Search results for: demand forecast updating

Authors: Nathenal Thomas Lambamo

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Based on the fact that more than 85% of the labor force and 90% of the export earnings are taken by agriculture in Ethiopia and it can be said that it is the backbone of the overall socio-economic activities in the country. Among the cereal crops that the agriculture sector provides for the country, wheat is the third-ranking one preceding teff and maize. In the present day, wheat is in higher demand related to the expansion of industries that use them as the main ingredient for their products. The local supply of wheat for these companies covers only 35 to 40% and the rest 60 to 65% percent is imported on behalf of potential customers that exhaust the country’s foreign currency reserves. The above facts show that the need for this crop in the country is too high and in reverse, the productivity of the crop is very less because of these reasons. Wheat disease is the most devastating disease that contributes a lot to this unbalance in the demand and supply status of the crop. It reduces both the yield and quality of the crop by 27% on average and up to 37% when it is severe. This study aims to detect the most frequent and degrading wheat diseases, Septoria and Leaf rust, using the most efficiently used subset of machine learning technology, deep learning. As a state of the art, a deep learning class classification technique called Convolutional Neural Network (CNN) has been used to detect diseases and has an accuracy of 99.01% is achieved.

Keywords: septoria, leaf rust, deep learning, CNN

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Authors: Nagini Sabbineni, Rajini T. V. Kanth, B. V. Kiranmayee

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India’s economy primarily depends on agriculture yield growth and their allied agro industry products. The agriculture yield prediction is the toughest task for agricultural departments across the globe. The agriculture yield depends on various factors. Particularly countries like India, majority of agriculture growth depends on rain water, which is highly unpredictable. Agriculture growth depends on different parameters, namely Water, Nitrogen, Weather, Soil characteristics, Crop rotation, Soil moisture, Surface temperature and Rain water etc. In our paper, lot of Explorative Data Analysis is done and various predictive models were designed. Further various regression models like Linear, Multiple Linear, Non-linear models are tested for the effective prediction or the forecast of the agriculture yield for various crops in Andhra Pradesh and Telangana states.

Keywords: agriculture yield growth, agriculture yield prediction, explorative data analysis, predictive models, regression models

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Authors: Aysun Pınarbaşı, Béla Vizvári

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The countries are the units that procure the vaccines during the COVID-19 pandemic. The delivered quantities are huge. The countries must bear the inventory holding cost according to the variation of stock quantities. This cost depends on the speed of the vaccination in the country. This speed is time-dependent. The vaccinated portion of the population can be approximated by the cumulative distribution function of the Cauchy distribution. A model is provided for determining the minimal-cost inventory policy, and its optimality conditions are provided. The model is solved for 20 countries for different numbers of procurements. The results reveal the individual behavior of each country. We provide an inventory policy for the pandemic period for the countries. This paper presents a deterministic model for vaccines with a demand rate variable over time for the countries. It is aimed to provide an analytical model to deal with the minimization of holding cost and develop inventory policies regarding this aim to be used for a variety of perishable products such as vaccines. The saturation process is introduced, and an approximation of the vaccination curve of the countries has been discussed. According to this aspect, a deterministic model for inventory policy has been developed.

Keywords: covid-19, vaccination, inventory policy, bounded total demand, inventory holding cost, cauchy distribution, sigmoid function

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Authors: Won Kyung Ham, Kang Hoon Cho, Sang C. Park

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Presented in this paper is a framework of a software ‘WEMax’. The WEMax is invented for analysis and simulation for manned assembly lines to sustain and improve performance of manufacturing systems. In a manufacturing system, performance, such as productivity, is a key of competitiveness for output products. However, the manned assembly lines are difficult to forecast performance, because human labors are not expectable factors by computer simulation models or mathematical models. Existing approaches to performance forecasting of the manned assembly lines are limited to matters of the human itself, such as ergonomic and workload design, and non-human-factor-relevant simulation. Consequently, an approach for the forecasting and improvement of manned assembly line performance is needed to research. As a solution of the current problem, this study proposes a framework that is for generation and simulation of virtual manned assembly lines, and the framework has been implemented as a software.

Keywords: performance forecasting, simulation, virtual manned assembly line, WEMax

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Authors: William Anderson, Kyle Kobold, Oleg Yakimenko

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Green microgrids using mostly renewable energy (RE) for generation, are complex systems with inherent nonlinear dynamics. Among a variety of different optimization tools there are only a few ones that adequately consider this complexity. This paper evaluates applicability of two somewhat similar optimization tools tailored for standalone RE microgrids and also assesses a machine learning tool for performance prediction that can enhance the reliability of any chosen optimization tool. It shows that one of these microgrid optimization tools has certain advantages over another and presents a detailed routine of preparing input data to simulate RE microgrid behavior. The paper also shows how neural-network-based predictive modeling can be used to validate and forecast solar power generation based on weather time series data, which improves the overall quality of standalone RE microgrid analysis.

Keywords: microgrid, renewable energy, complex systems, optimization, predictive modeling, neural networks

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Authors: Oluseyi Adunola Bamisaiye

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The frequency of occurrence of earth tremor in Nigeria has increased tremendously in recent years. Slow earthquakes/ tremor have preceded some large earthquakes in some other regions of the world and the Nigerian case may not be an exception. Timely and careful investigation of these tremors may reveal their relation to large earthquakes and provides important clues to constrain the slip rates on tectonic faults. Thus making it imperative to keep under watch and also study carefully the tectonically active terrains within the country, in order to adequately forecast, prescribe mitigation measures and in order to avoid a major disaster. This report provides new evidence of a slow slip transient in a strongly locked seismogenic zone of the Okemesi fold belt. The aim of this research is to investigate the different methods of earth tremor monitoring using fault slip analysis and mapping of Okemesi hills, which has been the most recent epicenter to most of the recent tremors.

Keywords: earth tremor, fault slip, intraplate activities, plate tectonics

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Authors: Sarbjit Singh, Amit Kumar Lal

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In India there is no governing body to control advertisement apart from ASCI due to which most of the companies are targeting children in their advertisements that have a negative impact on their behaviour. The main purpose of this research paper is to find out the impact of the television advertisement on the behaviour of the children as observed and reported by parents. The exploratory research design is adopted by using in-depth interviews with 20 parents in various cities of Punjab on the basis semi-structured interviews a self-administered structured Questionnaire was developed for data collection. Exploratory factor analysis using varimax rotation is used to analyse the data from 100 parents from the conjoint cities of Punjab. (Jalandhar, Amritsar and Ludhiana) The finding suggests that children demand those products which are more advertised. Parents believe that television advertisements are affecting the study of their children. Moreover, the children are becoming more violent, stubborn and rebellious. They try to start copying from the advertisements and indulge in bad habits. Children demand, nag and pester their parents to purchase the advertised product. This research paper would help advertisers to understand children behaviour towards advertisements and more over what should be done to control the negative impact of advertisement on children. Advertisers can also understand the parental perception towards advertisement.

Keywords: advertisement, consumer behaviour, children perception, teen marketing

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Authors: Md. Nazmul Haque, Mahinur Rahman

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The objective of the research is to determine the quantity of household waste generated and forecast the future condition of Ward No 24 (Nirala). For performing that, three core issues are focused: (i) the capacity and service area of the dumping stations; (ii) the present waste generation amount per capita per day; (iii) the responsibility of the local authority in the household waste collection. This research relied on field survey-based data collection from all stakeholders and GIS-based secondary analysis of waste collection points and their coverage. However, these studies are mostly based on the inherent forecasting approaches, cannot predict the amount of waste correctly. The findings of this study suggest that Nirala is a formal residential area introducing a better approach to the waste collection - self-controlled and collection system. Here, a forecasting model proposed for waste generation as Y = -2250387 + 1146.1 * X, where X = year.

Keywords: eco-friendly environment, household waste, linear regression, waste management

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Authors: Habib Alshuwaikhat, Nahid Hossain

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Residential sector consumes more than half of the produced electricity in Saudi Arabia, and fossil fuel is the main source of energy to meet growing household electricity demand in the Kingdom. Several studies forecasted and expressed concern that unless the domestic energy demand growth is controlled, it will reduce Saudi Arabia’s crude oil export capacity within a decade and the Kingdom is likely to be incapable of exporting crude oil within next three decades. Though the Saudi government has initiated to address the domestic energy demand growth issue, the demand side energy management policies and programs are focused on industrial and commercial sectors. It is apparent that there is an urgent need to develop a comprehensive energy efficiency strategy for addressing efficient energy use in residential sector in the Kingdom. Then again as Saudi Arabia is at its primary stage in addressing energy efficiency issues in its residential sector, there is a scope for the Kingdom to learn from global energy efficiency practices and design its own energy efficiency policies and programs. However, in order to do that sustainable, it is essential to address local contexts of energy efficiency. It is also necessary to find out the policies and programs that will fit to the local contexts. Thus the objective of this study was set to identify globally best practice energy efficiency policies and programs in residential sector that have replication potential in Saudi Arabia. In this regard two sets of multi-criteria decision analysis matrices were developed to evaluate the energy efficiency policies and programs. The first matrix was used to evaluate the global energy efficiency policies and programs, and the second matrix was used to evaluate the replication potential of global best practice energy efficiency policies and programs for Saudi Arabia. Wuppertal Institute’s guidelines for energy efficiency policy evaluation were used to develop the matrices, and the different attributes of the matrices were set through available literature review. The study reveals that the best practice energy efficiency policies and programs with good replication potential for Saudi Arabia are those which have multiple components to address energy efficiency and are diversified in their characteristics. The study also indicates the more diversified components are included in a policy and program, the more replication potential it has for the Kingdom. This finding is consistent with other studies, where it is observed that in order to be successful in energy efficiency practices, it is required to introduce multiple policy components in a cluster rather than concentrate on a single policy measure. The developed multi-criteria decision analysis matrices for energy efficiency policy and program evaluation could be utilized to assess the replication potential of other globally best practice energy efficiency policies and programs for the residential sector of the Kingdom. In addition it has potential to guide Saudi policy makers to adopt and formulate its own energy efficiency policies and programs for Saudi Arabia.

Keywords: Saudi Arabia, residential sector, energy efficiency, policy evaluation

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Authors: Md Mizanur Rahman, M. Aslam Alam, Muhammad Abu Yusuf

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The abundance of Jellyfish across the coasts of the Bay of Bengal is increasing sharply due to marine pollution, increased sea acidification and climate change. Jellyfish draws our attention to address the local and global stressors. This also indicates that something wrong is happening in this bay behind the scenes. This study aimed to investigate how the policy framework governing the sea can be reformed. To do so, this study evaluated the existing policy, regulatory and institutional framework. Empirical data were collected from the middle coastal zone of Bangladesh. The secondary literature on policy, legal documents, and institutional arrangements were reviewed. The causes of poor coordination among different public sectors and non-compliance of laws were identified. The key findings show that despite the existing of Department of Environment, poor coordination with other departments, and lack of logistics and technical staffs have resulted in severe marine pollution and degradation of coastal and marine living resources. The existing policies had no monitoring and evaluation mechanisms. Non-compliance of the existing laws has been fueling the problems. This study provides an integrated policy and a guideline for updating the legal and institutional mechanism to manage coastal and marine living resources sustainably in Bangladesh to achieve Sustainable Development Goal 14.

Keywords: legal, institutional, framework, jellyfish

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Authors: Saeed Sayyad Hagh Shomar

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Traffic congestion pricing – as a strategy in travel demand management in urban areas to reduce traffic congestion, air pollution and noise pollution – has drawn many attentions towards itself. Unlike the satisfying findings in this method, there are still problems in determining the best functional congestion pricing scheme with regard to the situation. The so-called problems in this process will result in further complications and even the scheme failure. That is why having proper knowledge of the significance of congestion pricing schemes and the effective factors in choosing them can lead to the success of this strategy. In this study, first, a variety of traffic congestion pricing schemes and their components are introduced; then, their functional usage is discussed. Next, by analyzing and comparing the barriers, limitations and advantages, the selection criteria of pricing schemes are described. The results, accordingly, show that the selection of the best scheme depends on various parameters. Finally, based on examining the effective parameters, it is concluded that the implementation of area-based schemes (cordon and zonal) has been more successful in non-diversion of traffic. That is considering the topology of the cities and the fact that traffic congestion is often created in the city centers, area-based schemes would be notably functional and appropriate.

Keywords: congestion pricing, demand management, flat toll, variable toll

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Authors: Mrinal Saurabh Bhaskar, Rahul E Ravindranathan, Priyangana Borah

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Energy plays a key role and as a driving force for economic and social growth for any country. To manage the energy sources and its efficient utilization in different economic sectors, energy policy of a country is critical. The energy performance of a country is measured in Energy Intensity and India’s Energy Intensity due to several policies interventions has reduced from 0.53 toe/1000USD (2010) in the year 2000 to 0.38 toe/1000USD (2010) in the year 2014, which is about 28 per cent reduction. The Government of India has taken several initiates to manage their increasing energy demand and meet the climate change goals defined by them. The major policy milestones in India related to energy are (i) Enactment of Energy Conservation (EC) Act 2001 (ii) Establishment of Bureau of Energy Efficiency 2001 (iii) National Action Plan on Climate Change (iv) Launch of Demand Side Management schemes (v) Amendment of EC Act 2010 (vi) Launch of Perform Achieve and Trade scheme 2012. Through a critical review, this paper highlights the key energy policy interventions by India, its benefits and impact, challenges faced and efforts of the Government to overcome such challenges. Such take away would be helpful for other countries who are proposing to prepare or amend their energy policy for their different economic sectors.

Keywords: energy, efficiency, climate, policy

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Authors: Alemi Asefa Wordofa

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The textile industry is among the biggest industries in the world, producing a wide variety of products. Industry plays an important role in the world economy as well as in our daily lives. In Ethiopia, this has also been aided by the country’s impressive economic growth over the years. However, Textile industries consume large amounts of water and produce colored wastewater, which results in polluting the environment. In this study, the efficiency of the electrocoagulation treatment process using Iron electrodes to treat textile wastewater containing Reactive black everzol was studied. The effects of parameters such as voltage, time of reaction, and inter-electrode distance on Chemical oxygen demand (COD) and dye removal efficiency were investigated. In addition, electrical energy consumption at optimum conditions has been investigated. The results showed that COD and dye removals were 90.76% and 97.66%, respectively, at the optimum point of input voltage of 14v, inter-electrode distance of 7.24mm, and 47.86min electrolysis time. Energy consumption at the optimum point is also 2.9*10-3. It can be concluded that the electrocoagulation process by the iron electrode is a very efficient and clean process for COD and reactive black removal from wastewater.

Keywords: iron electrode, electrocoagulation, chemical oxygen demand, wastewater

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Authors: Kiatkulchai Jitt-Aer, Graham Wall, Dylan Jones

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As a result of the Indian Ocean tsunami in 2004, logistics applied to disaster relief operations has received great attention in the humanitarian sector. As learned from such disaster, preparing and responding to the aspect of delivering essential items from distribution centres to affected locations are of the importance for relief operations as the nature of disasters is uncertain especially in suffering figures, which are normally proportional to quantity of supplies. Thus, this study proposes a spatial decision support system (SDSS) for humanitarian logistics by integrating Geographical Information Systems (GIS) and the capacitated vehicle routing problem (CVRP). The GIS is utilised for acquiring demands simulated from the tsunami flooding model of the affected area in the first stage, and visualising the simulation solutions in the last stage. While CVRP in this study encompasses designing the relief routes of a set of homogeneous vehicles from a relief centre to a set of geographically distributed evacuation points in which their demands are estimated by using both simulation and randomisation techniques. The CVRP is modeled as a multi-objective optimization problem where both total travelling distance and total transport resources used are minimized, while demand-cost efficiency of each route is maximized in order to determine route priority. As the model is a NP-hard combinatorial optimization problem, the Clarke and Wright Saving heuristics is proposed to solve the problem for the near-optimal solutions. The real-case instances in the coastal area of Phuket, Thailand are studied to perform the SDSS that allows a decision maker to visually analyse the simulation scenarios through different decision factors.

Keywords: demand simulation, humanitarian logistics, geographical information systems, relief operations, capacitated vehicle routing problem

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Authors: Aicha Assal, El Mostapha Lotfi

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According to data from the Directorate General of Meteorology (DGM), the average amount of precipitation recorded nationwide between September 1, 2021, and January 31, 2022, is 38.8 millimeters. This is well below the climatological normal of 106.8 millimeters for the same period between 1981 and 2010. This situation is becoming increasingly worrying, particularly for farmers who are finding it difficult to irrigate their land and feed their livestock. Drought is greatly influenced by the effects of climate change, mainly caused by pollution and greenhouse gases (GHGs). The aim of this work is to contribute to the purification of wastewater (considered as polluting) in order to reuse it for irrigation in agricultural areas or for livestock watering. This will be achieved once physico-chemical treatment tests on these waters have been carried out and validated. The main parameters analyzed in this study, after carrying out discoloration tests on domestic wastewater, include COD (chemical oxygen demand), BOD5 (biochemical oxygen demand), pH, conductivity, dissolved oxygen, suspended solids (SS), phosphate, nitrate, nitrite and ammonium ions, faecal and total coliforms, as well as monitoring heavy metal concentrations. This work is also aimed at reclaiming the sludge produced by the decantation process, which will enable the waste to be transformed and reused as compost in agriculture and gardening.

Keywords: wastewater, irrigation, COD, COB, SS

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Authors: Ramin Mirzada

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This research investigates the valuation of public transport importance in decreasing congestion and in introduction of bus rapid transit in Kabul city. The main concern and main problem of the Kabul city public transport is traffic congestion. When buses and trams are stuck in traffic jams, it is clear that they fall behind from the schedule and this cause lots of problem for Kabul residence. In this research, the main attention has been given to improve current public transport in Kabul city which Public transport has large share almost 50% share among all mode. The main purpose of this research is to improve public transport system, to examine the demand and the supply of public transport in Kabul city, and to improve public transport system by introducing Bus rapid transit (BRT) system in Kabul city. The data which is used in this research is gathered by Transport Ministry, Kabul Municipality and Japan Cooperation Agency in Afghanistan (JICA). Urban transportation modeling system (UTMS) which is also known as traditional four-step modeling is used as the methodology of this research. The outcome of this research shows that by improving public transport which is local bus system mostly congestion problem of Kabul city become solve, and for those lanes which has the high demand and has more congestion, it is needed to introduce bus rapid transit system.

Keywords: transportation, planning, public transport, bus rapid transit, Kabul, Afghanistan

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Authors: Chih-Hsiang Chang, Pei-Shan Kao

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This paper discusses the reaction of investors in the Taiwan stock market to the most probable unknown earnings-related information and the most probable known earnings-related information. As compared with the previous literature regarding the effect of an official announcement of earnings forecast revision, this paper further analyzes investors’ cognitive bias toward the unknown and known earnings-related information, and the role of media during the investors' reactions to the foresaid information shocks. The empirical results show that both the unknown and known earnings-related information provides useful information content for a stock market. In addition, cognitive bias and disposition effect are the behavioral pitfalls that commonly occur in the process of the investors' reactions to the earnings-related information. Finally, media coverage has a remarkable influence upon the investors' trading decisions.

Keywords: cognitive bias, role of media, disposition effect, earnings-related information, behavioral pitfall

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Authors: S. Hamid Mirmohammadi, Shahrazad Tamjidzad

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This paper is concerned with the single-item continuous review inventory system in which demand is stochastic and discrete. The budget consumed for purchasing the ordered items is not restricted but it incurs extra cost when exceeding specific value. The unit purchasing price depends on the quantity ordered under the all-units discounts cost structure. In many actual systems, the budget as a resource which is occupied by the purchased items is limited and the system is able to confront the resource shortage by charging more costs. Thus, considering the resource shortage costs as a part of system costs, especially when the amount of resource occupied by the purchased item is influenced by quantity discounts, is well motivated by practical concerns. In this paper, an optimization problem is formulated for finding the optimal (R, Q) policy, when the system is influenced by the budget limitation and a discount pricing simultaneously. Properties of the cost function are investigated and then an algorithm based on a one-dimensional search procedure is proposed for finding an optimal (R, Q) policy which minimizes the expected system costs .

Keywords: (R, Q) policy, stochastic demand, backorders, limited resource, quantity discounts

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Authors: Gabriela Tutuanu

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The economic, social and environmental undesirable impact of the existing development pattern pushes to the adoption and use of a new development paradigm that of sustainable development. This paper intends to substantiate how the marketing can help the sustainable development. It begins with the subjects of sustainable development and sustainable marketing as they are discussed in literature. The sustainable development is a three dimensional concept which embeds the economic dimension, the social dimension and the environmental dimension that ask to have in view the simultaneous pursuit of economic prosperity, social equity and environmental quality. A major challenge to achieve these goals at business level and to integrate all three dimensions of sustainability is the sustainable marketing. The sustainable marketing is a relationship marketing that aims at building lasting relationships with the social and natural environment on a long-term thinking and futurity and this philosophy allows helping all three dimensions of sustainability. As marketing solutions that could contribute to the sustainable development. We advance the stimulation of sustainable demand, the constant innovation and improvement of sustainable products, the design and use of customized communication, a multichannel distribution network and the sale of sustainable products and services at fair prices. Their implementation will increase the economic, social and environmental sustainability at a large extent in the future if they are supported by political, governmental and legal authorities.

Keywords: sustainable development, sustainable marketing, sustainable demand, sustainable product, credible communication, multi-channel distribution network, fair price

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Authors: Katharina Eberhardt, Florian Klaus Kaiser, Frank Schultmann

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Last-mile distribution is one of the most critical parts of a disaster relief operation. Various uncertainties, such as infrastructure conditions, resource availability, and fluctuating beneficiary demand, render last-mile distribution challenging in disaster relief operations. The need to balance critical performance criteria like response time, meeting demand and cost-effectiveness further complicates the task. The occurrence of disasters cannot be controlled, and the magnitude is often challenging to assess. In summary, these uncertainties create a need for additional flexibility, agility, and preparedness in logistics operations. As a result, strategic planning and efficient network design are critical for an effective and efficient response. Furthermore, the increasing frequency of disasters and the rising cost of logistical operations amplify the need to provide robust and resilient solutions in this area. Therefore, we formulate a scenario-based bi-objective optimization model that integrates pre-positioning, allocation, and distribution of relief supplies extending the general form of a covering location problem. The proposed model aims to minimize underlying logistics costs while maximizing demand coverage. Using a set of disruption scenarios, the model allows decision-makers to identify optimal network solutions to address the risk of disruptions. We provide an empirical case study of the public authorities’ emergency food storage strategy in Germany to illustrate the potential applicability of the model and provide implications for decision-makers in a real-world setting. Also, we conduct a sensitivity analysis focusing on the impact of varying stockpile capacities, single-site outages, and limited transportation capacities on the objective value. The results show that the stockpiling strategy needs to be consistent with the optimal number of depots and inventory based on minimizing costs and maximizing demand satisfaction. The strategy has the potential for optimization, as network coverage is insufficient and relies on very high transportation and personnel capacity levels. As such, the model provides decision support for public authorities to determine an efficient stockpiling strategy and distribution network and provides recommendations for increased resilience. However, certain factors have yet to be considered in this study and should be addressed in future works, such as additional network constraints and heuristic algorithms.

Keywords: humanitarian logistics, bi-objective optimization, pre-positioning, last mile distribution, decision support, disaster relief networks

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Authors: Panudet Saengseedam, Nanthachai Kantanantha

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This paper proposes a linear mixed model (LMM) with spatial effects to forecast rice and cassava yields in Thailand at the same time. A multivariate conditional autoregressive (MCAR) model is assumed to present the spatial effects. A Bayesian method is used for parameter estimation via Gibbs sampling Markov Chain Monte Carlo (MCMC). The model is applied to the rice and cassava yields monthly data which have been extracted from the Office of Agricultural Economics, Ministry of Agriculture and Cooperatives of Thailand. The results show that the proposed model has better performance in most provinces in both fitting part and validation part compared to the simple exponential smoothing and conditional auto regressive models (CAR) from our previous study.

Keywords: Bayesian method, linear mixed model, multivariate conditional autoregressive model, spatial time series

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Authors: Junaid Ahmed, Nandita Shenoy

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Maintaining lifelong knowledge and skills is essential for safe clinical practice. Continuing Professional Development (CPD) is an established method that can facilitate lifelong learning. It focuses on maintaining or developing knowledge, skills and relationships to ensure competent practice.To date, relatively little has been done to comprehensively and systematically synthesize evidence to identify subjects of interest among practising dentist. Hence the aim of our study was to identify areas in clinical practice that would be favourable for continuing professional dental education amongst practicing dentists. Participants of this study consisted of the practicing dental surgeons of Mangalore, a city in Dakshina Kannada, Karnataka. 95% of our practitioners felt that regular updating as a one day program once in 3-6 months is required, to keep them abreast in clinical practice. 60% of subjects feel that CPD programs enrich their theoretical knowledge and helps in patient care. 27% of them felt that CPD programs should be related to general dentistry. Most of them felt that CPD programs should not be charged nominally between one to two thousand rupees. The acronym ‘CPD’ should be seen in a broader view in which professionals continuously enhance not only their knowledge and skills, but also their thinking,understanding and maturity; they grow not only as professionals, but also as persons; their development is not restricted to their work roles, but may also extend to new roles and responsibilities.

Keywords: continuing professional development, competent practice, dental education, practising dentist

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Authors: Hamed Zolfaghari, Mojtaba Kord

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Project planners and controllers are frequently faced with the challenge of inadequate software for the preparation of automatic project progress reports based on actual project information updates. They usually make dashboards in Microsoft Excel, which is local and not applicable online. Another shortcoming is that it is not linked to planning software such as Microsoft Project, which lacks the database required for data storage. This study aimed to propose a model for the preparation of reports on automatic online project progress based on actual project information updates by the integration of Primavera P6, SQL database, and Power BI for a construction project. The designed model could be applicable to project planners and controller agents by enabling them to prepare project reports automatically and immediately after updating the project schedule using actual information. To develop the model, the data were entered into P6, and the information was stored on the SQL database. The proposed model could prepare a wide range of reports, such as earned value management, HR reports, and financial, physical, and risk reports automatically on the Power BI application. Furthermore, the reports could be published and shared online.

Keywords: primavera P6, SQL, Power BI, EVM, integration management

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Authors: JingWei Yu, Hong Yang Yu

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At present, the increasingly serious air pollution in various cities of China has made people pay more attention to the air quality index(hereinafter referred to as AQI) of their living areas. To face this situation, it is of great significance to predict air pollution in heavily polluted areas. In this paper, based on the time series model of LSTM, a spatiotemporal prediction model of PM2.5 concentration in Mianyang, Sichuan Province, is established. The model fully considers the temporal variability and spatial distribution characteristics of PM2.5 concentration. The spatial correlation of air quality at different locations is based on the Air quality status of other nearby monitoring stations, including AQI and meteorological data to predict the air quality of a monitoring station. The experimental results show that the method has good prediction accuracy that the fitting degree with the actual measured data reaches more than 0.7, which can be applied to the modeling and prediction of the spatial and temporal distribution of regional PM2.5 concentration.

Keywords: LSTM, PM2.5, neural networks, spatio-temporal prediction

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Authors: Dae-Hee Son, Soon-Ryul Nam

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The power system frequency falls when disturbance such as rapid increase of system load or loss of a generating unit occurs in power systems. Especially, increase in the number of renewable generating units has a bad influence on the power system because of loss of generating unit depending on the circumstance. Conventional technologies use frequency droop control battery output for the frequency regulation and balance between supply and demand. If power is supplied using the fast output characteristic of the battery, power system stability can be further more improved. To improve the power system stability, we propose battery output control using ROCOF (Rate of Change of Frequency) in this paper. The bigger the power difference between the supply and the demand, the bigger the ROCOF drops. Battery output is controlled proportionally to the magnitude of the ROCOF, allowing for faster response to power imbalances. To simulate the control method of battery output system, we develop the user defined model using PSS/E and confirm that power system stability is improved by comparing with frequency droop control.

Keywords: PSS/E user defined model, power deviation, frequency droop control, ROCOF (rate of change of frequency)

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Authors: Kushal Kumar Chode

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Increase in demand for fuel saving and demand for faster vehicles with decent fuel economy, researchers around the world started investigating in various passive flow control devices to improve the fuel efficiency of vehicles. In this paper, A roof fairing was investigated for reducing the aerodynamic drag of a bluff body. The bluff body considered for this work is Ahmed model with a rake angle of 25deg was and subjected to flow with a velocity of 40m/s having Reynolds number of 2.68million was analysed using a commercial Computational Fluid Dynamic (CFD) code Star CCM+. It was evident that pressure drag is the main source of drag on an Ahmed body from the initial study. Adding a roof fairing has delayed the flow separation and resulted in delaying wake formation, thus improving the pressure in near weak and reducing the wake region. Adding a roof fairing of height and length equal to 1/7H and 1/3L respectively has shown a drag reduction by 9%. However, an optimised fairing, which was obtained by changing height, length and width by 5% increase, recorded a drag reduction close 12%.

Keywords: Ahmed model, aerodynamic drag, passive flow control, roof fairing, wake formation

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Authors: Dimeji Abe, Nonso Okoye, Gideon Ikpimi, Prince Idemudia

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Multi-reservoir optimization operation has been a critical issue for river basin management. Water, as a scarce resource, is in high demand and the problems associated with the reservoir as its storage facility are enormous. The complexity in balancing the supply and demand of this prime resource has created the need to examine the best way to solve the problem using optimization techniques. The objective of this study is to evaluate the performance of the multi-objective meta-heuristic algorithm for the operation of Gariep Dam for satisfying ecological flow requirements. This study uses an evolutionary algorithm called backtrack search algorithm (BSA) to determine the best way to optimise the dam operations of hydropower production, flood control, and water supply without affecting the environmental flow requirement for the survival of aquatic bodies and sustain life downstream of the dam. To achieve this objective, the operations of the dam that corresponds to different tradeoffs between the objectives are optimized. The results indicate the best model from the algorithm that satisfies all the objectives without any constraint violation. It is expected that hydropower generation will be improved and more water will be available for ecological flow requirements with the use of the algorithm. This algorithm also provides farmers with more irrigation water as well to improve their business.

Keywords: BSA evolutionary algorithm, metaheuristics, optimization, river basin management

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Authors: Tippawan Nasawan

Abstract:

The objective of this study is to find the replenishment policy in Assembly-to-Order manufacturing (ATO) which some of the major components have lead-time longer than customer lead-time. The variety of products, independent component demand, and long component lead-time are the difficulty that has resulted in the overstock problem. In addition, the ordering cost is trivial when compared to the cost of material of the major component. A conceptual design of the Decision Supporting System (DSS) has introduced to assist the replenishment policy. Component replenishment by using the variable which calls Available to Promise (ATP) for making the decision is one of the keys. The Poisson distribution is adopted to realize demand patterns in order to calculate Safety Stock (SS) at the specified Customer Service Level (CSL). When distribution cannot identify, nonparametric will be applied instead. The test result after comparing the ending inventory between the new policy and the old policy, the overstock has significantly reduced by 46.9 percent or about 469,891.51 US-Dollars for the cost of the major component (material cost only). Besides, the number of the major component inventory is also reduced by about 41 percent which helps to mitigate the chance of damage and keeping stock.

Keywords: Assembly-to-Order, Decision Supporting System, Component replenishment , Poisson distribution

Procedia PDF Downloads 127

Authors: Raweyah Al-Sedairawi

Abstract:

While high-rise housing detained massive negative connotations on several societies and well-being, this typology did deliver housing demand efficiently. Despite its adverse reference due to declining precedents, high-rise housing is still in global demand. Yet the suitability of this typology is still questioned. In this research, the suitability of high-rise housing as a socio-culturally sustainable solution to meet housing demands will be examined. By questioning what is the potential of high-rise housing as a socio-culturally sustainable solution for housing demands, the research will examine some high-rise housing practices. Through reviewing the literature on the origins of high-rise housing, how and why they were developed, some unsuccessful cases, and some successful cases, with the identification of factors for successful high-rise living. Thus, the research groundings will materialize from existing patterns of housing demands. Whilst most of the literature covers the housing market from an economic, real estate, and political perspective, there is less amount that discloses occupants’ reactions towards this typology and its appropriateness for the reason that income controls individuals’ choices. To bridge the gap, the prospect of implementing the study would be effective. This will be applied through a mixture of a qualitative and a quantitative methodology by conducting questionnaires and focus groups on existing cases of high-net-worth residential towers.

Keywords: architecture, behaviors, high-rise, socio-cultural, sustainability

Procedia PDF Downloads 88

Authors: Selin Guney, Andres Riquelme

Abstract:

The traditional bio-economic method for fisheries modeling uses some estimate of the growth parameters and the system carrying capacity from a biological model for the population dynamics (usually a logistic population growth model) which is then analyzed as a traditional production function. The stock dynamic is transformed into a revenue function and then compared with the extraction costs to estimate the maximum economic yield. In this paper, the logistic population growth model for the population is combined with a forecast of the abundance and location of the stock by using a generalized additive model approach. The paper focuses on the Chilean hake population. This method allows for the incorporation of climatic variables and the interaction with other marine species, which in turn will increase the reliability of the estimates and generate better extraction paths for different conservation objectives, such as the maximum biological yield or the maximum economic yield.

Keywords: bio-economic, fisheries, GAM, production

Procedia PDF Downloads 252