Search results for: transaction cost

Authors: Dixit Garg, S. Luthra, A. Haleem

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During recent years, the natural environment has become a challenging topic that business organizations must consider due to the economic and ecological impacts and increasing awareness of environment protection among society. Organizations are trying to achieve the goals of improvement in environment, low cost, high quality, flexibility and more customer satisfaction. Performance measurement frameworks are very useful to monitor the performance of any organization. The basic goal of this paper is to identify performance measures and ranking of these performance measures of GSCM performance measurement towards sustainability framework. Five perspectives (Environment, Economic, Social, Operational and Cost performances) and nineteen performance measures of GSCM performance towards sustainability have been have been identified from extensive literature review. Analytical Hierarchy Process (AHP) technique has been utilized for ranking of these performance perspectives and measures. All pair comparisons in AHP have been made on the basis on the experts’ opinions (selected from academia and industry). Ranking of these performance perspectives and measures will help to understand the importance of environmental, economic, social, operational performances, and cost performances in the supply chain.

Keywords: analytical hierarchy process, green supply chain management, performance measures, sustainability

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Authors: Shobha Ramalingam

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The majority of the infrastructure projects are affected by time overrun, resulting in project delays and subsequently cost overruns. Time overrun may vary from a few months to as high as five or more years, placing the project viability at risk. One of the probable reasons noted in the literature for this outcome in projects is due to poor productivity. Researchers contend that productivity in construction has only marginally increased over the years. While studies in the literature have extensively focused on time and cost parameters in projects, there are limited studies that integrate time and cost with productivity to assess project performance. To this end, a study was conducted to understand the project delay factors concerning cost, time and productivity. A case-study approach was adopted to collect rich data from a nuclear power plant project site for two months through observation, interviews and document review. The data were analyzed using three different approaches for a comprehensive understanding. Foremost, a root-cause analysis was performed on the data using Ishikawa’s fish-bone diagram technique to identify the various factors impacting the delay concerning time. Based on it, a questionnaire was designed and circulated to concerned executives, including project engineers and contractors to determine the frequency of occurrence of the delay, which was then compiled and presented to the management for a possible solution to mitigate. Second, a productivity analysis was performed on select activities, including rebar bending and concreting through a time-motion study to analyze product performance. Third, data on cost of construction for three years allowed analyzing the cost performance using earned value management technique. All three techniques allowed to systematically and comprehensively identify the key factors that deter project performance and productivity loss in the construction of the nuclear power plant project. The findings showed that improper planning and coordination between multiple trades, concurrent operations, improper workforce and material management, fatigue due to overtime were some of the key factors that led to delays and poor productivity. The findings are expected to act as a stepping stone for further research and have implications for practitioners.

Keywords: earned value analysis, time performance, project costs, project delays, construction productivity

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Authors: Ali Kazemi

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The digital evolution of financial services, while offering unprecedented convenience and accessibility, has also escalated the vulnerabilities to fraudulent activities. In this study, we introduce a distinct approach to real-time anomaly detection in financial transactions, aiming to fortify the defenses of banking and financial institutions against such threats. Utilizing unsupervised machine learning algorithms, specifically autoencoders and isolation forests, our research focuses on identifying irregular patterns indicative of fraud within transactional data, thus enabling immediate action to prevent financial loss. The data we used in this study included the monetary value of each transaction. This is a crucial feature as fraudulent transactions may have distributions of different amounts than legitimate ones, such as timestamps indicating when transactions occurred. Analyzing transactions' temporal patterns can reveal anomalies (e.g., unusual activity in the middle of the night). Also, the sector or category of the merchant where the transaction occurred, such as retail, groceries, online services, etc. Specific categories may be more prone to fraud. Moreover, the type of payment used (e.g., credit, debit, online payment systems). Different payment methods have varying risk levels associated with fraud. This dataset, anonymized to ensure privacy, reflects a wide array of transactions typical of a global banking institution, ranging from small-scale retail purchases to large wire transfers, embodying the diverse nature of potentially fraudulent activities. By engineering features that capture the essence of transactions, including normalized amounts and encoded categorical variables, we tailor our data to enhance model sensitivity to anomalies. The autoencoder model leverages its reconstruction error mechanism to flag transactions that deviate significantly from the learned normal pattern, while the isolation forest identifies anomalies based on their susceptibility to isolation from the dataset's majority. Our experimental results, validated through techniques such as k-fold cross-validation, are evaluated using precision, recall, and the F1 score alongside the area under the receiver operating characteristic (ROC) curve. Our models achieved an F1 score of 0.85 and a ROC AUC of 0.93, indicating high accuracy in detecting fraudulent transactions without excessive false positives. This study contributes to the academic discourse on financial fraud detection and provides a practical framework for banking institutions seeking to implement real-time anomaly detection systems. By demonstrating the effectiveness of unsupervised learning techniques in a real-world context, our research offers a pathway to significantly reduce the incidence of financial fraud, thereby enhancing the security and trustworthiness of digital financial services.

Keywords: anomaly detection, financial fraud, machine learning, autoencoders, isolation forest, transactional data analysis

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Authors: Peyman Sindareh Esfahani, Jeffery Kurt Pieper

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In this paper, the problem of robust model predictive control (MPC) for discrete-time linear systems in linear fractional transformation form with structured uncertainty and norm-bounded disturbance is investigated. The problem of minimization of the cost function for MPC design is converted to minimization of the worst case of the cost function. Then, this problem is reduced to minimization of an upper bound of the cost function subject to a terminal inequality satisfying the l₂-norm of the closed loop system. The characteristic of the linear fractional transformation system is taken into account, and by using some mathematical tools, the robust predictive controller design problem is turned into a linear matrix inequality minimization problem. Afterwards, a formulation which includes an integrator to improve the performance of the proposed robust model predictive controller in steady state condition is studied. The validity of the approaches is illustrated through a robust control benchmark problem.

Keywords: linear fractional transformation, linear matrix inequality, robust model predictive control, state feedback control

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Authors: Wenjun Hou, Marek Perkowski

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The Traveling Salesman problem is famous in computing and graph theory. In short, it asks for the Hamiltonian cycle of the least total weight in a given graph with N nodes. All variations on this problem, such as those with K-bounded-degree nodes, are classified as NP-complete in classical computing. Although several papers propose theoretical high-level designs of quantum algorithms for the Traveling Salesman Problem, no quantum circuit implementation of these algorithms has been created up to our best knowledge. In contrast to previous papers, the goal of this paper is not to optimize some abstract complexity measures based on the number of oracle iterations, but to be able to evaluate the real circuit and time costs of the quantum computer. Using the emerging quantum programming language Q# developed by Microsoft, which runs quantum circuits in a quantum computer simulation, an implementation of the bounded-degree problem and its respective quantum circuit were created. To apply Grover’s algorithm to this problem, a quantum oracle was designed, evaluating the cost of a particular set of edges in the graph as well as its validity as a Hamiltonian cycle. Repeating the Grover algorithm with an oracle that finds successively lower cost each time allows to transform the decision problem to an optimization problem, finding the minimum cost of Hamiltonian cycles. N log₂ K qubits are put into an equiprobablistic superposition by applying the Hadamard gate on each qubit. Within these N log₂ K qubits, the method uses an encoding in which every node is mapped to a set of its encoded edges. The oracle consists of several blocks of circuits: a custom-written edge weight adder, node index calculator, uniqueness checker, and comparator, which were all created using only quantum Toffoli gates, including its special forms, which are Feynman and Pauli X. The oracle begins by using the edge encodings specified by the qubits to calculate each node that this path visits and adding up the edge weights along the way. Next, the oracle uses the calculated nodes from the previous step and check that all the nodes are unique. Finally, the oracle checks that the calculated cost is less than the previously-calculated cost. By performing the oracle an optimal number of times, a correct answer can be generated with very high probability. The oracle of the Grover Algorithm is modified using the recalculated minimum cost value, and this procedure is repeated until the cost cannot be further reduced. This algorithm and circuit design have been verified, using several datasets, to generate correct outputs.

Keywords: quantum computing, quantum circuit optimization, quantum algorithms, hybrid quantum algorithms, quantum programming, Grover’s algorithm, traveling salesman problem, bounded-degree TSP, minimal cost, Q# language

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Authors: Saifullahi Umar, Baba Mamman Yarima, Mohammed Bello Usman, Hassan Mohammed

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This study was conducted along with the Hadejia valley project irrigation under the Hadejia-Jama’are River Basin Development Authority (HRBDA) in Jigawa State. The multi-stage sampling procedure was used to select 72 rice farmers operating along with the Hadejia Valley Irrigation Project. Data for the study were collected using a structured questionnaire. The analytical tools employed for the study were descriptive statistics and Farm budget technique. The result shows that 55% of the farmers were between 31-40 years of age, 66.01% were male, and the result also revealed that the total cost of cultivation of an acre of land for rice production during the dry season was N73,900 with input cost accounting for 63.59% of the total cost of production. The gross return was N332,500, with a net return of N258,600 per acre. The estimated benefit-cost ratio of 3.449 indicates the strong performance of the dry season rice production. The leading constraints to dry season rice production were low access to quality extension services, low access to finance, poor quality fertilizers, and poor prices. The study, therefore, concludes that dry season rice production is a profitable enterprise in the study area hence, to productivity the farmers should be linked to effective extension service delivery institutions, expanding their access to productive sources of finances, the government should strengthen fertilizer quality control measures and comprehensive market linkages for the farmers.

Keywords: Auyo, dry season, Hadejia Valley, rice

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Authors: Z. Abdollahnejad, M. Mastali, F. Pacheco-Torgal

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Waste reuse is crucial in a context of circular economy and zero waste sustainable needs. Some wastes deserve further studies by the scientific community not only because they are generated in high amount but also because they have a low reuse rate. This paper reports results of 32 hybrid cement mortars based on fly ash and waste glass. They allow to explore the influence of mix design on the cost and on the embodied carbon of the hybrid cement mortars. The embodied carbon data for all constituents were taken from the database Ecoinvent. This study led to the development of a mixture with just 70 kg CO2e.

Keywords: waste reuse, fly ash, waste glass, hybrid cements, cost, embodied carbon

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Authors: Javed Kamal

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A proposed field study of wheat-based cropping systems was conducted at Faisalabad (Post-Graduate Research Station). We used 7 treatments and Jantar as a green manuring crop to increase the fertility status of soil; after the vegetative phases of wheat, rice, sorghum, and mungbean, the agronomic parameters of these crops were recorded. Hopefully, all increased with jantar treatment when compared with controls. The benefit: cost ratio and physicochemical characteristics of the soil before and after the crop harvest were also calculated.

Keywords: benifit cost ratio, jantar, sunflower, rice, wheat

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Authors: Jian Cao

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This paper describes a novel watermarking technique which we call the random direction embedding (RDE) watermarking. Unlike traditional watermarking techniques, the watermark energy after the RDE embedding does not focus on a fixed direction, leading to the security against the traditional unauthorized watermark removal attack. In addition, the experimental results show that when compared with the existing secure watermarking, namely natural watermarking (NW), the RDE watermarking gains significant improvement in terms of robustness. In fact, the security of the RDE watermarking is not at the cost of low robustness, and it can even achieve more robust than the traditional spread spectrum watermarking, which has been shown to be very insecure.

Keywords: robustness, spread spectrum watermarking, watermarking security, random direction embedding (RDE)

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Authors: Christos Spandonidis, Stefanos Tsantilas, Elias Sedikos, Nektarios Galiatsatos, Fotios Giannopoulos, Panagiotis Papadopoulos, Nikolaos Demagos, Dimitrios Reppas, Christos Giordamlis

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In the present paper, a low cost, compact and modular Internet of Things (IoT) platform for air quality monitoring in urban areas is presented. This platform comprises of dedicated low cost, low power hardware and the associated embedded software that enable measurement of particles (PM2.5 and PM10), NO, CO, CO₂ and O₃ concentration in the air, along with relative temperature and humidity. This integrated platform acts as part of a greater air pollution data collecting wireless network that is able to monitor the air quality in various regions and neighborhoods of an urban area, by providing sensor measurements at a high rate that reaches up to one sample per second. It is therefore suitable for Big Data analysis applications such as air quality forecasts, weather forecasts and traffic prediction. The first real world test for the developed platform took place in Thessaloniki, Greece, where 16 devices were installed in various buildings in the city. In the near future, many more of these devices are going to be installed in the greater Thessaloniki area, giving a detailed air quality map of the city.

Keywords: distributed sensor system, environmental monitoring, Internet of Things, smart cities

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Authors: P. Vanichkobchinda

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The Logistics Transportation techniques, Open Vehicle Routing (OVR) is an approach toward transportation cost reduction, especially for long distance pickup and delivery nodes. The outstanding characteristic of OVR is that the route starting node and ending node are not necessary the same as in typical vehicle routing problems. This advantage enables the routing to flow continuously and the vehicle does not always return to its home base. This research aims to develop a heuristic for the open vehicle routing problem with pickup and delivery under time window and loading capacity constraints to minimize the total distance. The proposed heuristic is developed based on the Insertion method, which is a simple method and suitable for the rapid calculation that allows insertion of the new additional transportation requirements along the original paths. According to the heuristic analysis, cost comparisons between the proposed heuristic and companies are using method, nearest neighbor method show that the insertion heuristic. Moreover, the proposed heuristic gave superior solutions in all types of test problems. In conclusion, the proposed heuristic can effectively and efficiently solve the open vehicle routing. The research indicates that the improvement of new transport's calculation and the open vehicle routing with "Insertion Heuristic" represent a better outcome with 34.3 percent in average. in cost savings. Moreover, the proposed heuristic gave superior solutions in all types of test problems. In conclusion, the proposed heuristic can effectively and efficiently solve the open vehicle routing.

Keywords: business competitiveness, cost reduction, SMEs, logistics transportation, VRP

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Authors: Mahshid Hatamzad, Geanette Polanco

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Improving the performance of Winter Road Maintenance (WRM) can increase the traffic safety and reduce the cost as well as environmental impacts. This study evaluates the efficiency of WRM technique, named salting, in the Arctic area by using Data Envelopment Analysis (DEA), which is a non-parametric linear method to measure the efficiencies of decision-making units (DMUs) based on handling multiple inputs and multiple outputs at the same time that their associated weights are not known. Here, roads are considered as DMUs for which the efficiency must be determined. The three input variables considered are traffic flow, road area and WRM cost. In addition, the two output variables included are level of safety in the roads and environment impacts resulted from WRM, which is also considered as an uncontrollable factor in the second scenario. The results show the performance of DMUs from the most efficient WRM to the inefficient/least efficient one and this information provides decision makers with technical support and the required suggested improvements for inefficient WRM, in order to achieve a cost-effective WRM and a safe road transportation during wintertime in the Arctic areas.

Keywords: environmental impacts, DEA, risk and safety, WRM

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Authors: Soebowo Musa

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Mining industries are known to be very volatile due to their sensitive nature toward changes in the environment, particularly coal mining. Heavy equipment distributors and coal mining contractors are among heavily affected by such volatility. They are facing more uncertainty on the sustainability of the coal mining industry. Strategic alliances and organizational capabilities such as innovation capability have long been seen as ways to stay competitive with a focus more on the strategic alliances partner-to-partner in serving their customers. In today’s rapid change in the environment, a shift in consumer behaviors, and the human-centric business approach, this study looks at the strategic alliance partner-to-customer relationship in both the industrial organization and resource-based theories. This study was conducted based on 250 respondents from the strategic alliances partner-to-customer between heavy equipment distributors and coal mining contractors in Indonesia. This study finds strategic alliances have the highest association toward cost reduction, a proxy of operational efficiency followed by its association toward innovation capability. Further, strategic alliances and innovation capability have a positive relationship with customer loyalty, while innovation capability and customer loyalty have no significant relationships toward the firm’s competitive advantage. This study also indicates that cost reduction is not a condition to develop customer loyalty in the strategic alliance partner-to-customer relationship. It confirms strategic alliances are a strategy that creates a firm’s operational efficiency, innovation capability that develops customer loyalty, and competitive advantage.

Keywords: strategic alliance, innovation capability, cost reduction, customer loyalty, competitive advantage

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Authors: Felipa De Mello-Sampayo

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Background: The aim of this study is to undertake, from a patient perspective, an economic analysis of presurgical teledermatology, comparing it with a conventional referral system. Store-and-forward teledermatology allows surgical planning, saving both time and number of visits involving travel, thereby reducing patients’ out-of-pocket expenses, i.e., costs that patients incur when traveling to and from health providers for treatment, visits’ fees, and the opportunity cost of time spent in visits. Method: Patients’ out-of-pocket expenses-effectiveness of presurgical teledermatology were analyzed in the setting of a public hospital during two years. The mean delay in surgery was used to measure effectiveness. The teledermatology network covering the area served by the Hospital Garcia da Horta (HGO), Portugal, linked the primary care centers of 24 health districts with the hospital’s dermatology department. The patients’ opportunity cost of visits, travel costs, and visits’ fee of each presurgical modality (teledermatology and conventional referral), the cost ratio between the most and least expensive alternative, and the incremental cost-effectiveness ratio were calculated from initial primary care visit until surgical intervention. Two groups of patients: those with squamous cell carcinoma and those with basal cell carcinoma were distinguished in order to compare the effectiveness according to the dermatoses. Results: From a patient perspective, the conventional system was 2.15 times more expensive than presurgical teledermatology. Teledermatology had an incremental out-of-pocket expenses-effectiveness ratio of €1.22 per patient and per day of delay avoided. This saving was greater in patients with squamous cell carcinoma than in patients with basal cell carcinoma. Conclusion: From a patient economic perspective, teledermatology used for presurgical planning and preparation is the dominant strategy in terms of out-of-pocket expenses-effectiveness than the conventional referral system, especially for patients with severe dermatoses.

Keywords: economic analysis, out-of-pocket expenses, opportunity cost, teledermatology, waiting time

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Authors: Tony Cripps, Larry Kimber

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This paper will begin by briefly explaining how blockchain technology works. Then, after highlighting a few of the ways it promises to heavily impact all aspects of the digital landscape, the focus will shift to Blockchain in the field of education, with specific emphasis placed on practical applications in foreign language education. Blockchain is a decentralized Internet-based software application that guarantees truth in transactions. This means whenever two parties engage in a transaction using Blockchain, it is time-stamped, added to a block of other transactions, and then permanently attached to an unalterable ‘chain’ of blocks. The potential for developing applications with Blockchain is therefore immense, since software systems that ensure the impossibility of outside tampering are invaluable. Innovative ideas in every imaginable domain are presently being entertained and Blockchain in education is no exception. For instance, records kept within and between institutions of students’ grade performance, academic achievement and verification of assignment/course completion are just a few examples of how this new technology might potentially be used to revolutionize education. It is hoped that this paper will be of use to all educators interested in the application of technology in the field of education.

Keywords: blockchain, disruption, potential, technology

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Authors: Ochuko K. Overen, Edson L. Meyer

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Uncontrolled heat transfer between the inner and outer space of low-cost housings through the thermal envelope result in indoor thermal discomfort. As a result, an excessive amount of energy is consumed for space heating and cooling. Thermo-optical properties are the ability of paints to reduce the rate of heat transfer through the thermal envelope. The aim of this study is to analyze the thermal performance of a low-cost house with its walls inner surface coated with transparent infrared reflective paint. The thermo-optical properties of the paint were analyzed using Scanning Electron Microscopy/ Energy Dispersive X-ray spectroscopy (SEM/EDX), Fourier Transform Infra-Red (FTIR) and thermal photographic technique. Meteorological indoor and ambient parameters such as; air temperature, relative humidity, solar radiation, wind speed and direction of a low-cost house in Golf-course settlement, South Africa were monitored. The monitoring period covers both winter and summer period before and after coating. The thermal performance of the coated walls was evaluated using time lag and decrement factor. The SEM image shows that the coat is transparent to light. The presence of Al as Al2O and other elements were revealed by the EDX spectrum. Before coating, the average decrement factor of the walls in summer was found to be 0.773 with a corresponding time lag of 1.3 hours. In winter, the average decrement factor and corresponding time lag were 0.467 and 1.6 hours, respectively. After coating, the average decrement factor and corresponding time lag were 0.533 and 2.3 hour, respectively in summer. In winter, an average decrement factor of 1.120 and corresponding time lag of 3 hours was observed. The findings show that the performance of the coats is influenced by the seasons. With a 74% reduction in decrement factor and 1.4 time lag increase in winter, it implies that the coatings have more ability to retain heat within the inner space of the house than preventing heat flow into the house. In conclusion, the results have shown that transparent infrared reflective paint has the ability to reduce the propagation of heat flux through building walls. Hence, it can serve as a remedy to the poor thermal performance of low-cost housings in South Africa.

Keywords: energy efficiency, decrement factor, low-cost housing, paints, rural development, thermal comfort, time lag

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Authors: Ganiyat Soliu, Glen Bright, Chiemela Onunka

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Performance optimization plays a key role in controlling the waiting time during manufacturing in an advanced manufacturing environment to improve productivity. Queuing mathematical modeling theory was used to examine the performance of the multi-stage production line. Robotics as a disruptive technology was implemented into a virtual manufacturing scenario during the packaging process to study the effect of waiting time on productivity. The queuing mathematical model was used to determine the optimum service rate required by robots during the packaging stage of manufacturing to yield an optimum production cost. Different rates of production were assumed in a virtual manufacturing environment, cost of packaging was estimated with optimum production cost. An equation was generated using queuing mathematical modeling theory and the theorem adopted for analysis of the scenario is the Newton Raphson theorem. Queuing theory presented here provides an adequate analysis of the number of robots required to regulate waiting time in order to increase the number of output. Arrival rate of the product was fast which shows that queuing mathematical model was effective in minimizing service cost and the waiting time during manufacturing. At a reduced waiting time, there was an improvement in the number of products obtained per hour. The overall productivity was improved based on the assumptions used in the queuing modeling theory implemented in the virtual manufacturing scenario.

Keywords: performance optimization, productivity, queuing theory, robotics

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Authors: Ali Youniss Aidbaiss, G. Unnikrishnan, Anoob Hakim

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Scope changes, scope creeps, cost and time overruns have become common in projects in the oil and gas sector. Even in repetitive projects, failure to implement lessons learnt and correct past mistakes have resulted in various setbacks. This paper describes the concept of reusing successfully implemented design packages as templates for repetitive projects, and thereby lowering the instances of project failures. Units or systems successfully installed in projects can be identified and taken up for preparing template design packages. Standardization of units and systems helps to develop templates from successful designs which can be repeatedly used with confidence. These packages can be used with minimum modifications for developing FEED packages faster, saving cost and other valuable resources. Lessons learnt from the completed project incorporated in the templates avoid repeating past mistakes during detailed design, procurement and execution. With template packages, consistent quality can be maintained for similar projects, avoiding scope creep and scope changes which will ultimately result in cost and time savings.

Keywords: engineering work package, repetitive construction, template design package, time saving in projects

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Authors: Muhammad Abdullah, Muhammad Atiq Ur Rehman Tariq, Faraz Ul Haq

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In developed countries, sustainability measures are widely accepted and acknowledged as crucial for addressing environmental concerns. Hydroponics, a soilless cultivation technique, has emerged as a potentially sustainable solution as it can reduce water consumption, land use, and environmental impacts. However, hydroponics may not be economically viable, especially when using reclaimed water, which may entail additional costs and risks. This study aims to address the critical question of whether hydroponics using reclaimed water can achieve a balance between sustainability and financial viability. Life Cycle Assessment (LCA) and Life Cycle Cost (LCC) will be integrated to assess the potential of hydroponics whether it is environmentally sustainable and economically viable. Life cycle assessment, or LCA, is a methodology for assessing environmental impacts associated with all the stages of the life cycle of a commercial product, process, or service. While Life Cycle Cost (LCC) is an approach that assesses the total cost of an asset over its life cycle, including initial capital costs and maintenance costs. The expected benefits of this study include supporting evidence-based decision-making for policymakers, farmers, and stakeholders involved in agriculture. By quantifying environmental impacts and economic costs, this research will facilitate informed choices regarding the adoption of hydroponics with reclaimed water. It is believed that the outcomes of this research work will help to achieve a sustainable approach to agricultural production, aligning with sustainability goals while considering economic factors by adopting hydroponic technique.

Keywords: hydroponic, life cycle assessment, life cycle cost, sustainability

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Authors: Ünal Kızıl, Levent Genç, Sefa Aksu, Ahmet Tapınç

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The Figaro AM-1 sensor module which employs TGS 2600 model gas sensor in air quality assessment was used. The system was coupled with a microprocessor that enables sensor module to create warning message via telephone. This low cot sensor system’s performance was compared with a Diagnose II commercial electronic nose system. Both air quality sensor and electronic nose system employ metal oxide chemical gas sensors. In the study experimental setup, data acquisition methods for electronic nose system, and performance of the low cost air quality system were evaluated and explained.

Keywords: air quality, electronic nose, environmental quality, gas sensor

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Authors: Hideaki Endo, Mika Goto

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The global outbreak of the COVID-19 pandemic has seriously affected railway businesses. The number of railway passengers decreased due to the decline in the number of commuters and business travelers to avoid crowded trains and a sharp drop in inbound tourists visiting Japan. This has affected not only railway businesses but also related businesses, including hotels, leisure businesses, and retail businesses at station buildings. In 2021, the companies were divided into profitable and loss-making companies. This division suggests that railway companies, particularly loss-making companies, needed to decrease operational inefficiency. To measure the impact of COVID-19 and discuss the sustainable management strategies of railway companies, we examine the cost inefficiency of Japanese listed railway companies by applying stochastic frontier analysis (SFA) to their operational and financial data. First, we employ the stochastic frontier cost function approach to measure inefficiency. The cost frontier function is formulated as a Cobb–Douglas type, and we estimated parameters and variables for inefficiency. This study uses panel data comprising 26 Japanese-listed railway companies from 2005 to 2020. This period includes several events deteriorating the business environment, such as the financial crisis from 2007 to 2008 and the Great East Japan Earthquake of 2011, and we compare those impacts with those of the COVID-19 pandemic after 2020. Second, we identify the characteristics of the best-practice railway companies and examine the drivers of cost inefficiencies. Third, we analyze the factors influencing cost inefficiency by comparing the profiles of the top 10 railway companies and others before and during the pandemic. Finally, we examine the relationship between cost inefficiency and the implementation of efficiency measures for each railway company. We obtained the following four findings. First, most Japanese railway companies showed the lowest cost inefficiency (most efficient) in 2014 and the highest in 2020 (least efficient) during the COVID-19 pandemic. The second worst occurred in 2009 when it was affected by the financial crisis. However, we did not observe a significant impact of the 2011 Great East Japan Earthquake. This is because no railway company was influenced by the earthquake in this operating area, except for JR-EAST. Second, the best-practice railway companies are KEIO and TOKYU. The main reason for their good performance is that both operate in and near the Tokyo metropolitan area, which is densely populated. Third, we found that non-best-practice companies had a larger decrease in passenger kilometers than best-practice companies. This indicates that passengers made fewer long-distance trips because they refrained from inter-prefectural travel during the pandemic. Finally, we found that companies that implement more efficiency improvement measures had higher cost efficiency and they effectively used their customer databases through proactive DX investments in marketing and asset management.

Keywords: COVID-19 pandemic, stochastic frontier analysis, railway sector, cost efficiency

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Authors: M. A. Fouad, M. A. Badr, Z. S. Abd El-Rehim, Taher Halawa, Mahmoud Bayoumi, M. M. Ibrahim

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Renewable energy-based micro-grids are presently attracting significant consideration. The smart grid system is presently considered a reliable solution for the expected deficiency in the power required from future power systems. The purpose of this study is to determine the optimal components sizes of a micro-grid, investigating technical and economic performance with the environmental impacts. The micro grid load is divided into two small factories with electricity, both on-grid and off-grid modes are considered. The micro-grid includes photovoltaic cells, back-up diesel generator wind turbines, and battery bank. The estimated load pattern is 76 kW peak. The system is modeled and simulated by MATLAB/Simulink tool to identify the technical issues based on renewable power generation units. To evaluate system economy, two criteria are used: the net present cost and the cost of generated electricity. The most feasible system components for the selected application are obtained, based on required parameters, using HOMER simulation package. The results showed that a Wind/Photovoltaic (W/PV) on-grid system is more economical than a Wind/Photovoltaic/Diesel/Battery (W/PV/D/B) off-grid system as the cost of generated electricity (COE) is 0.266 $/kWh and 0.316 $/kWh, respectively. Considering the cost of carbon dioxide emissions, the off-grid will be competitive to the on-grid system as COE is found to be (0.256 $/kWh, 0.266 $/kWh), for on and off grid systems.

Keywords: renewable energy sources, micro-grid system, modeling and simulation, on/off grid system, environmental impacts

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Authors: Assad Rashid, Umair Ahmed, Zafar Baig

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A new trend in construction is widely influenced by the use of Steel-Concrete Composite Columns. The rapid growth in Steel-Concrete Composite construction has widely decreased the conventional R.C.C structures. Steel Concrete composite construction has obtained extensive receiving around the globe. It is considering the fact that R.C.C structures construction is most suitable and economical for low-rise construction, so it is used in farming systems in most of the buildings. However, increased dead load, span restriction, less stiffness and risky formwork make R.C.C construction uneconomical and not suitable when it comes to intermediate to high-rise buildings. A Base + Ground +11 storey commercial building was designed on ETABS 2017 and made a comparison between conventional R.C.C and encased composite column structure. After performing Equivalent Static non-linear analysis, it has been found that construction cost is 13.01% more than R.C.C structure but encased composite column building has 7.7% more floor area. This study will help in understanding the behavior of conventional R.C.C structure and Encased Composite column structure.

Keywords: composite columns structure, equivalent static non-linear analysis, comparison between R.C.C and encased composite column structures, cost-effective structure

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Authors: Anita Setianingrum, Oki S. Jaya, Zuherman Rustam

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Forecasting stock price is a challenging task due to the complex time series of the data. The complexity arises from many variables that affect the stock market. Many time series models have been proposed before, but those previous models still have some problems: 1) put the subjectivity of choosing the technical indicators, and 2) rely upon some assumptions about the variables, so it is limited to be applied to all datasets. Therefore, this paper studied a novel Adaptive Neuro-Fuzzy Inference System (ANFIS) time series model based on Support Vector Regression (SVR) for forecasting the stock market. In order to evaluate the performance of proposed models, stock market transaction data of TAIEX and HIS from January to December 2015 is collected as experimental datasets. As a result, the method has outperformed its counterparts in terms of accuracy.

Keywords: ANFIS, fuzzy time series, stock forecasting, SVR

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Authors: Bentoutou Houari, Boutte Aissa, Belaidi El Yazid, Limam Lakhdar

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The integration of a load switch with a DC/DC buck converter using LM2596 for power distribution in low-cost educational nanosatellites is a technique that aims to efficiently manage the power distribution system in these small spacecraft. The converter is based on the LM2596 regulator and designed to step down the input voltage of +16.8V to +12V, +5V, and +3.3V output, which are suitable for the nanosatellite's various subsystems. The load switch is based on MOSFET and is used to turn on or off the power supply to a particular load and protect the nanosatellite from power surges. A prototype of a +12V DC/DC buck converter with a high side load switch has been realized and tested, which meets our requirements and shows a good efficiency of 89%. In addition, the prototype features a capacitor between the source and gate of the MOSFET, which has effectively reduced the inrush current, demonstrating the effectiveness of this approach in reducing surges of current when the load is connected. The output current and voltage were measured at 0.7A and 11.89V, respectively, making this design suitable for use in low-cost educational nanosatellites.

Keywords: DC/DC buck converter, load switch, LM2596, electrical power subsystems, nanosatellite, inrush current

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Authors: Maryam Safarirad

Abstract:

Fast and increasing growth of electronic commerce (e-commerce) in developed countries and its resulting competitive advantages mean that those countries should revise dramatically their trade and commercial strategies and policies. Regarding the importance of food industry in Iran, the current paper studies the feasibility of implementing the e-commerce system in Shiraz’s petrochemical unit. The statistical population of the study includes 29 senior managers and experts of the food industries. In the present Feasibility study of implementing electronic commerce 249 research, senior managers and experts’ opinions on feasibility have been examined and some feedbacks have resulted in from the opinions. The current research concludes that the organization under study does not have favorable state either in software or in hardware. Implementation of the e-commerce system in food industries would reduce the average value of the transaction costs.

Keywords: electronic trading, electronic commerce, electronic exchange of information, feasibility study, information technology, virtual shopping, computer networks, electronic commerce laws, food industry

Procedia PDF Downloads 397

Authors: Scott A. Abbott

Abstract:

This paper examines the increase in the occurrence of natural disasters worldwide and the need to support vulnerable communities in post-disaster recovery. Preparation and implementation of post-disaster recovery projects need to be improved to allow communities to recover infrastructure, housing, economically and socially following a catastrophe. With the continual rise in catastrophic events worldwide due to climate change, impacts on construction resources affect the ability for post-disaster recovery to be undertaken. This research focuses on case studies of catastrophic events in Queensland, Australia, to contribute to the body of knowledge and gain valuable insights on lessons learned from past events and how they have been managed. The aim of this research is to adopt qualitative data using semi-structured interviews from participants predominantly from the insurance sector to understand barriers that have previously and currently exist in post-disaster recovery. Existing literature was reviewed to reveal gaps in knowledge that needed to be tested. Qualitative data was collected and summarised from field research with the results analysed and discussed. Barriers that impacted post-disaster recovery included time, cost, and resource capability and capacity. Causal themes that impacted time and cost were identified as decision making, pre-planning, and preparedness, as well as effective communication across stakeholders. The research study applied a qualitative approach to the existing literature and case studies across Queensland, Australia, to identify existing and new barriers that impact post-disaster recovery. It was recommended to implement effective procurement strategies to assist in cost control; implement pre-planning and preparedness strategies across funder, contractor, and local governments; more effective and timely decision making to reduce time and cost impacts.

Keywords: construction recovery, cost, disaster recovery, resources, time

Procedia PDF Downloads 112

Authors: Adel A. Ghobbar

Abstract:

The airline industry is continuously challenging how to safely increase the service life of the aircraft with limited maintenance budgets. Operators are looking for the most qualified maintenance providers of aircraft components, offering the finest customer service. Component owner and maintenance provider is offering an Abacus agreement (Aircraft Component Leasing) to increase the efficiency and productivity of the customer service. To increase the customer service, the current focus on No Fault Found (NFF) units must change into the focus on Early Failure (EF) units. Since the effect of EF units has a significant impact on customer satisfaction, this needs to increase the reliability of EF units at minimal cost, which leads to the goal of this paper. By identifying the reliability of early failure (EF) units with regards to No Fault Found (NFF) units, in particular, the root cause analysis with an integrated cost analysis of EF units with the use of a failure mode analysis tool and a cost model, there will be a set of EF maintenance improvements. The data used for the investigation of the EF units will be obtained from the Pentagon system, an Enterprise Resource Planning (ERP) system used by Fokker Services. The Pentagon system monitors components, which needs to be repaired from Fokker aircraft owners, Abacus exchange pool, and commercial customers. The data will be selected on several criteria’s: time span, failure rate, and cost driver. When the selected data has been acquired, the failure mode and root cause analysis of EF units are initiated. The failure analysis approach tool was implemented, resulting in the proposed failure solution of EF. This will lead to specific EF maintenance improvements, which can be set-up to decrease the EF units and, as a result of this, increasing the reliability. The investigated EFs, between the time period over ten years, showed to have a significant reliability impact of 32% on the total of 23339 unscheduled failures. Since the EFs encloses almost one-third of the entire population.

Keywords: supportability, no fault found, FMEA, early failure, availability, operational reliability, predictive model

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Authors: Malaw Ndiaye, Karim Konate

Abstract:

Smart contracts are computer protocols that facilitate, verify, and execute the negotiation or execution of a contract, or that render a contractual term unnecessary. Blockchain and smart contracts can be used to facilitate almost any financial transaction. Thanks to these smart contracts, the settlement of dividends and coupons could be automated. Smart contracts have become lucrative and profitable targets for attackers because they can hold a great amount of money. Smart contracts, although widely used in blockchain technology, are far from perfect due to security concerns. Since there are recent studies on smart contract security, none of them systematically study the strengths and weaknesses of smart contract security. Some have focused on an analysis of program-related vulnerabilities by providing a taxonomy of vulnerabilities. Other studies are responsible for listing the series of attacks linked to smart contracts. Although a series of attacks are listed, there is a lack of discussions and proposals on improving security. This survey takes stock of smart contract security from a more comprehensive perspective by correlating the level of vulnerability and systematic review of security levels in smart contracts.

Keywords: blockchain, Bitcoin, smart contract, criminal smart contract, security

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Authors: Siriwan Saksiriruthai

Abstract:

This paper reviews and analyzes impact of foreign migration on innovation for Thailand. With the analysis of decades of industrial and economic development, Thailand has attracted investment by providing cheap labor and low cost of production. Foreign migrant substantially contribute to the development by supplying lower wages with low-skilled workers. However, it is revealed that foreign low-skilled labor influx has a negative effect on innovation. Firms concentrate on benefits from low cost of production and are not motivated to invest for innovation. Therefore, with the emerging of new economies where lower wage laborers are offered, Thailand has to promote innovation to maintain economic development sustainability.

Keywords: migration, innovation, Thailand, foreign

Procedia PDF Downloads 355