Search results for: fuzzy ranking

Authors: Gayani Ranawake, Kate Wilson

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Underrepresentation of women in academia, particularly in science, has been discussed by many scholars for decades. The causes of this underrepresentation are debated to this day. Publication is an important aspect of success in academia, and publication and citation rates are significant metrics in performance review, promotion, and employment. It has been established that men’s and women’s language use in general, both spoken and written, is different. However, no one, to our knowledge, has looked at whether men’s and women’s writing in science is different. If there are significant differences in the writing of men and women, then these differences may affect women’s ability to succeed in science. This study is part of a larger project to explore whether differences can be recognized in the academic science writing of men and women. Mono authored articles from high ranking physics, biology and psychology journals by men and women authors were compared in terms of readability statistics. In particular, the abstract and introduction sections were compared, as these are the first sections encountered by a reviewer, and so may have an important effect on their impression of the work. The Flesch Reading Ease, the percentage of passive sentences and the Flesch-Kincaid Reading Grade Level were calculated for each section of each article, along with counts of numbers of sentences, words per sentence and sentences per paragraph. Significance of differences was tested using the Behrens statistic. It was found that for both physics and biology papers there were no significant differences in the complexity or verbosity of the writing of men and women authors. However, there was a significant difference between the two disciplines, with physics articles being generally more readable (higher readability score) while also more passive (higher number of passive sentences). In contrast, the psychology articles showed a difference between men and women authors which may be significant. The average readability for introductions in women’s articles was 28 which was higher than for men’s articles, which was 19 (higher values indicate more readable). Women’s articles in psychology also had a greater proportion of passive sentences. It can be concluded that, at least in the more traditional sciences, men and women have adopted similar ways of writing, and that disciplinary differences are greater than gender differences. This may not be the case in psychology, which many consider to be more closely aligned with the humanities. Whether the lack of differences is because women have adapted to a masculine way of writing, or whether the genre itself is gender neutral needs further investigation.

Keywords: academic writing, gender differences, readability, science

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Authors: Hsu Kuo-Wei, Tan Roon Fang, Chao Jen-chih

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Cities face environmental challenges, including over-urbanization issues, air and water quality issues, lack of green space, excess heat capture, polluted storm water runoff and lack of ecological biodiversity. The vertical farming holds the condition of technology addressing these issues by enabling more food to be produced with finite less resources use and space. Most of the existing research regarding to technology Industry of agriculture between plant factory and vertical greening, which with high costs and high-technology. Relative research developed a sustainable model for construction and operation of the vertical farm in urban housing which aims to revolutionize our daily life of food production and urban development. However, those researches focused on quantitative analysis. This study utilized relative research for key variables of benefits of vertical farming. In the second stage, utilizes Fuzzy Delphi Method to obtain the critical factors of benefits of vertical farming using in Urban Renewal by interviewing the foregoing experts. Then, Analytic Hierarchy Process is applied to find the importance degree of each criterion as the measurable indices of the vertical farming method in urban renewal within the older city of Taichung.

Keywords: urban renewal, vertical farming, urban agriculture, benefit analysis, the older city of Taichung

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Authors: Sharifah Mousli, Sona Taheri, Jiayuan He

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Autism spectrum disorder (ASD) is a complex developmental condition involving persistent difficulties with social communication, restricted interests, and repetitive behavior. The challenges associated with ASD can interfere with an affected individual’s ability to function in social, academic, and employment settings. Although there is no effective medication known to treat ASD, to our best knowledge, early intervention can significantly improve an affected individual’s overall development. Hence, an accurate diagnosis of ASD at an early phase is essential. The use of machine learning approaches improves and speeds up the diagnosis of ASD. In this paper, we focus on the application of unsupervised clustering methods in ASD as a large volume of ASD data generated through hospitals, therapy centers, and mobile applications has no pre-existing labels. We conduct a comparative analysis using seven clustering approaches such as K-means, agglomerative hierarchical, model-based, fuzzy-C-means, affinity propagation, self organizing maps, linear vector quantisation – as well as the recently developed optimization-based clustering (COMSEP-Clust) approach. We evaluate the performances of the clustering methods extensively on real-world ASD datasets encompassing different age groups: toddlers, children, adolescents, and adults. Our experimental results suggest that the COMSEP-Clust approach outperforms the other seven methods in recognizing ASD with well-separated clusters.

Keywords: autism spectrum disorder, clustering, optimization, unsupervised machine learning

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Authors: Hans Tjio, Wee Meng Seng

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The interaction of contract and property has always been a concern in corporate and commercial law, where there are internal structures created that may not match the externally perceived image generated by the labels attached to those structures. We will focus, in particular, on the priority structures created by affirmative asset partitioning, which have increasingly come under challenge by those attempting to negotiate around them. The most prominent has been the AT1 bonds issued by Credit Suisse which were wiped out before its equity when the troubled bank was acquired by UBS. However, this should not have come as a surprise to those whose “bonds” had similarly been “redeemed” upon the occurrence of certain reference events in countries like Singapore, Hong Kong and Taiwan during their Minibond crisis linked to US sub-prime defaults. These were derivatives classified as debentures and sold as such. At the same time, we are again witnessing “liabilities” seemingly ranking higher up the balance sheet ladder, finding themselves lowered in events of default. We will examine the mechanisms holders of perpetual securities or preference shares have tried to use to protect themselves. This is happening against a backdrop that sees a rise in the strength of private credit and inter-creditor conflicts. The restructuring regime of the hybrid scheme in Singapore now, while adopting the absolute priority rule in Chapter 11 as the quid pro quo for creditor cramdown, does not apply to shareholders and so exempts them from cramdown. Complicating the picture further, shareholders are not exempted from cramdown in the Dutch scheme, but it adopts a relative priority rule. At the same time, the important UK Supreme Court decision in BTI 2014 LLC v Sequana [2022] UKSC 25 has held that directors’ duties to take account of creditor interests are activated only when a company is almost insolvent. All this has been complicated by digital assets created by businesses. Investors are quite happy to have them classified as property (like a thing) when it comes to their transferability, but then when the issuer defaults to have them seen as a claim on the business (as a choice in action), that puts them at the level of a creditor. But these hidden interests will not show themselves on an issuer’s balance sheet until it is too late to be considered and yet if accepted, may also prevent any meaningful restructuring.

Keywords: asset partitioning, creditor priority, restructuring, BTI v Sequana, digital assets

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Authors: Ahmad Shahin, Walid Moudani, Ali Bekraki

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This research aims at presenting a predictive data mining model to handle an accurate diagnosis of acute appendicitis with patients for the purpose of maximizing the health service quality, minimizing morbidity/mortality, and reducing cost. However, acute appendicitis is the most common disease which requires timely accurate diagnosis and needs surgical intervention. Although the treatment of acute appendicitis is simple and straightforward, its diagnosis is still difficult because no single sign, symptom, laboratory or image examination accurately confirms the diagnosis of acute appendicitis in all cases. This contributes in increasing morbidity and negative appendectomy. In this study, the authors propose to generate an accurate model in prediction of patients with acute appendicitis which is based, firstly, on the segmentation technique associated to ABC algorithm to segment the patients; secondly, on applying fuzzy logic to process the massive volume of heterogeneous and noisy data (age, sex, fever, white blood cell, neutrophilia, CRP, urine, ultrasound, CT, appendectomy, etc.) in order to express knowledge and analyze the relationships among data in a comprehensive manner; and thirdly, on applying dynamic programming technique to reduce the number of data attributes. The proposed model is evaluated based on a set of benchmark techniques and even on a set of benchmark classification problems of osteoporosis, diabetes and heart obtained from the UCI data and other data sources.

Keywords: healthcare management, acute appendicitis, data mining, classification, decision tree

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Authors: O. Fatemi

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Considering growing building construction industry in developing countries and sustainable development concept, as well as the importance of taking care of the future generations, codifying buildings scoring system based on environmental criteria, has always been a subject for discussion. The existing systems cannot be used for all the regions due to several reasons, including but not limited to variety in regional variables. In this article, the most important common LEED (Leadership in Energy and Environmental Design) and BREEAM (Building Research Establishment Environmental Assessment Method) common and Global environmental scoring systems, used in UK, USA, and Japan, respectively, have been discussed and compared with a special focus on CASBEE (Comprehensive Assessment System for Built Environment Efficiency), to credit assigning field (weighing and scores systems) as well as sustainable development criteria in each system. Then, converging and distinct fields of the foregoing systems are examined considering National Iranian Building Code. Furthermore, the common credits in the said systems not mentioned in National Iranian Building Code have been identified. These credits, which are generally included in well-known fundamental principles in sustainable development, may be considered as offered options for the Iranian building environmental scoring system. It is suggested that one of the globally and commonly accepted systems is chosen considering national priorities in order to offer an effective method for buildings environmental scoring, and then, a part of credits is added and/or removed, or a certain credit score is changed, and eventually, a new scoring system with a new title is developed for the country. Evidently, building construction industry highly affects the environment, economy, efficiency, and health of the relevant occupants. Considering the growing trend of cities and construction, achieving building scoring systems based on environmental criteria has always been a matter of discussion. The existing systems cannot be used for all the regions due to several reasons, including but not limited to variety in regional variables.

Keywords: scoring system, sustainability assessment, water efficiency, national Iranian building code

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Authors: Elahe Najafizade, Ahmad Mohammad Alkhateeb, Seyed Ali Hossein Zahraei, Iman Dianat

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Introduction: Hangnails are short, torn, down parts of the skin surrounding the nails. At times they are very painful. The usual treatment advised is cutting the excess skin with clippers or scissors. To provide instant relief to the patients, we describe a simpler and more effective way to use surgical glue to paste them back into their original position. Method: The cream should not be on the heat; it is on the bain-marie. To achieve the desired emulsifier, 1 gram of borax was mixed in 10 grams of distilled water in a bain-marie until it melted, then stirred oserin, beeswax, and oil in the bain-marie until it melted. After that, 32 grams of distilled water was added little by little. We add and stir and gradually add the borax dissolved in 10 grams of distilled water. The bowl of cream was placed in a bowl of cold water and stirred until the cream was smooth. After that, we add gasoline, alcohol, or methylparaben preservatives. It should be noted that this amount of ingredients is enough for a 350-gram can (when we prepare the cream, we also add the extract). Result: The patient was a 40-year-old female with a hangnail problem that had been used several different creams and Vaseline, but the treatment was not useful, but after this cream was applied for treatment; the hangnail started to cure within one week, and complete treatment achieved after two weeks. Conclusion: Traditional methods with modification without using chemical substances somehow work better and safer, so research programs on them will be useful for less risky treatment procedures.

Keywords: nail, cream, formula, traditional medicine

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Authors: Dadasaheb R. Jawre, Maya G. Unde

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Prioritization of sub-watershed plays important role in watershed management. It shows the requirement of watershed to give a treatment for the green growth of the region and conservation of the sub-watersheds. There is a number of factors like topography of the region, climatic characteristics like rainfall and runoff, land-use land-cover, social factors which are related to the development of watershed for agricultural uses and domestic purposes in the region. The present research is throwing a focus on how morphometric parameters in association with GIS analysis will help in identifying the ranking of the sub-watersheds for further development which help of suggested watershed structures. Shevgaon and Pathardi tahsils are drought prone tahsils of Ahmednagar district in Maharashtra. These tahsils come under the semi-arid region. Sub-watershed prioritization is necessary for proper planning and management of natural resources for sustainable development of the study area. Less rainfall and increasing population pressure on the land as well as water resources lead to scarcity of the water in the region. Hence, researcher has selected Shevgaon and Pathardi tahsils for sub-watershed prioritization. There are seven sub-watersheds which selected for the present research paper. In the morphological analysis linear aspects, aerial aspects and relief aspects are considered for the prioritization. The largest sub-watershed is Erdha which is located at Karanji in Pathardi tahsil having an area of 145.06 km2 and smallest sub-watershed is Erandgaon which is located in Shevgaon tahsil having an area of 40.143 km2. For all seven sub-watersheds, seven morphometric parameters were considered for calculating the compound parameter values. Finally, compound parameter values are grouped into three groups such as, high priority (below 4.0), moderate priority (4.0 to 5.0) and low priority (above 5.0) according to the compound value Erandgaon, Chapadgaon and Tarak sub-watersheds comes under high priority group, Erdha and Domeshwar sub-watersheds come under moderate priority group and Chandani and Kasichi sub-watershed come under low priority group. Both the tahsils falls in drought prone area, after getting the watershed structure overall development of the region will take place.

Keywords: sub-watersheds, GIS and remote sensing, morphometric analysis, compound parameter value, prioritization

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Authors: Chien-Kuo Chang, You-Syuan Wu, Min-Chiu Wu, Bharath-Kumar Boyanapalli

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The electrical treeing mechanism in epoxy resin insulation is a critical area of study concerning the degradation of high-voltage electrical equipment. In this study, we conducted pressure-induced degradation experiments on epoxy resin specimens using a needle-plane electrode structure to simulate electrical treeing. The specimens featured two different defect spacings, allowing for detailed observation facilitated by time-lapse photography. Our investigation revealed four distinct stages of insulation degradation: initial dark tree growth, filamentary tree growth, reverse tree growth, and eventual insulation breakdown. The initial dark treeing stage, though shortest in duration, exhibited a thicker main branch and shorter branching, ceasing upon the appearance of filamentary treeing. Filamentary treeing manifested in two forms: dark filamentary treeing during the resin's glassy state, characterized by branching structures, and fuzzy filamentary treeing during the rubbery state, resembling white feathers. The channels formed by filamentary treeing were observed to be as narrow as a few micrometers and continued to grow until the end of the experiment. Additionally, the transition to reverse treeing occurred when filamentary treeing reached the ground electrode, with the earliest manifestation being growth from the ground electrode towards the high-voltage end.

Keywords: epoxy resin insulation, high-voltage equipment, electrical treeing mechanism

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Authors: Chan Hui-Ya, Ding Shin-Tan

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Background and Aim: The discharge planning is considered helpful to reduce the hospital length of stay and readmission rate, and then increased satisfaction with healthcare for patients and professionals. In order to decrease the waiting time of long-term care and boost the care quality of patients after discharge from the hospital, the Ministry of Health and Welfare department in Taiwan initiates a program “discharge planning connects with long-term care 2.0 services” in 2017. The purpose of this study is to investigate the outcome of the pilot of this program in a medical center. Methods: By purpose sampling, the study chose five wards in a medical center as pilot units. The researchers compared the beds of service, the numbers of cases which were transferred to the long-term care center and transferred rates per month between the pilot units and the other units, and analyze the basic data, the long-term care service needs and the approval service items of cases transfer to the long-term care center in pilot units. Results: From June to September 2017, a total of 92 referrals were made, and 51 patients were enrolled into the pilot program. There is a significant difference of transferring rate between the pilot units and the other units (χ = 702.6683, p < 0.001). Only 20 cases (39.2% success rate) were approved to accept the parts of service items of long-term care in the pilot units. The most approval item was respite care service (n = 13; 65%), while it was third at needs ranking of service lists during linking services process. Among the reasons of patients who cancelled the request, 38.71% reasons were related to the services which could not match the patients’ needs and expectation. Conclusion: The results indicate there is a requirement to modify the long-term care services to fit the needs of cases. The researchers suggest estimating the potential cases by screening data from hospital informatics systems and to hire more case manager according the service time of potential cases. Meanwhile, the strategies shortened the assessment scale and authorized hospital case managers to approve some items of long-term care should be considered.

Keywords: discharge planning, long-term care, case manager, patient care

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Authors: Periklis Brakatsoulas

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Recent empirical research shows a growing interest in investment decision-making under market anomalies that contradict the rational paradigm. Momentum is undoubtedly one of the most robust anomalies in the empirical asset pricing research and remains surprisingly lucrative ever since first documented. Although predominantly phenomena identified across equities, momentum premia are now evident across various asset classes. Yet few many attempts are made so far to provide traders a diversified portfolio of strategies across different assets and markets. Moreover, literature focuses on patterns from past returns rather than mechanisms to signal future price directions prior to momentum runs. The aim of this paper is to develop a diversified portfolio approach to price distortion signals using daily position data on stocks, credit derivatives, and bonds. An algorithm allocates assets periodically, and new investment tactics take over upon price momentum signals and across different ranking groups. We focus on momentum life cycles, trend reversals, and price acceleration signals. The main effort here concentrates on the density, time span and maturity of momentum phenomena to identify consistent patterns over time and measure the predictive power of buy-sell signals generated by these anomalies. To tackle this, we propose a two-stage modelling process. First, we generate forecasts on core macroeconomic drivers. Secondly, satellite models generate market risk forecasts using the core driver projections generated at the first stage as input. Moreover, using a combination of the ARFIMA and FIGARCH models, we examine the dependence of consecutive observations across time and portfolio assets since long memory behavior in volatilities of one market appears to trigger persistent volatility patterns across other markets. We believe that this is the first work that employs evidence of volatility transmissions among derivatives, equities, and bonds to identify momentum life cycle patterns.

Keywords: forecasting, long memory, momentum, returns

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Authors: A. Buruzs, M. F. Hatwágner, A. Torma, L. T. Kóczy

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The development, operation and maintenance of Integrated Waste Management Systems (IWMS) affects essentially the sustainable concern of every region. The features of such systems have great influence on all of the components of sustainability. In order to reach the optimal way of processes, a comprehensive mapping of the variables affecting the future efficiency of the system is needed such as analysis of the interconnections among the components and modelling of their interactions. The planning of a IWMS is based fundamentally on technical and economical opportunities and the legal framework. Modelling the sustainability and operation effectiveness of a certain IWMS is not in the scope of the present research. The complexity of the systems and the large number of the variables require the utilization of a complex approach to model the outcomes and future risks. This complex method should be able to evaluate the logical framework of the factors composing the system and the interconnections between them. The authors of this paper studied the usability of the Fuzzy Cognitive Map (FCM) approach modelling the future operation of IWMS’s. The approach requires two input data set. One is the connection matrix containing all the factors affecting the system in focus with all the interconnections. The other input data set is the time series, a retrospective reconstruction of the weights and roles of the factors. This paper introduces a novel method to develop time series by content analysis.

Keywords: content analysis, factors, integrated waste management system, time series

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Authors: Masoud Rabbani, Majede Smizadeh, Hamed Farrokhi-Asl

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We study jointly determining prices and production in a multiple period horizon under a general non-stationary stochastic demand with continuous prices. In some periods we need to increase capacity of production to satisfy demand. This paper presents a model to aid multi-period production capacity planning by quantifying the trade-off between product quality and production cost. The product quality is estimated as the statistical variation from the target performances obtained from the output tolerances of the production machines that manufacture the components. We consider different tolerance for different machines that use to increase capacity. The production cost is estimated as the total cost of owning and operating a production facility during the planning horizon.so capacity planning has cost that impact on price. Pricing products often turns out to be difficult to measure them because customers have a reservation price to pay that impact on price and demand. We decide to determine prices and production for periods after enhance capacity and consider reservation price to determine price. First we use an algorithm base on fuzzy set of the optimal objective function values to determine capacity planning by determine maximize interval from upper bound in minimum objectives and define weight for objectives. Then we try to determine inventory and pricing policies. We can use a lemma to solve a problem in MATLAB and find exact answer.

Keywords: price policy, inventory policy, capacity planning, product quality, epsilon -constraint

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Authors: Seyed Esmail Seyedi Bariran, Khairul Salleh Mohamed Sahari

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In multi-echelon supply chain networks, optimal supplier selection significantly depends on the accuracy of suppliers’ performance prediction. Different methods of multi criteria decision making such as ANN, GA, Fuzzy, AHP, etc have been previously used to predict the supplier performance but the “black-box” characteristic of these methods is yet a major concern to be resolved. Therefore, the primary objective in this paper is to implement an artificial intelligence-based gene expression programming (GEP) model to compare the prediction accuracy with that of ANN. A full factorial design with %95 confidence interval is initially applied to determine the appropriate set of criteria for supplier performance evaluation. A test-train approach is then utilized for the ANN and GEP exclusively. The training results are used to find the optimal network architecture and the testing data will determine the prediction accuracy of each method based on measures of root mean square error (RMSE) and correlation coefficient (R2). The results of a case study conducted in Supplying Automotive Parts Co. (SAPCO) with more than 100 local and foreign supply chain members revealed that, in comparison with ANN, gene expression programming has a significant preference in predicting supplier performance by referring to the respective RMSE and R-squared values. Moreover, using GEP, a mathematical function was also derived to solve the issue of ANN black-box structure in modeling the performance prediction.

Keywords: Supplier Performance Prediction, ANN, GEP, Automotive, SAPCO

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Authors: Chih-Chieh Yang, Chung-Neng Huang

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

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

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Authors: Hani Malik

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Background: Clinician burnout is a growing phenomenon in current health systems worldwide. Increasing emotional exhaustion, depersonalisation, and reduced personal accomplishment threaten the effective delivery of healthcare. This can potentially be mitigated by mindfulness practice, which has shown promising results in reducing burnout, restoring compassion, and preventing moral injury in clinicians. Objectives: To conduct a scoping review and identify high-quality studies on mindfulness practice in clinician burnout, synthesize themes that emerge from these studies, and discuss the implications of the results to healthcare leadership and innovation. Methodology: A focused scoping review was carried out to investigate the effects of mindfulness practice on clinician burnout. High-ranking journals were targeted to analyse high-quality studies and synthesize common themes in the literature. Studies conducted on current, practicing physicians were included. Mindfulness practice of varying forms was the main intervention studied. Grey literature and studies conducted only on allied health personnel were excluded from this review. Analysis:31 studies were included in this scoping review. Mindfulness practice was found to decrease emotional exhaustion and depersonalisation while improving mood, responses to stress, and vigour. Self-awareness, compassion, and empathy were also increased in study participants. From this review, four themes emerged which include: innovations in mindfulness practice, mindfulness and positive psychology, the impact of mindfulness on work and patient care, and barriers and facilitators to clinician mindfulness practice. Conclusion: Mindfulness had widely been reported to benefit mental health and well-being, but the studies reviewed seemed to adopt a mono focus and omitted key considerations to healthcare leadership, systems-level culture, and practices. Mindfulness practice is a quintessential component of positive psychology and is inherently linked to effective leadership. A mindful and compassionate clinician leader will play a crucial role in addressing gaps in current practice, prioritise staff mental health, and provide a supportive platform for innovation.

Keywords: mindfulness practice, clinician burnout, healthcare leadership, COVID-19

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Authors: Azizah Ismail, Zainab Khalifah, Abbas Mardani

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Sustainable community-based tourism through homestay programme is a growing niche market that has impacted destinations in many countries including Malaysia. With demand predicted to continue increasing, the importance of the homestay product will grow in the tourism industry. This research examines the sustainability criteria for homestay programme in Malaysia covering economic, socio-cultural and environmental dimensions. This research applied a two-stage methodology for data analysis. Specifically, the researcher implements a hybrid method which combines two multi-criteria decision making approaches. In the first stage of the methodology, the Decision Making Trial and Evaluation Laboratory (DEMATEL) technique is applied. Then, Analytical Network Process (ANP) is employed for the achievement of the objective of the current research. After factors identification and problem formulation, DEMATEL is used to detect complex relationships and to build a Network Relation Map (NRM). Then ANP is used to prioritize and find the weights of the criteria and sub-criteria of the decision model. The research verifies the framework of multi-criteria for sustainable community-based tourism from the perspective of stakeholders. The result also provides a different perspective on the importance of sustainable criteria from the view of multi-stakeholders. Practically, this research gives the framework model and helps stakeholders to improve and innovate the homestay programme and also promote community-based tourism.

Keywords: community-based tourism, homestay programme, sustainable tourism criteria, sustainable tourism development

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Authors: Soheir Mohamed Hegazy

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Culture sustainability, which reflects a deep respect for people and history, is a cause of concern in contemporary architecture. Adopting ultramodern architecture styles was initiated in the 20th century by a plurality of states worldwide. Only a few countries, including Oman, realized that fashionable architectural designs ignore cultural values, identity, the context of its environment, economic perspective, and social performance. Stirring the Sultanate of Oman from being a listless and closed community to a modern country started in the year 1970. Despite unprecedented development in all aspects of Omani people's life, the leadership and the public had the capability to adjust to the changing global challenges without compromising social values and identity. This research provides a close analysis of one of the recent examples of contemporary vernacular architecture in the Sultanate of Oman, as a case study, Oman International Airport. The said airport gained an international appreciation for its Omani-themed architecture, distinguished traveler experience, and advanced technology. Accordingly, it was selected by the World Travel Awards as the Best Tourism Development Project in the Middle East only four weeks afterward after starting its operation. This paper aims to transfer this successful design approach of integrating the latest trends in technology, systems, eco-friendly aspects, and materials with the traditional Omani architectural features, which reflects symbiotic harmony of the community, individuals, and environment to other countries, designers, researchers, and students. In addition, the paper aims to encourage architects and teachers to take responsibility for valorizing built heritage as a source of inspiration for modern architecture, which could be considered as an added value. The work depends on reviewing the relevant literature, a case study, interviews with two architects who were involved in the project’s site work, and one current high-ranking employee in the airport besides data analysis and conclusion.

Keywords: contemporary vernacular architecture, culture sustainability, Oman international airport, current Omani architecture type

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Authors: Metin Özkan

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In the last decade, Turkish higher education has been expanded dramatically. With this expansion, Turkey has come a long way in establishing an efficient system of higher education which is moving into a ‘mass’ system with institutions spanning the whole country. This expansion as a quantitative target leads to questioning the quality of higher education services. Especially, the qualities of higher education services depend on mainly quality of educators. Qualities of educators are most important in Turkish higher education system due to rapid rise in the number of universities and students. Therefore, it is seen important that reveals the portrait of ideal university teacher from the point of view student enrolled in Turkish higher education system. The purpose of this current study is to determine the portrait of ideal university teacher according to the views of Turkish Students. This research is carried out with descriptive scanning method and combined and mixed of qualitative and quantitative methodologies. Research data of qualitative section were collected at Gaziantep University with the participation of 45 students enrolled in 15 different faculties. Quantitative section was performed on 217 students. The data were obtained through semi-structured interview and “Ideal University Teacher Assessment” form developed by the researcher. The interview form consists of basically two parts. The first part of the interview was about personal information, the second part included questions about the characteristic of ideal university teacher. The questions which constitute the second part of the interview are; "what is a good university teacher like?” and “What human qualities and professional skills should a university teacher have? ". Assessment form which was created from the qualitative data obtained from interviews was used to attain scaling values for pairwise comparison and ranking judgment. According to study results, it has been found that ideal university teacher characteristics include the features like patient, tolerant, comprehensive and tolerant. Ideal university teacher, besides, implement the teaching methods like encouraging the students’ critical thinking, accepting the students’ recommendations on how to conduct the lesson and making use of the new technologies etc. Motivating and respecting the students, adopting a participative style, adopting a sincere way of manner also constitute the ideal university features relationships with students.

Keywords: faculty, higher education, ideal university teacher, teacher behavior

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Authors: Purba Biswas, Priyanka Dey

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Worldwide rapid urbanisation has accelerated city expansion in both developed and developing nations. This unprecedented urbanisation trend due to the increasing population and economic growth has caused challenges for the decision-makers in city planning and urban management. Metropolitan cities, class-I towns, and major urban centres undergo a continuous process of evolution due to interaction between socio-cultural and economic attributes. This constant evolution leads to urban expansion in all directions. Understanding the patterns and dynamics of urban built-up growth is crucial for policymakers, urban planners, and researchers, as it aids in resource management, decision-making, and the development of sustainable strategies to address the complexities associated with rapid urbanisation. Identifying spatio-temporal patterns of urban growth has emerged as a crucial challenge in monitoring and assessing present and future trends in urban development. Analysing urban growth patterns and tracking changes in land use is an important aspect of urban studies. This study analyses spatio-temporal urban transformations and land-use and land cover changes using remote sensing and GIS techniques. Built-up growth analysis has been done for the city of Surat as a case example, using the GIS tools of NDBI and GIS models of the Built-up Urban Density Index and Shannon Entropy Index to identify trends and the geographical direction of transformation from 2005 to 2020. Surat is one of the fastest-growing urban centres in both the state and the nation, ranking as the 4th fastest-growing city globally. This study analyses the dynamics of urban built-up area transformations both zone-wise and geographical direction-wise, in which their trend, rate, and magnitude were calculated for the period of 15 years. This study also highlights the need for analysing and monitoring the urban growth pattern of class-I cities in India using spatio-temporal and quantitative techniques like GIS for improved urban management.

Keywords: urban expansion, built-up, geographic information system, remote sensing, Shannon’s entropy

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Authors: Robert Jedrys, Zdzislaw Kobos, Justyna Skrzynska, Zbigniew Wochynski

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Professions connected to aviation require an assessment of the suitability of health, psychological and psychomotor skills and overall physical fitness of the organism, who applies. Assessment of the physical condition is conducted by the committees consisting of aero-medical specialists in clinical medicine and aviation. In addition, psychological predispositions should be evaluated by specialized psychologists familiar with the specifics of the tasks and requirements for the various positions in aviation. Both, physical abilities and general physical fitness of candidates for aviation shall be assessed during the selection exams, which also test the ability to deal with stress what is very important in aviation. Hence, the mentioned exams in physical education not only help to judge on the ranking in candidates in terms of their efficiency and performance, but also allows to evaluate the functioning under stress measured using psychological tests. Moreover, before-test stress is a predictors of successfulness in the next stages of education and practical training in the aviation. The aim of the study was to evaluate the influence of temperamental traits on strategies used for coping with stress during selection exams in physical education, deciding on admission to aviation school. The study involved 30 candidates for fighter pilot training in aviation school . To evaluate the temperament 'The Formal Characteristics of Behavior-Temperament Inventory' (FCB-TI) by B. Zawadzki and J.Strelau was used. To determine the pattern of coping with stress 'The Coping Inventory for Stressful Situations' (CISS) to N. S. Endler and J. D. A. Parker were engaged. Study of temperament and styles of coping with stress was conducted directly before the exam selection of physical education. The results were analyzed with 'Statistica 9' program. The studies showed that:-There is a negative correlation between such a temperament feature as 'perseverance' and preferred style of coping with stress concentrated on the task (r = -0.590; p < 0.004); -There is a positive correlation between such a feature of temperament as 'emotional reactivity,' and preference to deal with a stressful situation with ‘style centered on emotions’ (r = 0.520; p <0.011); -There is a negative correlation between such a feature of temperament as ‘strength’ and ‘style of coping with stress concentrated on emotions’ (r = -0.580; p < 0.004). Studies indicate that temperament traits determine the perception of stress and preferred coping styles used during the selection, as during the exams in physical education.

Keywords: aviation, physical education, stress, temperamental traits

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Authors: Manuela S. Tolentino, John G. Nepomuceno

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The purpose of this investigation was to assess the implementation of inclusive education (IE) in 6 elementary and 5 secondary public schools in the City Schools Division of Dasmarinas. Participants in this study were 11 school heads, 73 teachers, 22 parents and 22 students (regular and with special needs) who were selected using purposive sampling. A 30-item questionnaire was used to gather data on the extent of the implementation of IE in the division while focus group discussion (FGD) was used to gather insights on what facilitate and hinder the implementation of the IE program. This study assessed the following variables: school culture and environment, inclusive education policy implementation, and curriculum design and practices. Data were analyzed using frequency count, mean and ranking. Results revealed that participants have similar assessment on the extent of the implementation of IE. School heads rated school culture and environment as highest in terms of implementation while teachers and pupils chose curriculum design and practices. On the other hand, parents felt that inclusive education policies are implemented best. School culture and environment are given high ratings. Participants perceived that the IE program in the division is making everyone feel welcome regardless of age, sex, social status, physical, mental and emotional state; students with or without disability are equally valued, and students help each. However, some aspects of the IE program implementation are given low ratings namely: partnership between staff, parents and caregivers, school’s effort to minimize discriminatory practice, and stakeholders sharing the philosophy of inclusion. As regards education policy implementation, indicators with the highest ranks were school’s effort to admit students from the locality especially students with special needs, and the implementation of the child protection policy and anti-bullying policy. The results of the FGD revealed that both school heads and teachers possessed the welcoming gesture to accommodate students with special needs. This can be linked to the increasing enrolment of SNE in the division. However, limitations of the teachers’ knowledge on handling learners, facilities and collaboration among stakeholders hinder the implementation of IE program. Based on the findings, inclusion program framework was developed for program enhancement. This will be the basis for the improvement of the program’s efficiency, the relationship between stakeholders, and formulation of solutions.

Keywords: inclusion, inclusive education, framework, special education

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Authors: Mihretu Erjabo

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Halaba special district is characterized by drought, soil erosion, high population pressure, poor livestock production, lack of feed for livestock, very deep water table, very low productivity of crops and food insufficiency. In order to address these problems, the woreda agricultural development office along with other management practices such as soil physical conservation measures agroforestry was introduced decades ago as a means to alleviate the problem. However, the level of agroforestry adoption remains low. Objective of this study was to identify the factors that influence adoption of agroforestry technologies by farmers in the district. Random sampling was employed to select two kebele administrations and respondents. Data collection was conducted by rural household questionnaire survey, participatory rural appraisal, questionnaires for local and woreda extension staff, secondary data resources and field observation. A sample of 12 key informants, 6 extension staffs, and 182 households, were used in the data collection. Chi square test used to determine significant relationships between adoption of agroforestry and 15 selected variables. Out of which eleven were found to be significant to affect farmers’ adoptiveness. These were frequency of visits of farmers (13.39%), participation in training (11.49%), farmers’ attitude towards agroforestry practices (10.61%), frequency of visits of extensionists (10.38%), participation in extension meeting (10.34%), participation in field day (10.28%), land holding size (9.29%), level of literacy (8.78%), awareness about the importance of agroforestry technology packages (7.06%), time taken from their residence to nearest extension (5.04%) and gender of respondents (3.34%). This study also identified various factors that result in low adoption rates of agroforestry including fear of competition, seedling, rainfall and labour shortage, free grazing, financial problem, expecting trees as soil degrader and long span of trees and lack of need ranking. To improve farmers’ adoption, the factors identified should be well addressed by launching a series and recurrent outreach extension program appropriate and suitable to farmers need.

Keywords: farmers attitude, farmers participation, soil degradation, technology packages

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Authors: Yeliz Karaca, Rana Karabudak

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Multifractal Denoising techniques are used in the identification of significant attributes by removing the noise of the dataset. Magnetic resonance (MR) image technique is the most sensitive method so as to identify chronic disorders of the nervous system such as Multiple Sclerosis. MRI and Expanded Disability Status Scale (EDSS) data belonging to 120 individuals who have one of the subgroups of MS (Relapsing Remitting MS (RRMS), Secondary Progressive MS (SPMS), Primary Progressive MS (PPMS)) as well as 19 healthy individuals in the control group have been used in this study. The study is comprised of the following stages: (i) L2 Norm Multifractal Denoising technique, one of the multifractal technique, has been used with the application on the MS data (MRI and EDSS). In this way, the new dataset has been obtained. (ii) The new MS dataset obtained from the MS dataset and L2 Multifractal Denoising technique has been applied to the K-Means and Fuzzy C Means clustering algorithms which are among the unsupervised methods. Thus, the clustering performances have been compared. (iii) In the identification of significant attributes in the MS dataset through the Multifractal denoising (L2 Norm) technique using K-Means and FCM algorithms on the MS subgroups and control group of healthy individuals, excellent performance outcome has been yielded. According to the clustering results based on the MS subgroups obtained in the study, successful clustering results have been obtained in the K-Means and FCM algorithms by applying the L2 norm of multifractal denoising technique for the MS dataset. Clustering performance has been more successful with the MS Dataset (L2_Norm MS Data Set) K-Means and FCM in which significant attributes are obtained by applying L2 Norm Denoising technique.

Keywords: clinical decision support, clustering algorithms, multiple sclerosis, multifractal techniques

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Authors: Asinguza P. Allan

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The Advocacy for Better Health aims to equip citizens with enabling environment and systems to effectively advocate for strong action plans to improve health services. This is because the 2020 Government target for Uganda to transform into a middle income country will be achieved if investment is made in keeping the population healthy and productive. Citizen participation as an important foundation for change has been emphasized to gather data through participatory rural appraisal and inform evidence-based advocacy for recruitment and motivation of human resources. Citizens conduct problem ranking during advocacy forums on staffing levels and health worker absenteeism. Citizens prioritised inadequate number of midwives and absenteeism. On triangulation, health worker to population ratio in Uganda remains at 0.25/1,000 which is far below the World Health Organization (WHO) threshold of 2.3/1,000. Working with IntraHealth, the project advocated for recruitment of critical skilled staff (doctors and midwives) and scale up health workers motivation strategy to reduce Uganda’s Neonatal Mortality Rate of 22/1,000 and Maternal Mortality Ratio of 320/100,000. Government has committed to increase staffing to 80% by 2018 (10 districts have passed ordinances and revived use of duty rosters to address health worker absenteeism. On the other hand, the better health advocacy debate has been elevated with need to increase health sector budget allocations from 8% to 10%. The project has learnt that building a body of evidence from citizens enhances the advocacy agenda. Communities will further monitor government commitments to reduce Neonatal Mortality Rate and Maternal Mortality Ratio. The project has learnt that interface meeting between duty bearers and the community allows for immediate feedback and the process is a strong instrument for empowerment. It facilitates monitoring and performance evaluation of services, projects and government administrative units (like district assemblies) by the community members themselves. This, in turn, makes the human resources in health to be accountable, transparent and responsive to communities where they work. This, in turn, promotes human resource performance.

Keywords: advocacy, empowerment, evidence, human resources

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Authors: J. S. Dhillon, K. K. Dhaliwal

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In almost all the digital filtering applications the digital infinite impulse response (IIR) filters are preferred over finite impulse response (FIR) filters because they provide much better performance, less computational cost and have smaller memory requirements for similar magnitude specifications. However, the digital IIR filters are generally multimodal with respect to the filter coefficients and therefore, reliable methods that can provide global optimal solutions are required. The artificial bee colony (ABC) algorithm is one such recently introduced meta-heuristic optimization algorithm. But in some cases it shows insufficiency while searching the solution space resulting in a weak exchange of information and hence is not able to return better solutions. To overcome this deficiency, the opposition based learning strategy is incorporated in ABC and hence a modified version called oppositional artificial bee colony (OABC) algorithm is proposed in this paper. Duplication of members is avoided during the run which also augments the exploration ability. The developed algorithm is then applied for the design of optimal and stable digital IIR filter structure where design of low-pass (LP) and high-pass (HP) filters is carried out. Fuzzy theory is applied to achieve maximize satisfaction of minimum magnitude error and stability constraints. To check the effectiveness of OABC, the results are compared with some well established filter design techniques and it is observed that in most cases OABC returns better or atleast comparable results.

Keywords: digital infinite impulse response filter, artificial bee colony optimization, opposition based learning, digital filter design, multi-parameter optimization

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Authors: Zurina Mahadi, Hukil Sino

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United Nations resolved 2030 Sustainable Development Goals (SDGs) in 2015 to complete what Millennium Development Goals did not achieve. Accommodating 17 goals and 169 targets, Sustainable Development Goals are designated to be achieved over the next 15 years. A survey was conducted in July 2019 among the undergraduate students of a public university in Selangor, Malaysia, to learn their selection over Sustainable Development Goals, which they think is the most critical in the Malaysian scenario. This study adopted a qualitative approach, and data is gathered from a single instruction questionnaire administered to a purposive sample of participants. 13 goals were selected by the participants which are Goal 1, 2, 3, 4, 5, 6, 8, 10, 11, 12, 13, 16 and 17 while none has selected Goal 7, 9, 14 and 15 which are ‘Affordable and Clean Energy’; ‘Industry, Innovation and Infrastructure’; ‘Life Below Water’ and ‘Life On Land’ respectively. The selected goals are then ranked according to the number of participants who chose that particular goal. Goal 8 is found to be at the highest position of the ranking while Goal 5, 6, 10, and 13 accommodating the lowest position. Goal 8, which is ‘Decent Work and Economic Growth’ is chosen by 13 participants as the most critical goal in Malaysia while Goal 5,6 10, and 13, which are ‘Gender Equality’; ‘Clean Water and Sanitation’; ‘Reduced Inequalities’ and ‘Climate Action’ respectively, are chosen by only one participant each. Issues highlighted by the participants are themed into 10 themes, which are job availability, cost of living, well-being, corruption, education, environment, gender, development planning, consumption, and partnership. The theme of the cost of living has the highest number of issues, followed by the theme of job availability and the environment. The theme of gender has the least number of issues, followed by the theme of corruption and development planning. In principle, these findings, therefore, conclude that from a public university students’ point of view, the most critical sustainable development goal is decent work and economic growth while the most concerning issue is the cost of living. The implications of these findings are students’ knowledge towards the current issues of development, and their views of future sustainable development are considerably high. This study, therefore, suggests their views be inculcated into local, sustainable development frameworks to increase the inclusiveness of the young generation as they are the future SDGs stakeholders.

Keywords: cost of living, inclusiveness, job availability, sustainable development goals

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Authors: M. N. Khajavi, S. Nasiri, E. Farokhi, M. R. Bavir

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Alcohol fuels are renewable, have low pollution and have high octane number; therefore, they are important as fuel in internal combustion engines. Percentage detection of these alcoholic fuels with gasoline is a complicated, time consuming, and expensive process. Nowadays, these processes are done in equipped laboratories, based on international standards. The aim of this research is to determine percentage detection of different fuels based on vibration analysis of engine block signals. By doing, so considerable saving in time and cost can be achieved. Five different fuels consisted of pure gasoline (G) as base fuel and combination of this fuel with different percent of ethanol and methanol are prepared. For example, volumetric combination of pure gasoline with 10 percent ethanol is called E10. By this convention, we made M10 (10% methanol plus 90% pure gasoline), E30 (30% ethanol plus 70% pure gasoline), and M30 (30% Methanol plus 70% pure gasoline) were prepared. To simulate real working condition for this experiment, the vehicle was mounted on a chassis dynamometer and run under 1900 rpm and 30 KW load. To measure the engine block vibration, a three axis accelerometer was mounted between cylinder 2 and 3. After acquisition of vibration signal, eight time feature of these signals were used as inputs to an Adaptive Neuro Fuzzy Inference System (ANFIS). The designed ANFIS was trained for classifying these five different fuels. The results show suitable classification ability of the designed ANFIS network with 96.3 percent of correct classification.

Keywords: internal combustion engine, vibration signal, fuel composition, classification, ANFIS

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Authors: Serhat Tuzun, Tufan Demirel

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Multi-Criteria Decision Making (MCDM) is the modelling of real-life to solve problems we encounter. It is a discipline that aids decision makers who are faced with conflicting alternatives to make an optimal decision. MCDM problems can be classified into two main categories: Multi-Attribute Decision Making (MADM) and Multi-Objective Decision Making (MODM), based on the different purposes and different data types. Although various MADM techniques were developed for the problems encountered, their methodology is limited in modelling real-life. Moreover, objective results are hard to obtain, and the findings are generally derived from subjective data. Although, new and modified techniques are developed by presenting new approaches such as fuzzy logic; comprehensive techniques, even though they are better in modelling real-life, could not find a place in real world applications for being hard to apply due to its complex structure. These constraints restrict the development of MADM. This study aims to conduct a comprehensive analysis of preference methods in MADM and propose an approach based on information. For this purpose, a detailed literature review has been conducted, current approaches with their advantages and disadvantages have been analyzed. Then, the approach has been introduced. In this approach, performance values of the criteria are calculated in two steps: first by determining the distribution of each attribute and standardizing them, then calculating the information of each attribute as informational energy.

Keywords: literature review, multi-attribute decision making, operations research, preference method, informational energy

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Authors: N. H. Harun, A. S. Abdul Nasir, M. Y. Mashor, R. Hassan

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Leukaemia is a blood cancer disease that contributes to the increment of mortality rate in Malaysia each year. There are two main categories for leukaemia, which are acute and chronic leukaemia. The production and development of acute leukaemia cells occurs rapidly and uncontrollable. Therefore, if the identification of acute leukaemia cells could be done fast and effectively, proper treatment and medicine could be delivered. Due to the requirement of prompt and accurate diagnosis of leukaemia, the current study has proposed unsupervised pixel segmentation based on clustering algorithm in order to obtain a fully segmented abnormal white blood cell (blast) in acute leukaemia image. In order to obtain the segmented blast, the current study proposed three clustering algorithms which are k-means, fuzzy c-means and moving k-means algorithms have been applied on the saturation component image. Then, median filter and seeded region growing area extraction algorithms have been applied, to smooth the region of segmented blast and to remove the large unwanted regions from the image, respectively. Comparisons among the three clustering algorithms are made in order to measure the performance of each clustering algorithm on segmenting the blast area. Based on the good sensitivity value that has been obtained, the results indicate that moving k-means clustering algorithm has successfully produced the fully segmented blast region in acute leukaemia image. Hence, indicating that the resultant images could be helpful to haematologists for further analysis of acute leukaemia.

Keywords: acute leukaemia images, clustering algorithms, image segmentation, moving k-means

Procedia PDF Downloads 284