Search results for: transformal operators

Authors: Bruno de Almeida Vilela, Heinz Ahn, Ana Lúcia Miranda Lopes, Marcelo Azevedo Costa

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Benchmarking public utilities such as transmission system operators (TSOs) is one of the main strategies employed by regulators in order to fix monopolistic companies’ revenues. Since 2007 the Brazilian regulator has been utilizing Data Envelopment Analysis (DEA) to benchmark TSOs. Despite the application of DEA to improve the transmission sector’s efficiency, some problems can be pointed out, such as the high price of electricity in Brazil; the limitation of the benchmarking only to operational expenses (OPEX); the absence of variables that represent the outcomes of the transmission service; and the presence of extremely low and high efficiencies. As an alternative to the current concept of benchmarking the Brazilian regulator uses, we propose a goal-oriented approach. Our proposal supports input/output selection by taking traditional organizational goals and measures as a basis for the selection of factors for benchmarking purposes. As the main advantage, it resolves the classical DEA problems of input/output selection, undesirable and dual-role factors. We also provide a demonstration of our goal-oriented concept regarding service quality. As a result, most TSOs’ efficiencies in Brazil might improve when considering quality as important in their efficiency estimation.

Keywords: decision making, goal-oriented benchmarking, input/output factor determination, TSO regulation

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Authors: Yosia Mulumba, Klaus Schmidt

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Financial Inclusion is considered a key pillar for development in most countries around the world. Access to affordable financial services in a country’s economy can be a driver to overcome poverty and reduce income inequalities, and thus increase economic growth. Nevertheless, the number of financially excluded populations in developing countries continues to be very high. This paper explores the role of Financial Technology (Fintech) as a key driver for achieving financial inclusion in developing countries post the COVID-19 pandemic with an emphasis on four East African countries: Kenya, Tanzania, Uganda, and Rwanda. The research paper is inspired by the positive disruption caused by the pandemic, which has compelled societies in East Africa to adapt and embrace the use of financial technology innovations, specifically Mobile Money Services (MMS), to access financial services. MMS has been further migrated and integrated with other financial technology innovations such as Mobile Banking, Micro Savings, and Loans, and Insurance, to mention but a few. These innovations have been adopted across key sectors such as commerce, health care, or agriculture. The research paper will highlight the Mobile Network Operators (MNOs) that are behind MMS, along with numerous innovative products and services being offered to the customers. It will also highlight the regulatory framework under which these innovations are being governed to ensure the safety of the customers' funds.

Keywords: financial inclusion, financial technology, regulatory framework, mobile money services

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Authors: Robbie C. Murchison, Ibrahim Küçükdemiral, Andrew Cowell

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Thermal effects are the largest source of dimensional error in precision machining, and a major proportion is caused by ambient temperature variation. The use of coolant is a primary means of mitigating these effects, but there has been limited work on coolant temperature control. This research critically explored whether CNC-machine coolant refrigeration systems adapted to actively compensate for ambient temperature variation could increase machining accuracy. Accuracy data were collected from operators’ checklists for a CNC 5-axis mill and statistically reduced to bias and precision metrics for observations of one day over a sample period of 27 days. Temperature data were collected using three USB dataloggers in ambient air, the chiller inflow, and the chiller outflow. The accuracy and temperature data were analysed using Pearson correlation, then the thermodynamics of the system were described using system identification with MATLAB. It was found that 75% of thermal error is reflected in the hot coolant temperature but that this is negligibly dependent on ambient temperature. The effect of the coolant refrigeration process on hot coolant outflow temperature was also found to be negligible. Therefore, the evidence indicated that it would not be beneficial to adapt coolant chillers to compensate for ambient temperature variation. However, it is concluded that hot coolant outflow temperature is a robust and accessible source of thermal error data which could be used for prevention strategy evaluation or as the basis of other thermal error strategies.

Keywords: CNC manufacturing, machine-tool, precision machining, thermal error

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Authors: Patrick Cummings, Laura Cassani, Deirdre Kelliher

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In this paper we present findings from a research effort to apply a hybrid collaborative-context approach for a system focused on Marine Corps civil affairs data collection, aggregation, and analysis called the Marine Civil Information Management System (MARCIMS). The goal of this effort is to provide operators with information to make sense of the interconnectedness of entities and relationships in their area of operation and discover existing data to support civil military operations. Our approach to build a recommendation engine was designed to overcome several technical challenges, including 1) ensuring models were robust to the relatively small amount of data collected by the Marine Corps civil affairs community; 2) finding methods to recommend novel data for which there are no interactions captured; and 3) overcoming confirmation bias by ensuring content was recommended that was relevant for the mission despite being obscure or less well known. We solve this by implementing a combination of collective matrix factorization (CMF) and graph-based random walks to provide recommendations to civil military operations users. We also present a method to resolve the challenge of computation complexity inherent from highly connected nodes through a precomputed process.

Keywords: Recommendation engine, collaborative filtering, context based recommendation, graph analysis, coverage, civil affairs operations, Marine Corps

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Authors: Haruna Abdu Usman, Bashir Usman Mohammed, Mohammed Umar Jamil

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Municipal solid waste management constitutes a serious problem bedeviling environmental protection agencies in many cities of developing countries. Most agencies do not collect the totality of the waste generated in their cities. This study presents the current solid waste management practices and problems in Bauchi metropolis, Bauchi state Nigeria. The general feature is characterized by inefficient, insufficient and irrational collection and improper disposal alternatives. The consequent environmental effects of these problems depict clogged city drains, uncollected heap of waste on road sides of residential areas, vacant plots and uncompleted buildings and highways. This contributes immensely to flooding in the city. The major challenges facing the state environmental protection agency includes; lack of collection and disposal points, technical and institutional arrangements, financial resources and general attitude of the serving public among others. The study suggested a comprehensive and integrated approach to the solid waste management which recognizes and incorporates the interventionist role of the state government, the private formal and informal waste management operators and the serving public.

Keywords: municipal solid waste, bauchi metropolitan area, environmental protection agency, solid waste management, waste disposal

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Authors: Lukumba Phiri, Simon Tembo, Kumbuso Joshua Nyoni

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In Zambia recent initiatives by various power operators like ZESCO, CEC, and consumers like the mines to upgrade power systems into smart grids target an even tighter integration with information technologies to enable the integration of renewable energy sources, local and bulk generation, and demand response. Thus, for the reliable operation of smart grids, its information infrastructure must be secure and reliable in the face of both failures and cyberattacks. Due to the nature of the systems, ICS/SCADA cybersecurity and governance face additional challenges compared to the corporate networks, and critical systems may be left exposed. There exist control frameworks internationally such as the NIST framework, however, there are generic and do not meet the domain-specific needs of the SCADA systems. Zambia is also lagging in cybersecurity awareness and adoption, therefore there is a concern about securing ICS controlling key infrastructure critical to the Zambian economy as there are few known facts about the true posture. In this paper, we introduce a stochastic Edged-based Anomaly Detection for SCADA systems (SEADS) framework for threat modeling and risk assessment. SEADS enables the calculation of steady-steady probabilities that are further applied to establish metrics like system availability, maintainability, and reliability.

Keywords: anomaly, availability, detection, edge, maintainability, reliability, stochastic

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Authors: Ming-Yang Guo, Cheng-Xian Wu, Wei-Xiang Chen, Chun-Yuan Lin, Yen-Jen Lin, Ann-Shyn Chiang

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With more and more Drosophila Driver and Neuron images, it is an important work to find the similarity relationships among them as the functional inference. There is a general problem that how to find a Drosophila Driver image, which can cover a set of Drosophila Driver/Neuron images. In order to solve this problem, the intersection/union region for a set of images should be computed at first, then a comparison work is used to calculate the similarities between the region and other images. In this paper, three encoding schemes, namely Integer, Boolean, Decimal, are proposed to encode each image as a one-dimensional structure. Then, the intersection/union region from these images can be computed by using the compare operations, Boolean operators and lookup table method. Finally, the comparison work is done as the union region computation, and the similarity score can be calculated by the definition of Tanimoto coefficient. The above methods for the region computation are also implemented in the multi-core CPUs environment with the OpenMP. From the experimental results, in the encoding phase, the performance by the Boolean scheme is the best than that by others; in the region computation phase, the performance by Decimal is the best when the number of images is large. The speedup ratio can achieve 12 based on 16 CPUs. This work was supported by the Ministry of Science and Technology under the grant MOST 106-2221-E-182-070.

Keywords: Drosophila driver image, Drosophila neuron images, intersection/union computation, parallel processing, OpenMP

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Authors: Sanpetchuda Krutkrua, Suphawatchara Malanond

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Throughout the history of Antitrust regimes in Thailand, Thailand has been trying to prevent collusive practices in the market through the amendments of the Trade Competition Act, and Thailand just passed the current Trade Competition Act of B.E. 2560 in 2017 of which several aspects of the law were amended in order to enhance the prevention of collusive outcome through both vertical trade restraints and horizontal trade restraints. An agreement is vertical when it involves arrangements that are in a complementary relationship. In Section 55 of the Act, any agreements to reduce the price, quantity, or quality of the goods, agreements to assign a sole retailer for the goods, and the agreement to impose conditions on the retailers are not allowed. However, Section 56 provides exemptions for the vertical relationship between the business operators, the franchise agreement, and the licensing agreement as long as such agreements do not surpass the necessity to do so, create monopolization, or affect the consumers in terms of price, quality, quantity, or options. The paper aims to explore the extent of the exemption under Section 56 and sequential regulations in terms of the vertical trade restraints regarding intellectual property licensing, and, at the same time, compare with the exemptions under the European Union competition law, and Singapore competition law. Comparative legal analysis with leading jurisdiction will illustrate the application of the newly enacted Thai Competition Act in terms of its enforcement in the global impact of IP rights, which, by nature are de jure or de facto international protection.

Keywords: antitrust, competition law, vertical restraint, intellectual property, IP licensing

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Authors: Volker Wannack

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Regional, national, and international strategies focusing on hydrogen (H₂) and blockchain are driving significant advancements in hydrogen and blockchain technology worldwide. These strategies lay the foundation for the groundbreaking "Blockchain Based Hydrogen Market (BBH₂)" project. The primary goal of this project is to develop a functional Blockchain Minimum Viable Product (B-MVP) for the hydrogen market. The B-MVP will leverage blockchain as an enabling technology with a common database and platform, facilitating secure and automated transactions through smart contracts. This innovation will revolutionize logistics, trading, and transactions within the hydrogen market. The B-MVP has transformative potential across various sectors. It benefits renewable energy producers, surplus energy-based hydrogen producers, hydrogen transport and distribution grid operators, and hydrogen consumers. By implementing standardized, automated, and tamper-proof processes, the B-MVP enhances cost efficiency and enables transparent and traceable transactions. Its key objective is to establish the verifiable integrity of climate-friendly "green" hydrogen by tracing its supply chain from renewable energy producers to end users. This emphasis on transparency and accountability promotes economic, ecological, and social sustainability while fostering a secure and transparent market environment. A notable feature of the B-MVP is its cross-border operability, eliminating the need for country-specific data storage and expanding its global applicability. This flexibility not only broadens its reach but also creates opportunities for long-term job creation through the establishment of a dedicated blockchain operating company. By attracting skilled workers and supporting their training, the B-MVP strengthens the workforce in the growing hydrogen sector. Moreover, it drives the emergence of innovative business models that attract additional company establishments and startups and contributes to long-term job creation. For instance, data evaluation can be utilized to develop customized tariffs and provide demand-oriented network capacities to producers and network operators, benefitting redistributors and end customers with tamper-proof pricing options. The B-MVP not only brings technological and economic advancements but also enhances the visibility of national and international standard-setting efforts. Regions implementing the B-MVP become pioneers in climate-friendly, sustainable, and forward-thinking practices, generating interest beyond their geographic boundaries. Additionally, the B-MVP serves as a catalyst for research and development, facilitating knowledge transfer between universities and companies. This collaborative environment fosters scientific progress, aligns with strategic innovation management, and cultivates an innovation culture within the hydrogen market. Through the integration of blockchain and hydrogen technologies, the B-MVP promotes holistic innovation and contributes to a sustainable future in the hydrogen industry. The implementation process involves evaluating and mapping suitable blockchain technology and architecture, developing and implementing the blockchain, smart contracts, and depositing certificates of origin. It also includes creating interfaces to existing systems such as nomination, portfolio management, trading, and billing systems, testing the scalability of the B-MVP to other markets and user groups, developing data formats for process-relevant data exchange, and conducting field studies to validate the B-MVP. BBH₂ is part of the "Technology Offensive Hydrogen" funding call within the research funding of the Federal Ministry of Economics and Climate Protection in the 7th Energy Research Programme of the Federal Government.

Keywords: hydrogen, blockchain, sustainability, innovation, structural change

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Authors: Ali Alavi, Hong-Oanh Nguyen, ‎Jiangang Fei, Jafar Sayareh

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The recent competitive market in the port sector highly depend on logistics practices, functions ‎and activities and seaports play a key role in port logistics chains. Despite the well-articulated importance of ports and terminals in integrated logistics, the role of success factors in port logistics integration has been rarely mentioned‎. The objective of this paper is to ‎fill this gap in the literature and provide an insight into how seaports and terminals may improve their logistics integration. First, a literature review of studies on logistics integration in seaports and terminals is conducted. Second, a new conceptual framework for port logistics integration is proposed to incorporate the role of the new variables emerging from the recent developments in the global business environment. Third, the model tested in Iranian port and maritime sector using self-administered and online survey among logistics chain actors in Iranian seaports such shipping line operators, logistics service providers, port authorities, logistics companies and other related actors. The results have found the logistics process and operations, information integration, ‎value-added services, and logistics practices being influential to logistics integration. A proposed conceptual framework is developed to extend the existing ‎framework and incorporates the variables namely organizational activities, resource ‎sharing, and institutional support.‎ Further examination of the proposed model across multiple contexts is necessary for the validity of the findings. The framework could be more detailed on each factor and consider actors perspective.

Keywords: maritime logistics‎, port integration‎, logistics integration‎, supply chain integration

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Authors: Egor Stadnichuk

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Relativistic runaway electron avalanches (RREA) are a widely accepted source of thunderstorm gamma-radiation. In regions with huge electric field strength, RREA can multiply via relativistic feedback. The relativistic feedback is caused both by positron production and by runaway electron bremsstrahlung gamma-rays reversal. In complex multilayer thunderstorm electric field structures, an additional reactor feedback mechanism appears due to gamma-ray exchange between separate strong electric field regions with different electric field directions. The study of this reactor mechanism in conjunction with the relativistic feedback with Monte Carlo simulations or by direct solution of the kinetic Boltzmann equation requires a significant amount of computational time. In this work, a theoretical approach to study feedback mechanisms in RREA physics is developed. It is based on the matrix of feedback operators construction. With the feedback matrix, the problem of the dynamics of avalanches in complex electric structures is reduced to the problem of finding eigenvectors and eigenvalues. A method of matrix elements calculation is proposed. The proposed concept was used to study the dynamics of RREAs in multilayer thunderclouds.

Keywords: terrestrial Gamma-ray flashes, thunderstorm ground enhancement, relativistic runaway electron avalanches, gamma-rays, high-energy atmospheric physics, TGF, TGE, thunderstorm, relativistic feedback, reactor feedback, reactor model

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Authors: Chih-Chieh Yang, Chung-Neng Huang

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In power system, how to improve the fault diagnosis technology of transmission line has always been the primary goal of power grid operators. In recent years, due to the rise of green energy, the addition of all kinds of distributed power also has an impact on the stability of the power system. Because the smart meters are with the function of data recording and bidirectional transmission, the adaptive Fuzzy Neural inference system, ANFIS, as well as the artificial intelligence that has the characteristics of learning and estimation in artificial intelligence. For transmission network, in order to avoid misjudgment of the fault type and location due to the input of these unstable power sources, combined with the above advantages of smart meter and ANFIS, a method for identifying fault types and location of faults is proposed in this study. In ANFIS training, the bus voltage and current information collected by smart meters can be trained through the ANFIS tool in MATLAB to generate fault codes to identify different types of faults and the location of faults. In addition, due to the uncertainty of distributed generation, a wind power system is added to the transmission network to verify the diagnosis correctness of the study. Simulation results show that the method proposed in this study can correctly identify the fault type and location of fault with more efficiency, and can deal with the interference caused by the addition of unstable power sources.

Keywords: ANFIS, fault diagnosis, power system, smart meter

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Authors: Syed Ahsan, Saleh Alshomrani, Ishtiaq Rasool, Ali Hassan

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In this oral presentation, we will provide an overview of the technical and semantic architecture of a desert border security and critical infrastructure protection security system. Modern border security systems are designed to reduce the dependability and intrusion of human operators. To achieve this, different types of sensors are use along with video surveillance technologies. Application of these technologies in a harsh desert environment of Saudi Arabia poses unique challenges. Environmental and geographical factors including high temperatures, desert storms, temperature variations and remoteness adversely affect the reliability of surveillance systems. To successfully implement a reliable, effective system in a harsh desert environment, the following must be achieved: i) Selection of technology including sensors, video cameras, and communication infrastructure that suit desert environments. ii) Reduced power consumption and efficient usage of equipment to increase the battery life of the equipment. iii) A reliable and robust communication network with efficient usage of bandwidth. Also, to reduce the expert bottleneck, an ontology-based intelligent information systems needs to be developed. Domain knowledge unique and peculiar to Saudi Arabia needs to be formalized to develop an expert system that can detect abnormal activities and any intrusion.

Keywords: border security, sensors, abnormal activity detection, ontologies

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Authors: Weerakarj Dokchan

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The purposes of this research are to find out the factors for developing trainers in the auto part manufacturing factories (AMF) in Amata Nakon Industrial Estate Cholburi. Population in this study included 148 operators to complete the questionnaires and 10 trainers to provide the information on the interview. The research statistics consisted of percentage, mean, standard deviation and step-wise multiple linear regression analysis.The analysis of the training model revealed that: The research result showed that the development factors of trainers in AMF consisted of 3 main factors and 8 sub-factors: 1) knowledge competency consisting of 4 sub-factors; arrangement of critical thinking, organizational loyalty, working experience of the trainers, analysis of behavior, and work and organization loyalty which could predict the success of the trainers at 55.60%. 2) Skill competency consisted of 4 sub-factors, arrangement of critical thinking, organizational loyalty and analysis of behavior and work and the development of emotional quotient. These 4 sub-factors could predict the success of the trainers in skill aspect 55.90%. 3) The attitude competency consisted of 4 sub-factors, arrangement of critical thinking, intention of trainee computer competency and teaching psychology. In conclusion, these 4 sub-factors could predict the success of the trainers in attitude aspect 58.50%.

Keywords: the development factors, trainers development, trainer competencies, auto part manufacturing factory (AMF), AmataNakon Industrial Estate Cholburi

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Authors: E. Tandis, E. Assareh

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Designing the optimal shape of MW wind turbine blades is provided in a number of cases through evolutionary algorithms associated with mathematical modeling (Blade Element Momentum Theory). Evolutionary algorithms, among the optimization methods, enjoy many advantages, particularly in stability. However, they usually need a large number of function evaluations. Since there are a large number of local extremes, the optimization method has to find the global extreme accurately. The present paper introduces a new population-based hybrid algorithm called Genetic-Based Bees Algorithm (GBBA). This algorithm is meant to design the optimal shape for MW wind turbine blades. The current method employs crossover and neighborhood searching operators taken from the respective Genetic Algorithm (GA) and Bees Algorithm (BA) to provide a method with good performance in accuracy and speed convergence. Different blade designs, twenty-one to be exact, were considered based on the chord length, twist angle and tip speed ratio using GA results. They were compared with BA and GBBA optimum design results targeting the power coefficient and solidity. The results suggest that the final shape, obtained by the proposed hybrid algorithm, performs better compared to either BA or GA. Furthermore, the accuracy and speed convergence increases when the GBBA is employed

Keywords: Blade Design, Optimization, Genetic Algorithm, Bees Algorithm, Genetic-Based Bees Algorithm, Large Wind Turbine

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Authors: Hatim Laalej, Salvador Sumohano-Verdeja, Thomas McLeay

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Monitoring of tool wear in milling operations is essential for achieving the desired dimensional accuracy and surface finish of a machined workpiece. Although there are numerous statistical models and artificial intelligence techniques available for monitoring the wear of cutting tools, these techniques cannot pin point which cutting edge of the tool, or which insert in the case of indexable tooling, is worn or broken. Currently, the task of monitoring the wear on the tool cutting edges is carried out by the operator who performs a manual inspection, causing undesirable stoppages of machine tools and consequently resulting in costs incurred from lost productivity. The present study is concerned with the development of a flute tracking system to segment signals related to each physical flute of a cutter with three flutes used in an end milling operation. The purpose of the system is to monitor the cutting condition for individual flutes separately in order to determine their progressive wear rates and to predict imminent tool failure. The results of this study clearly show that signals associated with each flute can be effectively segmented using the proposed flute tracking system. Furthermore, the results illustrate that by segmenting the sensor signal by flutes it is possible to investigate the wear in each physical cutting edge of the cutting tool. These findings are significant in that they facilitate the online condition monitoring of a cutting tool for each specific flute without the need for operators/engineers to perform manual inspections of the tool.

Keywords: machining, milling operation, tool condition monitoring, tool wear prediction

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Authors: Mahawish Masud, Muhammad Iqbal, M. U. Khan, Farooque Azam

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Manual writing of test cases from functional requirements is a time-consuming task. Such test cases are not only difficult to write but are also challenging to maintain. Test cases can be drawn from the functional requirements that are expressed in natural language. However, manual test case generation is inefficient and subject to errors.  In this paper, we have presented a systematic procedure that could automatically derive test cases from user stories. The user stories are specified in a restricted natural language using a well-defined template.  We have also presented a detailed methodology for writing our test ready user stories. Our tool “Test-o-Matic” automatically generates the test cases by processing the restricted user stories. The generated test cases are executed by using open source Selenium IDE.  We evaluate our approach on a case study, which is an open source web based application. Effectiveness of our approach is evaluated by seeding faults in the open source case study using known mutation operators.  Results show that the test case generation from restricted user stories is a viable approach for automated testing of web applications.

Keywords: automated testing, natural language, restricted user story modeling, software engineering, software testing, test case specification, transformation and automation, user story, web application testing

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Authors: Tzay-An Shiau, Kuan-Lin Ho

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This study developed sustainability and quality of life indicators for urban passenger transportation by using Social Construction of Technology (SCOT). The initial indicators were proposed by referring to literatures and were summarized by using impact-based framework. Subsequently, the stakeholders were defined according to their interest, power and then classified into scientific, operational, policy making, policy monitoring and nonprofessional frames. The scientific frame consisted of nine scholars in transportation field. Ten representatives from Taipei Rapid Transit Corporation (TRTC), Taiwan Railways Administration (TRA) and bus operators were grouped into the operational frame. The policy making frame comprised of ten representatives from Department of Transportation, Taipei City Government (DOT, TCG), Department of Railways and Highways, Ministry of Transportation and Communication (DORH, MOTC), Directorate General of Highways, Ministry of Transportation and Communication (DGOH, MOTC) and Institute of Transportation, Ministry of Transportation and Communication (IOT, MOTC). The policy monitoring frame consisted of 15 representatives from Taipei City Councilor, legislator and reporter. The nonprofessional frame comprised of 72 Taipei citizens. The stakeholders were asked to evaluate the relative importance of indicators using Delphi survey method. Social construction of 14 transport sustainability indicators and 12 transport quality of life indicators were obtained.

Keywords: sustainability, quality of life, Social Construction of Technology (SCOT), stakeholder

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Authors: Damir Latypov

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A hybrid classical-quantum algorithm to solve boundary integral equations (BIE) arising in problems of electromagnetic and acoustic scattering is proposed. The quantum speed-up is due to a Quantum Linear System Algorithm (QLSA). The original QLSA of Harrow et al. provides an exponential speed-up over the best-known classical algorithms but only in the case of sparse systems. Due to the non-local nature of integral operators, matrices arising from discretization of BIEs, are, however, dense. A QLSA for dense matrices was introduced in 2017. Its runtime as function of the system's size N is bounded by O(√Npolylog(N)). The run time of the best-known classical algorithm for an arbitrary dense matrix scales as O(N².³⁷³). Instead of exponential as in case of sparse matrices, here we have only a polynomial speed-up. Nevertheless, sufficiently high power of this polynomial, ~4.7, should make QLSA an appealing alternative. Unfortunately for the QLSA, the asymptotic separability of the Green's function leads to high compressibility of the BIEs matrices. Classical fast algorithms such as Multilevel Fast Multipole Method (MLFMM) take advantage of this fact and reduce the runtime to O(Nlog(N)), i.e., the QLSA is only quadratically faster than the MLFMM. To be truly impactful for computational electromagnetics and acoustics engineers, QLSA must provide more substantial advantage than that. We propose a computational scheme which combines elements of the classical fast algorithms with the QLSA to achieve the required performance.

Keywords: quantum linear system algorithm, boundary integral equations, dense matrices, electromagnetic scattering theory

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Authors: Dararat Tongdee, Surapong Chirarattananon, Somchai Maneewan, Chantana Punlek

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Recently, the Internet of Things (IoT) is the important technology that connects devices to the network and people can access real-time communication. This technology is used to report, collect, and analyze the big data for achieving a purpose. For a smart building, there are many IoT technologies that enable management and building operators to improve occupant thermal comfort, indoor air quality, and building energy efficiency. In this research, we propose monitoring and controlling performance of a smart dedicated outdoor air system (SDOAS) based on IoT platform. The SDOAS was specifically designed with the desiccant unit and thermoelectric module. The designed system was intended to monitor, notify, and control indoor environmental factors such as temperature, humidity, and carbon dioxide (CO₂) level. The SDOAS was tested under the American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE 62.2) and indoor air quality standard. The system will notify the user by Blynk notification when the status of the building is uncomfortable or tolerable limits are reached according to the conditions that were set. The user can then control the system via a Blynk application on a smartphone. The experimental result indicates that the temperature and humidity of indoor fresh air in the comfort zone are approximately 26 degree Celsius and 58% respectively. Furthermore, the CO₂ level was controlled lower than 1000 ppm by indoor air quality standard condition. Therefore, the proposed system can efficiently work and be easy to use for buildings.

Keywords: internet of things, indoor air quality, smart dedicated outdoor air system, thermal comfort

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Authors: Bongs Lainjo

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The evolution and escalation of bike-sharing programs (BSP) continue unabated. Since the sixties, many countries have introduced different models and strategies of BSP. These include variations ranging from dockless models to electronic real-time monitoring systems. Reasons for using this BSP include recreation, errands, work, etc. And there is all indication that complex, and more innovative rider-friendly systems are yet to be introduced. The objective of this paper is to analyze current variables established by different operators and streamline them identifying the most compelling ones using analytics. Given the contents of available databases, there is a lack of uniformity and common standard on what is required and what is not. Two factors appear to be common: user type (registered and unregistered, and duration of each trip). This article uses historical data provided by one operator based in the greater Washington, District of Columbia, USA area. Several variables including categorical and continuous data types were screened. Eight out of 18 were considered acceptable and significantly contribute to determining a useful and reliable predictive model. Bike-sharing systems have become popular in recent years all around the world. Although this trend has resulted in many studies on public cycling systems, there have been few previous studies on the factors influencing public bicycle travel behavior. A bike-sharing system is a computer-controlled system in which individuals can borrow bikes for a fee or free for a limited period. This study has identified unprecedented useful, and pragmatic parameters required in improving BSP ridership dynamics.

Keywords: sharing program, historical data, parameters, ridership dynamics, trip duration

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Authors: Hyeon-Kyo Lim, Tong-Il Jang, Yong-Hee Lee

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For the past several decades, not a few researchers have warned that even a trivial human error may result in unexpected accidents, especially in Nuclear Power Plants. To prevent accidents in Nuclear Power Plants, it is quite indispensable to make any factors under the effective control that may raise the possibility of human errors for accident prevention. This study aimed to develop a risk management program, especially in the sense that guaranteeing Fitness-for-Duty (FFD) of human beings working in Nuclear Power Plants. Throughout a literal survey, it was found that work stress and fatigue are major psychophysical factors requiring sophisticated management. A set of major management factors related to work stress and fatigue was through repetitive literal surveys and classified into several categories. To maintain the fitness of human workers, a 4-level – individual worker, team, staff within plants, and external professional - approach was adopted for FFD management program. Moreover, the program was arranged to envelop the whole employment cycle from selection and screening of workers, job allocation, and job rotation. Also, a managerial care program was introduced for employee assistance based on the concept of Employee Assistance Program (EAP). The developed program was reviewed with repetition by ex-operators in nuclear power plants, and assessed in the affirmative. As a whole, responses implied additional treatment to guarantee high performance of human workers not only in normal operations but also in emergency situations. Consequently, the program is under administrative modification for practical application.

Keywords: fitness-for-duty (FFD), human error, work stress, fatigue, Employee-Assistance-Program (EAP)

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Authors: Ming-Jong Yao, Chin-Sum Shui, Chih-Han Wang

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This paper is developed based on a real-world decision scenario that an industrial gas company that applies the Vendor Managed Inventory model and supplies liquid oxygen with a self-operated heterogeneous vehicle fleet to hospitals in nearby cities. We name it as a Joint Replenishment and Heterogeneous Vehicle Routing Problem with Cyclical Schedule and formulate it as a non-linear mixed-integer linear programming problem which simultaneously determines the length of the planning cycle (PC), the length of the replenishment cycle and the dates of replenishment for each customer and the vehicle routes of each day within PC, such that the average daily operation cost within PC, including inventory holding cost, setup cost, transportation cost, and overtime labor cost, is minimized. A solution method based on genetic algorithm, embedded with an encoding and decoding mechanism and local search operators, is then proposed, and the hash function is adopted to avoid repetitive fitness evaluation for identical solutions. Numerical experiments demonstrate that the proposed solution method can effectively solve the problem under different lengths of PC and number of customers. The method is also shown to be effective in determining whether the company should expand the storage capacity of a customer whose demand increases. Sensitivity analysis of the vehicle fleet composition shows that deploying a mixed fleet can reduce the daily operating cost.

Keywords: cyclic inventory routing problem, joint replenishment, heterogeneous vehicle, genetic algorithm

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Authors: Dilang Thouk Tharjiath

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This study seeks to examine determinants of access to finance: the case of micro and small enterprises in bonga town. It identifies the sector as the key to unlocking the economic potentials of the country. For the achievement of the objective of the study simple random and stratified sampling has been used to select 179 respondents, primary and secondary data were used, primary data were collected through face to face interview and preparing questionnaire and secondary data were collected through reviewing firms record and reports, quantitative research approach were used and the data obtained were analyzed using descriptive research design. Access to finance is one of the key obstacles of MSE’s not only when starting the business project but also when operating. Identifying the major determinants of access to finance is therefore quite crucial. Based on descriptive result the financiers specially formal financiers tend to grant credit easily for enterprises which are located near to town, having operators with higher educational level, experienced and with a positive attitudes towards or fulfill their lending procedures, and a firm having collateralized asset, prepare business plan, maintain accounting practice ,large and old enough. Finally the study recommended that As Educational level of entrepreneurs has significant effect on access to credit from bank and the managers or owners education level is low in Bonga town the concerned bodies of both the government and non-governmental institutions in collaboration with Bonga town MSE development office are recommended to create awareness and facilitate the provision of additional training for those with lower educational level.

Keywords: credit, entrepreneur, enterprise, manager

Procedia PDF Downloads 65

Authors: Arfan Ali Nagra, Tariq Shahzad, Meshal Alharbi, Khalid Masood Khan, Muhammad Mugees Asif, Taher M. Ghazal, Khmaies Ouahada

Abstract:

Gene selection is an essential step for the classification of microarray cancer data. Gene expression cancer data (DNA microarray) facilitates computing the robust and concurrent expression of various genes. Particle swarm optimization (PSO) requires simple operators and less number of parameters for tuning the model in gene selection. The selection of a prognostic gene with small redundancy is a great challenge for the researcher as there are a few complications in PSO based selection method. In this research, a new variant of PSO (Self-inertia weight adaptive PSO) has been proposed. In the proposed algorithm, SIW-APSO-ELM is explored to achieve gene selection prediction accuracies. This new algorithm balances the exploration capabilities of the improved inertia weight adaptive particle swarm optimization and the exploitation. The self-inertia weight adaptive particle swarm optimization (SIW-APSO) is used to search the solution. The SIW-APSO is updated with an evolutionary process in such a way that each particle iteratively improves its velocities and positions. The extreme learning machine (ELM) has been designed for the selection procedure. The proposed method has been to identify a number of genes in the cancer dataset. The classification algorithm contains ELM, K- centroid nearest neighbor (KCNN), and support vector machine (SVM) to attain high forecast accuracy as compared to the start-of-the-art methods on microarray cancer datasets that show the effectiveness of the proposed method.

Keywords: microarray cancer, improved PSO, ELM, SVM, evolutionary algorithms

Procedia PDF Downloads 52

Authors: Olivier Chaigneau, Damianos Oikonomidis, Marie-Cecile Delmas

Abstract:

GAMBAS (Galileo Advanced features for the Maritime domain: Breakthrough Applications for Safety and security) is a project funded by the European Space Program Agency (EUSPA) aiming at identifying the search-and-rescue and ship security alert system needs for maritime users (including operators and fishing stakeholders) and developing operational concepts to answer these needs. The general objective of the GAMBAS project is to support the deployment of Galileo exclusive features in the maritime domain in order to improve safety and security at sea, detection of illegal activities and associated surveillance means, resilience to natural and human-induced emergency situations, and develop, integrate, demonstrate, standardize and disseminate these new associated capabilities. The project aims to demonstrate: improvement of the SAR (Search And Rescue) and SSAS (Ship Security Alert System) detection and response to maritime distress through the integration of new features into the beacon for SSAS in terms of cost optimization, user-friendly aspects, integration of Galileo and OS NMA (Open Service Navigation Message Authentication) reception for improved authenticated localization performance and reliability, and at sea triggering capabilities, optimization of the responsiveness of RCCs (Rescue Co-ordination Centre) towards the distress situations affecting vessels, the adaptation of the MCCs (Mission Control Center) and MEOLUT (Medium Earth Orbit Local User Terminal) to the data distribution of SSAS alerts.

Keywords: Galileo new advanced features, maritime, safety, security

Procedia PDF Downloads 62

Authors: Zeinab Haji Abolhasani, Romeo Marian, Lee Luong

Abstract:

This paper and its companions (Part II, Part III) will concentrate on optimizing a class of supply chain problems known as Multi- Commodities Consumer Supply Chain (MCCSC) problem. MCCSC problem belongs to production-distribution (P-D) planning category. It aims to determine facilities location, consumers’ allocation, and facilities configuration to minimize total cost (CT) of the entire network. These facilities can be manufacturer units (MUs), distribution centres (DCs), and retailers/end-users (REs) but not limited to them. To address this problem, three major tasks should be undertaken. At the first place, a mixed integer non-linear programming (MINP) mathematical model is developed. Then, system’s behaviors under different conditions will be observed using a simulation modeling tool. Finally, the most optimum solution (minimum CT) of the system will be obtained using a multi-objective optimization technique. Due to the large size of the problem, and the uncertainties in finding the most optimum solution, integration of modeling and simulation methodologies is proposed followed by developing new approach known as GASG. It is a genetic algorithm on the basis of granular simulation which is the subject of the methodology of this research. In part II, MCCSC is simulated using discrete-event simulation (DES) device within an integrated environment of SimEvents and Simulink of MATLAB® software package followed by a comprehensive case study to examine the given strategy. Also, the effect of genetic operators on the obtained optimal/near optimal solution by the simulation model will be discussed in part III.

Keywords: supply chain, genetic algorithm, optimization, simulation, discrete event system

Procedia PDF Downloads 276

Authors: Mary Rose Everan, Michael McCann, Gary Cullen

Abstract:

International travel journeys, by their nature, incorporate elements provided by multiple service providers such as airlines, rail carriers, airports, and ground handlers. Data needs to be stored by and exchanged between these parties in the process of managing the journey. The fragmented nature of this shared management of mutual clients is a limiting factor in the development of a seamless, hassle-free, end-to-end travel experience. Traditional interlining agreements attempt to facilitate many separate aspects of co-operation between service providers, typically between airlines and, to some extent, intermodal travel operators, including schedules, fares, ticketing, through check-in, and baggage handling. These arrangements rely on pre-agreement. The development of Virtual Interlining - that is, interlining facilitated by a third party (often but not always an airport) without formal pre-agreement by the airlines or rail carriers - demonstrates an underlying demand for a better quality end-to-end travel experience. Blockchain solutions are being explored in a number of industries and offer, at first sight, an immutable, single source of truth for this data, avoiding data conflicts and misinterpretation. Combined with Smart Contracts, they seemingly offer a more robust and dynamic platform for multi-stakeholder ventures, and even perhaps the ability to join and leave consortia dynamically. Applying blockchain to the intermodal interlining space – termed Blocklining in this paper - is complex and multi-faceted because of the many aspects of cooperation outlined above. To explore its potential, this paper concentrates on one particular dimension, that of through baggage interlining.

Keywords: aviation, baggage, blocklining, intermodal, interlining

Procedia PDF Downloads 121

Authors: Gerard Bray, Derek Mao, Arya Bahadori, Sachinka Ranasinghe

Abstract:

The EAU currently recommends partial nephrectomy as the preferred management for localised cT1 renal tumours, irrespective of surgical approach. With the advent of robotic assisted partial nephrectomy, there is growing evidence that warm ischaemia time may be reduced compared to the traditional laparoscopic approach. There is still no clear differences between the two approaches with regards to other peri-operative and oncological outcomes. Current limitations in the field denote the lack of single surgeon series to compare the two approaches as other studies often include multiple operators of different experience levels. To the best of our knowledge, this study is the first single surgeon series comparing peri-operative outcomes of robotic assisted and laparoscopic PN. The current study aims to reduce intra-operator bias while maintaining an adequate sample size to assess the differences in outcomes between the two approaches. We retrospectively compared patient demographics, peri-operative outcomes, and renal function derangements of all partial nephrectomies undertaken by a single surgeon with experience in both laparoscopic and robotic surgery. Warm ischaemia time, length of stay, and acute renal function deterioration were all significantly reduced with robotic partial nephrectomy, compared to laparoscopic nephrectomy. This study highlights the benefits of robotic partial nephrectomy. Further prospective studies with larger sample sizes would be valuable additions to the current literature.

Keywords: partial nephrectomy, robotic assisted partial nephrectomy, warm ischaemia time, peri-operative outcomes

Procedia PDF Downloads 109

Authors: Mokhtar Azizi

Abstract:

Due to heavy traffic and congested roads, it is crucial that the most popular main public transport services in Kuala Lumpur i.e. Putra LRT, Star LRT, KTM Commuter, KL Monorail and Rapid Bus must be continuously monitored and improved to fulfill the rider’s requirement and kept updated by the transit agencies. Evaluation on the current status of the services has been determined out by calculating the transit supportive area (TSA) and level of service (LOS) for each transit station. This research study has carried out the TSA and LOS mapping based on GIS techniques. The detailed census data of the region along the line of services has been collected from the Department of Statistics Malaysia for this purpose. The service coverage has been decided by 400 meters buffer zone for bus stations and 800 meters for rails station and railways in measurement the Quality of Service along the line of services. All the required information has been calculated by using the customized GIS software called Kuala Lumpur Transit Information System (KLTIS). The transit supportive area was calculated with the employment density at least 10 job/hectare or household density at 7.5 unit/hectare and total area covered by transit supportive area is 22516 hectare and the total area that is not supported by transit is 1718 hectare in Kuala Lumpur. The level of service is calculated with the percentage of transit supportive area served by transit for each station. In overall the percentage transit supportive areas served by transit for all the stations were less than 50% which falls in a very low level of service category. This research has proven its benefit by providing the current transit services operators with vital information for improvement of existing public transport services.

Keywords: service coverage, transit supportive area, level of service, transit system

Procedia PDF Downloads 349