Search results for: ethical decision making

Authors: Malraj Bharatha Kiriella

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The purpose of this paper is to investigate the determinants of tourism foreign direct investment (TFDI) to selected developing countries during 1978-2017. The study used pooled panel data to estimate an econometric model. The findings show that market size and institutional barriers are determining factors for TFDI in countries, while other variables of positive country conditions, FDI-related government policy, tourism-related infrastructure and labor conditions are insignificant. The result shows that institutional effects are positive, while market size negatively affects TFDI inflows. The research is limited to eight developing countries. The results can be used to support government policy on TFDI. The paper makes the following contributions: First, it provides important insight and understanding into the TFDI decision-making process in developing countries. Second, both TFDI theory and evidence are minimal, and an econometric model developed on the basis of available literature has been empirically tested.

Keywords: determinants, developing countries, FDI in tourism, panel data

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Authors: M. A. Mulatu, L. C. Chang, Y. S. Han

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Energy harvesting tags with cooperative communication capabilities are emerging as possible infrastructure for internet of things (IoT) applications. This paper studies about the \ cooperative transmission strategy for a network of energy harvesting active networked tags (EnHANTs), that is adapted to the available energy resource and identification request. We consider a network of EnHANT-equipped objects to communicate with the destination either directly or by cooperating with neighboring objects. We formulate the the problem as a Markov decision process (MDP) under synchronised On/Off keying (S-OOK) pulse modulation format. The simulation results are provided to show the the performance of the cooperative transmission policy and compared against the greedy and conservative policies of single-link transmission.

Keywords: cooperative communication, transmission strategy, energy harvesting, Markov decision process, value iteration

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Authors: Yi-Hsien Wang, Fu-Ju Yang, Hwa-Rong Shen, Rui-Lin Tseng

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The business is notably related to the market risk according to the increase of liberalization of financial markets. Hence, the company usually utilized high financial leverage of derivatives to hedge the risk. When the company choose different hedging instruments to face a variety of exchange rate risk, we employ the Multinomial Logistic-AHP to analyze the impact of various derivatives. Hence, the research summarized the literature on relevant factors affecting managers selected exchange rate hedging instruments, using Multinomial Logistic Model and and further integrate AHP. Using Experts’ Questionnaires can test multi-level selection and hedging effect of different hedging instruments in order to calculate the hedging instruments and the multi-level factors of weights to understand the gap between the empirical results and practical operation. Finally, the Multinomial Logistic-AHP Model will sort the weights to analyze. The research findings can be a basis reference for investors in decision-making.

Keywords: exchange rate risk, derivatives, hedge, multinomial logistic-AHP

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Authors: Abiodun Ladanu Ajala, Wuyi Oke

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Mathematical simulation and optimization models packaged within interactive computer programs provide a common way for planners and managers to predict the behaviour of any proposed water resources system design or management policy before it is implemented. Modeling presents a principal technique of predicting the behaviour of the proposed infrastructural designs or management policies. Models can be developed and used to help identify specific alternative plans that best meet those objectives. This study discusses various types of models, their development, architecture, data requirements, and applications in the field of engineering. It also outlines the advantages and limitations of each the optimization and simulation models presented. The techniques explored in this review include; dynamic programming, linear programming, fuzzy optimization, evolutionary algorithms and finally artificial intelligence techniques. Previous studies carried out using some of the techniques mentioned above were reviewed, and most of the results from different researches showed that indeed optimization and simulation provides viable alternatives and predictions which form a basis for decision making in building engineering structures and also in engineering planning and management.

Keywords: linear programming, mutation, optimization, simulation

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Authors: Leon Mortari

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The Metropolitan East region of Rio de Janeiro state, Brazil, faces a historic water scarcity. Among the alternatives studied to solve this situation, the possibility of adduction of the available water in the reservoir Lagoa de Juturnaíba to supply the region's municipalities stands out. The allocation of a linear engineering project must occur through an evaluation of different aspects, such as altitude, slope, proximity to roads, distance from watercourses, land use and occupation, and physical and chemical features of the soil. This work aims to apply a multi-criteria model that combines geoprocessing techniques, decision-making, and geometric search algorithm to optimize a hypothetical adductor system in the scenario of expanding the water supply system that serves this region, known as Imunana-Laranjal, using the Lagoa de Juturnaíba as the source. It is proposed in this study, the construction of a spatial database related to the presented evaluation criteria, treatment and rasterization of these data, and standardization and reclassification of this information in a Geographic Information System (GIS) platform. The methodology involves the integrated analysis of these criteria, using their relative importance defined by weighting them based on expert consultations and the Analytic Hierarchy Process (AHP) method. Three approaches are defined for weighting the criteria by AHP: the first treats all criteria as equally important, the second considers weighting based on a pairwise comparison matrix, and the third establishes a hierarchy based on the priority of the criteria. For each approach, a distinct group of weightings is defined. In the next step, map algebra tools are used to overlay the layers and generate cost surfaces, that indicates the resistance to the passage of the adductor route, using the three groups of weightings. The Dijkstra algorithm, a geometric search algorithm, is then applied to these cost surfaces to find an optimized path within the geographical space, aiming to minimize resources, time, investment, maintenance, and environmental and social impacts.

Keywords: geometric search algorithm, GIS, pipeline, route optimization, spatial multi-criteria analysis model

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Authors: Adeolu O. Dairo

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Getting the consumer marketing strategy right is a crucial and complex task for firms with a large customer base such as mobile operators in a competitive mobile market. While empirical studies have made efforts to identify key constructs, no geospatial model has been developed to comprehensively assess the viability and interdependency of ground realities regarding the customer, competition, channel and the network quality of mobile operators. With this research, a geo-analytic framework is proposed for strategy formulation and allocation for mobile operators. Firstly, a fuzzy analytic network using a self-organizing feature map clustering technique based on inputs from managers and literature, which depicts the interrelationships amongst ground realities is developed. The model is tested with a mobile operator in the Nigeria mobile market. As a result, a customer-centric geospatial and visualization solution is developed. This provides a consolidated and integrated insight that serves as a transparent, logical and practical guide for strategic, tactical and operational decision making.

Keywords: geospatial, geo-analytics, self-organizing map, customer-centric

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Authors: Mehmet Yörükoğlu, Serhat Aydın

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Since the discovery of the manuscript, mechanical methods for storing, transferring and using the information have evolved into digital methods over the time. In this process, libraries that are the center of the information have also become digitized and become accessible from anywhere and at any time in the world by taking on a structure that has no physical boundaries. In this context, some criteria for information obtained from digital libraries have become more important for users. This paper evaluates the user criteria from different perspectives that make a digital library more useful. The Step-Wise Weight Assessment Ratio Analysis-Weighted Aggregated Sum Product Assessment (SWARA-WASPAS) method is used with flexibility and easy calculation steps for the evaluation of digital library criteria. Three different digital libraries are evaluated by information technology experts according to five conflicting main criteria, ‘interface design’, ‘effects on users’, ‘services’, ‘user engagement’ and ‘context’. Finally, alternatives are ranked in descending order.

Keywords: digital library, multi criteria decision making, SWARA-WASPAS method

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Authors: Shima Soltanzadeh, Mohammad Hosain Fazel Zarandi, Mojtaba Barzegar Astanjin

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Diagnosis of male infertility by the laboratory tests is expensive and, sometimes it is intolerable for patients. Filling out the questionnaire and then using classification method can be the first step in decision-making process, so only in the cases with a high probability of infertility we can use the laboratory tests. In this paper, we evaluated the performance of four classification methods including naive Bayesian, neural network, logistic regression and fuzzy c-means clustering as a classification, in the diagnosis of male infertility due to environmental factors. Since the data are unbalanced, the ROC curves are most suitable method for the comparison. In this paper, we also have selected the more important features using a filtering method and examined the impact of this feature reduction on the performance of each methods; generally, most of the methods had better performance after applying the filter. We have showed that using fuzzy c-means clustering as a classification has a good performance according to the ROC curves and its performance is comparable to other classification methods like logistic regression.

Keywords: classification, fuzzy c-means, logistic regression, Naive Bayesian, neural network, ROC curve

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Authors: Guilherme Gorgulho, Carlos Roberto Camello Lima

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Over the past five years between 2011 and 2015, the license plate of cars, light commercial vehicles, trucks and buses have suffered retraction. This sector's decline can be explained by economic and national policy in the Brazilian industry operates. In parallel to the reduction of sales and license plate of vehicles, their suppliers are also affected influencing its results, among these vendors, there is the auto parts sector. The existence of international companies, and featured strongly in Asia and Mexico due to low production costs, encourage companies to constantly seek continuous improvement and operational efficiency. Under this argument, the decision making based on lean manufacturing tools it is essential for the management of operations. The purpose of this article is to analyze between lean practices in Brazilian auto parts industries, through the application of a questionnaire with employees who practice lean thinking in organizations. The purpose is to confront the extracted data in the questionnaires, and debate on which of lean tools help organizations as a competitive advantage.

Keywords: autoparts, brazilian industry, lean practices, survey

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Authors: S. Cowley, M. Lawrance, D. Bick, R. McCord

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Technology that automates manual handling (musculoskeletal disorder or MSD) risk assessments is increasingly available to ergonomists, engineers, generalist health and safety practitioners alike. The risk assessment process is generally based on the use of wearable motion sensors that capture information about worker movements for real-time or for posthoc analysis. Traditionally, MSD risk assessment is undertaken with the assistance of a checklist such as that from the SafeWork Australia code of practice, the expert assessor observing the task and ideally engaging with the worker in a discussion about the detail. Automation enables the non-expert to complete assessments and does not always require the assessor to be there. This clearly has cost and time benefits for the practitioner but is it an improvement on the assessment by the human. Human risk assessments draw on the knowledge and expertise of the assessor but, like all risk assessments, are highly subjective. The complexity of the checklists and models used in the process can be off-putting and sometimes will lead to the assessment becoming the focus and the end rather than a means to an end; the focus on risk control is lost. Automated risk assessment handles the complexity of the assessment for the assessor and delivers a simple risk score that enables decision-making regarding risk control. Being machine-based, they are objective and will deliver the same each time they assess an identical task. However, the WHS professional needs to know that this emergent technology asks the right questions and delivers the right answers. Whether it improves the risk assessment process and results or simply distances the professional from the task and the worker. They need clarity as to whether automation of manual task risk analysis and reporting leads to risk control or to a focus on the worker. Critically, they need evidence as to whether automation in this area of hazard management leads to better risk control or just a bigger collection of assessments. Practitioner experienced determinants of this automated manual task risk analysis and reporting being a benefit or distraction will address an understanding of emergent risk assessment technology, its use and things to consider when making decisions about adopting and applying these technologies.

Keywords: automated, manual-handling, risk-assessment, machine-based

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Authors: Nasser Al-Azmi, Al-Sabea Salem, Abu-Eida Abdullah, Milan Patra, Mohamed Elyas, Daniel Freile, Larisa Tagarieva

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Well intervention was done along with Production Logging Tools (PLT) to detect sources of water, and to check well integrity for two West Kuwait oil wells started to produce 100 % water. For the first well, to detect the source of water, PLT was performed to check the perforations, no production observed from the bottom two perforation intervals, and an intake of water was observed from the top most perforation. Then a decision was taken to extend the PLT survey from tag depth to the Y-tool. For the second well, the aim was to detect the source of water and if there was a leak in the 7’’liner in front of the upper zones. Data could not be recorded in flowing conditions due to the casing deformation at almost 8300 ft. For the first well from the interpretation of PLT and well integrity data, there was a hole in the 9 5/8'' casing from 8468 ft to 8494 ft producing almost the majority of water, which is 2478 bbl/d. The upper perforation from 10812 ft to 10854 ft was taking 534 stb/d. For the second well, there was a hole in the 7’’liner from 8303 ft MD to 8324 ft MD producing 8334.0 stb/d of water with an intake zone from10322.9-10380.8 ft MD taking the whole fluid. To restore the oil production, W/O rig was mobilized to prevent dump flooding, and during the W/O, the leaking interval was confirmed for both wells. The leakage was cement squeezed and tested at 900-psi positive pressure and 500-psi drawdown pressure. The cement squeeze job was successful. After W/O, the wells kept producing for cleaning, and eventually, the WC reduced to 0%. Regular PLT and well integrity logs are required to study well performance, and well integrity issues, proper cement behind casing is essential to well longevity and well integrity, and the presence of the Y-tool is essential as monitoring of well parameters and ESP to facilitate well intervention tasks. Cost and time optimization in oil and gas and especially during rig operations is crucial. PLT data quality and the accuracy of the interpretations contributed a lot to identify the leakage interval accurately and, in turn, saved a lot of time and reduced the repair cost with almost 35 to 45 %. The added value here was more related to the cost reduction and effective and quick proper decision making based on the economic environment.

Keywords: leak, water shut-off, cement, water leak

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Authors: Chris Preston

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As we devise ever more sophisticated methods of on-line marketing, devising systems that are able to reach into the everyday lives of consumers, we are confronted by a generation of children who face unprecedented intervention by commercial organisations into young minds, via electronic devices, and whether by computer, tablet or phone, such children have been somehow reduced to the status of their devices, with little regard for their well being as individuals. This discussion paper seeks to draw attention to such practice and questions the ethics of digital marketing methods.

Keywords: online marketing to children, online research of children, online targeting of children, consumer rights, ethics

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Authors: Shamim Ali

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Researchers and teachers have begun developing digital games and model environments for educational purpose; therefore this study examines the effect of a videos game on secondary school students’ language learning motivation. Secondly, it tries to find out the opportunities to develop a decision making process and simultaneously it analyzes the solutions for further implementation in educational setting. Participants were 30 male students randomly assigned to one of the following three treatments: 10 students were assigned to read the game’s story; 10 students were players, who played video game; and, and the last 10 students acted as watchers and observers, their duty was to watch their classmates play the digital video game. A language learning motivation scale was developed and it was given to the participants as a pre- and post-test. Results indicated a significant language learning motivation and the participants were quite motivated in the end. It is, thus, concluded that the use of video games can help enhance high school students’ language learning motivation. It was suggested that video games should be used as a complementary activity not as a replacement for textbook since excessive use of video games can divert the original purpose of learning.

Keywords: EFL, English as a Foreign Language, motivation, video games, EFL learners

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Authors: Tetsuro Saeki, Yuichi Kato, Shoutarou Mizuno

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STRIM (Statistical Test Rule Induction Method) has been proposed as a method to effectively induct if-then rules from the decision table which is considered as a sample set obtained from the population of interest. Its usefulness has been confirmed by simulation experiments specifying rules in advance, and by comparison with conventional methods. However, scope for future development remains before STRIM can be applied to the analysis of real-world data sets. The first requirement is to determine the size of the dataset needed for inducting true rules, since finding statistically significant rules is the core of the method. The second is to examine the capacity of rule induction from datasets with contaminated attribute values created by missing data and noise, since real-world datasets usually contain such contaminated data. This paper examines the first problem theoretically, in connection with the rule length. The second problem is then examined in a simulation experiment, utilizing the critical size of dataset derived from the first step. The experimental results show that STRIM is highly robust in the analysis of datasets with contaminated attribute values, and hence is applicable to realworld data.

Keywords: rule induction, decision table, missing data, noise

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Authors: Nadjat Zerf Boudjettou, Fahima Nader, Rachid Chalal

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Knowledge management is to acquire and represent knowledge relevant to a domain, a task or a specific organization in order to facilitate access, reuse and evolution. This usually means building, maintaining and evolving an explicit representation of knowledge. The next step is to provide access to that knowledge, that is to say, the spread in order to enable effective use. Knowledge management in the medical field aims to improve the performance of the medical organization by allowing individuals in the care facility (doctors, nurses, paramedics, etc.) to capture, share and apply collective knowledge in order to make optimal decisions in real time. In this paper, we propose a knowledge management approach based on integration technique of heterogeneous data in the medical field by creating a data warehouse, a technique of extracting knowledge from medical data by choosing a technique of data mining, and finally an exploitation technique of that knowledge in a case-based reasoning system.

Keywords: data warehouse, data mining, knowledge discovery in database, KDD, medical knowledge management, Bayesian networks

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Authors: B. Sudarsan Baskar, S. Pooja Pragati, S. Raj Kumar

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The cost effectiveness in aircraft maintenance is of high privilege in the recent days. The cost effectiveness can be effectively made when line maintenance activities are incorporated at airports during Turn around time (TAT). The present work outcomes the shortcomings that affect the dispatching of the aircrafts, aiming at high fleet operability and low maintenance cost. The operational and cost constraints have been discussed and a suggestive alternative mechanism is proposed. The possible allocation of all deferred maintenance tasks to a set of all deferred maintenance tasks to a set of suitable airport resources have termed as alternative and is discussed in this paper from the data’s collected from the kingfisher airlines.

Keywords: decision support system, aircraft maintenance planning, maintenance-cost, RUL(remaining useful life), logistics, supply chain management

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Authors: Qasim Zafar, Matthew Anderson, Esteban Garcia, Steven Drager

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Software failures can present an enormous detriment to people's lives and cost millions of dollars to repair when they are unexpectedly encountered in the wild. Despite a significant portion of the software development lifecycle and resources are dedicated to testing, software failures are a relatively frequent occurrence. Nevertheless, the evaluation of testing effectiveness remains at the forefront of ensuring high-quality software and software metrics play a critical role in providing valuable insights into quantifiable objectives to assess the level of assurance and confidence in the system. As the selection of appropriate metrics can be an arduous process, the goal of this paper is to shed light on the significance of software metrics by examining a range of testing techniques and metrics as well as identifying key areas for improvement. Additionally, through this investigation, readers will gain a deeper understanding of how metrics can help to drive informed decision-making on delivering high-quality software and facilitate continuous improvement in testing practices.

Keywords: software testing, software metrics, testing effectiveness, black box testing, random testing, adaptive random testing, combinatorial testing, fuzz testing, equivalence partition, boundary value analysis, white box testing

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Authors: Selin Guney, Andres Riquelme

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Among the main purposes of optimal and efficient forecasts of agricultural commodity prices is to guide the firms to advance the economic decision making process such as planning business operations and marketing decisions. Governments are also the beneficiaries and suppliers of agricultural price forecasts. They use this information to establish a proper agricultural policy, and hence, the forecasts affect social welfare and systematic errors in forecasts could lead to a misallocation of scarce resources. Various empirical approaches have been applied to forecast commodity prices that have used different methodologies. Most commonly-used approaches to forecast commodity sectors depend on classical time series models that assume values of the response variables are precise which is quite often not true in reality. Recently, this literature has mostly evolved to a consideration of fuzzy time series models that provide more flexibility in terms of the classical time series models assumptions such as stationarity, and large sample size requirement. Besides, fuzzy modeling approach allows decision making with estimated values under incomplete information or uncertainty. A number of fuzzy time series models have been developed and implemented over the last decades; however, most of them are not appropriate for forecasting repeated and nonconsecutive transitions in the data. The modeling scheme used in this paper eliminates this problem by introducing Markov modeling approach that takes into account both the repeated and nonconsecutive transitions. Also, the determination of length of interval is crucial in terms of the accuracy of forecasts. The problem of determining the length of interval arbitrarily is overcome and a methodology to determine the proper length of interval based on the distribution or mean of the first differences of series to improve forecast accuracy is proposed. The specific purpose of this paper is to propose and investigate the potential of a new forecasting model that integrates methodologies for determining the proper length of interval based on the distribution or mean of the first differences of series and Fuzzy Time Series- Markov Chain model. Moreover, the accuracy of the forecasting performance of proposed integrated model is compared to different univariate time series models and the superiority of proposed method over competing methods in respect of modelling and forecasting on the basis of forecast evaluation criteria is demonstrated. The application is to daily corn and soybean prices observed at three commercially important North Carolina markets; Candor, Cofield and Roaring River for corn and Fayetteville, Cofield and Greenville City for soybeans respectively. One main conclusion from this paper is that using fuzzy logic improves the forecast performance and accuracy; the effectiveness and potential benefits of the proposed model is confirmed with small selection criteria value such MAPE. The paper concludes with a discussion of the implications of integrating fuzzy logic and nonarbitrary determination of length of interval for the reliability and accuracy of price forecasts. The empirical results represent a significant contribution to our understanding of the applicability of fuzzy modeling in commodity price forecasts.

Keywords: commodity, forecast, fuzzy, Markov

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Authors: Amin Ebrahimi Ghadi, Morteza Moalagh

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This research is carried out to find how a perfect combination of IoT architecture (Internet of Things) and ERP system can strengthen environmental accounting to incorporate both economic and environmental information. IoT (e.g., sensors, software, and other technologies) can be used in the company’s value chain from raw material extraction through materials processing, manufacturing products, distribution, use, repair, maintenance, and disposal or recycling products (Cradle to Grave model). The desired ERP software then will have the capability to track both midpoint and endpoint environmental impacts on a green supply chain system for the whole life cycle of a product. All these enable environmental accounting to calculate, and real-time analyze the operation environmental impacts, control costs, prepare for environmental legislation and enhance the decision-making process. In this study, we have developed a model on how to use IoT devices in life cycle assessment (LCA) to gather emissions, energy consumption, hazards, and wastes information to be processed in different modules of ERP systems in an integrated way for using in environmental accounting to achieve sustainability.

Keywords: ERP, environmental accounting, green supply chain, IOT, life cycle assessment, sustainability

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Authors: S. Kaira, S. Mohamed, A. Rahman

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Traditionally, highway infrastructure projects are initiated based on their economic benefits, thereafter environmental, social and governance impacts are addressed discretely for the selected project from a set of pre-determined alternatives. When opting for cost-benefit analysis (CBA), multi-criteria decision-making (MCDM) has been used as the default assessment tool. But this tool has been critiqued as it does not mimic the real-world dynamic environment. Indeed, it is because of the fact that public sector projects like highways have to experience intense exposure to dynamic environments. Therefore, it is essential to appreciate the impacts of various dynamic factors (factors that change or progress with the system) on project performance. Thus, this paper presents various sustainability assessment tools that have been globally developed to determine sustainability performance of infrastructure projects during the design, procurement and commissioning phase. Indeed, identification of the current gaps in the available assessment methods provides a potential to add prominent part of knowledge in the field of ‘road project development systems and procedures’ that are generally used by road agencies.

Keywords: dynamic impact factors, micro and macro factors, sustainability assessment framework, sustainability performance

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Authors: Mercy E. Makpor

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Traditional Corporate Social Responsibility (CSR) idea has gone beyond just ensuring safety environments, caring about global warming and ensuring good living standards and conditions for the society at large. The paradigm shift is towards a focus on strategic objectives and the long-term value creation for both businesses and the society at large for a realistic future. As an important approach to solving social and environment issues, CSR has been accepted globally. Yet the approach is expected to go beyond where it is currently. So much is expected from businesses and governments at every level globally and locally. This then leads to the original idea of the concept, that is, how it originated and how it has been perceived over the years. Little wonder there has been a lot of definitions surrounding the concept without a major globally acceptable definition of it. The definition of CSR given by the European Commission will be considered for the purpose of this paper. Sustainable Development (SD), on the other hand, has been viewed in recent years as an ethical concept explained in the UN-Report termed “Our Common Future,” which can also be referred to as the Brundtland report. The report summarises the need for SD to take place in the present without comprising the future. However, the recent 21st-century framework on sustainability known as the “Triple Bottom Line (TBL)” framework, has added its voice to the concepts of CSR and sustainable development. The TBL model is of the opinion that businesses should not only report on their financial performance but also on their social and environmental performances, highlighting that CSR has gone beyond just the “material-impact” approach towards a “Future-Oriented” approach (sustainability). In this paper, the concept of CSR is revisited by exploring the various theories therein. The discourse on the concepts of sustainable development and sustainable development frameworks will also be indicated, thereby inducing these into how CSR can benefit both businesses and their stakeholders as well as the entirety of the society, not just for the present but for the future. It does this by exploring the importance of both concepts (CSR and SD) and concludes by making recommendations for a more empirical research in the near future.

Keywords: corporate social responsibility, sustainable development, sustainability, triple bottom line model

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Authors: Mehwish Durrani, Rubina Nazli, Muhammad Abubakr, Muhammad Shafiq

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Objectives: To evaluate the high socio-economic status, urbanization, and decrease ambulation can lead to early osteoporosis in women reporting from Peshawar region. Study Design: Descriptive cross-sectional study was done. Sample size was 100 subjects, using 30% proportion of osteoporosis, 95% confidence level, and 9% margin of error under WHO software for sample size determination. Place and Duration of study: This study was carried out in the tertiary referral health care facilities of Peshawar viz PGMI Hayatabad Medical Complex, Peshawar, Khyber Pakhtunkhwa Province, Pakistan. Ethical approval for the study was taken from the Institutional Ethical Research board (IERD) at Post Graduate Medical Institute, Hayatabad Medical Complex, and Peshawar.The study was done in six months time period. Patients and Methods: Levels of CTX1 as a marker of bone degradation in radiographically assessed perimenopausal women was determined. These females were randomly selected and screened for osteoporosis. Hemoglobin in gm/dl, ESR by Westergren method as millimeter in 1 hour, Serum Ca mg/dl, Serum alkaline Phosphatase international units per liter radiographic grade of osteoporosis according to Singh index as 1-6 and CTX 1 level in pg/ml. Results: High levels of CTX1 was observed in perimenopausal osteoporotic women which were radiographically diagnosed as osteoporotic patients. The High socio-economic class also predispose to osteoporosis. Decrease ambulation another risk factor showed significant association with the increased levels of CTX1. Conclusion: The results of this study propose that minimum ambulation and high socioeconomic class both had significance association with the increase levels of serum CTX1, which in turn will lead to osteoporosis and to its complications.

Keywords: osteoporosis, CTX1, perimenopausal women, Hayatabad Medical Complex, Khyberpuktoonkhwa

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Authors: Jamil Ahmed

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Access control models aim to decide whether a user should be denied or granted access to the user‟s requested activity. Various access control models have been established and proposed. The most prominent of these models include role-based, attribute-based, policy based access control models as well as role-centric attribute based access control model. In this paper, a novel access control model is presented called “Role centric Attribute based Policy Driven Access Control (RAPDAC) model”. RAPDAC incorporates the concept of “policy” in the “role centric attribute based access control model”. It leverages the concept of "policy‟ by precisely combining the evaluation of conditions, attributes, permissions and roles in order to allow authorization access. This approach allows capturing the "access control policy‟ of a real time application in a well defined manner. RAPDAC model allows making access decision at much finer granularity as illustrated by the case study of a real time library information system.

Keywords: authorization, access control model, role based access control, attribute based access control

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Authors: Lee Jeong Min, Lee Mi Hee, Eo Yang Dam

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Geospatial feature extraction is a very important issue in the remote sensing research. In the meantime, the image classification based on statistical techniques, but, in recent years, data mining and machine learning techniques for automated image processing technology is being applied to remote sensing it has focused on improved results generated possibility. In this study, artificial neural network and decision tree technique is applied to classify the high-resolution satellite images, as compared to the MLC processing result is a statistical technique and an analysis of the pros and cons between each of the techniques.

Keywords: remote sensing, artificial neural network, decision tree, maximum likelihood classification

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Authors: Azadeh Bashiri

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Introduction: Lack of proper diagnosis and inadequate treatment of asthma leads to physical and financial complications. This study aimed to use data mining techniques and creating a neural network intelligent system for diagnosis of asthma. Methods: The study population is the patients who had visited one of the Lung Clinics in Tehran. Data were analyzed using the SPSS statistical tool and the chi-square Pearson's coefficient was the basis of decision making for data ranking. The considered neural network is trained using back propagation learning technique. Results: According to the analysis performed by means of SPSS to select the top factors, 13 effective factors were selected, in different performances, data was mixed in various forms, so the different models were made for training the data and testing networks and in all different modes, the network was able to predict correctly 100% of all cases. Conclusion: Using data mining methods before the design structure of system, aimed to reduce the data dimension and the optimum choice of the data, will lead to a more accurate system. Therefore, considering the data mining approaches due to the nature of medical data is necessary.

Keywords: asthma, data mining, Artificial Neural Network, intelligent system

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Authors: Aleksandar Hatzivelkos

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The term ”compromise” is mostly used casually within the social choice theory. It is usually used as a mere result of the social choice function, and this omits its deeper meaning and ramifications. This paper is based on a mathematical model for the description of a compromise as a version of the Sorites paradox. It introduces a formal definition of d-measure of divergence from a compromise and models a notion of compromise that is often used only colloquially. Such a model for vagueness phenomenon, which lies at the core of the notion of compromise enables the introduction of new mathematical structures. In order to maximize compromise, different methods can be used. In this paper, we explore properties of a social welfare function TdM (from Total d-Measure), which is defined as a function which minimizes the total sum of d-measures of divergence over all possible linear orderings. We prove that TdM satisfy strict Pareto principle and behaves well asymptotically. Furthermore, we show that for certain domain restrictions, TdM satisfy positive responsiveness and IIIA (intense independence of irrelevant alternatives) thus being equivalent to Borda count on such domain restriction. This result gives new opportunities in social choice, especially when there is an emphasis on compromise in the decision-making process.

Keywords: borda count, compromise, measure of divergence, minimization

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Authors: Maria Tsompanoglou, Dimitris Armenis

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Vessel behavior in different operational and weather conditions constitutes the main area of interest for the ship operator. Ship speed and fuel consumption are the most decisive parameters in this respect, as their correlation provides information about the economic and environmental efficiency of the vessel, becoming the basis of decision making in terms of maintenance and trading. In the analysis of vessel operational profile for the evaluation of fuel consumption and the equivalent CO2 emissions footprint, the indications of Speed Through Water are widely used. The seasonal and regional variations in seawater characteristics, which are available nowadays, can provide the basis for accurate estimation of the errors in Speed Through Water indications at any time. Accuracy in the speed value on a route basis can enable operator identify the ship fuel and propulsion efficiency and proceed with improvements. This paper discusses case studies, where the actual vessel speed was corrected by a post-processing algorithm. The effects of the vessel correction to standard Key Performance Indicators, as well as operational findings not identified earlier, are also discussed.

Keywords: data analytics, MATLAB, vessel performance monitoring, speed through water

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Authors: Ahmed Mateen, Zhu Qingsheng, Faisal Shahzad

Abstract:

Requirement Engineering (RE) is a part being created for programming structure during the software development lifecycle. Software product line development is a new topic area within the domain of software engineering. It also plays important role in decision making and it is ultimately helpful in rising business environment for productive programming headway. Decisions are central to engineering processes and they hold them together. It is argued that better decisions will lead to better engineering. To achieve better decisions requires that they are understood in detail. In order to address the issues, companies are moving towards Software Product Line Engineering (SPLE) which helps in providing large varieties of products with minimum development effort and cost. This paper proposed a new framework for software product line and compared with other models. The results can help to understand the needs in SPL testing, by identifying points that still require additional investigation. In our future scenario, we will combine this model in a controlled environment with industrial SPL projects which will be the new horizon for SPL process management testing strategies.

Keywords: requirements engineering, software product lines, scoping, process structure, domain specific language

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Authors: S. Vlasyan

Abstract:

The article deals with the implementation of the right to self-determination of peoples on the example of Nagorno-Karabakh Republic. The problem of correlation of two fundamental principles of international law i. e. territorial integrity and the right to self-determination of peoples is considered to be one of the vital issues in the field of international law for several decades. So, in this article, the author analyzes the decision of the Supreme Court of Canada regarding specific issues of secession of Quebec from Canada, as well as the decision of the International Court of Justice in the case concerning East Timor (Portugal v. Australia), and in the case of Western Sahara. The author formulates legal conditions of Nagorno-Karabakh secession.

Keywords: right of self-determination, territorial integrity, the principles of International Law, Nagorno-Karabakh Republic

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Authors: Shem Ikoojo Ayegba, Ye Qi

Abstract:

Public-private partnerships (PPPs) can potentially be a transformative mechanism for advancing affordable housing in Nigeria., considering the current housing deficit between 17 – 24 million. Nevertheless, their effectiveness is marred by persistent unethical practices such as corruption and the utilization of subpar materials. Through a comprehensive mixed-methods approach, this study delves into the ethical quandaries within Nigerian housing construction and their cascading effects on the success of PPPs. Semi-structured interviews encompassing seasoned construction professionals and an in-depth content analysis of ongoing housing policies and projects in Nigeria reveal a culture of corruption across the value chain. This malaise is exacerbated by glaring deficiencies in oversight and a lack of transparent practices. A robust statistical survey involving diverse professionals, including engineers, architects, and project managers, echoes these findings, emphasizing that a frail institutional framework facilitates the persistence of substandard material use, professional negligence, and rampant bribery. Such compromised construction standards place residents in potential jeopardy and impede the achievement of broader sustainability objectives. This study propounds a suite of policy interventions to pave the way for thriving affordable housing PPPs: initiating transparent bidding processes, establishing non-negotiable quality benchmarks for construction materials, and incorporating independent third-party audits throughout the building phase. Furthermore, cultivating a culture of professional integrity through targeted ethics training for all construction personnel is imperative. This research furnishes pragmatic strategies that can radically enhance the potency of housing PPPs, thereby ensuring safe, durable, and affordable housing solutions for Nigeria's underserved populace.

Keywords: public-private partnerships, affordable housing, unethical practicies, housing policies, construction ethics

Procedia PDF Downloads 79