Search results for: truncated travel cost model

Authors: Muhammad Umer Zubair, Kamran Akhtar, Muhammad Arsalan Khan

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This paper is based on a research carried out on a failed slope in Defence Housing Authority (DHA) Phase I, Islamabad. The research included determination of Soil parameters, Site Surveying and Cost Estimation. Apart from these, the use of three dimensional (3D) slope stability analysis in conjunction with two dimensional (2D) analysis was used determination of slope conditions. In addition collection of soil reports, a detailed survey was carried out to create a 3D model in Surfer 8 software. 2D cross-sections that needed to be analyzed for stability were generated from 3D model. Slope stability softwares, Rocscience Slide 6.0 and Clara-W were employed for 2D and 3D Analyses respectively which have the ability to solve complex mathematical functions. Results of the analyses were used to confirm site conditions and the threats were identified to recommend suitable remedies.The most effective remedy was suggested for slope stability after analyzing all remedies in software Slide 6 and its feasibility was determined through cost benefit analysis. This paper should be helpful to Geotechnical engineers, design engineers and the organizations working with slope stability.

Keywords: slope stability, Rocscience, Clara W., 2d analysis, 3D analysis, sensitivity analysis

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Authors: Dimitra Alexiou, Stefanos Katsavounis, Ria Kalfakakou

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In an urban area the determination of transportation routes should be planned so as to minimize the provoked pollution taking into account the cost of such routes. In the sequel these routes are cited as pollution routes. The transportation network is expressed by a weighted graph G= (V, E, D, P) where every vertex represents a location to be served and E contains unordered pairs (edges) of elements in V that indicate a simple road. The distances/cost and a weight that depict the provoked air pollution by a vehicle transition at every road are assigned to each road as well. These are the items of set D and P respectively. Furthermore the investigated pollution routes must not exceed predefined corresponding values concerning the route cost and the route pollution level during the vehicle transition. In this paper we present an algorithm that generates such routes in order that the decision maker selects the most appropriate one.

Keywords: bi-criteria, pollution, shortest paths, computation

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Authors: Chris Durden, Peter Lane

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Cost accounting information potentially plays an important role in price setting. According to prior research fixed and variable cost information often is a key influence on pricing decisions. The literature highlights the benefits of applying systematic costing systems for enhanced price setting processes. This paper explores how costing systems are used for pricing decisions in the tourism and hospitality industry relative to other sources of price setting information. Pricing based on full cost information was found to have relatively greater importance and short-term survival and customer oriented objectives were found to be the more important pricing objectives. This paper contributes to the literature by providing a recent analysis of accounting’s role in price setting within the tourism and hospitality industry.

Keywords: cost accounting systems, pricing decisions, cost-plus pricing, market pricing, tourism industry

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Authors: Karima Megdouli, Bourhan tachtouch

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Ejector refrigeration cycles offer an alternative to conventional systems for producing cold from low-temperature heat. In this article, a thermodynamic model is presented. This model has the advantage of simplifying the calculation algorithm and describes the complex double-throttling mechanism that occurs in the ejector. The model assumption and calculation algorithm are presented first. The impact of each efficiency is evaluated. Validation is performed on several data sets. The ejector model is then used to simulate a RES (refrigeration ejector system), to validate its robustness and suitability for use in predicting thermodynamic cycle performance. A Taguchi and ANOVA optimization is carried out on a RES. TOPSIS analysis was applied to decide the optimum refrigerants with cost, safety, environmental and enviro economic concerns along with thermophysical properties.

Keywords: ejector, velocity distribution, shock circle, Taguchi and ANOVA optimization, TOPSIS analysis

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Authors: Filippo Ranalli, Forest Flager, Martin Fischer

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This paper presents a ground structure method to optimize the topology and discrete member sizing of steel frame structures in order to minimize total installed cost, including material, fabrication and erection components. The proposed method improves upon existing cost-based ground structure methods by incorporating constructability considerations well as satisfying both strength and serviceability constraints. The architecture for the method is a bi-level Multidisciplinary Feasible (MDF) architecture in which the discrete member sizing optimization is nested within the topology optimization process. For each structural topology generated, the sizing optimization process seek to find a set of discrete member sizes that result in the lowest total installed cost while satisfying strength (member utilization) and serviceability (node deflection and story drift) criteria. To accurately assess cost, the connection details for the structure are generated automatically using accurate site-specific cost information obtained directly from fabricators and erectors. Member continuity rules are also applied to each node in the structure to improve constructability. The proposed optimization method is benchmarked against conventional weight-based ground structure optimization methods resulting in an average cost savings of up to 30% with comparable computational efficiency.

Keywords: cost-based structural optimization, cost-based topology and sizing, optimization, steel frame ground structure optimization, multidisciplinary optimization of steel structures

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Authors: Jinkoo Kim, Hyungoo Kang, Hyungjun Shin

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In this study, a hybrid energy dissipation device is developed by combining a steel slit plate and friction pads to be used for seismic retrofit of structures, and its effectiveness is investigated by comparing the life cycle costs of the structure before and after the retrofit. The seismic energy dissipation capability of the dampers is confirmed by cyclic loading tests. The probabilities of reaching various damage states are obtained by fragility analysis, and the life cycle costs of the model structures are computed using the PACT (Performance Assessment Calculation Tool) program based on FEMA P-58 methodology. The fragility analysis shows that the probabilities of reaching limit states are minimized by the seismic retrofit with hybrid dampers and increasing column size. The seismic retrofit with increasing column size and hybrid dampers results in the lowest repair cost and shortest repair time.

Keywords: slit dampers, friction dampers, seismic retrofit, life cycle cost, FEMA P-58, PACT

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Authors: M. Karimpour, L. Hitihamillage, N. Elkhoury, S. Moridpour, R. Hesami

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Rail transport authorities around the world have been facing a significant challenge when predicting rail infrastructure maintenance work for a long period of time. Generally, maintenance monitoring and prediction is conducted manually. With the restrictions in economy, the rail transport authorities are in pursuit of improved modern methods, which can provide precise prediction of rail maintenance time and location. The expectation from such a method is to develop models to minimize the human error that is strongly related to manual prediction. Such models will help them in understanding how the track degradation occurs overtime under the change in different conditions (e.g. rail load, rail type, rail profile). They need a well-structured technique to identify the precise time that rail tracks fail in order to minimize the maintenance cost/time and secure the vehicles. The rail track characteristics that have been collected over the years will be used in developing rail track degradation prediction models. Since these data have been collected in large volumes and the data collection is done both electronically and manually, it is possible to have some errors. Sometimes these errors make it impossible to use them in prediction model development. This is one of the major drawbacks in rail track degradation prediction. An accurate model can play a key role in the estimation of the long-term behavior of rail tracks. Accurate models increase the track safety and decrease the cost of maintenance in long term. In this research, a short review of rail track degradation prediction models has been discussed before estimating rail track degradation for the curve sections of Melbourne tram track system using Adaptive Network-based Fuzzy Inference System (ANFIS) model.

Keywords: ANFIS, MGT, prediction modeling, rail track degradation

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Authors: Hui-Chieh Li

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Circular economy promotes greater resource productivity and avoids pollution through greater recycling and re-use which bring benefits for both the environment and the economy. The concept is contrast to a linear economy which is ‘take, make, dispose’ model of production. A well-design reverse logistics service strategy could enhance the willingness of recycling of the users and reduce the related logistics cost as well as carbon emissions. Moreover, the recycle brings the manufacturers most advantages as it targets components for closed-loop reuse, essentially converting materials and components from worn-out product into inputs for new ones at right time and right place. This study considers demand-supply interaction, time-dependent recycle demand, time-dependent surplus value of recycled product and constructs models on recycle service strategy for the recyclable waste collector. A crucial factor in optimizing a recycle service strategy is consumer demand. The study considers the relationships between consumer demand towards recycle and product characteristics, surplus value and user behavior. The study proposes a recycle service strategy which differs significantly from the conventional and typical uniform service strategy. Periods with considerable demand and large surplus product value suggest frequent and short service cycle. The study explores how to determine a recycle service strategy for recyclable waste collector in terms of service cycle frequency and duration and vehicle type for all service cycles by considering surplus value of recycled product, time-dependent demand, transportation economies and demand-supply interaction. The recyclable waste collector is responsible for the collection of waste product for the manufacturer. The study also examines the impacts of utilization rate on the cost and profit in the context of different sizes of vehicles. The model applies mathematical programming methods and attempts to maximize the total profit of the distributor during the study period. This study applies the binary logit model, analytical model and mathematical programming methods to the problem. The model specifically explores how to determine a recycle service strategy for the recycler by considering product surplus value, time-dependent recycle demand, transportation economies and demand-supply interaction. The model applies mathematical programming methods and attempts to minimize the total logistics cost of the recycler and maximize the recycle benefits of the manufacturer during the study period. The study relaxes the constant demand assumption and examines how service strategy affects consumer demand towards waste recycling. Results of the study not only help understanding how the user demand for recycle service and product surplus value affects the logistics cost and manufacturer’s benefits, but also provide guidance such as award bonus and carbon emission regulations for the government.

Keywords: circular economy, consumer demand, product surplus value, recycle service strategy

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Authors: Vaibhav V. Dixit, Shubham Ajay Karwa

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Diabetic foot ulcers speak to a critical medical problem. Right now, clinicians and medical caretakers primarily construct their injury evaluation in light of visual examination of wound size and mending status, while the patients themselves rarely have a chance to play a dynamic part. Henceforth, love quantitative and practical examination technique that empowers the patients and their parental figures to take a more dynamic part in every day wound care possibly can quicken wound recuperating, spare travel cost and diminish human services costs. Considering the commonness of cell phones with a high-determination computerized camera, evaluating wounds by breaking down pictures of ceaseless foot ulcers is an alluring choice. In this paper, we propose a novel injury picture examination framework actualized using feature extraction and color segmentation. Here we are using the Normalized minimum distance classifier for classifying the output.

Keywords: diabetic, Gabor wavelet, normalized minimum distance classifier, quantiable parameters

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Authors: Sajjad Farahani, Wilkistar Otieno, Xiaohang Yue

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This paper develops a model for the optimal disposition decision for product returns in a remanufacturing system with limited recoverable inventory capacity. In this model, a constant demand is satisfied by remanufacturing returned products which are up to the minimum required quality grade. The quality grade of returned products is uncertain and remanufacturing cost increases as the quality level decreases, and remanufacturer wishes to determine which returned product to accept to be remanufactured for reselling, and any unaccepted returns may be salvaged at a value that increases with their quality level. Accepted returns can be stocked for remanufacturing upon demand requests, but incur a holding cost. A Markov decision problem is formulated in order to evaluate various performance measures for this system and obtain the optimal remanufacturing policy. A detailed numerical study reveals that our approach to the disposition problem outperforms the current industrial practice ignoring quality grade of returned products. In addition, we identify conditions under which this improvement is the highest.

Keywords: green supply chain management, matrix geometric method, production recovery, reverse supply chains

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Authors: Khaled S. Abdallah, Abdel-Aziz M. Mohamed

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Moving industries consume numerous resources and dispose masses of used packaging materials. Proper sorting, recycling and disposing the packaging materials is necessary to avoid a sever pollution disaster. This research paper presents a conceptual model to propose sustainable truck rental operations instead of the regular one. An optimization model was developed to select the locations of truck rental centers, collection sites, maintenance and repair sites, and identify the rental fees to be charged for all routes that maximize the total closed supply chain profits. Fixed costs of vehicle purchasing, costs of constructing collection centers and repair centers, as well as the fixed costs paid to use disposal and recycling centers are considered. Operating costs include the truck maintenance, repair costs as well as the cost of recycling and disposing the packing materials, and the costs of relocating the truck are presented in the model. A mixed integer model is developed followed by a simulation model to examine the factors affecting the operation of the model.

Keywords: modeling, truck rental, supply chains management.

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Authors: Frimpong Kyeremeh, Albert Y. Appiah, Ben B. K. Ayawli

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Energy storage system (ESS) is an essential part of a microgrid (MG) because of its immense benefits to the economics and the stability of MG. For a direct current (DC) MG (DCMG) in which the generating units are mostly variable renewable energy generators, DC bus voltage fluctuation is inevitable; hence ESS is vital in managing the mismatch between load demand and generation. Besides, to accrue the maximum benefits of ESS in the microgrid, there is the need for proper sizing and location of the ESSs. In this paper, a performance comparison is made between two configurations of ESS; distributed battery energy storage system (D-BESS) and an aggregated (centralized) battery energy storage system (A-BESS), on the basis of stability and operational cost for a DCMG. The configuration consists of four households with rooftop PV panels and a wind turbine. The objective is to evaluate and analyze the technical efficiencies, cost effectiveness as well as controllability of each configuration. The MG is first modelled with MATLAB Simulink then, a mathematical model is used to determine the optimal size of the BESS that minimizes the total operational cost of the MG. The performance of the two configurations would be tested with simulations. The two configurations are expected to reduce DC bus voltage fluctuations, but in the cases of voltage stability and optimal cost, the best configuration performance will be determined at the end of the research. The work is in progress, and the result would help MG designers and operators to make the best decision on the use of BESS for DCMG configurations.

Keywords: aggregated energy storage system, DC bus voltage, DC microgrid, distributed battery energy storage, stability

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Authors: Roshanim Koris, Norashidah Mohamed Nor, Sharifah Azizah Haron, Normaz Wana Ismail, Syed Mohamed Aljunid Syed Junid, Amrizal Muhammad Nur, Asrul Akmal Shafie, Suraya Yusuff, Namaitijiang Maimaiti

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An ageing population has huge implications for virtually every aspect of Malaysian societies. The elderly consume a greater volume of healthcare facilities not because they are older, but because of they are sick. The chronic comorbidities and deterioration of cognitive ability would lead the elderly’s health to become worst. This study aims to provide a comprehensive estimate of the direct and indirect costs of health care used in a nationally representative sample of community-dwelling elderly with dementia and as well as the determinants of healthcare cost. A survey using multi-stage random sampling techniques recruited a final sample of 2274 elderly people (60 years and above) in the state of Johor, Perak, Selangor and Kelantan. Mini Mental State Examination (MMSE) score was used to measure the cognitive capability among the elderly. Only the elderly with a score less than 19 marks were selected for further analysis and were classified as dementia. By using a two-part model findings also indicate household income and education level are variables that strongly significantly influence the healthcare cost among elderly with dementia. A number of visits and admission are also significantly affect healthcare expenditure. The comorbidity that highly influences healthcare cost is cancer and seeking the treatment in private facilities is also significantly affected the healthcare cost among the demented elderly. The level of dementia severity is not significant in determining the cost. This study is expected to attract the government's attention and act as a wake-up call for them to be more concerned about the elderly who are at high risk of having chronic comorbidities and cognitive problems by providing more appropriate health and social care facilities. The comorbidities are one of the factor that could cause dementia among elderly. It is hoped that this study will promote the issues of dementia as a priority in public health and social care in Malaysia.

Keywords: ageing population, dementia, elderly, healthcare cost, healthcare utiliztion

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Authors: Barry Aifesehi Aiworo, Henry Oriakhi

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This paper, examines the analysis of access pattern to school and travel risks among school children in Benin City, Edo State, Nigeria. The risk includes accident, molestation (sexually) and kidnapping. The objective of this paper are to examine the various means (modes) of transport to school; determine the type and incidences of risk experienced by school children in the study area; examine the risk incidences and ages of school children in the study area. Hypothesis which states that the types of risks encountered by school children are independent of means of transport was tested using the chi-square test (X2). A sampling ratio of twelve percent (12%) was taken from 396 schools in Benin City. By implication, 49 schools were randomly selected in Benin City for this research. A total of 42,053 students in the 49 schools constitute the sample frame for the research. Two percent (2%), 841 students were taken as the sample size. The use of stratified sampling method was applied by stratifying the study area (Benin City) into local governments- Egor, Ikpoba-Okha and Oredo. Thereafter, the lists of schools in the various local governments were obtained from the Ministry of Education before the schools for research were randomly chosen from each local government area. The analysis revealed that 6.7% of the total students interviewed have been involved in road accidents. 1.04% of the total respondents said at one time or the other that they have been kidnapped. Finally, the research found that travel is comparatively safe and believes this may be partly attributable to safer route to schools and school children being more familiar with the school journey. The research indicates that children aged between eleven and fifteen are most at risk of hit or knocked down on Benin City’s roads. These findings may help in planning and targeting road safety initiative (education, campaigns) in Benin City.

Keywords: accident, molestation (sexually), kidnapping, pedophile, pedestrian

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Authors: Lai Ving Kam

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Many markets are maturing, consumer buying powers are weakening and customer preferences change rapidly. To survive, many adopt fast paced continuous cost reduction and competitive pricing to remain relevance. Marketers desire to push for more sales to increase revenues have intensified competitions at time cannibalize the product and market. The amazing technologies changes have created both hope and despair to the industries. The pressure to constantly reduce cost, on the one hand, create and market new products in cheaper prices and shorter life cycles, on the other has become a continuous endeavour. The twin trends appear irreconcilable. Can core strategic vision provides and adapts new directions in continuous cost reduction? This study investigates core strategic vision able to meet this need, for firms to survive and stay profitable. Under current uncertainty market, are firms falling back on their core strategic visions to take them out of the unfavourable positions?

Keywords: core strategy vision, continuous cost reduction, fashionable products industry, competitive pricing

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Authors: Shadab Bahreini

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Public transportation is one of the most important aspects of cities, which impacts various factors of the Quality of Life (QoL) of citizens. A passenger's experience is influenced by a variety of indicators in addition to the cost and safety of the trip. This article intends to investigate how QoL is affected by public transport in an urban environment by introducing a literature review of QoL and Quality of Urban Life (QoUL), investigating the intersection of QoL and public transport, and reviewing the background theory for Transport Quality of Life (TQoL). The article proposes a Public Transport Quality of Life (PTQoL) framework comprised of a set of indicators that measure how public transport impacts QoL across personal (physical and mental), socioeconomic, and environmental dimensions. The study proposes using the framework to evaluate objective or subjective factors affecting a person's QoL regarding public transport. Finally, it concludes that public transport is a key component in shaping QoL in urban environments and that policymakers and urban planners should use the PTQoL framework to make evidence-based decisions to improve public transport systems and their impact on QoL.

Keywords: public transport, quality of life, subjective and objective indicators, urban environment

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Authors: Kyle Burke Pfeiffer, Carmella Burdi, Karen Marsh

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The evacuation and shelter-in-place planning process employed by most jurisdictions within the United States is not informed by a scientifically-derived framework that is inclusive of the behavioral and policy-related indicators of public compliance with evacuation orders. While a significant body of work exists to define these indicators, the research findings have not been well-integrated nor translated into useable planning factors for public safety officials. Additionally, refinement of the planning factors alone is insufficient to support science-based evacuation planning as the behavioral elements of evacuees—even with consideration of policy-related indicators—must be examined in the context of specific regional transportation and shelter networks. To address this problem, the Federal Emergency Management Agency and Argonne National Laboratory developed an agent-based model to support regional analysis of zone-based evacuation in southeastern Georgia. In particular, this model allows public safety officials to analyze the consequences that a range of hazards may have upon a community, assess evacuation and shelter-in-place decisions in the context of specified evacuation and response plans, and predict outcomes based on community compliance with orders and the capacity of the regional (to include extra-jurisdictional) transportation and shelter networks. The intention is to use this model to aid evacuation planning and decision-making. Applications for the model include developing a science-driven risk communication strategy and, ultimately, in the case of evacuation, the shortest possible travel distance and clearance times for evacuees within the regional boundary conditions.

Keywords: agent-based modeling for evacuation, decision-support for evacuation planning, evacuation planning, human behavior in evacuation

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Authors: Robin Molinier

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Industrial symbiosis (I.S) rely on two modes of cooperation that are infrastructure sharing and resource substitution to obtain economic and environmental benefits. The former consists in the intensification of use of an asset while the latter is based on the use of waste, fatal energy (and utilities) as alternatives to standard inputs. Both modes, in fact, rely on the shift from a business-as-usual functioning towards an alternative production system structure so that in a business point of view the distinction is not clear. In order to investigate the way those cooperation modes can be distinguished, we consider the stakeholders' interplay in the business model structure regarding their resources and requirements. For infrastructure sharing (following economic engineering literature) the cost function of capacity induces economies of scale so that demand pooling reduces global expanses. Grassroot investment sizing decision and the ex-post pricing strongly depends on the design optimization phase for capacity sizing whereas ex-post operational cost sharing minimizing budgets are less dependent upon production rates. Value is then mainly design driven. For resource substitution, synergies value stems from availability and is at risk regarding both supplier and user load profiles and market prices of the standard input. Baseline input purchasing cost reduction is thus more driven by the operational phase of the symbiosis and must be analyzed within the whole sourcing policy (including diversification strategies and expensive back-up replacement). Moreover, while resource substitution involves a chain of intermediate processors to match quality requirements, the infrastructure model relies on a single operator whose competencies allow to produce non-rival goods. Transaction costs appear higher in resource substitution synergies due to the high level of customization which induces asset specificity, and non-homogeneity following transaction costs economics arguments.

Keywords: business model, capacity, sourcing, synergies

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Authors: Hninn Thiri Naing

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In Myanmar, there are many regions that are far away from the national grid. For these areas, isolated regional micro-grids are one of the solutions. The study area in this paper is also operating in such way. The main difficulty in such regions is the high cost of electrical energy. This paper will be approached to cost-effective or cost-optimization by energy planning with renewable energy resources and natural gas. Micro-grid will be set up for performance in the Dawei region since it is economic zone in lower Myanmar and so far from national grids. The required metrological and geographical data collections are done. Currently, the status is electric unit rate is higher than the other. For microgrid planning and optimization, Homer Pro-software is employed in this research.

Keywords: energy planning, renewable energy, homer pro, cost of energy

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Authors: Ariangelo Hauer Dias Filho, Gustavo Antoniácomi de Carvalho, Benjamim de Melo Carvalho

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The work´s purpose was to evaluate the possibility of manufacturing casting tools utilizing Fused Filament Fabrication, a 3D printing technique, without any post-processing on the printed part. Taguchi Orthogonal array was used to evaluate the influence of extrusion temperature, bed temperature, layer height, and infill on the dimensional accuracy of a 3D-Printed Polymer Model. A Zeiss T-SCAN CS 3D Scanner was used for dimensional evaluation of the printed parts within the limit of ±0,2 mm. The mold capabilities were tested with the printed model to check how it would interact with the green sand. With little adjustments in the 3D model, it was possible to produce rapid tools without the need for post-processing for iron casting. The results are important for reducing time and cost in the development of such tools.

Keywords: additive manufacturing, Taguchi method, rapid tooling, fused filament fabrication, casting mold

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Authors: Soheila Sadeghi

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Accurate forecasting of project performance metrics is crucial for successfully managing and delivering urban road reconstruction projects. Traditional methods often rely on static baseline plans and fail to consider the dynamic nature of project progress and external factors. This research proposes a machine learning-based approach to forecast project performance metrics, such as cost variance and earned value, for each Work Breakdown Structure (WBS) category in an urban road reconstruction project. The proposed model utilizes time series forecasting techniques, including Autoregressive Integrated Moving Average (ARIMA) and Long Short-Term Memory (LSTM) networks, to predict future performance based on historical data and project progress. The model also incorporates external factors, such as weather patterns and resource availability, as features to enhance the accuracy of forecasts. By applying the predictive power of machine learning, the performance forecasting model enables proactive identification of potential deviations from the baseline plan, which allows project managers to take timely corrective actions. The research aims to validate the effectiveness of the proposed approach using a case study of an urban road reconstruction project, comparing the model's forecasts with actual project performance data. The findings of this research contribute to the advancement of project management practices in the construction industry, offering a data-driven solution for improving project performance monitoring and control.

Keywords: project performance forecasting, machine learning, time series forecasting, cost variance, earned value management

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Authors: Salami Akeem Olanrewaju

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The transportation models or problems are primarily concerned with the optimal (best possible) way in which a product produced at different factories or plants (called supply origins) can be transported to a number of warehouses or customers (called demand destinations). The objective in a transportation problem is to fully satisfy the destination requirements within the operating production capacity constraints at the minimum possible cost. The objective of this study is to determine ways of minimizing transport cost in order to maximum profit. Data were gathered from the records of the Distribution Department of 7-Up Bottling Company Plc. Ilorin, Kwara State, Nigeria. The data were analyzed using SPSS (Statistical Package for Social Sciences) while applying the three methods of solving a transportation problem. The three methods produced the same results; therefore, any of the method can be adopted by the company in transporting its final products to the wholesale dealers in order to minimize total production cost.

Keywords: cost minimization, resources utilization, distribution system, allocation problem

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Authors: Robin Molinier

Abstract:

Industrial symbiosis (I.S) rely on two basic modes of cooperation between organizations that are infrastructure/service sharing and resource substitution (the use of waste materials, fatal energy and recirculated utilities for production). The former consists in the intensification of use of an asset and thus requires to compare the incremental investment cost to be incurred and the stand-alone cost faced by each potential participant to satisfy its own requirements. In order to investigate the way such a cooperation mode can be implemented we formulate a game theoretic model integrating the grassroot investment decision and the ex-post access pricing problem. In the first period two actors set cooperatively (resp. non-cooperatively) a level of common (resp. individual) infrastructure capacity oversizing to attract ex-post a potential entrant with a plug-and-play offer (available capacity, tariff). The entrant’s requirement is randomly distributed and known only after investments took place. Capacity cost exhibits sub-additive property so that there is room for profitable overcapacity setting in the first period under some conditions that we derive. The entrant willingness-to-pay for the access to the infrastructure is driven by both her standalone cost and the complement cost to be incurred in case she chooses to access an infrastructure whose the available capacity is lower than her requirement level. The expected complement cost function is thus derived, and we show that it is decreasing, convex and shaped by the entrant’s requirements distribution function. For both uniform and triangular distributions optimal capacity level is obtained in the cooperative setting and equilibrium levels are determined in the non-cooperative case. Regarding the latter, we show that competition is deterred by the first period investor with the highest requirement level. Using the non-cooperative game outcomes which gives lower bounds for the profit sharing problem in the cooperative one we solve the whole game and describe situations supporting sharing agreements.

Keywords: capacity, cooperation, industrial symbiosis, pricing

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Authors: Minoo Ghasemzadeh, Rouzbeh Riazi, Shidvash Vakilipour, Alireza Ramezani

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In this study, thermo acoustic oscillations of a lean premixed combustor has been investigated, and a mono-dimensional code was developed in this regard. The linearized equations of motion are solved for perturbations with time dependence〖 e〗^iwt. Two flame models were considered in this paper and the effect of mean flow and boundary conditions were also investigated. After manipulation of flame heat release equation together with the equations of flow perturbation within the main components of the combustor model (i.e., plenum/ premixed duct/ and combustion chamber) and by considering proper boundary conditions between the components of model, a system of eight homogeneous equations can be obtained. This simplification, for the main components of the combustor model, is convenient since low frequency acoustic waves are not affected by bends. Moreover, some elements in the combustor are smaller than the wavelength of propagated acoustic perturbations. A convection time is also assumed to characterize the required time for the acoustic velocity fluctuations to travel from the point of injection to the location of flame front in the combustion chamber. The influence of an extended flame model on the acoustic frequencies of combustor was also investigated, assuming the effect of flame speed as a function of equivalence ratio perturbation, on the rate of flame heat release. The abovementioned system of equations has a related eigenvalue equation which has complex roots. The sign of imaginary part of these roots determines whether the disturbances grow or decay and the real part of these roots would give the frequency of the modes. The results show a reasonable agreement between the predicted values of dominant frequencies in the present model and those calculated in previous related studies.

Keywords: combustion instability, dominant frequencies, flame speed, premixed combustor

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Authors: Angela U. Makolo

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

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

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Authors: Swapna Begum, Higano Yoshiro

Abstract:

Dhaka is the capital city of Bangladesh. It is considered as one of the traffic congested cities in the world. The growth of the population of this city is increasing day by day. The land use pattern and the increased socio-economic characteristics increase the motor vehicle ownership of this city. The rapid unplanned urbanization and poor transportation planning have deteriorated the transport environment of this city. Also, the huge travel demand with non-motorized traffics on streets is accounted for enormous traffic congestion in this city. The land transport sector in Dhaka is mainly dependent on road transport comprised of both motorized and non-motorized modes of travel. This improper modal mix and the un-integrated system have resulted in huge traffic congestion in this city. Moreover, this city has no well-organized public transport system and any Mass Transit System to cope with this ever increasing demand. Traffic congestion causes serious air pollution and adverse impact on the economy by deteriorating the accessibility, level of service, safety, comfort and operational efficiency. Therefore, there is an imperative need to introduce a well-organized, properly scheduled mass transit system like (Bus Rapid Transit) BRT minimizing the existing problems.

Keywords: air pollution, BRT, mass transit, traffic congestion

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Authors: Zainab Khalifah, Wong Chiet Bing, Noor Hazarina Hashim

Abstract:

The evolution of customer behavior in purchasing products or services through the Internet leads to airline companies engaging in the e-ticketing process in order to maintain their business. A well-designed website is vitally significant for the airline companies to provide effective communication, support, and competitive advantage. This study was conducted to identify the dimensions of website quality for low cost airline and to investigate the relationship between the website quality and customer e-satisfaction at low cost airline. A total of 381 responses were conveniently collected among local passengers at Low Cost Carrier Terminal, Kuala Lumpur via questionnaire distribution. This study found that the five determinant factors of website quality for AirAsia were Information Content, Navigation, Responsiveness, Personalization, and Security and Privacy. The results of this study revealed that there is a positive relationship between the five dimensions of website quality and customer e-satisfaction, and also information content was the most significant contributor to customer e-satisfaction.

Keywords: website quality, customer e-satisfaction, low cost airline, e-ticketing

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Authors: Elmo Thiago Lins Cöuras Ford, Valentina Alessandra Carvalho do Vale

Abstract:

It is presented a model of two subsystems of Central Solar Tower to produce steam in applications to help in energy consumption. The first subsystem consists of 24 heliostats constructed of adaptive and mobile metal structures to track the apparent movement of the sun on its focus and covered by 96 layers of mirror of 150 mm at width and 220 mm at length, totaling an area of concentration of 3.2 m². Thereby obtaining optical parameters essential to reflection of sunlight by the reflector surface and absorption of this light by focus located in the light receiver, which is inserted in the second subsystem, which is at the top of a tower. The tower was built in galvanized iron able to support the absorber, and a gas cylinder to cool the equipment. The area illuminated by the sun was 9 x 10-2m2, yielding a concentration factor of 35.22. It will be shown the processes of manufacture and assembly of the Mini-Central Tower proposal, which has as main characteristics the construction and assembly facilities, in addition to reduced cost. Data of tests to produce water vapor parameters are presented and determined to diagnose the efficiency of the mini-solar central tower. It will be demonstrated the thermal, economic and material viability of the proposed system.

Keywords: solar oven, solar cooker, composite material, low cost, sustainable development

Procedia PDF Downloads 417

Authors: Soheila Sadeghi

Abstract:

Construction projects are complex and often subject to significant cost overruns due to the multifaceted nature of the activities involved. Accurate cost estimation is crucial for effective budget planning and resource allocation. Traditional methods for predicting overruns often rely on expert judgment or analysis of historical data, which can be time-consuming, subjective, and may fail to consider important factors. However, with the increasing availability of data from construction projects, machine learning techniques can be leveraged to improve the accuracy of overrun predictions. This study applied machine learning algorithms to enhance the prediction of cost overruns in a case study of a construction project. The methodology involved the development and evaluation of two machine learning models: Random Forest and Neural Networks. Random Forest can handle high-dimensional data, capture complex relationships, and provide feature importance estimates. Neural Networks, particularly Deep Neural Networks (DNNs), are capable of automatically learning and modeling complex, non-linear relationships between input features and the target variable. These models can adapt to new data, reduce human bias, and uncover hidden patterns in the dataset. The findings of this study demonstrate that both Random Forest and Neural Networks can significantly improve the accuracy of cost overrun predictions compared to traditional methods. The Random Forest model also identified key cost drivers and risk factors, such as changes in the scope of work and delays in material delivery, which can inform better project risk management. However, the study acknowledges several limitations. First, the findings are based on a single construction project, which may limit the generalizability of the results to other projects or contexts. Second, the dataset, although comprehensive, may not capture all relevant factors influencing cost overruns, such as external economic conditions or political factors. Third, the study focuses primarily on cost overruns, while schedule overruns are not explicitly addressed. Future research should explore the application of machine learning techniques to a broader range of projects, incorporate additional data sources, and investigate the prediction of both cost and schedule overruns simultaneously.

Keywords: cost prediction, machine learning, project management, random forest, neural networks

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Authors: Mariem Kchaou, Wiem Khlif, Faiez Gargouri

Abstract:

Modeling business processes is an essential task when evaluating, improving, or documenting existing business processes. To be efficient in such tasks, a business process model (BPM) must have high structural quality and high performance. Evidently, evaluating the performance of a business process model is a necessary step to reduce time, cost, while assessing the structural quality aims to improve the understandability and the modifiability of the BPMN model. To achieve these objectives, a set of structural and performance measures have been proposed. Since the diversity of measures, we propose a framework that integrates both structural and performance aspects for classifying them. Our measure classification is based on business process model perspectives (e.g., informational, functional, organizational, behavioral, and temporal), and the elements (activity, event, actor, etc.) involved in computing the measures. Then, we implement this framework in a tool assisting the structural quality and the performance of a business process. The tool helps the designers to select an appropriate subset of measures associated with the corresponding perspective and to calculate and interpret their values in order to improve the structural quality and the performance of the model.

Keywords: performance, structural quality, perspectives, tool, classification framework, measures

Procedia PDF Downloads 156