trust, quality and sustainability. The paper contends that employees are indeed an organization’s ‘brand ambassadors. Internal branding involves taking care of these ambassadors of corporate brand i.e. human resource. If employees of an organization are not exposed to the organization’s branding (an ongoing process that functionally aligns, motivates and empower employees at all levels to consistently provide a satisfying customer experience), the external brand could be jeopardized. Internal branding, on the other hand, refers to employee’s perception of the organization’s brand. The current business environment can at best, be termed as volatile. Employees with the right technical and behavioral skills remain a scarce resource and the employers need to be ready to capture the attention, interest and commitment of the best and brightest candidates. This paper attempts to review and understand the relationship between employer branding and employee retention. The paper also seeks to identify potential impact of employer branding across all the factors affecting employees.

Keywords: alignment, external branding, internal branding, leadership

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3246 A Hybrid Feature Selection and Deep Learning Algorithm for Cancer Disease Classification

Authors: Niousha Bagheri Khulenjani, Mohammad Saniee Abadeh

Abstract:

Learning from very big datasets is a significant problem for most present data mining and machine learning algorithms. MicroRNA (miRNA) is one of the important big genomic and non-coding datasets presenting the genome sequences. In this paper, a hybrid method for the classification of the miRNA data is proposed. Due to the variety of cancers and high number of genes, analyzing the miRNA dataset has been a challenging problem for researchers. The number of features corresponding to the number of samples is high and the data suffer from being imbalanced. The feature selection method has been used to select features having more ability to distinguish classes and eliminating obscures features. Afterward, a Convolutional Neural Network (CNN) classifier for classification of cancer types is utilized, which employs a Genetic Algorithm to highlight optimized hyper-parameters of CNN. In order to make the process of classification by CNN faster, Graphics Processing Unit (GPU) is recommended for calculating the mathematic equation in a parallel way. The proposed method is tested on a real-world dataset with 8,129 patients, 29 different types of tumors, and 1,046 miRNA biomarkers, taken from The Cancer Genome Atlas (TCGA) database.

Keywords: cancer classification, feature selection, deep learning, genetic algorithm

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3245 Cost-Based Analysis of Cloud and Traditional ERP Systems in Small and Medium Enterprises

Authors: Indu Saini, Ashu Khanna, S. K. Peddoju

Abstract:

Cloud computing is the new buzz word today attracting high interest among various domains like business enterprises, Particularly in Small and Medium Enterprises. As it is a pay-per-use model, SMEs have high expectations that adapting this model will not only make them flexible, hassle-free but also economic. In view of such expectations, this paper analyses the possibility of adapting cloud computing technologies in SMEs in light of economic concerns. In this paper, two hypotheses are developed to compare the average annual per-user costs of using Enterprise Resource Planning systems in two ways, The traditional approach and the cloud approach. A web based survey is conducted apart from the Interviews with the peers to collect the data across the selected SMEs and t-test is performed to compare both the technologies on the proposed hypothesis. Results achieved are produced and discussed.

Keywords: cloud computing, small and medium enterprises, enterprise resource solutions, interviews

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3244 A Review of the Potential Impact of Employer Branding on Employee

Authors: K. V. N. K. C. Sharma

Abstract:

Globalization, coupled with increase in competition is compelling organizations to adopt innovative strategies and identify core competencies in order to distinguish themselves from the competition. The capability of an organization is no longer determined by their products or services alone. The intellectual assets and quality of the human resource are fast emerging as key differentiators. Corporations are now positioning themselves as ‘brands’ not solely to market their products and services, but also to lure and to retain the best talent in the business. This paper identifies leadership as the ‘key element’ in developing an organization’s brand, which has a significant influence on the employee’s eventual perception of this external brand as portrayed by the organization. External branding incorporates innovation, consumer concern, trust, quality and sustainability. The paper contends that employees are indeed an organization’s ‘brand ambassadors. Internal branding involves taking care of these ambassadors of corporate brand i.e. human resource. If employees of an organization are not exposed to the organization’s branding (an ongoing process that functionally aligns, motivates and empower employees at all levels to consistently provide a satisfying customer experience), the external brand could be jeopardized. Internal branding, on the other hand, refers to employee’s perception of the organization’s brand. The current business environment can at best, be termed as volatile. Employees with the right technical and behavioral skills remain a scarce resource and the employers need to be ready to capture the attention, interest and commitment of the best and brightest candidates. This paper attempts to review and understand the relationship between employer branding and employee retention. The paper also seeks to identify potential impact of employer branding across all the factors affecting employees.

Keywords: external branding, organisation personnel, internal branding, leadership

Procedia PDF Downloads 239
3243 Research on Load Balancing Technology for Web Service Mobile Host

Authors: Yao Lu, Xiuguo Zhang, Zhiying Cao

Abstract:

In this paper, Load Balancing idea is used in the Web service mobile host. The main idea of Load Balancing is to establish a one-to-many mapping mechanism: An entrance-mapping request to plurality of processing node in order to realize the dividing and assignment processing. Because the mobile host is a resource constrained environment, there are some Web services which cannot be completed on the mobile host. When the mobile host resource is not enough to complete the request, Load Balancing scheduler will divide the request into a plurality of sub-requests and transfer them to different auxiliary mobile hosts. Auxiliary mobile host executes sub-requests, and then, the results will be returned to the mobile host. Service request integrator receives results of sub-requests from the auxiliary mobile host, and integrates the sub-requests. In the end, the complete request is returned to the client. Experimental results show that this technology adopted in this paper can complete requests and have a higher efficiency.

Keywords: Dinic, load balancing, mobile host, web service

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3242 Relations between Human Capital Investments and Business Excellence in Croatian Companies

Authors: Ivana Tadić, Željana Aljinović Barać, Nikolina Plazonić

Abstract:

Living today in turbulent business environment forces companies to distinguish from each other, securing sustainable competitive growth and competitive advantage. The best possible solution is to invest (effort and financial resources) within companies’ different practices of human resource management (HRM), more specifically in employees’ knowledge, skills and abilities. Applying this approach companies will create enviable level of human capital securing its economic growth. Employees become human capital for their employers at the moment when they contribute with their own knowledge and abilities in creating material and non-material value of the company. The main aim of this research is to explore the relations between human capital investments and business excellence of Croatian companies. Furthermore, the differences in the level of human capital investments with regard to several companies’ characteristics (e.g. size of the company, ownership and type of the industry) are investigated.

Keywords: business excellence, Croatian industries, human capital investments, human resource management

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3241 Scheduling of Cross-Docking Center: An Auction-Based Algorithm

Authors: Eldho Paul, Brijesh Paul

Abstract:

This work proposes an auction mechanism based solution methodology for the optimum scheduling of trucks in a cross-docking centre. The cross-docking centre is an important element of lean supply chain. It reduces the amount of storage and transportation costs in the distribution system compared to an ordinary warehouse. Better scheduling of trucks in a cross-docking center is the best way to reduce storage and transportation costs. Auction mechanism is commonly used for allocation of limited resources in different real-life applications. Here, we try to schedule inbound trucks by integrating auction mechanism with the functioning of a cross-docking centre. A mathematical model is developed for the optimal scheduling of inbound trucks based on the auction methodology. The determination of exact solution for problems involving large number of trucks was found to be computationally difficult, and hence a genetic algorithm based heuristic methodology is proposed in this work. A comparative study of exact and heuristic solutions is done using five classes of data sets. It is observed from the study that the auction-based mechanism is capable of providing good solutions to scheduling problem in cross-docking centres.

Keywords: auction mechanism, cross-docking centre, genetic algorithm, scheduling of trucks

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3240 A System Dynamic Based DSS for Ecological Urban Management in Alexandria, Egypt

Authors: Mona M. Salem, Khaled S. Al-Hagla, Hany M. Ayad

Abstract:

The concept of urban metabolism has increasingly been employed in a diverse range of disciplines as a mean to analyze and theorize the city. Urban ecology has a particular focus on the implications of applying the metabolism concept to the urban realm. This approach has been developed by a few researchers, though it has rarely if ever been used in policy development for city planning. The aim of this research is to use ecologically informed urban planning interventions to increase the sustainability of urban metabolism; with special focus on land stock as a most important city resource by developing a system dynamic based DSS. This model identifies two critical management strategy variables for the Strategic Urban Plan Alexandria SUP 2032. As a result, this comprehensive and precise quantitative approach is needed to monitor, measure, evaluate and observe dynamic urban changes working as a decision support system (DSS) for policy making.

Keywords: ecology, land resource, LULCC, management, metabolism, model, scenarios, system dynamics, urban development

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3239 Factor Analysis on Localization of Human Resources of Japanese Firms in Taiwan

Authors: Nana Weng

Abstract:

Localization in the aspect of human resource means more diversity and more opportunities. The main purpose of this article is to identify the perception of local employees and intermediate managers (non-Japanese) and figure out exploratory factors which have been contributing and blocking the level of localization in the aspect of human resource management by using EFA (Exploratory Factors Analysis). Questionnaires will be designed for local employees and managers to inquire about the perceptions of regulations and implementation regarding recruitment, training and development, promotion and rewarding. The study finds that Japanese firms have worked well in the process of localization, especially in hiring and training local staffs in Taiwan. The significance of this study lies in paying more attention to the perception of local employees and intermediate managers regarding localization rather than interviews results from Japanese expatriates or top HR managers who are in charging of localization policy-making.

Keywords: Japanese firms in Taiwan, localization of human resources, exploratory factors analysis, local employees and intermediate managers

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3238 Agent-Based Simulation for Supply Chain Transport Corridors

Authors: Kamalendu Pal

Abstract:

Supply chains are the spinal cord of trade and commerce. Their logistics use different transport corridors on regular basis for operational purpose. The international supply chain transport corridors include different infrastructure elements (e.g. weighbridge, package handling equipment, border clearance authorities, and so on) in supply chains. This paper presents the use of multi-agent systems (MAS) to model and simulate some aspects of transportation corridors, and in particular the area of weighbridge resource optimization for operational profit generation purpose. An underlying multi-agent model provides a means of modeling the relationships among stakeholders in order to enable coordination in a transport corridor environment. Simulations of the costs of container unloading, reloading, and waiting time for queuing up tracks have been carried out using data sets. Results of the simulation provide the potential guidance in making decisions about optimal service resource allocation in a trade corridor.

Keywords: multi-agent systems, simulation, supply chain, transport corridor, weighbridge

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3237 Effect of an Interface Defect in a Patch/Layer Joint under Dynamic Time Harmonic Load

Authors: Elisaveta Kirilova, Wilfried Becker, Jordanka Ivanova, Tatyana Petrova

Abstract:

The study is a continuation of the research on the hygrothermal piezoelectric response of a smart patch/layer joint with undesirable interface defect (gap) at dynamic time harmonic mechanical and electrical load and environmental conditions. In order to find the axial displacements, shear stress and interface debond length in a closed analytical form for different positions of the interface gap, the 1D modified shear lag analysis is used. The debond length is represented as a function of many parameters (frequency, magnitude, electric displacement, moisture and temperature, joint geometry, position of the gap along the interface, etc.). Then the Genetic algorithm (GA) is implemented to find this position of the gap along the interface at which a vanishing/minimal debond length is ensured, e.g to find the most harmless position for the safe work of the structure. The illustrative example clearly shows that analytical shear-lag solutions and GA method can be combined successfully to give an effective prognosis of interface shear stress and interface delamination in patch/layer structure at combined loading with existing defects. To show the effect of the position of the interface gap, all obtained results are given in figures and discussed.

Keywords: genetic algorithm, minimal delamination, optimal gap position, shear lag solution

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3236 Evaluation of Genetic Diversity for Salt Stress in Maize Hybrids (Zea Mays L.) at Seedling Stage

Authors: Abdu Qayyum, Hafiz Muhammad Saeed, Mamoona Hanif, Etrat Noor, Waqas Malik, Shoaib Liaqat

Abstract:

Salinity is extremely serious problem that has a drastic effect on maize crop, environment and causes economic losses of country. An advance technique to overcome salinity is to develop salt tolerant geno types which require screening of huge germ plasm to start a breeding program. Therefore, present study was undertaken to screen out 25 maize hybrids of different origin for salinity tolerance at seedling stage under three levels of salt stress 250 and 300 mM NaCl including one control. The existence of variation for tolerance to enhanced NaCl salinity levels at seedling stage in maize proved that hybrids had differing ability to grow under saline environment and potential variability within specie. Almost all the twenty five maize hybrids behaved varyingly in response to different salinity levels. However, the maize hybrids H6, H13, H21, H23 and H24 expressed better performance under salt stress in terms of all six characters and proved to be as highly tolerant while H22, H17 H20, H18, H4, H9, and H8 were identified as moderately tolerant. Hybrids H14, H5, H11 and H3 H12, H2, were expressed as most sensitive to salinity suggesting that screening is an effective tool to exploit genetic variation among maize hybrids and salt tolerance in maize can be enhanced through selection and breeding procedure.

Keywords: salinity, hybrids, maize, variation

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3235 Evaluation of Egg Quality Parameters in the Isa Brown Line in Intensive Production Systems in the Ocaña Region, Norte de Santander

Authors: Meza-Quintero Myriam, Lobo Torrado Katty Andrea, Sanchez Picon Yesenia, Hurtado-Lugo Naudin

Abstract:

The objective of the study was to evaluate the internal and external quality of the egg in the three production housing systems: floor, cage, and grazing of laying birds of the Isa Brown line, in the laying period between weeks 35 to 41; 135 hens distributed in 3 treatments of 45 birds per repetition were used (the replicas were the seven weeks of the trial). The feeding treatment supplied in the floor and cage systems contained 114 g/bird/day; for the grazing system, 14 grams less concentrate was provided. Nine eggs were collected to be studied and analyzed in the animal nutrition laboratory (3 eggs per housing system). The random statistical model was implemented: for the statistical analysis of the data, the statistical software of IBM® Statistical Products and Services Solution (SPSS) version 2.3 was used. The evaluation and follow-up instruments were the vernier caliper for the measurement in millimeters, a YolkFan™16 from Roche DSM for the evaluation of the egg yolk pigmentation, a digital scale for the measurement in grams, a micrometer for the measurement in millimeters and evaluation in the laboratory using dry matter, ashes, and ethereal extract. The results suggested that equivalent to the size of the egg (0.04 ± 3.55) and the thickness of the shell (0.46 ± 3.55), where P-Value> 0.05 was obtained, weight albumen (0.18 ± 3.55), albumen height (0.38 ± 3.55), yolk weight (0.64 ± 3.55), yolk height (0.54 ± 3.55) and for yolk pigmentation (1.23 ± 3.55). It was concluded that the hens in the three production systems, floor, cage, and grazing, did not show significant statistical differences in the internal and external quality of the chicken in the parameters studied egg for the production system.

Keywords: biological, territories, genetic resource, egg

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3234 A Hybrid Expert System for Generating Stock Trading Signals

Authors: Hosein Hamisheh Bahar, Mohammad Hossein Fazel Zarandi, Akbar Esfahanipour

Abstract:

In this paper, a hybrid expert system is developed by using fuzzy genetic network programming with reinforcement learning (GNP-RL). In this system, the frame-based structure of the system uses the trading rules extracted by GNP. These rules are extracted by using technical indices of the stock prices in the training time period. For developing this system, we applied fuzzy node transition and decision making in both processing and judgment nodes of GNP-RL. Consequently, using these method not only did increase the accuracy of node transition and decision making in GNP's nodes, but also extended the GNP's binary signals to ternary trading signals. In the other words, in our proposed Fuzzy GNP-RL model, a No Trade signal is added to conventional Buy or Sell signals. Finally, the obtained rules are used in a frame-based system implemented in Kappa-PC software. This developed trading system has been used to generate trading signals for ten companies listed in Tehran Stock Exchange (TSE). The simulation results in the testing time period shows that the developed system has more favorable performance in comparison with the Buy and Hold strategy.

Keywords: fuzzy genetic network programming, hybrid expert system, technical trading signal, Tehran stock exchange

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3233 Forecasting Optimal Production Program Using Profitability Optimization by Genetic Algorithm and Neural Network

Authors: Galal H. Senussi, Muamar Benisa, Sanja Vasin

Abstract:

In our business field today, one of the most important issues for any enterprises is cost minimization and profit maximization. Second issue is how to develop a strong and capable model that is able to give us desired forecasting of these two issues. Many researches deal with these issues using different methods. In this study, we developed a model for multi-criteria production program optimization, integrated with Artificial Neural Network. The prediction of the production cost and profit per unit of a product, dealing with two obverse functions at same time can be extremely difficult, especially if there is a great amount of conflict information about production parameters. Feed-Forward Neural Networks are suitable for generalization, which means that the network will generate a proper output as a result to input it has never seen. Therefore, with small set of examples the network will adjust its weight coefficients so the input will generate a proper output. This essential characteristic is of the most important abilities enabling this network to be used in variety of problems spreading from engineering to finance etc. From our results as we will see later, Feed-Forward Neural Networks has a strong ability and capability to map inputs into desired outputs.

Keywords: project profitability, multi-objective optimization, genetic algorithm, Pareto set, neural networks

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3232 Agricultural Biotechnology Crop Improvement

Authors: Mohsen Rezaei Aghdam

Abstract:

Recombinant DNA technology has meaningfully augmented the conventional crop improvement and has a great possibility to contribution plant breeders to encounter the augmented food request foretold for the 21st century. Predictable changes in weather and its erraticism, chiefly extreme fevers and vicissitudes in rainfall are expected to brand crop upgrading even more vital for food manufacture. Tissue attitude has been downtrodden to create genetic erraticism from which harvest plants can be better, to improve the state of health of the recognized physical and to upsurge the number of wanted germplasms obtainable to the plant breeder. This appraisal delivers an impression of the chances obtainable by the integration of vegetable biotechnology into plant development efforts and increases some of the social subjects that need to be considered in their application. Public-private companies offer chances to catalyze new approaches and investment while accelerating integrated research and development and commercial supply chain-based solutions. Novel varieties derivative by encouraged mutatgenesis are used commonly: rice in Thailand. These paper combinations obtainable data about the influence of change breeding-derived crop changes around the world, traveler magnetism the possibility of mutation upbringing as a flexible and feasible approach appropriate to any crop if that suitable objectives and selection approaches are used.

Keywords: crop, improve, genetic, agricultural

Procedia PDF Downloads 167
3231 Smart Production Planning: The Case of Aluminium Foundry

Authors: Samira Alvandi

Abstract:

In the context of the circular economy, production planning aims to eliminate waste and emissions and maximize resource efficiency. Historically production planning is challenged through arrays of uncertainty and complexity arising from the interdependence and variability of products, processes, and systems. Manufacturers worldwide are facing new challenges in tackling various environmental issues such as climate change, resource depletion, and land degradation. In managing the inherited complexity and uncertainty and yet maintaining profitability, the manufacturing sector is in need of a holistic framework that supports energy efficiency and carbon emission reduction schemes. The proposed framework addresses the current challenges and integrates simulation modeling with optimization for finding optimal machine-job allocation to maximize throughput and total energy consumption while minimizing lead time. The aluminium refinery facility in western Sydney, Australia, is used as an exemplar to validate the proposed framework.

Keywords: smart production planning, simulation-optimisation, energy aware capacity planning, energy intensive industries

Procedia PDF Downloads 76
3230 Wait-Optimized Scheduler Algorithm for Efficient Process Scheduling in Computer Systems

Authors: Md Habibur Rahman, Jaeho Kim

Abstract:

Efficient process scheduling is a crucial factor in ensuring optimal system performance and resource utilization in computer systems. While various algorithms have been proposed over the years, there are still limitations to their effectiveness. This paper introduces a new Wait-Optimized Scheduler (WOS) algorithm that aims to minimize process waiting time by dividing them into two layers and considering both process time and waiting time. The WOS algorithm is non-preemptive and prioritizes processes with the shortest WOS. In the first layer, each process runs for a predetermined duration, and any unfinished process is subsequently moved to the second layer, resulting in a decrease in response time. Whenever the first layer is free or the number of processes in the second layer is twice that of the first layer, the algorithm sorts all the processes in the second layer based on their remaining time minus waiting time and sends one process to the first layer to run. This ensures that all processes eventually run, optimizing waiting time. To evaluate the performance of the WOS algorithm, we conducted experiments comparing its performance with traditional scheduling algorithms such as First-Come-First-Serve (FCFS) and Shortest-Job-First (SJF). The results showed that the WOS algorithm outperformed the traditional algorithms in reducing the waiting time of processes, particularly in scenarios with a large number of short tasks with long wait times. Our study highlights the effectiveness of the WOS algorithm in improving process scheduling efficiency in computer systems. By reducing process waiting time, the WOS algorithm can improve system performance and resource utilization. The findings of this study provide valuable insights for researchers and practitioners in developing and implementing efficient process scheduling algorithms.

Keywords: process scheduling, wait-optimized scheduler, response time, non-preemptive, waiting time, traditional scheduling algorithms, first-come-first-serve, shortest-job-first, system performance, resource utilization

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3229 The Sustainability of Human Resource Planning for Construction Projects

Authors: Adegbenga Ashiru, Adebimpe L. Ashiru

Abstract:

The construction industry is considered to work by diversifying personnel. Hence managing human resource is an issue considered to be a highly challenging task. Nonetheless, HR planning for the construction project is a very critical aspect of managing human resource within an expanding nature of construction industry, and there are rising concerns over the failure of construction planning to achieve its goals in spite of the substantial resources allocated to it and as a result of different planning strategies. To justify the above statement, this research was carried out to examine the sustainability of HR planning for construction project. Based on the researcher’s experience, a quantitative approach was adopted that provided a broader understanding of the research and was analysed using descriptive statistics and inferential statistics. The Statistical Package for the Social Sciences (SPSS) was used to obtain the descriptive and inferential statistical analysis. However, research findings showed that literature sources agreed with varying challenges of HR planning on construction projects which were justified by empirical findings. Also, the paper identified four major factors and the key consideration for Project HR Planning (Organisation’s structure with right individuals at right positions and evaluation current resources) will lead to the efficient utilisation implementation of new HR Planning technique and tools for a construction project. Essentially the main reoccurring theme identified was that management of the construction organisations needs to look into the essential factors needed to be considered at the strategic level. Furthermore, leaders leading a construction project team should consider those essential factors needed at the operational level to clarify the numerous functions of HRM in the construction organisations and avoid inconsistencies among several practices on construction projects. The Sustainability of HR planning for construction project policy was indicated and recommendations were made for further future research.

Keywords: construction industry, HRM planning in construction, SHRM in construction, HR planning in construction

Procedia PDF Downloads 351
3228 An Improved Data Aided Channel Estimation Technique Using Genetic Algorithm for Massive Multi-Input Multiple-Output

Authors: M. Kislu Noman, Syed Mohammed Shamsul Islam, Shahriar Hassan, Raihana Pervin

Abstract:

With the increasing rate of wireless devices and high bandwidth operations, wireless networking and communications are becoming over crowded. To cope with such crowdy and messy situation, massive MIMO is designed to work with hundreds of low costs serving antennas at a time as well as improve the spectral efficiency at the same time. TDD has been used for gaining beamforming which is a major part of massive MIMO, to gain its best improvement to transmit and receive pilot sequences. All the benefits are only possible if the channel state information or channel estimation is gained properly. The common methods to estimate channel matrix used so far is LS, MMSE and a linear version of MMSE also proposed in many research works. We have optimized these methods using genetic algorithm to minimize the mean squared error and finding the best channel matrix from existing algorithms with less computational complexity. Our simulation result has shown that the use of GA worked beautifully on existing algorithms in a Rayleigh slow fading channel and existence of Additive White Gaussian Noise. We found that the GA optimized LS is better than existing algorithms as GA provides optimal result in some few iterations in terms of MSE with respect to SNR and computational complexity.

Keywords: channel estimation, LMMSE, LS, MIMO, MMSE

Procedia PDF Downloads 191
3227 Geospatial Information for Smart City Development

Authors: Simangele Dlamini

Abstract:

Smart city development is seen as a way of facing the challenges brought about by the growing urban population the world over. Research indicates that cities have a role to play in combating urban challenges like crime, waste disposal, greenhouse gas emissions, and resource efficiency. These solutions should be such that they do not make city management less sustainable but should be solutions-driven, cost and resource-efficient, and smart. This study explores opportunities on how the City of Johannesburg, South Africa, can use Geographic Information Systems, Big Data and the Internet of Things (IoT) in identifying opportune areas to initiate smart city initiatives such as smart safety, smart utilities, smart mobility, and smart infrastructure in an integrated manner. The study will combine Big Data, using real-time data sources to identify hotspot areas that will benefit from ICT interventions. The GIS intervention will assist the city in avoiding a silo approach in its smart city development initiatives, an approach that has led to the failure of smart city development in other countries.

Keywords: smart cities, internet of things, geographic information systems, johannesburg

Procedia PDF Downloads 148