Search results for: Access algorithm

Authors: Giorgi Gaprindashvili

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One of the best examples, in evolution of the public procurement, from post-soviet countries are reforms carried out in Georgia, which brought them close to international standards of procurement. In Georgia, public procurement legislation started functioning short after gaining independence. The reform has passed several stages and came in the form as it is today. It should also be noted, that countries with economy in transition, including Georgia, implemented all the reforms in public procurement based on recommendations and support of World Bank, the United Nations and other international organizations. The aim of first adopted law was regulation of the procurement process of budget-organizations, transparency and creation of competitive environment for private companies to access state funds legally. The priorities were identified quite clearly in the wording of the law, but operation/function of this law could not be reached on its level, because of some objective and subjective reasons. The high level of corruption in all levels of governance can be considered as a main obstacle reason and of course, it is natural, that it had direct impact on the procurement process, as well as on transparency and rational use of state funds. These circumstances were the reasons that reforms in this sphere continued, to improve procurement process, in particular, the first wave of reforms began after several years. Public procurement agency carried out reform with World Bank with main purpose of smartening the procurement legislation and its harmonization with international treaties and agreements. Also with the support of World Bank various activities were carried out to raise awareness of participants involved in procurement system. Further major changes in the legislation were filed bit later, which was also directed towards the improvement and smarten of the procurement process. The third wave of the reform more or less guaranteed the transparency of the procurement process, which later became the basis for the rational spending of state funds. The reform of the procurement system completely changed the procedures. Carried out reform in Georgia resulted in introducing new electronic tendering system, which benefit the transparency of the process, after this became the basis for the further development of a competitive environment, which become a prerequisite for the state rational spending. Increased number of supplier organizations participating in the procurement process resulted in reduction of the estimated cost and the actual cost. Assessment of the reforms in Georgia in the field of public procurement can be concluded, that proper regulation of the sector and relevant policy may proceed to rational and transparent spending of the budget from country’s state institutions. Also, the business sector has the opportunity to work in competitive market conditions and to make a preliminary analysis, which is a prerequisite for future strategy and development.

Keywords: Public Administration, Public Procurement, Reforms, Transparency.

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Authors: May Fadheel Estephan, Richard Perks

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Cancer is a serious health concern that affects millions of people worldwide. Early detection and treatment are essential for improving patient outcomes. However, current methods for cancer detection have limitations, such as low sensitivity and specificity. The aim of this study was to develop an optical sensor for cancer detection using elastic light scattering spectroscopy (ELSS). ELSS is a non-invasive optical technique that can be used to characterize the size and concentration of particles in a solution. An optical probe was fabricated with a 100-μm-diameter core and a 132-μm centre-to-centre separation. The probe was used to measure the ELSS spectra of polystyrene spheres with diameters of 2 μm, 0.8 μm, and 0.413 μm. The spectra were then analysed to determine the size and concentration of the spheres. The results showed that the optical probe was able to differentiate between the three different sizes of polystyrene spheres. The probe was also able to detect the presence of polystyrene spheres in suspension concentrations as low as 0.01%. The results of this study demonstrate the potential of ELSS for cancer detection. ELSS is a non-invasive technique that can be used to characterize the size and concentration of cells in a tissue sample. This information can be used to identify cancer cells and assess the stage of the disease. The data for this study were collected by measuring the ELSS spectra of polystyrene spheres with different diameters. The spectra were collected using a spectrometer and a computer. The ELSS spectra were analysed using a software program to determine the size and concentration of the spheres. The software program used a mathematical algorithm to fit the spectra to a theoretical model. The question addressed by this study was whether ELSS could be used to detect cancer cells. The results of the study showed that ELSS could be used to differentiate between different sizes of cells, suggesting that it could be used to detect cancer cells. The findings of this research show the utility of ELSS in the early identification of cancer. ELSS is a non-invasive method for characterizing the number and size of cells in a tissue sample. To determine cancer cells and determine the disease's stage, this information can be employed. Further research is needed to evaluate the clinical performance of ELSS for cancer detection.

Keywords: Elastic Light Scattering Spectroscopy, Polystyrene spheres in suspension, optical probe, fibre optics.

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Authors: Refaat H. Abd El Razek, Ahmed M. Diab, Sherif M. Hafez, Remon F. Aziz

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Time-Cost Optimization "TCO" is one of the greatest challenges in construction project planning and control, since the optimization of either time or cost, would usually be at the expense of the other. Since there is a hidden trade-off relationship between project and cost, it might be difficult to predict whether the total cost would increase or decrease as a result of the schedule compression. Recently third dimension in trade-off analysis is taken into consideration that is quality of the projects. Few of the existing algorithms are applied in a case of construction project with threedimensional trade-off analysis, Time-Cost-Quality relationships. The objective of this paper is to presents the development of a practical software system; that named Automatic Multi-objective Typical Construction Resource Optimization System "AMTCROS". This system incorporates the basic concepts of Line Of Balance "LOB" and Critical Path Method "CPM" in a multi-objective Genetic Algorithms "GAs" model. The main objective of this system is to provide a practical support for typical construction planners who need to optimize resource utilization in order to minimize project cost and duration while maximizing its quality simultaneously. The application of these research developments in planning the typical construction projects holds a strong promise to: 1) Increase the efficiency of resource use in typical construction projects; 2) Reduce construction duration period; 3) Minimize construction cost (direct cost plus indirect cost); and 4) Improve the quality of newly construction projects. A general description of the proposed software for the Time-Cost-Quality Trade-Off "TCQTO" is presented. The main inputs and outputs of the proposed software are outlined. The main subroutines and the inference engine of this software are detailed. The complexity analysis of the software is discussed. In addition, the verification, and complexity of the proposed software are proved and tested using a real case study.

Keywords: Project management, typical (repetitive) large scale projects, line of balance, multi-objective optimization, genetic algorithms, time-cost-quality trade-offs.

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Authors: Naeleh Motamedi, Masoud Mahmoudkhan Shirazi, Nima Nouraei

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Natural disasters, including earthquake, kill many people around the world every year. Society rescue actions, which start after the earthquake and are called LAST in abbreviation, include locating, access, stabilization and transportation. In the present article, we have studied the process of local accessibility to the injured and transporting them to health care centers. With regard the heavy traffic load due to earthquake, the destruction of connecting roads and bridges and the heavy debris in alleys and street, which put the lives of the injured and the people buried under the debris in danger, accelerating the rescue actions and facilitating the accessibilities are of great importance, obviously. Tehran, the capital of Iran, is among the crowded cities in the world and is the center of extensive economic, political, cultural and social activities. Tehran has a population of about 9.5 millions and because of the immigration of people from the surrounding cities. Furthermore, considering the fact that Tehran is located on two important and large faults, a 6 Richter magnitude earthquake in this city could lead to the greatest catastrophe during the entire human history. The present study is a kind of review and a major part of the required information for it, has been obtained from libraries all of the rescue vehicles around the world, including rescue helicopters, ambulances, fire fighting vehicles and rescue boats, and their applied technology, and also the robots specifically designed for the rescue system and the advantages and disadvantages of them, have been investigated. The studies show that there is a significant relationship between the rescue team-s arrival time at the incident zone and the number of saved people; so that, if the duration of burial under debris 30 minutes, the probability of survival is %99.3, after a day is %81, after 2days is %19 and after 5days is %7.4. The exiting transport systems all have some defects. If these defects are removed, more people could be saved each hour and the preparedness against natural disasters is increased. In this study, transport system has been designed for the rescue team and the injured; which could carry the rescue team to the incident zone and the injured to the health care centers. In addition, this system is able to fly in the air and move on the earth as well; so that the destruction of roads and the heavy traffic load could not prevent the rescue team from arriving early at the incident zone. The system also has the equipment required firebird for debris removing, optimum transport of the injured and first aid.

Keywords: earthquake, accelerating, accessibilities transportation, rescue system

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Authors: Malte Brettel, Niklas Friederichsen, Michael Keller, Marius Rosenberg

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The German manufacturing industry has to withstand an increasing global competition on product quality and production costs. As labor costs are high, several industries have suffered severely under the relocation of production facilities towards aspiring countries, which have managed to close the productivity and quality gap substantially. Established manufacturing companies have recognized that customers are not willing to pay large price premiums for incremental quality improvements. As a consequence, many companies from the German manufacturing industry adjust their production focusing on customized products and fast time to market. Leveraging the advantages of novel production strategies such as Agile Manufacturing and Mass Customization, manufacturing companies transform into integrated networks, in which companies unite their core competencies. Hereby, virtualization of the process- and supply-chain ensures smooth inter-company operations providing real-time access to relevant product and production information for all participating entities. Boundaries of companies deteriorate, as autonomous systems exchange data, gained by embedded systems throughout the entire value chain. By including Cyber-Physical-Systems, advanced communication between machines is tantamount to their dialogue with humans. The increasing utilization of information and communication technology allows digital engineering of products and production processes alike. Modular simulation and modeling techniques allow decentralized units to flexibly alter products and thereby enable rapid product innovation. The present article describes the developments of Industry 4.0 within the literature and reviews the associated research streams. Hereby, we analyze eight scientific journals with regards to the following research fields: Individualized production, end-to-end engineering in a virtual process chain and production networks. We employ cluster analysis to assign sub-topics into the respective research field. To assess the practical implications, we conducted face-to-face interviews with managers from the industry as well as from the consulting business using a structured interview guideline. The results reveal reasons for the adaption and refusal of Industry 4.0 practices from a managerial point of view. Our findings contribute to the upcoming research stream of Industry 4.0 and support decision-makers to assess their need for transformation towards Industry 4.0 practices. 

Keywords: Industry 4.0., Mass Customization, Production networks, Virtual Process-Chain.

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Authors: Xiangtuo Chen, Paul-Henry Cournéde

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Crop yield prediction is a paramount issue in agriculture. The main idea of this paper is to find out efficient way to predict the yield of corn based meteorological records. The prediction models used in this paper can be classified into model-driven approaches and data-driven approaches, according to the different modeling methodologies. The model-driven approaches are based on crop mechanistic modeling. They describe crop growth in interaction with their environment as dynamical systems. But the calibration process of the dynamic system comes up with much difficulty, because it turns out to be a multidimensional non-convex optimization problem. An original contribution of this paper is to propose a statistical methodology, Multi-Scenarios Parameters Estimation (MSPE), for the parametrization of potentially complex mechanistic models from a new type of datasets (climatic data, final yield in many situations). It is tested with CORNFLO, a crop model for maize growth. On the other hand, the data-driven approach for yield prediction is free of the complex biophysical process. But it has some strict requirements about the dataset. A second contribution of the paper is the comparison of these model-driven methods with classical data-driven methods. For this purpose, we consider two classes of regression methods, methods derived from linear regression (Ridge and Lasso Regression, Principal Components Regression or Partial Least Squares Regression) and machine learning methods (Random Forest, k-Nearest Neighbor, Artificial Neural Network and SVM regression). The dataset consists of 720 records of corn yield at county scale provided by the United States Department of Agriculture (USDA) and the associated climatic data. A 5-folds cross-validation process and two accuracy metrics: root mean square error of prediction(RMSEP), mean absolute error of prediction(MAEP) were used to evaluate the crop prediction capacity. The results show that among the data-driven approaches, Random Forest is the most robust and generally achieves the best prediction error (MAEP 4.27%). It also outperforms our model-driven approach (MAEP 6.11%). However, the method to calibrate the mechanistic model from dataset easy to access offers several side-perspectives. The mechanistic model can potentially help to underline the stresses suffered by the crop or to identify the biological parameters of interest for breeding purposes. For this reason, an interesting perspective is to combine these two types of approaches.

Keywords: Crop yield prediction, crop model, sensitivity analysis, paramater estimation, particle swarm optimization, random forest.

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Authors: Fazıl Gökgöz, Fahrettin Filiz

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Load forecasting has become crucial in recent years and become popular in forecasting area. Many different power forecasting models have been tried out for this purpose. Electricity load forecasting is necessary for energy policies, healthy and reliable grid systems. Effective power forecasting of renewable energy load leads the decision makers to minimize the costs of electric utilities and power plants. Forecasting tools are required that can be used to predict how much renewable energy can be utilized. The purpose of this study is to explore the effectiveness of LSTM-based neural networks for estimating renewable energy loads. In this study, we present models for predicting renewable energy loads based on deep neural networks, especially the Long Term Memory (LSTM) algorithms. Deep learning allows multiple layers of models to learn representation of data. LSTM algorithms are able to store information for long periods of time. Deep learning models have recently been used to forecast the renewable energy sources such as predicting wind and solar energy power. Historical load and weather information represent the most important variables for the inputs within the power forecasting models. The dataset contained power consumption measurements are gathered between January 2016 and December 2017 with one-hour resolution. Models use publicly available data from the Turkish Renewable Energy Resources Support Mechanism. Forecasting studies have been carried out with these data via deep neural networks approach including LSTM technique for Turkish electricity markets. 432 different models are created by changing layers cell count and dropout. The adaptive moment estimation (ADAM) algorithm is used for training as a gradient-based optimizer instead of SGD (stochastic gradient). ADAM performed better than SGD in terms of faster convergence and lower error rates. Models performance is compared according to MAE (Mean Absolute Error) and MSE (Mean Squared Error). Best five MAE results out of 432 tested models are 0.66, 0.74, 0.85 and 1.09. The forecasting performance of the proposed LSTM models gives successful results compared to literature searches.

Keywords: Deep learning, long-short-term memory, energy, renewable energy load forecasting.

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Authors: R. Abdulrahman, A. Eardley, A. Soliman

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The proliferation in the development of mobile learning (m-learning) has played a vital role in the rapidly growing electronic learning market. This relatively new technology can help to encourage the development of in learning and to aid knowledge transfer a number of areas, by familiarizing students with innovative information and communications technologies (ICT). M-learning plays a substantial role in the deployment of learning methods for nursing students by using the Internet and portable devices to access learning resources ‘anytime and anywhere’. However, acceptance of m-learning by students is critical to the successful use of m-learning systems. Thus, there is a need to study the factors that influence student’s intention to use m-learning. This paper addresses this issue. It outlines the outcomes of a study that evaluates the unified theory of acceptance and use of technology (UTAUT) model as applied to the subject of user acceptance in relation to m-learning activity in nurse education. The model integrates the significant components across eight prominent user acceptance models. Therefore, a standard measure is introduced with core determinants of user behavioural intention. The research model extends the UTAUT in the context of m-learning acceptance by modifying and adding individual innovativeness (II) and quality of service (QoS) to the original structure of UTAUT. The paper goes on to add the factors of previous experience (of using mobile devices in similar applications) and the nursing students’ readiness (to use the technology) to influence their behavioural intentions to use m-learning. This study uses a technique called ‘convenience sampling’ which involves student volunteers as participants in order to collect numerical data. A quantitative method of data collection was selected and involves an online survey using a questionnaire form. This form contains 33 questions to measure the six constructs, using a 5-point Likert scale. A total of 42 respondents participated, all from the Nursing Institute at the Armed Forces Hospital in Saudi Arabia. The gathered data were then tested using a research model that employs the structural equation modelling (SEM), including confirmatory factor analysis (CFA). The results of the CFA show that the UTAUT model has the ability to predict student behavioural intention and to adapt m-learning activity to the specific learning activities. It also demonstrates satisfactory, dependable and valid scales of the model constructs. This suggests further analysis to confirm the model as a valuable instrument in order to evaluate the user acceptance of m-learning activity.

Keywords: Mobile learning, nursing institute, unified theory of acceptance and use of technology model.

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Authors: Saska Alexandria Hayes

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Multiple Convention Refugees in New Zealand are stuck in a state of immigration limbo due to a lack of defined immigration policies. The Refugee Convention of 1951 does not give the right to be issued a permanent right to live and work in the country of asylum. A gap in New Zealand's immigration law and policy has left Convention Refugees without the right to obtain a resident or temporary entry visa. The significant lack of literature on this topic suggests that the lack of visa options for Convention Refugees in New Zealand is a widely unknown or unacknowledged issue. Refugees in New Zealand enjoy the right of non-refoulement contained in Article 33 of the Refugee Convention 1951, whether lawful or unlawful. However, a number of rights contained in the Refugee Convention 1951, such as the right to gainful employment and social security, are limited to refugees who maintain lawful immigration status. If a Convention Refugee is denied a resident visa, the only temporary entry visa a Convention Refugee can apply for in New Zealand is discretionary. The appeal cases heard at the Immigration Protection Tribunal establish that Immigration New Zealand has declined resident and discretionary temporary entry visa applications by Convention Refugees for failing to meet the health or character immigration instructions. The inability of a Convention Refugee to gain residency in New Zealand creates a dependence on the issue of discretionary temporary entry visas to maintain lawful status. The appeal cases record that this reliance has led to Convention Refugees' lawful immigration status being in question, temporarily depriving them of the rights contained in the Refugee Convention 1951 of lawful refugees. In one case, the process of applying for a discretionary temporary entry visa led to a lawful Convention Refugee being temporarily deprived of the right to social security, breaching Article 24 of the Refugee Convention 1951. The judiciary has stated a constant reliance on the issue of discretionary temporary entry visas for Convention Refugees can lead to a breach of New Zealand's international obligations under Article 7 of the International Covenant on Civil and Political Rights. The appeal cases suggest that, despite successful judicial proceedings, at least three persons have been made to rely on the issue of discretionary temporary entry visas potentially indefinitely. The appeal cases establish that a Convention Refugee can be denied a discretionary temporary entry visa and become unlawful. Unlawful status could ultimately breach New Zealand's obligations under Article 33 of the Refugee Convention 1951 as it would procedurally deny Convention Refugees asylum. It would force them to choose between the right of non-refoulement or leaving New Zealand to seek the ability to access all the human rights contained in the Universal Declaration of Human Rights elsewhere. This paper discusses how the current system has given rise to these breaches and emphasizes a need to create a designated temporary entry visa category for Convention Refugees.

Keywords: Domestic policy, immigration, migration, New Zealand.

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Authors: K. Sasikala, R. S. D Wahidabanu

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Various fairness models and criteria proposed by academia and industries for wired networks can be applied for ad hoc wireless network. The end-to-end fairness in an ad hoc wireless network is a challenging task compared to wired networks, which has not been addressed effectively. Most of the traffic in an ad hoc network are transport layer flows and thus the fairness of transport layer flows has attracted the interest of the researchers. The factors such as MAC protocol, routing protocol, the length of a route, buffer size, active queue management algorithm and the congestion control algorithms affects the fairness of transport layer flows. In this paper, we have considered the rate of data transmission, the queue management and packet scheduling technique. The ad hoc network is dynamic in nature due to various parameters such as transmission of control packets, multihop nature of forwarding packets, changes in source and destination nodes, changes in the routing path influences determining throughput and fairness among the concurrent flows. In addition, the effect of interaction between the protocol in the data link and transport layers has also plays a role in determining the rate of the data transmission. We maintain queue for each flow and the delay information of each flow is maintained accordingly. The pre-processing of flow is done up to the network layer only. The source and destination address information is used for separating the flow and the transport layer information is not used. This minimizes the delay in the network. Each flow is attached to a timer and is updated dynamically. Finite State Machine (FSM) is proposed for queue and transmission control mechanism. The performance of the proposed approach is evaluated in ns-2 simulation environment. The throughput and fairness based on mobility for different flows used as performance metrics. We have compared the performance of the proposed approach with ATP and the transport layer information is used. This minimizes the delay in the network. Each flow is attached to a timer and is updated dynamically. Finite State Machine (FSM) is proposed for queue and transmission control mechanism. The performance of the proposed approach is evaluated in ns-2 simulation environment. The throughput and fairness based on not mobility for different flows used as performance metrics. We have compared the performance of the proposed approach with ATP and MC-MLAS and the performance of the proposed approach is encouraging.

Keywords: ATP, End-to-End fairness, FSM, MAC, QoS.

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Authors: Samuel O. Alamu, Seong W. Lee, Blaise Kalmia, Marc J. Louise Caballes, Xuejun Qian

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The application of combustion technologies for thermal conversion of biomass and solid wastes to energy has been a major solution to the effective handling of wastes over a long period of time. Lab-scale biomass combustion systems have been observed to be economically viable and socially acceptable, but major concerns are the environmental impacts of the process and deviation of temperature distribution within the combustion chamber. Both high and low combustion chamber temperature may affect the overall combustion efficiency and gaseous emissions. Therefore, there is an urgent need to develop a control system which measures the deviations of chamber temperature from set target values, sends these deviations (which generates disturbances in the system) in the form of feedback signal (as input), and control operating conditions for correcting the errors. In this research study, major components of the feedback control system were determined, assembled, and tested. In addition, control algorithms were developed to actuate operating conditions (e.g., air velocity, fuel feeding rate) using ladder logic functions embedded in the Programmable Logic Controller (PLC). The developed control algorithm having chamber temperature as a feedback signal is integrated into the lab-scale swirling fluidized bed combustor (SFBC) to investigate the temperature distribution at different heights of the combustion chamber based on various operating conditions. The air blower rates and the fuel feeding rates obtained from automatic control operations were correlated with manual inputs. There was no observable difference in the correlated results, thus indicating that the written PLC program functions were adequate in designing the experimental study of the lab-scale SFBC. The experimental results were analyzed to study the effect of air velocity operating at 222-273 ft/min and fuel feeding rate of 60-90 rpm on the chamber temperature. The developed temperature-based feedback control system was shown to be adequate in controlling the airflow and the fuel feeding rate for the overall biomass combustion process as it helps to minimize the steady-state error.

Keywords: Air flow, biomass combustion, feedback control system, fuel feeding, ladder logic, programmable logic controller, temperature.

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Authors: Astrid Bagireanu, Julio Bros-Williamson, Mila Duncheva, John Currie

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Digital Twins (DTs) have entered the built environment from more established industries like aviation and manufacturing, although there has never been a common goal for utilising DTs at scale. Their assimilation into the built environment lacked its very own handover documentation: how should DTs be implemented into a project and what responsibilities should each project stakeholder hold in the realisation of a DT vision. What is needed is an approach to translate these requirements into actionable DT dimensions. This paper presents a foundation for an overarching framework specific to the built environment. For the purposes of this research, the project timeline is established by referencing the Royal Institute of British Architects (RIBA) Plan of Work from 2020, providing a foundation for delineating project stages. The RIBA Plan of Work consists of eight stages designed to inform on the definition, briefing, design, coordination, construction, handover, and use of a built asset. Similar project stages are utilised in other countries; therefore, the recommendations from the interviews presented in this paper are applicable internationally. Simultaneously, there is not a single mainstream software resource that leverages DT abilities. This ambiguity meets an unparalleled ambition from governments and industries worldwide to achieve a national grid of interconnected DTs. For the construction industry to access these benefits, it necessitates a defined starting point. This research aims to provide a comprehensive understanding of the potential applications and ramifications of DT in the context of the built environment. This paper is an integral part of a larger research aimed at developing a conceptual framework for the Architecture, Engineering, and Construction (AEC) sector following a conventional project timeline. Therefore, this paper plays a pivotal role in providing practical insights and a tangible foundation for developing a stage-by-stage approach to assimilate the potential of DT within the built environment. First, the research focuses on a review of relevant literature, albeit acknowledging the inherent constraint of limited sources available. Secondly, a qualitative study compiling the views of 14 DT experts is presented, concluding with an inductive analysis of the interview findings - ultimately highlighting the barriers and strengths of DT in the context of framework development. As parallel developments aim to progress net-zero-centred design and improve project efficiencies across the built environment, the limited resources available to support DTs should be leveraged to propel the industry to reach its digitalisation era, in which AEC stakeholders have a fundamental role in understanding this, from the earliest stages of a project.

Keywords: Digital twins, decision making, design, net-zero, built environment.

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Authors: Mehmet Altınöz

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This study focuses on bureau management technologies and information systems in developing countries. Developing countries use such systems which facilitate executive and organizational functions through the utilization of bureau management technologies and provide the executive staff with necessary information. The concepts of data and information differ from each other in developing countries, and thus the concepts of data processing and information processing are different. Symbols represent ideas, objects, figures, letters and numbers. Data processing system is an integrated system which deals with the processing of the data related to the internal and external environment of the organization in order to make decisions, create plans and develop strategies; it goes without saying that this system is composed of both human beings and machines. Information is obtained through the acquisition and the processing of data. On the other hand, data are raw communicative messages. Within this framework, data processing equals to producing plausible information out of raw data. Organizations in developing countries need to obtain information relevant to them because rapid changes in the organizational arena require rapid access to accurate information. The most significant role of the directors and managers who work in the organizational arena is to make decisions. Making a correct decision is possible only when the directors and managers are equipped with sound ideas and appropriate information. Therefore, acquisition, organization and distribution of information gain significance. Today-s organizations make use of computer-assisted “Management Information Systems" in order to obtain and distribute information. Decision Support System which is closely related to practice is an information system that facilitates the director-s task of making decisions. Decision Support System integrates human intelligence, information technology and software in order to solve the complex problems. With the support of the computer technology and software systems, Decision Support System produces information relevant to the decision to be made by the director and provides the executive staff with supportive ideas about the decision. Artificial Intelligence programs which transfer the studies and experiences of the people to the computer are called expert systems. An expert system stores expert information in a limited area and can solve problems by deriving rational consequences. Bureau management technologies and information systems in developing countries create a kind of information society and information economy which make those countries have their places in the global socio-economic structure and which enable them to play a reasonable and fruitful role; therefore it is of crucial importance to make use of information and management technologies in order to work together with innovative and enterprising individuals and it is also significant to create “scientific policies" based on information and technology in the fields of economy, politics, law and culture.

Keywords: Bureau Management, Information Systems.

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Authors: Sayem Zafar, Mahmood Rahi

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Rigorous international maritime regulations are in place to limit boat and ship hydrocarbon emissions. The global sustainability goals are reducing the fuel consumption and minimizing the emissions from the ships and boats. These maritime sustainability goals have attracted a lot of research interest. Energy harvesting and storage system is designed in this study based on hybrid renewable and conventional energy systems. This energy harvesting and storage system is designed for marine applications, such as, boats and small ships. These systems can be utilized for mobile use or off-grid remote electrification. This study analyzed the use of micro power generation for boats and small ships. The energy harvesting and storage system has two distinct systems i.e. dockside shore-based system and on-board system. The shore-based system consists of a small wind turbine, photovoltaic (PV) panels, small gas turbine, hydrogen generator and high-pressure hydrogen storage tank. This dockside system is to provide easy access to the boats and small ships for supply of hydrogen. The on-board system consists of hydrogen storage tanks and fuel cells. The wind turbine and PV panels generate electricity to operate electrolyzer. A small gas turbine is used as a supplementary power system to contribute in case the hybrid renewable energy system does not provide the required energy. The electrolyzer performs the electrolysis on distilled water to produce hydrogen. The hydrogen is stored in high-pressure tanks. The hydrogen from the high-pressure tank is filled in the low-pressure tanks on-board seagoing vessels to operate the fuel cell. The boats and small ships use the hydrogen fuel cell to provide power to electric propulsion motors and for on-board auxiliary use. For shore-based system, a small wind turbine with the total length of 4.5 m and the disk diameter of 1.8 m is used. The small wind turbine dimensions make it big enough to be used to charge batteries yet small enough to be installed on the rooftops of dockside facility. The small dimensions also make the wind turbine easily transportable. In this paper, PV, sizing and solar flux are studied parametrically. System performance is evaluated under different operating and environmental conditions. The parametric study is conducted to evaluate the energy output and storage capacity of energy storage system. Results are generated for a wide range of conditions to analyze the usability of hybrid energy harvesting and storage system. This energy harvesting method significantly improves the usability and output of the renewable energy sources. It also shows that small hybrid energy systems have promising practical applications.

Keywords: Energy harvesting, fuel cell, hybrid energy system, hydrogen, wind turbine.

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Authors: Jung-Hong Hong, Jing-Cen Yang, Cai-Yu Ou

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The analysis of geographic inequality heavily relies on the use of location-enabled statistical data and quantitative measures to present the spatial patterns of the selected phenomena and analyze their differences. To protect the privacy of individual instance and link to administrative units, point-based datasets are spatially aggregated to area-based statistical datasets, where only the overall status for the selected levels of spatial units is used for decision making. The partition of the spatial units thus has dominant influence on the outcomes of the analyzed results, well known as the Modifiable Areal Unit Problem (MAUP). A new spatial reference framework, the Taiwan Geographical Statistical Classification (TGSC), was recently introduced in Taiwan based on the spatial partition principles of homogeneous consideration of the number of population and households. Comparing to the outcomes of the traditional township units, TGSC provides additional levels of spatial units with finer granularity for presenting spatial phenomena and enables domain experts to select appropriate dissemination level for publishing statistical data. This paper compares the results of respectively using TGSC and township unit on the mortality data and examines the spatial characteristics of their outcomes. For the mortality data between the period of January 1^st, 2008 and December 31^st, 2010 of the Taitung County, the all-cause age-standardized death rate (ASDR) ranges from 571 to 1757 per 100,000 persons, whereas the 2^nd dissemination area (TGSC) shows greater variation, ranged from 0 to 2222 per 100,000. The finer granularity of spatial units of TGSC clearly provides better outcomes for identifying and evaluating the geographic inequality and can be further analyzed with the statistical measures from other perspectives (e.g., population, area, environment.). The management and analysis of the statistical data referring to the TGSC in this research is strongly supported by the use of Geographic Information System (GIS) technology. An integrated workflow that consists of the tasks of the processing of death certificates, the geocoding of street address, the quality assurance of geocoded results, the automatic calculation of statistic measures, the standardized encoding of measures and the geo-visualization of statistical outcomes is developed. This paper also introduces a set of auxiliary measures from a geographic distribution perspective to further examine the hidden spatial characteristics of mortality data and justify the analyzed results. With the common statistical area framework like TGSC, the preliminary results demonstrate promising potential for developing a web-based statistical service that can effectively access domain statistical data and present the analyzed outcomes in meaningful ways to avoid wrong decision making.

Keywords: Mortality map, spatial patterns, statistical area, variation.

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Authors: Sagir M. Yusuf, Chris Baber

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In this paper, we describe how to achieve knowledge understanding and prediction (Situation Awareness (SA)) for multiple-agents conducting searching activity using Bayesian inferential reasoning and learning. Bayesian Belief Network was used to monitor agents' knowledge about their environment, and cases are recorded for the network training using expectation-maximisation or gradient descent algorithm. The well trained network will be used for decision making and environmental situation prediction. Forest fire searching by multiple UAVs was the use case. UAVs are tasked to explore a forest and find a fire for urgent actions by the fire wardens. The paper focused on two problems: (i) effective agents’ path planning strategy and (ii) knowledge understanding and prediction (SA). The path planning problem by inspiring animal mode of foraging using Lévy distribution augmented with Bayesian reasoning was fully described in this paper. Results proof that the Lévy flight strategy performs better than the previous fixed-pattern (e.g., parallel sweeps) approaches in terms of energy and time utilisation. We also introduced a waypoint assessment strategy called k-previous waypoints assessment. It improves the performance of the ordinary levy flight by saving agent’s resources and mission time through redundant search avoidance. The agents (UAVs) are to report their mission knowledge at the central server for interpretation and prediction purposes. Bayesian reasoning and learning were used for the SA and results proof effectiveness in different environments scenario in terms of prediction and effective knowledge representation. The prediction accuracy was measured using learning error rate, logarithm loss, and Brier score and the result proves that little agents mission that can be used for prediction within the same or different environment. Finally, we described a situation-based knowledge visualization and prediction technique for heterogeneous multi-UAV mission. While this paper proves linkage of Bayesian reasoning and learning with SA and effective searching strategy, future works is focusing on simplifying the architecture.

Keywords: Lèvy flight, situation awareness, multi-agent system, multi-robot coordination, autonomous system, swarm intelligence.

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Authors: Wisam H. Benamer, Ehab A. Elfallah, Mohamed A. Elshaari, Farag A. Elshaari

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A challenge for laboratories is to provide bacterial identification and antibiotic sensitivity results within a short time. Hence, advancement in the required technology is desirable to improve timing, accuracy and quality. Even with the current advances in methods used for both phenotypic and genotypic identification of bacteria the need is there to develop method(s) that enhance the outcome of bacteriology laboratories in accuracy and time. The hypothesis introduced here is based on the assumption that the chromosome of any bacteria contains unique sequences that can be used for its identification and typing. The outcome of a pilot study designed to test this hypothesis is reported in this manuscript. Methods: The complete chromosome sequences of several bacterial species were downloaded to use as search targets for unique sequences. Visual basic and SQL server (2014) were used to generate a complete set of 18-base long primers, a process started with reverse translation of randomly chosen 6 amino acids to limit the number of the generated primers. In addition, the software used to scan the downloaded chromosomes using the generated primers for similarities was designed, and the resulting hits were classified according to the number of similar chromosomal sequences, i.e., unique or otherwise. Results: All primers that had identical/similar sequences in the selected genome sequence(s) were classified according to the number of hits in the chromosomes search. Those that were identical to a single site on a single bacterial chromosome were referred to as unique. On the other hand, most generated primers sequences were identical to multiple sites on a single or multiple chromosomes. Following scanning, the generated primers were classified based on ability to differentiate between medically important bacterial and the initial results looks promising. Conclusion: A simple strategy that started by generating primers was introduced; the primers were used to screen bacterial genomes for match. Primer(s) that were uniquely identical to specific DNA sequence on a specific bacterial chromosome were selected. The identified unique sequence can be used in different molecular diagnostic techniques, possibly to identify bacteria. In addition, a single primer that can identify multiple sites in a single chromosome can be exploited for region or genome identification. Although genomes sequences draft of isolates of organism DNA enable high throughput primer design using alignment strategy, and this enhances diagnostic performance in comparison to traditional molecular assays. In this method the generated primers can be used to identify an organism before the draft sequence is completed. In addition, the generated primers can be used to build a bank for easy access of the primers that can be used to identify bacteria.

Keywords: Bacteria chromosome, bacterial identification, sequence, primer generation.

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Authors: Nicolò Vaiana, Filip C. Filippou, Giorgio Serino

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In order to reduce numerical computations in the nonlinear dynamic analysis of seismically base-isolated structures, a Mixed Explicit-Implicit time integration Method (MEIM) has been proposed. Adopting the explicit conditionally stable central difference method to compute the nonlinear response of the base isolation system, and the implicit unconditionally stable Newmark’s constant average acceleration method to determine the superstructure linear response, the proposed MEIM, which is conditionally stable due to the use of the central difference method, allows to avoid the iterative procedure generally required by conventional monolithic solution approaches within each time step of the analysis. The main aim of this paper is to investigate the stability and computational efficiency of the MEIM when employed to perform the nonlinear time history analysis of base-isolated structures with sliding bearings. Indeed, in this case, the critical time step could become smaller than the one used to define accurately the earthquake excitation due to the very high initial stiffness values of such devices. The numerical results obtained from nonlinear dynamic analyses of a base-isolated structure with a friction pendulum bearing system, performed by using the proposed MEIM, are compared to those obtained adopting a conventional monolithic solution approach, i.e. the implicit unconditionally stable Newmark’s constant acceleration method employed in conjunction with the iterative pseudo-force procedure. According to the numerical results, in the presented numerical application, the MEIM does not have stability problems being the critical time step larger than the ground acceleration one despite of the high initial stiffness of the friction pendulum bearings. In addition, compared to the conventional monolithic solution approach, the proposed algorithm preserves its computational efficiency even when it is adopted to perform the nonlinear dynamic analysis using a smaller time step.

Keywords: Base isolation, computational efficiency, mixed explicit-implicit method, partitioned solution approach, stability.

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Authors: Yu-Yu Wang, Shih-Hua Hsieh, Ru-Shian Hsieh

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Wishes and choices being respected, and the right to be supported rather than coerced, have been internationally recognized as the human rights of persons with mental illness. In Taiwan, ‘coerced hospitalization’ has become difficult since the revision of the mental health legislation in 2007. Despite trend towards human rights, the real problem families face when their family members are in mental health crisis is the lack of alternative services. This study aims to explore: 1) When is hospitalization seen as the only solution by family members? 2) What are the barriers for arranging hospitalization, and how are they managed? 3) What have family carers learned, in their experiences of caring for their family members with mental illness? To answer these questions, qualitative approach was adopted, and focus group interviews were taken to collect data. This study includes 24 family carers. The main findings of this research include: First, hospital is the last resort for carers in helplessness. Family carers tend to do everything they could to provide care at home for their family members with mental illness. Carers seek hospitalization only when a patient’s behavior is too violent, weird, and/or abnormal, and beyond their ability to manage. Hospitalization, nevertheless, is never an easy choice. Obstacles emanate from the attitudes of the medical doctors, the restricted areas of ambulance service, and insufficient information from the carers’ part. On the other hand, with some professionals’ proactive assistance, access to medical care while in crisis becomes possible. Some family carers obtained help from the medical doctor, nurse, therapist and social workers. Some experienced good help from policemen, taxi drivers, and security guards at the hospital. The difficulty in accessing medical care prompts carers to work harder on assisting their family members with mental illness to stay in stable states. Carers found different ways of helping the ‘person’ to get along with the ‘illness’ and have better quality of life. Taking back ‘the right to control’ in utilizing medication, from passiveness to negotiating with medical doctors and seeking alternative therapies, are seen in many carers’ efforts. Besides, trying to maintain regular activities in daily life and play normal family roles are also experienced as important. Furthermore, talking with the patient as a person is also important. The authors conclude that in order to protect the human rights of persons with mental illness, it is crucial to make the medical care system more flexible and to make the services more humane: sufficient information should be provided and communicated, and efforts should be made to maintain the person’s social roles and to support the family.

Keywords: Family carers, coercive treatment, independent living, mental health crisis, persons with mental illness.

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Authors: Jožef Ritonja, Bojan Grčar, Boštjan Polajžer

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In recent years, electricity trade between neighboring countries has become increasingly intense. Increasing power transmission over long distances has resulted in an increase in the oscillations of the transmitted power. The damping of the oscillations can be carried out with the reconfiguration of the network or the replacement of generators, but such solution is not economically reasonable. The only cost-effective solution to improve the damping of power oscillations is to use power system stabilizers. Power system stabilizer represents a part of synchronous generator control system. It utilizes semiconductor’s excitation system connected to the rotor field excitation winding to increase the damping of the power system. The majority of the synchronous generators are equipped with the conventional power system stabilizers with fixed parameters. The control structure of the conventional power system stabilizers and the tuning procedure are based on the linear control theory. Conventional power system stabilizers are simple to realize, but they show non-sufficient damping improvement in the entire operating conditions. This is the reason that advanced control theories are used for development of better power system stabilizers. In this paper, the adaptive control theory for power system stabilizers design and synthesis is studied. The presented work is focused on the use of model reference adaptive control approach. Control signal, which assures that the controlled plant output will follow the reference model output, is generated by the adaptive algorithm. Adaptive gains are obtained as a combination of the "proportional" term and with the σ-term extended "integral" term. The σ-term is introduced to avoid divergence of the integral gains. The necessary condition for asymptotic tracking is derived by means of hyperstability theory. The benefits of the proposed model reference adaptive power system stabilizer were evaluated as objectively as possible by means of a theoretical analysis, numerical simulations and laboratory realizations. Damping of the synchronous generator oscillations in the entire operating range was investigated. Obtained results show the improved damping in the entire operating area and the increase of the power system stability. The results of the presented work will help by the development of the model reference power system stabilizer which should be able to replace the conventional stabilizers in power systems.

Keywords: Power system, stability, oscillations, power system stabilizer, model reference adaptive control.

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Authors: Priyanka Chaudhary, M. Rizwan

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This paper presents a grid synchronization technique based on adaptive notch filter for SPV (Solar Photovoltaic) system along with MPPT (Maximum Power Point Tracking) techniques. An efficient grid synchronization technique offers proficient detection of various components of grid signal like phase and frequency. It also acts as a barrier for harmonics and other disturbances in grid signal. A reference phase signal synchronized with the grid voltage is provided by the grid synchronization technique to standardize the system with grid codes and power quality standards. Hence, grid synchronization unit plays important role for grid connected SPV systems. As the output of the PV array is fluctuating in nature with the meteorological parameters like irradiance, temperature, wind etc. In order to maintain a constant DC voltage at VSC (Voltage Source Converter) input, MPPT control is required to track the maximum power point from PV array. In this work, a variable step size P & O (Perturb and Observe) MPPT technique with DC/DC boost converter has been used at first stage of the system. This algorithm divides the dPpv/dVpv curve of PV panel into three separate zones i.e. zone 0, zone 1 and zone 2. A fine value of tracking step size is used in zone 0 while zone 1 and zone 2 requires a large value of step size in order to obtain a high tracking speed. Further, adaptive notch filter based control technique is proposed for VSC in PV generation system. Adaptive notch filter (ANF) approach is used to synchronize the interfaced PV system with grid to maintain the amplitude, phase and frequency parameters as well as power quality improvement. This technique offers the compensation of harmonics current and reactive power with both linear and nonlinear loads. To maintain constant DC link voltage a PI controller is also implemented and presented in this paper. The complete system has been designed, developed and simulated using SimPower System and Simulink toolbox of MATLAB. The performance analysis of three phase grid connected solar photovoltaic system has been carried out on the basis of various parameters like PV output power, PV voltage, PV current, DC link voltage, PCC (Point of Common Coupling) voltage, grid voltage, grid current, voltage source converter current, power supplied by the voltage source converter etc. The results obtained from the proposed system are found satisfactory.

Keywords: Solar photovoltaic systems, MPPT, voltage source converter, grid synchronization technique.

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Authors: E. Dabbour, S. M. Easa

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Most of the collision warning systems currently available in the automotive market are mainly designed to warn against imminent rear-end and lane-changing collisions. No collision warning system is commercially available to warn against imminent turning collisions at intersections, especially for left-turn collisions when a driver attempts to make a left-turn at either a signalized or non-signalized intersection, conflicting with the path of other approaching vehicles traveling on the opposite-direction traffic stream. One of the major factors that lead to left-turn collisions is the human error and misjudgment of the driver of the turning vehicle when perceiving the speed and acceleration of other vehicles traveling on the opposite-direction traffic stream; therefore, using a properly-designed collision warning system will likely reduce, or even eliminate, this type of collisions by reducing human error. This paper introduces perceptual framework for a proposed collision warning system that can detect imminent left-turn collisions at intersections. The system utilizes a commercially-available detection sensor (either a radar sensor or a laser detector) to detect approaching vehicles traveling on the opposite-direction traffic stream and calculate their speeds and acceleration rates to estimate the time-tocollision and compare that time to the time required for the turning vehicle to clear the intersection. When calculating the time required for the turning vehicle to clear the intersection, consideration is given to the perception-reaction time of the driver of the turning vehicle, which is the time required by the driver to perceive the message given by the warning system and react to it by engaging the throttle. A regression model was developed to estimate perception-reaction time based on age and gender of the driver of the host vehicle. Desired acceleration rate selected by the driver of the turning vehicle, when making the left-turn movement, is another human factor that is considered by the system. Another regression model was developed to estimate the acceleration rate selected by the driver of the turning vehicle based on driver-s age and gender as well as on the location and speed of the nearest approaching vehicle along with the maximum acceleration rate provided by the mechanical characteristics of the turning vehicle. By comparing time-to-collision with the time required for the turning vehicle to clear the intersection, the system displays a message to the driver of the turning vehicle when departure is safe. An application example is provided to illustrate the logic algorithm of the proposed system.

Keywords: Collision warning systems, intelligent transportationsystems, vehicle safety.

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Authors: Victoria C. Valdebenito

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Located within the context of accelerating globalization in the 21^st-century knowledge society, this paper focuses on one selected university in Chile at which radical curriculum policy changes have been taking place, diverging from the traditional curriculum in Chile at the undergraduate level as a section of a larger investigation. Using a ‘policy trajectory’ framework, and guided by the interpretivist approach to research, interview transcripts and institutional documents were analyzed in relation to the meso (university administration) and the micro (academics) level. Inside the case study, participants from the university administration and academic levels were selected both via snow-ball technique and purposive selection, thus they had different levels of seniority, with some participating actively in the curriculum reform processes. Guided by an interpretivist approach to research, documents and interview transcripts were analyzed to reveal major themes emerging from the data. A further ‘bigger picture’ analysis guided by critical theory was then undertaken, involving interrogation of underlying ideologies and how political and economic interests influence the cultural production of policy. The case-study university was selected because it represents a traditional and old case of university setting in the country, undergoing curriculum changes based on international trends such as the competency model and the liberal arts. Also, it is representative of a particular socioeconomic sector of the country. Access to the university was gained through email contact. Qualitative research methods were used, namely interviews and analysis of institutional documents. In all, 18 people were interviewed. The number was defined by when the saturation criterion was met. Semi-structured interview schedules were based on the four research questions about influences, policy texts, policy enactment and longer-term outcomes. Triangulation of information was used for the analysis. While there was no intention to generalize the specific findings of the case study, the results of the research were used as a focus for engagement with broader themes, often evident in global higher education policy developments. The research results were organized around major themes in three of the four contexts of the ‘policy trajectory’. Regarding the context of influences and the context of policy text production, themes relate to hegemony exercised by first world countries’ universities in the higher education field, its associated neoliberal ideology, with accountability and the discourse of continuous improvement, the local responses to those pressures, and the value of interdisciplinarity. Finally, regarding the context of policy practices and effects (enactment), themes emerged around the impacts of the curriculum changes on university staff, students, and resistance amongst academics. The research concluded with a few recommendations that potentially provide ‘food for thought’ beyond the localized settings of this study, as well as possibilities for further research.

Keywords: Curriculum, policy, higher education, global-local dynamics.

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Authors: S. Mehrab Amiri, Nasser Talebbeydokhti

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Modeling sediment transport processes by means of numerical approach often poses severe challenges. In this way, a number of techniques have been suggested to solve flow and sediment equations in decoupled, semi-coupled or fully coupled forms. Furthermore, in order to capture flow discontinuities, a number of techniques, like artificial viscosity and shock fitting, have been proposed for solving these equations which are mostly required careful calibration processes. In this research, a numerical scheme for solving shallow water and Exner equations in fully coupled form is presented. First-Order Centered scheme is applied for producing required numerical fluxes and the reconstruction process is carried out toward using Monotonic Upstream Scheme for Conservation Laws to achieve a high order scheme.  In order to satisfy C-property of the scheme in presence of bed topography, Surface Gradient Method is proposed. Combining the presented scheme with fourth order Runge-Kutta algorithm for time integration yields a competent numerical scheme. In addition, to handle non-prismatic channels problems, Cartesian Cut Cell Method is employed. A trained Multi-Layer Perceptron Artificial Neural Network which is of Feed Forward Back Propagation (FFBP) type estimates sediment flow discharge in the model rather than usual empirical formulas. Hydrodynamic part of the model is tested for showing its capability in simulation of flow discontinuities, transcritical flows, wetting/drying conditions and non-prismatic channel flows. In this end, dam-break flow onto a locally non-prismatic converging-diverging channel with initially dry bed conditions is modeled. The morphodynamic part of the model is verified simulating dam break on a dry movable bed and bed level variations in an alluvial junction. The results show that the model is capable in capturing the flow discontinuities, solving wetting/drying problems even in non-prismatic channels and presenting proper results for movable bed situations. It can also be deducted that applying Artificial Neural Network, instead of common empirical formulas for estimating sediment flow discharge, leads to more accurate results.

Keywords: Artificial neural network, morphodynamic model, sediment continuity equation, shallow water equations.

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Authors: Suraiya Jabin, Kamal K. Bharadwaj

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In the recent past Learning Classifier Systems have been successfully used for data mining. Learning Classifier System (LCS) is basically a machine learning technique which combines evolutionary computing, reinforcement learning, supervised or unsupervised learning and heuristics to produce adaptive systems. A LCS learns by interacting with an environment from which it receives feedback in the form of numerical reward. Learning is achieved by trying to maximize the amount of reward received. All LCSs models more or less, comprise four main components; a finite population of condition–action rules, called classifiers; the performance component, which governs the interaction with the environment; the credit assignment component, which distributes the reward received from the environment to the classifiers accountable for the rewards obtained; the discovery component, which is responsible for discovering better rules and improving existing ones through a genetic algorithm. The concatenate of the production rules in the LCS form the genotype, and therefore the GA should operate on a population of classifier systems. This approach is known as the 'Pittsburgh' Classifier Systems. Other LCS that perform their GA at the rule level within a population are known as 'Mitchigan' Classifier Systems. The most predominant representation of the discovered knowledge is the standard production rules (PRs) in the form of IF P THEN D. The PRs, however, are unable to handle exceptions and do not exhibit variable precision. The Censored Production Rules (CPRs), an extension of PRs, were proposed by Michalski and Winston that exhibit variable precision and supports an efficient mechanism for handling exceptions. A CPR is an augmented production rule of the form: IF P THEN D UNLESS C, where Censor C is an exception to the rule. Such rules are employed in situations, in which conditional statement IF P THEN D holds frequently and the assertion C holds rarely. By using a rule of this type we are free to ignore the exception conditions, when the resources needed to establish its presence are tight or there is simply no information available as to whether it holds or not. Thus, the IF P THEN D part of CPR expresses important information, while the UNLESS C part acts only as a switch and changes the polarity of D to ~D. In this paper Pittsburgh style LCSs approach is used for automated discovery of CPRs. An appropriate encoding scheme is suggested to represent a chromosome consisting of fixed size set of CPRs. Suitable genetic operators are designed for the set of CPRs and individual CPRs and also appropriate fitness function is proposed that incorporates basic constraints on CPR. Experimental results are presented to demonstrate the performance of the proposed learning classifier system.

Keywords: Censored Production Rule, Data Mining, GeneticAlgorithm, Learning Classifier System, Machine Learning, PittsburgApproach, , Reinforcement learning.

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Authors: K. J. Sannapapamma, H. Malligawad Lokanath, Sakeena Naikwadi

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Eco-friendly textiles are gaining importance among the consumers and textile manufacturers in the healthcare sector due to increased environmental pollution which leads to several health and environmental hazards. Hence, the research was designed to cultivate and develop the organic cotton knit, to prepare and characterize the Vetiver oil microcapsules for textile finishing and to access the wash durability of finished knits. The cotton SAHANA variety grown under organic production systems was processed and spun into 30 single yarn dyed with four natural colorants (Arecanut slurry, Eucalyptus leaves, Pomegranate rind and Indigo) and eco dyed yarn was further used for development of single jersy knitted fabric. Vetiveria zizanioides is an aromatic grass which is being traditionally used in medicine and perfumery. Vetiver essential oil was used for preparation of microcapsules by interfacial polymerization technique subjected to Gas Chromatography Mass Spectrometry (GCMS), Fourier Transform Infrared Spectroscopy (FTIR), Thermo Gravimetric Analyzer (TGA) and Scanning Electron Microscope (SEM) for characterization of microcapsules. The knitted fabric was finished with vetiver oil microcapsules by exhaust and pad dry cure methods. The finished organic knit was assessed for laundering on antimicrobial efficiency and aroma intensity. GCMS spectral analysis showed that, diethyl phthalate (28%) was the major compound found in vetiver oil followed by isoaromadendrene epoxide (7.72%), beta-vetivenene (6.92%), solavetivone (5.58%), aromadenderene, azulene and khusimol. Bioassay explained that, the vetiver oil and diluted vetiver oil possessed greater zone of inhibition against S. aureus and E. coli than the coconut oil. FTRI spectra of vetiver oil and microcapsules possessed similar peaks viz., C-H, C=C & C꞊O stretching and additionally oil microcapsules possessed the peak of 3331.24 cm^-1 at 91.14 transmittance was attributed to N-H stretches. TGA of oil microcapsules revealed that, there was a minimum weight loss (5.835%) recorded at 467.09°C compared to vetiver oil i.e., -3.026% at the temperature of 396.24°C. The shape of the microcapsules was regular and round, some were spherical in shape and few were rounded by small aggregates. Irrespective of methods of application, organic cotton knits finished with microcapsules by pad dry cure method showed maximum zone of inhibition compared to knits finished by exhaust method against S. aureus and E. coli. The antimicrobial activity of the finished samples was subjected to multiple washing which indicated that knits finished with pad dry cure method showed a zone of inhibition even after 20^th wash and better aroma retention compared to knits finished with the exhaust method of application. Further, the group of respondents rated that the 5^th washed samples had the greater aroma intensity in both the methods than the other samples. Thus, the vetiver microencapsulated organic cotton knits are free from hazardous chemicals and have multi-functional properties that can be suitable for medical and healthcare textiles.

Keywords: Exhaust and pad dry cure finishing, interfacial polymerization, organic cotton knits, vetiver oil microcapsules.

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Authors: Sanjeev Kumar Appicharla

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This paper presents the results of the modelling and analysis of the European Railway Traffic Management (ERTMS) safety critical incident to raise awareness of biases in systems engineering process on the Cambrian Railway in the UK using the RAIB 17/2019 as a primary input. The RAIB, the UK independent accident investigator, published the Report- RAIB 17/2019 giving the details of their investigation of the focal event in the form of immediate cause, causal factors and underlying factors and recommendations to prevent a repeat of the safety-critical incident on the Cambrian Line. The Systems for Investigation of Railway Interfaces (SIRI) is the Methodology used to model and analyse the safety-critical incident. The SIRI Methodology uses the Swiss Cheese Model to model the incident and identify latent failure conditions (potentially less than adequate conditions) by means of the Management Oversight and Risk Tree technique. The benefits of the SIRI Methodology are threefold: first is that it incorporates “Heuristics and Biases” approach, in the Management Oversight and Risk Tree technique to identify systematic errors. Civil engineering and programme management railway professionals are aware of role “optimism bias” plays in programme cost overruns and are aware of bow tie (fault and event tree) model-based safety risk modelling technique. However, the role of systematic errors due to “Heuristics and Biases” is not appreciated as yet. This overcomes the problems of omission of human and organisational factors from accident analysis. Second, the scope of the investigation includes all levels of the socio-technical system, including government, regulatory, railway safety bodies, duty holders, signalling firms and transport planners, and front-line staff such that lessons learned at the decision making and implementation level as well. Third, the author’s past accident case studies are supplemented with research pieces of evidence drawn from the practitioner’s and academic researchers’ publications as well. This is to discuss the role of system thinking to improve the decision making and risk management processes and practices in the IEC 15288 Systems Engineering standard, and in the industrial context such as the GB railways and Artificial Intelligence (AI) contexts as well.

Keywords: Accident analysis, AI algorithm internal audit, bounded rationality, Byzantine failures, heuristics and biases approach.

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Authors: Harriet Koshie Lamptey, Richard Boateng

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Mobile learning (m-learning) is a novel approach to knowledge acquisition and dissemination and is gaining global attention. Steady progress in wireless technologies and the portability of communication devices continue to broaden the scope and use of mobiles. With the convergence of Web functionality onto mobile platforms and the affordability and availability of mobile technology, m-learning has the potential of being the next prevalent channel of education in both formal and informal settings. There is substantive literature on developed countries but the state in developing countries (DCs) however appears vague. This paper is a synthesis of extant literature on mobile learning in DCs. The research interest is based on the fact that in DCs, mobile communication and internet connectivity are popular. However, its use in education is under explored. There are some reviews on the state, conceptualizations, trends and teacher education, but to the authors’ knowledge, no study has focused on mobile learning adoption and integration issues. This study examines issues and gaps associated with its adoption and integration in DCs higher education institutions. A qualitative build-up of literature was conducted using articles pooled from electronic databases (Google Scholar and ERIC). To enable criteria for inclusion and incorporate diverse study perspectives, search terms used were m-learning, DCs, higher education institutions, challenges, benefits, impact, gaps and issues. The synthesis revealed that though mobile technology has diffused globally, its pedagogical pursuit in DCs remains quite low. The absence of a mobile Web and the difficulty of resource conversion into mobile format due to lack of funding and technical competence is a stumbling block. Again, the lack of established design and implementation rules to guide the development of m-learning platforms in DCs is a hindrance. The absence of access restrictions on devices poses security threats to institutional systems. Negative perceptions that devices are taking over faculty roles lead to resistance in some situations. Resistance to change can be a hindrance to the acceptance and success of new systems. Lack of interest for m-learning is also attributed to lower technological literacy levels of the underprivileged masses. Scholarly works on m-learning in DCs is yet to mature. Most technological innovations are handed down from developed countries, and this constantly creates a lag for DCs. Lack of theoretical grounding was also identified which reduces the objectivity of study reports. The socio-cultural terrain of DCs results in societies with different views and needs that have been identified as a hindrance to research. Institutional commitment decisions, adequate funding for the necessary infrastructural development as well as multiple stakeholder participation is important for project success. Evidence suggests that while adoption decisions are readily made, successful integration of the concept for its full benefits to be realized is often neglected. Recommendations to findings were made to provide possible remedies to identified issues.

Keywords: Developing countries, higher education institutions, mobile learning, literature review.

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Authors: Olivier Mills, Bernard McDonell, Laura A. S. MacDonald

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The increasing availability and quality of internet access throughout the developing world provides an opportunity to utilize online spaces to disseminate water, sanitation and hygiene (WASH) knowledge to practitioners. Since 2001, CAWST has provided in-person education, training and consulting services to thousands of WASH practitioners all over the world, supporting them to start, troubleshoot, improve and expand their WASH projects. As CAWST continues to grow, the organization faces challenges in meeting demand from clients and in providing consistent, timely technical support. In 2012, CAWST began utilizing online spaces to expand its reach by developing a series of resources websites and webinars. CAWST has developed a WASH Education and Training resources website, a Biosand Filter (BSF) Knowledge Base, a Household Water Treatment and Safe Storage Knowledge Base, a mobile app for offline users, a live chat support tool, a WASH e-library, and a series of webinar-style online training sessions to complement its in-person capacity development services. In order to determine the preliminary outcomes of providing these online services, CAWST has monitored and analyzed registration to the online spaces, downloads of the educational materials, and webinar attendance; as well as conducted user surveys. The purpose of this analysis was to find out who was using the online spaces, where users came from, and how the resources were being used. CAWST’s WASH Resources website has served over 5,800 registered users from 3,000 organizations in 183 countries. Additionally, the BSF Knowledge Base has served over 1000 registered users from 68 countries, and over 540 people from 73 countries have attended CAWST’s online training sessions. This indicates that the online spaces are effectively reaching a large numbers of users, from a range of countries. A 2016 survey of the Biosand Filter Knowledge Base showed that approximately 61% of users are practitioners, and 39% are either researchers or students. Of the respondents, 46% reported using the BSF Knowledge Base to initiate a BSF project and 43% reported using the information to train BSF technicians. Finally, 61% indicated they would like even greater support from CAWST’s Technical Advisors going forward. The analysis has provided an encouraging indication that CAWST’s online spaces are contributing to its objective of engaging and supporting WASH practitioners to start, improve and expand their initiatives. CAWST has learned several lessons during the development of these online spaces, in particular related to the resources needed to create and maintain the spaces, and respond to the demand created. CAWST plans to continue expanding its online spaces, improving user experience of the sites, and involving new contributors and content types. Through the use of online spaces, CAWST has been able to increase its global reach and impact without significantly increasing its human resources by connecting WASH practitioners with the information they most need, in a practical and accessible manner. This paper presents on CAWST’s use of online spaces through the CAWST-developed platforms discussed above and the analysis of the use of these platforms.

Keywords: Education and training, knowledge sharing, online resources, water and sanitation.

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Authors: O. Adjoul, A. Feugier, K. Benfriha, A. Aoussat

Abstract:

In general, issues related to design and maintenance are considered in an independent manner. However, the decisions made in these two sets influence each other. The design for maintenance is considered an opportunity to optimize the life cycle cost of a product, particularly in the nuclear or aeronautical field, where maintenance expenses represent more than 60% of life cycle costs. The design of large-scale systems starts with product architecture, a choice of components in terms of cost, reliability, weight and other attributes, corresponding to the specifications. On the other hand, the design must take into account maintenance by improving, in particular, real-time monitoring of equipment through the integration of new technologies such as connected sensors and intelligent actuators. We noticed that different approaches used in the Design For Maintenance (DFM) methods are limited to the simultaneous characterization of the reliability and maintainability of a multi-component system. This article proposes a method of DFM that assists designers to propose dynamic maintenance for multi-component industrial systems. The term "dynamic" refers to the ability to integrate available monitoring data to adapt the maintenance decision in real time. The goal is to maximize the availability of the system at a given life cycle cost. This paper presents an approach for simultaneous optimization of the design and maintenance of multi-component systems. Here the design is characterized by four decision variables for each component (reliability level, maintainability level, redundancy level, and level of monitoring data). The maintenance is characterized by two decision variables (the dates of the maintenance stops and the maintenance operations to be performed on the system during these stops). The DFM model helps the designers choose technical solutions for the large-scale industrial products. Large-scale refers to the complex multi-component industrial systems and long life-cycle, such as trains, aircraft, etc. The method is based on a two-level hybrid algorithm for simultaneous optimization of design and maintenance, using genetic algorithms. The first level is to select a design solution for a given system that considers the life cycle cost and the reliability. The second level consists of determining a dynamic and optimal maintenance plan to be deployed for a design solution. This level is based on the Maintenance Free Operating Period (MFOP) concept, which takes into account the decision criteria such as, total reliability, maintenance cost and maintenance time. Depending on the life cycle duration, the desired availability, and the desired business model (sales or rental), this tool provides visibility of overall costs and optimal product architecture.

Keywords: Availability, design for maintenance, DFM, dynamic maintenance, life cycle cost, LCC, maintenance free operating period, MFOP, simultaneous optimization.

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