Search results for: Demand & supply chain management

Authors: Myagmarsuren Soronzonjav, N. Togtokhbayar, L. Davaahuu, B. Minjigdorj, Seong Gu Hwang

Abstract:

The number of natural or organic product consumers is increased in recent years and this healthy demand pushes to increase usage of healthy meat. At the same time, consumers pay more attention on the healthy fat, especially on unsaturated fatty acids. These long chain carbohydrates reduce heart diseases, improve memory and eye sight and activate the immune system. One of the important issues to be solved for our Mongolia’s food security is to provide healthy, fresh, widely available and cheap meat for the population. Thus, an importance of the Selenge breed meat production is increasing in order to supply the quality meat food security since the Selenge breed cattle are rapidly multiplied, beneficial in term of income, the same quality as Mongolian breed, and well digested for human body. We researched the lipid, unsaturated and saturated fatty acid contents of meat of Selenge breed younger cattle by their muscle types. Result of our research reveals that 11 saturated fatty acids are detected. For the content of palmitic acid among saturated fatty acids, 23.61% was in the sirloin meat, 24.01% was in the round and chuck meat, and 24.83% was in the short loin meat.

Keywords: Chromatogram, gas chromatography, organic resolving, saturated and unsaturated fatty acids.

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Authors: Ghulam Haider Haidaree, Nsenda Lukumwena

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Most developing nations face energy production and supply problems. This is also the case of Afghanistan whose generating capacity does not meet its energy demand. This is due in part to high security and risk caused by war which deters foreign investments and insufficient internal revenue. To address the issue above, this paper would like to suggest an alternative and affordable way to deal with the energy problem. That is by converting Solid Waste to energy. As a result, this approach tackles the municipal solid waste issue (potential cause of several diseases), contributes to the improvement of the quality of life, local economy, and so on. While addressing the solid waste problem in general, this paper samples specifically one municipality which is District-12, one of the 22 districts of Kabul city. Using geographic information system (GIS) technology, District-12 is divided into nine different zones whose municipal solid waste is respectively collected, processed, and converted into electricity and distributed to the closest area. It is important to mention that GIS has been used to estimate the amount of electricity to be distributed and to optimally position the production plant.

Keywords: Energy problem, estimation of electricity, GIS zones, solid waste management system.

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Authors: Tsietsi J. Pilusa, Tumisang G. Seodigeng

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This study evaluates the benefits of advanced waste management practices in unlocking waste-to-energy opportunities within the solid waste industry. The key drivers of sustainable waste management practices, specifically with respect to packaging waste-to-energy technology options are discussed. The success of a waste-to-energy system depends significantly on the appropriateness of available technologies, including those that are well established as well as those that are less so. There are hard and soft interventions to be considered when packaging an integrated waste treatment solution. Technology compatibility with variation in feedstock (waste) quality and quantities remains a key factor. These factors influence the technology reliability in terms of production efficiencies and product consistency, which in turn, drives the supply and demand network. Waste treatment technologies rely on the waste material as feedstock; the feedstock varies in quality and quantities depending on several factors; hence, the technology fails, as a result. It is critical to design an advanced waste treatment technology in an integrated approach to minimize the possibility of technology failure due to unpredictable feedstock quality, quantities, conversion efficiencies, and inconsistent product yield or quality. An integrated waste-to-energy approach offers a secure system design that considers sustainable waste management practices.

Keywords: Emerging markets, evaluation tool, interventions, waste treatment technologies.

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Authors: Linh Thi Truc Doan, Yousef Amer, Sang-Heon Lee, Phan Nguyen Ky Phuc

Abstract:

During the last few decades, with the high-speed upgrade of electronic products, electronic waste (e-waste) has become one of the fastest growing wastes of the waste stream. In this context, more efforts and concerns have already been placed on the treatment and management of this waste. To mitigate their negative influences on the environment and society, it is necessary to establish appropriate strategies for e-waste management. Hence, this paper aims to review and analysis some useful strategies which have been applied in several countries to handle e-waste. Future perspectives on e-waste management are also suggested. The key findings found that, to manage e-waste successfully, it is necessary to establish effective reverse supply chains for e-waste, and raise public awareness towards the detrimental impacts of e-waste. The result of the research provides valuable insights to governments, policymakers in establishing e-waste management in a safe and sustainable manner.

Keywords: E-waste, e-waste management, life cycle assessment, recycling regulations.

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Authors: G. S. Ayyappan, M. Raja Raghavan, R. Poonthalir, Kota Srinivas, B. Ramesh Babu

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Electrical energy demand in the World and particularly in India, is increasing drastically more than its production over a period of time. In order to reduce the demand-supply gap, conserving energy becomes mandatory. Induction motors are the main driving force in the industries and contributes to about half of the total plant energy consumption. By effective monitoring and control of induction motors, huge electricity can be saved. This paper deals about the design and development of such a system, which employs iLON Smart Server and motor performance monitoring nodes. These nodes will monitor the performance of induction motors on-line, on-site and in-situ in the industries. The node monitors the performance of motors by simply measuring the electrical power input and motor shaft speed; coupled to genetic algorithm to estimate motor efficiency. The nodes are connected to the iLON Server through RS485 network. The web server collects the motor performance data from nodes, displays online, logs periodically, analyzes, alerts, and generates reports. The system could be effectively used to operate the motor around its Best Operating Point (BOP) as well as to perform the Life Cycle Assessment of Induction motors used in the industries in continuous operation.

Keywords: Best operating point, iLON smart server, motor asset management, LONWORKS, Modbus RTU, motor performance.

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Authors: Ahmed Elsayed, Andrew Shea, Nicolas Kelly, John Allison

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In northern European climates, domestic space heating and hot water represents a significant proportion of total primary total primary energy use and meeting these demands from a national electricity grid network supplied by renewable energy sources provides an opportunity for a significant reduction in EU CO₂ emissions. However, in order to adapt to the intermittent nature of renewable energy generation and to avoid co-incident peak electricity usage from consumers that may exceed current capacity, the demand for heat must be decoupled from its generation. Storage of heat within the fabric of dwellings for use some hours, or days, later provides a route to complete decoupling of demand from supply and facilitates the greatly increased use of renewable energy generation into a local or national electricity network. The integration of thermal energy storage into the building fabric for retrieval at a later time requires much evaluation of the many competing thermal, physical, and practical considerations such as the profile and magnitude of heat demand, the duration of storage, charging and discharging rate, storage media, space allocation, etc. In this paper, the authors report investigations of thermal storage in building fabric using concrete material and present an evaluation of several factors that impact upon performance including heating pipe layout, heating fluid flow velocity, storage geometry, thermo-physical material properties, and also present an investigation of alternative storage materials and alternative heat transfer fluids. Reducing the heating pipe spacing from 200 mm to 100 mm enhances the stored energy by 25% and high-performance Vacuum Insulation results in heat loss flux of less than 3 W/m², compared to 22 W/m² for the more conventional EPS insulation. Dense concrete achieved the greatest storage capacity, relative to medium and light-weight alternatives, although a material thickness of 100 mm required more than 5 hours to charge fully. Layers of 25 mm and 50 mm thickness can be charged in 2 hours, or less, facilitating a fast response that could, aggregated across multiple dwellings, provide significant and valuable reduction in demand from grid-generated electricity in expected periods of high demand and potentially eliminate the need for additional new generating capacity from conventional sources such as gas, coal, or nuclear.

Keywords: Fabric integrated thermal storage, FITS, demand side management, energy storage, load shifting, renewable energy integration.

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Authors: Haiyan Wang

Abstract:

Business interpreting talents are in badly need for local economic development, but currently there are problems of traditional business interpreting training mode in China. In view of the good opportunity for college business interpreters provided by international trading center development in Qingdao China and with the aim of being in line with market demand and enhancing business interpreters' employment competitive advantage, this paper aims to explore how to cultivate interdisciplinary business interpreting talents based on market demand.

Keywords: Interdisciplinary talents, business interpreting, market demand.

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Authors: G. M. Arun Prasath, N. Arthi

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This work proposed a multi-objective mathematical programming approach to select the appropriate supply network elements. The multi-item multi-objective production-distribution inventory model is formulated with possible constraints under fuzzy environment. The unit cost has taken under fuzzy environment. The inventory model and warehouse location model has combined to formulate the production-distribution inventory model. Warehouse location is important in supply chain network. Particularly, if a company maintains more selling stores it cannot maintain individual secondary warehouse near to each selling store. Hence, maintaining the optimum number of secondary warehouses is important. Hence, the combined mathematical model is formulated to reduce the total expenditure of the organization by arranging the network of minimum number of secondary warehouses. Numerical example has been taken to illustrate the proposed model.

Keywords: Fuzzy inventory model, warehouse location model, triangular fuzzy number, secondary warehouse, LINGO software.

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Authors: Yi Yu, Lin Ma, Yong Sun, Yuantong Gu

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This paper presents a novel method for remaining useful life prediction using the Elliptical Basis Function (EBF) network and a Markov chain. The EBF structure is trained by a modified Expectation-Maximization (EM) algorithm in order to take into account the missing covariate set. No explicit extrapolation is needed for internal covariates while a Markov chain is constructed to represent the evolution of external covariates in the study. The estimated external and the unknown internal covariates constitute an incomplete covariate set which are then used and analyzed by the EBF network to provide survival information of the asset. It is shown in the case study that the method slightly underestimates the remaining useful life of an asset which is a desirable result for early maintenance decision and resource planning.

Keywords: Elliptical Basis Function Network, Markov Chain, Missing Covariates, Remaining Useful Life

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Authors: Govind Shay Sharma, Randhir Singh Baghel

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The stock management of raw materials and finished goods is a significant issue for industries in fulfilling customer demand. Optimization of inventory strategies is crucial to enhancing customer service, reducing lead times and costs, and meeting market demand. This paper suggests finding an approach to predict the optimum stock level by utilizing past stocks and forecasting the required quantities. In this paper, we utilized Artificial Neural Network (ANN) to determine the optimal value. The objective of this paper is to discuss the optimized ANN that can find the best solution for the inventory model. In the context of the paper, we mentioned that the k-means algorithm is employed to create homogeneous groups of items. These groups likely exhibit similar characteristics or attributes that make them suitable for being managed using uniform inventory control policies. The paper proposes a method that uses the neural fit algorithm to control the cost of inventory.

Keywords: Artificial Neural Network, inventory management, optimization, distributor center.

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Authors: A. Bumbová, M. Čáslavský, F. Božek, J. Dvořák, E. Bakoš

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The paper presents the case study of hazard identification and sensitivity of potential resource of emergency water supply as part of the application of methodology classifying the resources of drinking water for emergency supply of population. The case study has been carried out on a selected resource of emergency water supply in one region of the Czech Republic. The hazard identification and sensitivity of potential resource of emergency water supply is based on a unique procedure and developed general registers of selected types of hazards and sensitivities. The registers have been developed with the help of the “Fault Tree Analysis” method in combination with the “What if method”. The identified hazards for the assessed resource include hailstorms and torrential rains, drought, soil erosion, accidents of farm machinery, and agricultural production. The developed registers of hazards and vulnerabilities and a semi-quantitative assessment of hazards for individual parts of hydrological structure and technological elements of presented drilled wells are the basis for a semi-quantitative risk assessment of potential resource of emergency supply of population and the subsequent classification of such resource within the system of crisis planning.

Keywords: Hazard identification, register of hazards, sensitivity identification, register of sensitivity, emergency water supply, state of crisis, resource of emergency water supply, ground water.

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Authors: Huey-Kuo Chen

Abstract:

Travel demand forecasting including four travel choices, i.e., trip generation, trip distribution, modal split and traffic assignment constructs the core of transportation planning. In its current application, travel demand forecasting has associated with three important issues, i.e., interface inconsistencies among four travel choices, inefficiency of commonly used solution algorithms, and undesirable multiple path solutions. In this paper, each of the three issues is extensively elaborated. An ideal unified framework for the combined model consisting of the four travel choices and variable demand functions is also suggested. Then, a few remarks are provided in the end of the paper

Keywords: Travel choices, B algorithm, entropy maximization, dynamic traffic assignment.

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Authors: Yousef S. Al-Othman

Abstract:

The growth and expansion of the industrial facilities comes proportional to the market increasing demand of products and services. Furthermore, raw material producers such as oil companies usually undergo massive revamping projects to maintain a synchronized supply. These revamping projects are usually delivered through challenging construction projects held and associated with daily site risks related to the construction process. Henceforth, a case study related to these risks and corresponding on-spot corrective measurements has been made on a certain number of construction project contractors at Kuwait Oil Company (KOC) to derive the benefits and overall effectiveness of the on-spot corrective measurements during the construction phase of a project, and how would the same help in avoiding major incidents, ensuring a smooth, cost effective and on time delivery of the project. Findings of this case study shall have an added value to the overall risk management process by minimizing the daily site risks that may affect the project lead time, resulting in an undisturbed on-site construction process.

Keywords: Oil and gas, risk management, construction projects, project lead time.

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Authors: Zhaohui Wen

Abstract:

In this paper, a food chain model with Holling type II functional response on time scales is investigated. By using the Mawhin-s continuation theorem in coincidence degree theory, sufficient conditions for existence of periodic solutions are obtained.

Keywords: Periodic solutions, food chain model, coincidence degree, time scales.

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Authors: Li Qiang, Yang Ze-Ming, Liu Bao-Xu, Jiang Zheng-Wei

Abstract:

With the increasing complexity of cyberspace security, the cyber-attack attribution has become an important challenge of the security protection systems. The difficult points of cyber-attack attribution were forced on the problems of huge data handling and key data missing. According to this situation, this paper presented a reasoning method of cyber-attack attribution based on threat intelligence. The method utilizes the intrusion kill chain model and Bayesian network to build attack chain and evidence chain of cyber-attack on threat intelligence platform through data calculation, analysis and reasoning. Then, we used a number of cyber-attack events which we have observed and analyzed to test the reasoning method and demo system, the result of testing indicates that the reasoning method can provide certain help in cyber-attack attribution.

Keywords: Reasoning, Bayesian networks, cyber-attack attribution, kill chain, threat intelligence.

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Authors: B. J. C. Perera, D. A. Sachindra, W. Godoy., A.F. Barton, F. Huang

Abstract:

Many water supply systems in Australia are currently undergoing significant reconfiguration due to reductions in long term average rainfall and resulting low inflows to water supply reservoirs since the second half of the 20th century. When water supply systems undergo change, it is necessary to develop new operating rules, which should consider climate, because the climate change is likely to further reduce inflows. In addition, water resource systems are increasingly intended to be operated to meet complex and multiple objectives representing social, economic, environmental and sustainability criteria. This is further complicated by conflicting preferences on these objectives from diverse stakeholders. This paper describes a methodology to develop optimum operating rules for complex multi-reservoir systems undergoing significant change, considering all of the above issues. The methodology is demonstrated using the Grampians water supply system in northwest Victoria, Australia. Initial work conducted on the project is also presented in this paper.

Keywords: Climate change, Multi-objective planning, Pareto optimal; Stakeholder preference, Statistical downscaling, Water supply systems.

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Authors: F. Abujalala, A. Elmangoush, M. Ashibani

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The adoption of Blockchain technology introduces the possibility to decentralize cold chain systems. This adaptation enhances them to be more efficient, accessible, verifiable, and data security. Additionally, the Internet of Things (IoT) concept is considered as an added-value to various application domains. Cargo tracking and cold chain are a few to name. However, the security of the IoT transactions and integrated devices remains one of the key challenges to the IoT application’s success. Consequently, Blockchain technology and its consensus protocols have been used to solve many information security problems. In this paper, we discuss the advantages of integrating Blockchain technology into IoT platform to improve security and provide an overview of existing literature on integrating Blockchain and IoT platforms. Then, we present the immunization cold chain solution as a use-case that could be applied to any critical goods based on integrating Hyperledger fabric platform and IoT platform.

Keywords: Blockchain, Hyperledger fabric, internet of things, security, traceability.

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Authors: Lien Fa Lin, Yung Ming Li, Hsin Chen Hsieh

Abstract:

The rise of smartphones brings new concept So-Lo-Mo (social-local-mobile) in mobile commerce area in recent years. However, current So-Lo-Mo services only focus on individual users but not a group of users, and the development of group commerce is not enough to satisfy the demand of real-time group buying and less to think about the social relationship between customers. In this research, we integrate mobile intelligence with group commerce and consider customers' preference, real-time context, and social influence as components in the mechanism. With the support of this mechanism, customers are able to gather near customers with the same potential purchase willingness through mobile devices when he/she wants to purchase products or services to have a real-time group-buying. By matching the demand and supply of mobile group-buying market, this research improves the business value of mobile commerce and group commerce further.

Keywords: Group formation, group commerce, mobile commerce, So-Lo-Mo, social influence.

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Authors: Kejun Zhuang, Hailong Zhu

Abstract:

In this paper, the three species food chain model on time scales is established. The Monod–Haldane functional response and time delay are considered. With the help of coincidence degree theory, existence of periodic solutions is investigated, which unifies the continuous and discrete analogies.

Keywords: Food chain system, periodic solution, time scales, coincidence degree.

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Authors: M. Boudjerda, B. Touaibia, M. K. Mihoubi

Abstract:

In Algeria agricultural irrigation is the primary water consuming sector followed by the domestic and industrial sectors. Economic development in the last decade has weighed heavily on water resources which are relatively limited and gradually decreasing to the detriment of agriculture. The research presented in this paper focuses on the optimization of irrigation water demand. Dynamic Programming-Neural Network (DPNN) method is applied to investigate reservoir optimization. The optimal operation rule is formulated to minimize the gap between water release and water irrigation demand. As a case study, Foum El-Gherza dam’s reservoir system in south of Algeria has been selected to examine our proposed optimization model. The application of DPNN method allowed increasing the satisfaction rate (SR) from 12.32% to 55%. In addition, the operation rule generated showed more reliable and resilience operation for the examined case study.

Keywords: ater management, agricultural demand, dam and reservoir operation, Foum el-Gherza dam, dynamic programming, artificial neural network.

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Authors: P. Puustinen, A. Kanto

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This paper proposes a new procedure for analyzing means-end chain data in marketing research. Most commonly the collected data is summarized in the Hierarchical Value Map (HVM) illustrating the main attribute-consequence-value linkages. This paper argues that traditionally constructed HVM may give an erroneous impression of the results of a means-end study. To justify the arguments, an alternative procedure to (1) determine the dominant attribute-consequence-value linkages and (2) construct HVM in a precise manner is presented. The current approach makes a contribution to means-end analysis, allowing marketers to address a set of marketing problems, such as advertising strategy.

Keywords: Means-end chain analysis, Laddering, Hierarchical Value Map.

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Authors: Manisha Dubey, Gaurav Gupta, Anoop Arya

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The demand for power supply increases day by day in developing countries like India henceforth demand of reactive power support in the form of ancillary services provider also has been increased. The multi-line and multi-type Flexible alternating current transmission system (FACTS) controllers are playing a vital role to regulate power flow through the transmission line. Unified power flow controller and interline power flow controller can be utilized to control reactive power flow through the transmission line. In a restructured power system, the demand of such controller is being popular due to their inherent capability. The transmission pricing by using reactive power cost allocation through modified matrix methodology has been proposed. The FACTS technologies have quite costly assembly, so it is very useful to apportion the expenses throughout the restructured electricity industry. Therefore, in this work, after embedding the FACTS devices into load flow, the impact on the costs allocated to users in fraction to the transmission framework utilization has been analyzed. From the obtained results, it is clear that the total cost recovery is enhanced towards the Reactive Power flow through the different transmission line for 5 bus test system. The fair pricing policy towards reactive power can be achieved by the proposed method incorporating FACTS controller towards cost recovery of the transmission network.

Keywords: Inter line power flow controller, Transmission Pricing, Unified power flow controller, cost allocation.

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Authors: Shi-Yu Lu, Chung-Han Yeh, Li-Ping Chen, Yu-Cheng Chang

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This paper uses both quantitative and qualitative approaches to survey the current status of AI-related applications and the structure of key AI jobs in Taiwan's high-tech manufacturing industry, as well as the demand for professional AI talents, skills, and training. The result shows that AI applications and talent demand vary from different industries in many aspects, including technologies used, talent structure, and training methods. This paper serves as a reference for the government to establish appropriate talent training programs, and to reduce the demand gap for professional AI talents in Taiwan manufacturers.

Keywords: Artificial intelligence, manufacturing, talent, training.

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Authors: Madhukar Nagare, Pankaj Dutta

Abstract:

Inventory decisional environment of short life-cycle products is full of uncertainties arising from randomness and fuzziness of input parameters like customer demand requiring modeling under hybrid uncertainty. Prior inventory models incorporating fuzzy demand have unfortunately ignored stochastic variation of demand. This paper determines an unambiguous optimal order quantity from a set of n fuzzy observations in a newsvendor inventory setting in presence of fuzzy random variable demand capturing both fuzzy perception and randomness of customer demand. The stress of this paper is in providing solution procedure that attains optimality in two steps with demand information availability in linguistic phrases leading to fuzziness along with stochastic variation. The first step of solution procedure identifies and prefers one best fuzzy opinion out of all expert opinions and the second step determines optimal order quantity from the selected event that maximizes profit. The model and solution procedure is illustrated with a numerical example.

Keywords: Fuzzy expected value, Fuzzy random demand, Hybrid uncertainty, Optimal order quantity, Single-period inventory

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Authors: Amir Azizi, Amir Yazid B. Ali, Loh Wei Ping

Abstract:

Throughput is an important measure of performance of production system. Analyzing and modeling of production throughput is complex in today-s dynamic production systems due to uncertainties of production system. The main reasons are that uncertainties are materialized when the production line faces changes in setup time, machinery break down, lead time of manufacturing, and scraps. Besides, demand changes are fluctuating from time to time for each product type. These uncertainties affect the production performance. This paper proposes Bayesian inference for throughput modeling under five production uncertainties. Bayesian model utilized prior distributions related to previous information about the uncertainties where likelihood distributions are associated to the observed data. Gibbs sampling algorithm as the robust procedure of Monte Carlo Markov chain was employed for sampling unknown parameters and estimating the posterior mean of uncertainties. The Bayesian model was validated with respect to convergence and efficiency of its outputs. The results presented that the proposed Bayesian models were capable to predict the production throughput with accuracy of 98.3%.

Keywords: Bayesian inference, Uncertainty modeling, Monte Carlo Markov chain, Gibbs sampling, Production throughput

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Authors: Jamal Laaouine, Mohammed Elhassani Charkani

Abstract:

Let p be a prime and let b be an integer. MDS b-symbol codes are a direct generalization of MDS codes. The γ-constacyclic codes of length pˢ over the finite commutative chain ring Fₚm [u]/ < u² > had been classified into four distinct types, where is a nonzero element of the field Fₚm. Let C₃ be a code of Type 3. In this paper, we obtain the b-symbol distance db(C₃) of the code C₃. Using this result, necessary and sufficient conditions under which C₃ is an MDS b-symbol code are given.

Keywords: constacyclic code, repeated-root code, maximum distance separable, MDS codes, b-symbol distance, finite chain rings

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Authors: Dilek Özdemir, Gül Tekin Temur

Abstract:

In Supply Chain Management (SCM), strengthening partnerships with suppliers is a significant factor for enhancing competitiveness. Hence, firms increasingly emphasize supplier evaluation processes. Supplier evaluation systems are basically developed in terms of criteria such as quality, cost, delivery, and flexibility. Because there are many variables to be analyzed, this process becomes hard to execute and needs expertise. On this account, this study aims to develop an expert system on supplier evaluation process by designing Artificial Neural Network (ANN) that is supported with Data Envelopment Analysis (DEA). The methods are applied on the data of 24 suppliers, which have longterm relationships with a medium sized company from German Iron and Steel Industry. The data of suppliers consists of variables such as material quality (MQ), discount of amount (DOA), discount of cash (DOC), payment term (PT), delivery time (DT) and annual revenue (AR). Meanwhile, the efficiency that is generated by using DEA is added to the supplier evaluation system in order to use them as system outputs.

Keywords: Artificial Neural Network (ANN), DataEnvelopment Analysis (DEA), Supplier Evaluation System.

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Authors: Yamini Raju, Parminder S. Kang, Adam Moroz, Ross Clement, Ashley Hopwell, Alistair Duffy

Abstract:

Accurate forecasting of fresh produce demand is one the challenges faced by Small Medium Enterprise (SME) wholesalers. This paper is an attempt to understand the cause for the high level of variability such as weather, holidays etc., in demand of SME wholesalers. Therefore, understanding the significance of unidentified factors may improve the forecasting accuracy. This paper presents the current literature on the factors used to predict demand and the existing forecasting techniques of short shelf life products. It then investigates a variety of internal and external possible factors, some of which is not used by other researchers in the demand prediction process. The results presented in this paper are further analysed using a number of techniques to minimize noise in the data. For the analysis past sales data (January 2009 to May 2014) from a UK based SME wholesaler is used and the results presented are limited to product ‘Milk’ focused on café’s in derby. The correlation analysis is done to check the dependencies of variability factor on the actual demand. Further PCA analysis is done to understand the significance of factors identified using correlation. The PCA results suggest that the cloud cover, weather summary and temperature are the most significant factors that can be used in forecasting the demand. The correlation of the above three factors increased relative to monthly and becomes more stable compared to the weekly and daily demand.

Keywords: Demand Forecasting, Deteriorating Products, Food Wholesalers, Principal Component Analysis and Variability Factors.

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Authors: Dewi Nasien, Habibollah Haron, Siti SophiayatiYuhaniz

Abstract:

This paper presents a comparison of metaheuristic algorithms, Genetic Algorithm (GA) and Ant Colony Optimization (ACO), in producing freeman chain code (FCC). The main problem in representing characters using FCC is the length of the FCC depends on the starting points. Isolated characters, especially the upper-case characters, usually have branches that make the traversing process difficult. The study in FCC construction using one continuous route has not been widely explored. This is our motivation to use the population-based metaheuristics. The experimental result shows that the route length using GA is better than ACO, however, ACO is better in computation time than GA.

Keywords: Handwriting Recognition, Feature Extraction, Freeman Chain Code, Genetic Algorithm and Ant ColonyOptimization.

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Authors: Irena Durdová

Abstract:

Most people know through experience and intuition what the word „sport“ means. Sport includes a combination of these configurations when it involves team competitions, tournaments, or matches in dual sports or individual sports. Sport management - it is an area of professional endeavor in which a variety of sport-related managerial careers exist and it is also an area of academic professional preparation. Exists three unique aspects of sport management: sport marketing, sport enterprise financial structures and sport industry career paths. The aim of the paper was to highlight the growing importance of sport in contemporary society, especially to emphasize its socio-economic benefits and refer to the development of sport management and marketing. The article has shown that sport contributes 2-3% to gross domestic product in the Czech Republic and that the demand for experts, specialists educated for the sports manager profession is growing.

Keywords: management, sport, sport management, marketing

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