Search results for: contingency theory approach

Authors: George Ogono Muok, N. Obange, S. A. Odhiambo

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Empirical literature on the determinants of foreign direct investments (FDI) flows is extensive but controversial over some determinants of FDI in-flows in developing countries. The objective of this study therefore was to investigate the overall determinants of FDI inflows in Kenya. Dynamic macroeconomic theory and correlational study design provided theoretical framework for specification of a time series model. The study used data observed from 1970 to 2015 in World Development Indicators (WDI) data bank. The results show that annual growth rate of GDP, inflation rates and external debt as a proportion of GDP are significant determinants of FDI inflows in Kenya and are therefore important macroeconomic parameters for policy formulation for promotion of FDI inflows in Kenya.

Keywords: determinants of foreign, direct, investment inflows in, Kenya, Africa

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Authors: Sakti Mandal

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Varying distribution of land surface temperature in an urbanized environment is a globally addressed phenomenon. Usually has been noticed that criticality of surface temperature increases from the periphery to the urban centre. As the centre experiences maximum severity of heat throughout the year, it also represents most critical zone in terms of thermal condition. In this present study, an attempt has been taken to propose a quantitative approach of thermal critical zonation (TCZ) on the basis of seasonal temperature variation. Here the zonation is done by calculating thermal critical value (TCV). From the Landsat 8 thermal digital data of summer and winter seasons for the year 2014, the land surface temperature maps and thermally critical zonation has been prepared, and corresponding dataset has been computed to conduct the overall study of that particular study area. It is shown that TCZ can be clearly identified and analyzed by the help of inter-seasonal temperature range. The results of this study can be utilized effectively in future urban development and planning projects as well as a framework for implementing rules and regulations by the authorities for a sustainable urban development through an environmentally affable approach.

Keywords: thermal critical values (TCV), thermally critical zonation (TCZ), land surface temperature (LST), Landsat 8, Kolkata Municipal Corporation (KMC)

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Authors: N. D'Amico, E. Grossi, B. Colombo, F. Rigiroli, M. Buscema, D. Fazzini, G. Cornalba, S. Papa

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Purpose: To characterize, through a radiomic approach, the nature of nodules considered non-specific by expert radiologists, recognized in magnetic resonance mammography (MRm) with T1-weighted (T1w) sequences with paramagnetic contrast. Material and Methods: 47 cases out of 1200 undergoing MRm, in which the MRm assessment gave uncertain classification (non-specific nodules), were admitted to the study. The clinical outcome of the non-specific nodules was later found through follow-up or further exams (biopsy), finding 35 benign and 12 malignant. All MR Images were acquired at 1.5T, a first basal T1w sequence and then four T1w acquisitions after the paramagnetic contrast injection. After a manual segmentation of the lesions, done by a radiologist, and the extraction of 150 radiomic features (30 features per 5 subsequent times) a machine learning (ML) approach was used. An evolutionary algorithm (TWIST system based on KNN algorithm) was used to subdivide the dataset into training and validation test and to select features yielding the maximal amount of information. After this pre-processing, different machine learning systems were applied to develop a predictive model based on a training-testing crossover procedure. 10 cases with a benign nodule (follow-up older than 5 years) and 18 with an evident malignant tumor (clear malignant histological exam) were added to the dataset in order to allow the ML system to better learn from data. Results: NaiveBayes algorithm working on 79 features selected by a TWIST system, resulted to be the best performing ML system with a sensitivity of 96% and a specificity of 78% and a global accuracy of 87% (average values of two training-testing procedures ab-ba). The results showed that in the subset of 47 non-specific nodules, the algorithm predicted the outcome of 45 nodules which an expert radiologist could not identify. Conclusion: In this pilot study we identified a radiomic approach allowing ML systems to perform well in the diagnosis of a non-specific nodule at MR mammography. This algorithm could be a great support for the early diagnosis of malignant breast tumor, in the event the radiologist is not able to identify the kind of lesion and reduces the necessity for long follow-up. Clinical Relevance: This machine learning algorithm could be essential to support the radiologist in early diagnosis of non-specific nodules, in order to avoid strenuous follow-up and painful biopsy for the patient.

Keywords: breast, machine learning, MRI, radiomics

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Authors: Madiha Liaqat, Rehan Ahmed Khan, Shahid Kamal

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Multiple imputation with delta adjustment is a versatile and transparent technique for addressing univariate missing data in the presence of various missing mechanisms. This approach allows for the exploration of sensitivity to the missing-at-random (MAR) assumption. In this review, we outline the delta-adjustment procedure and illustrate its application for assessing the sensitivity to deviations from the MAR assumption. By examining diverse missingness scenarios and conducting sensitivity analyses, we gain valuable insights into the implications of missing data on our analyses, enhancing the reliability of our study's conclusions. In our study, we focused on assessing logPSA, a continuous biomarker in incomplete prostate cancer data, to examine the robustness of conclusions against plausible departures from the MAR assumption. We introduced several approaches for conducting sensitivity analyses, illustrating their application within the pattern mixture model (PMM) under the delta adjustment framework. This proposed approach effectively handles missing data, particularly loss to follow-up.

Keywords: loss to follow-up, incomplete response, multiple imputation, sensitivity analysis, prostate cancer

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Authors: Cahyaningsih Cahyaningsih, Fu'ad Rakhman

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This study examines empirically the association between corporate social responsibility (CSR) and tax avoidance. This study also investigates the effect of earnings on the relation between CSR and tax avoidance. Effective tax rate (ETR) and cash effective tax rate (CETR) were used to measure tax avoidance. Corporate social responsibility fund (CSRF) and corporate social responsibility disclosure (CSRD) were used as proxies for CSR. Test was conducted for public firms which were listed in the Indonesia Stock Exchange during the period of 2011-2014. Based on slack resource theory, this study finds that the relation between CSR and tax avoidance is moderated by earnings.

Keywords: corporate social responsibility disclosure, corporate social responsibility fund, earnings, tax avoidance

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Authors: Naman Solanki, Souraj Mondal

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With the world moving towards online communication, the video datastore has exploded in the past few years. Consequently, it has become crucial to analyse participant’s engagement levels in online communication videos. Engagement prediction of people in videos can be useful in many domains, like education, client meetings, dating, etc. Video-level or frame-level prediction of engagement for a user involves the development of robust models that can capture facial micro-emotions efficiently. For the development of an engagement prediction model, it is necessary to have a widely-accepted standard dataset for engagement analysis. DAiSEE is one of the datasets which consist of in-the-wild data and has a gold standard annotation for engagement prediction. Earlier research done using the DAiSEE dataset involved training and testing standard models like CNN-based models, but the results were not satisfactory according to industry standards. In this paper, a multi-level classification approach has been introduced to create a more robust model for engagement analysis using the DAiSEE dataset. This approach has recorded testing accuracies of 0.638, 0.7728, 0.8195, and 0.866 for predicting boredom level, engagement level, confusion level, and frustration level, respectively.

Keywords: computer vision, engagement prediction, deep learning, multi-level classification

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Authors: Yalisa Tonsorn

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The objectives of this study are 1) to study the readiness of Thai tour operators in order to prepare for being ASEAN members, 2) to study opportunity and obstacles of the management of Thai tour operators, and 3) to find approach for developing value chain in order to enhance the management efficiency of Thai tour operators in order to support free trade within the framework of ASEAN cooperation. The research methodology is mixed between qualitative method and quantitative method. In-depth interview was done with key informants, including management supervisors, medium managers, and officers of the travel agencies. The questionnaire was conducted with 300 sampling. According to the study, it was found that the approach for developing value chain to enhance the management efficiency of Thai travel agencies in order to support free trade within the framework of ASEAN cooperation, the tour operators must give priority to the customer and deliver the service exceeding the customer’s expectation. There are 2 groups of customers: 1) external customers referring to tourist, and 2) internal customers referring to staff who deliver the service to the customers, including supervisors, colleagues, or subordinates. There are 2 issues which need to be developed: 1) human resource development in order to cultivate the working concept by focusing on importance of customers, and excellent service providing, and 2) working system development by building value and innovation in operational process including services to the company in order to deliver the highest impressive service to both internal and external customers. Moreover, the tour operators could support the increased number of tourists significantly. This could enhance the capacity of the business and affect the increase of competition capability in the economic dimension of the country.

Keywords: AEC (ASEAN Economic Eommunity), core activities, support activities, values chain

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Authors: Duaa Mughal, Syeda Areeba Nadeem, Shakil Ahmed, Ishtiaq Ahmed Khan

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The identification of porcine DNA in Halal food items is critical to ensuring compliance with dietary restrictions and religious beliefs. In Islam, Porcine is prohibited as clearly mentioned in Quran (Surah Al-Baqrah, Ayat 173). The purpose of this study was to compare two DNA extraction procedures for detecting 0.001% of porcine DNA in processed Halal food sample mixtures containing chicken, camel, veal, turkey and goat meat using the TaqMan Real-Time PCR technology. In this research, two different commercial kit protocols were compared. The processed sample mixtures were prepared by spiking known concentration of porcine DNA to non-porcine food matrices. Afterwards, TaqMan Real-Time PCR technique was used to target a particular porcine gene from the extracted DNA samples, which was quantified after extraction. The results of the amplification were evaluated for sensitivity, specificity, and reproducibility. The results of the study demonstrated that two DNA extraction techniques can detect 0.01% of porcine DNA in mixture of Halal food samples. However, as compared to the alternative approach, Eurofins| GeneScan GeneSpin DNA Isolation kit showed more effective sensitivity and specificity. Furthermore, the commercial kit-based approach showed great repeatability with minimal variance across repeats. Quantification of DNA was done by using fluorometric assay. In conclusion, the comparison of DNA extraction methods for detecting porcine DNA in Halal food sample mixes using the TaqMan Real-Time PCR technology reveals that the commercial kit-based approach outperforms the other methods in terms of sensitivity, specificity, and repeatability. This research helps to promote the development of reliable and standardized techniques for detecting porcine DNA in Halal food items, religious conformity and assuring nutritional.

Keywords: real time PCR (qPCR), DNA extraction, porcine DNA, halal food authentication, religious conformity

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Authors: S. Nagheli, N. Samani, D. A. Barry

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In this paper, the velocity potential and stream function of capture zone for a well field in an aquifer bounded by two parallel streams with or without a uniform regional flow of any directions are presented. The well field includes any number of extraction or injection wells or a combination of both types with any pumping rates. To delineate the capture envelope, the potential and streamlines equations are derived by conformal mapping method. This method can help us to release constrains of other methods. The equations can be applied as useful tools to design in-situ groundwater remediation systems, to evaluate the surface–subsurface water interaction and to manage the water resources.

Keywords: complex potential, conformal mapping, image well theory, Laplace’s equation, superposition principle

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Authors: A. A. Hassani, M. Nasri Nasrabadi

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According to population growth and increasing water needs of industrial and agricultural sections and lack of existing water sources, also increases of wastewater and new wastewater treatment plant construction’s high costs, it is inevitable to reuse wastewater with the approach of increasing wastewater treatment capacity and output sewage quality. In this regard, the first sewage reuse plan in industrial uses was designed with the approach of qualitative and quantitative improvement due to the increased organic load of the output sewage of Qom Shokohieh city’s’ in wastewater treatment plant. This research investigated qualitative factors COD, BOD, TSS, TDS, and input and output heavy metal of MBR-RO system and ability of increase wastewater acceptance capacity by existing in wastewater treatment plant. For this purpose, experimental results of seven-month navigation system have been used from 07/01/2013 to 02/01/2014. Existing data analysis showed that MBR system is able to remove 93.2% COD, 94.4% BOD, 13.8% TDS, 98% heavy metals and RO system is able to remove 98.9% TDS. This study showed that MBR-RO integration system is able to increase the capacity of refinery by 30%.

Keywords: industrial wastewater, wastewater reuse, MBR, RO

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Authors: Omid Allan

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The advent of ultra-narrow diameter implants initially offered an alternative to wider conventional implants. However, their design limitations have restricted their applicability primarily to overdentures and cement-retained fixed prostheses, often with unpredictable long-term outcomes. The introduction of the new Miniature Implants has revolutionized the field of implant dentistry, leading to a more streamlined approach. The utilization of Miniature Implants has emerged as a promising alternative to the traditional approach that entails the traumatic sequential bone drilling procedures and the use of conventional implants for full and partial arch restorations. The innovative "BioMiniatures Implant System serves as a groundbreaking bridge connecting mini implants with standard implant systems. This system allows practitioners to harness the advantages of ultra-small implants, enabling minimally invasive insertion and facilitating the application of fixed screw-retained prostheses, which were only available to conventional wider implant systems. This approach streamlines full and partial arch rehabilitation with minimal or even no bone drilling, significantly reducing surgical risks and complications for clinicians while minimizing patient morbidity. The ultra-narrow diameter and self-advancing features of these implants eliminate the need for invasive and technically complex procedures such as bone augmentation and guided bone regeneration (GBR), particularly in cases involving thin alveolar ridges. Furthermore, the absence of a microcap between the implant and abutment eliminates the potential for micro-leakage and micro-pumping effects, effectively mitigating the risk of marginal bone loss and future peri-implantitis. The cumulative experience of restoring over 50 full and partial arch edentulous cases with this system has yielded an outstanding success rate exceeding 97%. The long-term success with a stable marginal bone level in the study firmly establishes these implants as a dependable alternative to conventional implants, especially for full arch rehabilitation cases. Full arch rehabilitation with these implants holds the promise of providing a simplified solution for edentulous patients who typically present with atrophic narrow alveolar ridges, eliminating the need for extensive GBR and bone augmentation to restore their dentition with fixed prostheses.

Keywords: mini-implant, biominiatures, miniature implants, minimally invasive dentistry, full arch rehabilitation

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Authors: Markus Nordlund, Arkadiusz K. Kuczaj

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Philip Morris International (PMI) is developing a range of novel tobacco products with the potential to reduce individual risk and population harm in comparison to smoking cigarettes. One of these products is the Tobacco Heating System 2.2 (THS 2.2), (named as the Electrically Heated Tobacco System (EHTS) in this paper), already commercialized in a number of countries (e.g., Japan, Italy, Switzerland, Russia, Portugal and Romania). During use, the patented EHTS heats a specifically designed tobacco product (Electrically Heated Tobacco Product (EHTP)) when inserted into a Holder (heating device). The EHTP contains tobacco material in the form of a porous plug that undergoes a controlled heating process to release chemical compounds into vapors, from which an aerosol is formed during cooling. The aim of this work was to investigate the aerosol formation characteristics for realistic operating conditions of the EHTS as well as for relevant gas mixture compositions measured in the EHTP aerosol consisting mostly of water, glycerol and nicotine, but also other compounds at much lower concentrations. The nucleation process taking place in the EHTP during use when operated in the Holder has therefore been modeled numerically using an extended Classical Nucleation Theory (CNT) for multicomponent gas mixtures. Results from the performed simulations demonstrate that aerosol droplets are formed only in the presence of an aerosol former being mainly glycerol. Minor compounds in the gas mixture were not able to reach a supersaturated state alone and therefore could not generate aerosol droplets from the multicomponent gas mixture at the operating conditions simulated. For the analytically characterized aerosol composition and estimated operating conditions of the EHTS and EHTP, glycerol was shown to be the main aerosol former triggering the nucleation process in the EHTP. This implies that according to the CNT, an aerosol former, such as glycerol needs to be present in the gas mixture for an aerosol to form under the tested operating conditions. To assess if these conclusions are sensitive to the initial amount of the minor compounds and to include and represent the total mass of the aerosol collected during the analytical aerosol characterization, simulations were carried out with initial masses of the minor compounds increased by as much as a factor of 500. Despite this extreme condition, no aerosol droplets were generated when glycerol, nicotine and water were treated as inert species and therefore not actively contributing to the nucleation process. This implies that according to the CNT, an aerosol cannot be generated without the help of an aerosol former, from the multicomponent gas mixtures at the compositions and operating conditions estimated for the EHTP, even if all minor compounds are released or generated in a single puff.

Keywords: aerosol, classical nucleation theory (CNT), electrically heated tobacco product (EHTP), electrically heated tobacco system (EHTS), modeling, multicomponent, nucleation

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Authors: Endrick Barnacin, Jean-Luc Henry, Jack Molinié, Jimmy Nagau, Hélène Delatte, Gérard Lebreton

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Palynology is a field of interest for many disciplines. It has multiple applications such as chronological dating, climatology, allergy treatment, and even honey characterization. Unfortunately, the analysis of a pollen slide is a complicated and time-consuming task that requires the intervention of experts in the field, which is becoming increasingly rare due to economic and social conditions. So, the automation of this task is a necessity. Pollen slides analysis is mainly a visual process as it is carried out with the naked eye. That is the reason why a primary method to automate palynology is the use of digital image processing. This method presents the lowest cost and has relatively good accuracy in pollen retrieval. In this work, we propose a system combining recognition and grouping of pollen. It consists of using a Logistic Model Tree to classify pollen already known by the proposed system while detecting any unknown species. Then, the unknown pollen species are divided using a cluster-based approach. Success rates for the recognition of known species have been achieved, and automated clustering seems to be a promising approach.

Keywords: pollen recognition, logistic model tree, expectation-maximization, local binary pattern

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Authors: Shilpa Balan

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Radio Frequency Identification, also popularly known as RFID is used to automatically identify and track tags attached to items. This study focuses on the application of RFID in healthcare. The adoption of RFID in healthcare is a crucial technology to patient safety and inventory management. Data from RFID tags are used to identify the locations of patients and inventory in real time. Medical errors are thought to be a prominent cause of loss of life and injury. The major advantage of RFID application in healthcare industry is the reduction of medical errors. The healthcare industry has generated huge amounts of data. By discovering patterns and trends within the data, big data analytics can help improve patient care and lower healthcare costs. The number of increasing research publications leading to innovations in RFID applications shows the importance of this technology. This study explores the current state of research of RFID in healthcare using a text mining approach. No study has been performed yet on examining the current state of RFID research in healthcare using a data mining approach. In this study, related articles were collected on RFID from healthcare journal and news articles. Articles collected were from the year 2000 to 2015. Significant keywords on the topic of focus are identified and analyzed using open source data analytics software such as Rapid Miner. These analytical tools help extract pertinent information from massive volumes of data. It is seen that the main benefits of adopting RFID technology in healthcare include tracking medicines and equipment, upholding patient safety, and security improvement. The real-time tracking features of RFID allows for enhanced supply chain management. By productively using big data, healthcare organizations can gain significant benefits. Big data analytics in healthcare enables improved decisions by extracting insights from large volumes of data.

Keywords: RFID, data mining, data analysis, healthcare

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Authors: Dimple Juneja, Aarti Singh, Renu Hooda

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Knowledge Query Manipulation Language (KQML) and FIPA ACL are two prime communication languages existing in multi agent systems (MAS). Both languages are more or less similar in terms of semantics (based on speech act theory) and offer cutting edge competition while establishing agent communication across Internet. In contrast to the fact that software agents operating on the internet are required to be more safeguarded from their counter-peer, both protocols lack security performatives. The paper proposes a three tier security interface with few novel security related performatives enhancing the basic architecture of KQML. The three levels are attestation, certification and trust establishment which enforces a tight security and hence reduces the security breeches.

Keywords: multiagent systems, KQML, FIPA ACL, performatives

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Authors: Guohong Wang, Hao Huang, Rui Xing, Liyan Tang, Yu Wang

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Start-ups are consistently under pressure to overcome liabilities of newness and smallness. They must focus on assembling resource and engaging constant renewal and repeated entrepreneurial activities to survive and grow. As an important form of resource, knowledge is constantly vital to start-ups, which will help start-ups with developing new product in hence forming competitive advantage. However, significant knowledge is usually needed to be identified and exploited from external entities, which makes it difficult to achieve knowledge transfer; with limited resources, it can be quite challenging for start-ups balancing the exploration and exploitation of knowledge. The research on knowledge transfer has become a relatively well-developed domain by indicating that knowledge transfer can be achieved through plenty of patterns, yet it is still under-explored that what processes and organizational practices help start-ups facilitating knowledge transfer for new product in the context portfolio entrepreneurship. Resource orchestration theory emphasizes the initiative and active management of company or the manager to explain the fulfillment of resource utility, which will help understand the process of managing knowledge as a certain kind of resource in start-ups. Drawing on the resource orchestration theory, this research aims to explore how knowledge transfer can be facilitated through resource orchestration. A qualitative single-case study of a sodium-ion battery new venture was conducted. The case company is sampled deliberately from representative industrial agglomeration areas in Liaoning Province, China. It is found that distinctive resource orchestration sub-processes are leveraged to facilitate knowledge transfer: (i) resource structuring makes knowledge available across the portfolio; (ii) resource bundling makes combines internal and external knowledge to form new knowledge; and (iii) resource harmonizing balances specific knowledge configurations across the portfolio. Meanwhile, by purposefully reallocating knowledge configurations to new product development in a certain new venture (exploration) and gradually adjusting knowledge configurations to being applied to existing products across the portfolio (exploitation), resource orchestration processes as a whole make exploration and exploitation of knowledge balanced. This study contributes to the knowledge management literature through proposing a resource orchestration view and depicting how knowledge transfer can be facilitated through different resource orchestration processes and mechanisms. In addition, by revealing the balancing process of exploration and exploitation of knowledge, and laying stress on the significance of the idea of making exploration and exploitation of knowledge balanced in the context of portfolio entrepreneurship, this study also adds specific efforts to entrepreneurship and strategy management literature.

Keywords: exploration and exploitation, knowledge transfer, new product development, portfolio entrepreneur, resource orchestration

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Authors: Md. Mahamud Hassan, Shantanu Biswas Linkon, Nur Mohammad Khan

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Over the last three decades, the primary education system in Bangladesh has experienced significant improvement, but it has failed to cope with different social and cultural aspects, which present many challenges for children, families, and the public school system. Neglecting our own contextual learning environment, it is a matter of sorrow that much attention has been paid to the more physical outcome-focused model, which is nothing but mere infrastructural development, and less subtle to the environment that suits the child's psychology and improves their social, emotional, physical, and moral competency. In South Asia, the symbol of education was never the little red house of colonial architecture but “A Guru sitting under a tree", whereas a responsive and inclusive design approach could help to create more innovative learning environments. Such an approach incorporates how the built, natural, and cultural environment shapes the learner; in turn, learners shape the learning. This research will be conducted to, i) identify the major issues and drawbacks of government policy for primary education development programs; ii) explore and evaluate the morphology of the conventional model of school, and iii) propose an alternative model in a collaborative design process with the stakeholders for maximizing the relationship between the physical learning environments and learners by treating “the built environment” as “the third teacher.” Based on observation, this research will try to find out to what extent built, and natural environments can be utilized as a teaching tool for a more optimal learning environment. It should also be evident that there is a significant gap in the state policy, predetermined educational specifications, and implementation process in response to stakeholders’ involvement. The outcome of this research will contribute to a people-place sensitive design approach through a more thoughtful and responsive architectural process.

Keywords: built environment, conventional planning, indigenous learning space, responsive design

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Authors: Shane-Anthony Smith

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Teachers across grade levels and content areas face a myriad of challenges in the classroom. From inconsistent attendance to disruptive behaviors, these challenges can have a dire impact on the educational space, untimely leading to a loss of instructional time and student disenfranchisement from learning. While these challenges are not new to the educational landscape, the post-COVID classroom has, in many instances, been more severely impacted by behaviors that are not conducive to learning. Despite the mounting challenges, the role of the teacher remains unchanged - that is, to create and maintain a safe environment that is conducive to learning and promotes successful learning outcomes. Accomplishing this feat is no easy task. Yet, there are steps teachers can - indeed, must - take to better set themselves and their students up for success. The key to achieving this success is effective classroom transitions. This paper presents a four-step approach for teachers to engage in successful classroom transitions to promote meaningful student engagement and active positive learning outcomes. The transition strategy I will explore is called PREP (Pause, Reset, Establish Expectations, and Proceed). I developed this strategy in my work as a Residency Director for my university’s teacher residency program. In this role, I am tasked with coaching emerging teachers and their in-service teaching mentors in the field, as well as providing mentorship to special education resident teachers pursuing teaching degrees in the program. As a teacher educator, being in Middle and High school classrooms provides an intricate and critical understanding of the challenges, opportunities, and possibilities in the classroom. For this paper, I will explore how teachers can optimize the opportunities PREP provides to keep students engaged and, thus, improve student achievement. I will describe the approach, explain its use, and provide case-study examples of its classroom application.

Keywords: classroom management, teaching strategies, student engagement, classroom transition

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Authors: Yi-Min Lan, Hung-Wen Cheng, Hsuan-Ling Chang, Jou-Ping Yu

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The study applies machine learning models to construct momentum strategies and utilizes the information coefficient as an indicator for selecting stocks with strong and weak momentum characteristics. Through this approach, the study has built investment portfolios capable of generating superior returns and conducted a thorough analysis. Compared to existing research on momentum strategies, machine learning is incorporated to capture non-linear interactions. This approach enhances the conventional stock selection process, which is often impeded by difficulties associated with timeliness, accuracy, and efficiency due to market risk factors. The study finds that implementing bidirectional momentum strategies outperforms unidirectional ones, and momentum factors with longer observation periods exhibit stronger correlations with returns. Optimizing the number of stocks in the portfolio while staying within a certain threshold leads to the highest level of excess returns. The study presents a novel framework for momentum strategies that enhances and improves the operational aspects of asset management. By introducing innovative financial technology applications to traditional investment strategies, this paper can demonstrate significant effectiveness.

Keywords: information coefficient, machine learning, momentum, portfolio, return prediction

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Authors: Munir Kassa, Mengistu Hailemariam, Meghan Obermeyer, Kefelegn Baruda, Yonas Getachew, Asnakech Dessie

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Improving the quality of sexual and reproductive health services that women receive is expected to have an impact on women’s satisfaction with the services, on their continued use and, ultimately, on their ability to achieve their fertility goals or reproductive intentions. Surprisingly, however, there is little empirical evidence of either whether this expectation is correct, or how best to improve service quality within sexual and reproductive health programs so that these impacts can be achieved. The Recent focus on quality has prompted more physicians to do quality improvement work, but often without the needed skill sets, which results in poorly conceived and ultimately unsuccessful improvement initiatives. As this renders the work unpublishable, it further impedes progress in the field of health care improvement and widens the quality chasm. Moreover, since 2014, the Center for International Reproductive Health Training (CIRHT) has worked diligently with 11 teaching hospitals across Ethiopia to increase access to contraception and abortion care services. This work has included improving pre-service training through education and curriculum development, expanding hands-on training to better learn critical techniques and counseling skills, and fostering a “team science” approach to research by encouraging scientific exploration. This is the first time this systematic approach has been applied and documented to improve access to high-quality services in Ethiopia. The purpose of this article is to report initiatives undertaken, and findings concluded by the clinical service team at CIRHT in an effort to provide a pragmatic approach to quality improvement projects. An audit containing nearly 300 questions about several aspects of patient care, including structure, process, and outcome indicators was completed by each teaching hospital’s quality improvement team. This baseline audit assisted in identifying major gaps and barriers, and each team was responsible for determining specific quality improvement aims and tasks to support change interventions using Shewart’s Cycle for Learning and Improvement (the Plan-Do-Study-Act model). To measure progress over time, quality improvement teams met biweekly and compiled monthly data for review. Also, site visits to each hospital were completed by the clinical service team to ensure monitoring and support. The results indicate that applying an evidence-based, participatory approach to quality improvement has the potential to increase the accessibility and quality of services in a short amount of time. In addition, continued ownership and on-site support are vital in promoting sustainability. This approach could be adapted and applied in similar contexts, particularly in other African countries.

Keywords: abortion, contraception, quality improvement, service provision

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Authors: A. T. Muruviwa

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To-date, the discourse on corporate social responsibility (CSR) has primarily centred on the actions and inactions of corporations; hence, the dominant focus on CSR has been on impacts and outcomes. The obscuring effect of this approach has, arguably, resulted in the emergence of what may be termed a ‘Northern’ agenda on CSR theory and practice, in contrast to an emergency ‘Southern’ discourse, which appears to highlight the crucial issues of poverty reduction, infrastructure development and the broader questions of social provisioning and community empowerment. Some scholars have explicitly called for a CSR research agenda that focuses on the 'reciprocal duties' of the stakeholders in the CSR process rather than fixate on the actions and inactions of business. It is against the backdrop of these contestations that this study assesses the reciprocal relationships amongst CSR stakeholders in a Zimbabwean platinum mining town, with a view to demonstrating how such relationships – and the expectations and obligations embedded in them – impact on the success or failure of CSR initiatives. The existence of mutual relations between the corporation and its stakeholders signifies the successes of CSR processes and hence the outcomes. The company is Zimplats Mining Company; the community is Mhondoro-Ngezi, and the stakeholders are clearly identified in the study. The study utilised a triangulated design, with data collected using a mini survey, focus groups, in-depth interview and observation. The key findings are that the CSR process in the study community is dominated by the mining company. Despite the existence of a CSR framework that recognises government, local leaders and community members as legitimate stakeholders, there is little evidence of concrete contributions made by these stakeholders towards the realisation of CSR objectives. As a result, the community development process – in so far as CSR is concerned – fails to address the developmental concerns of the various stakeholders. On the basis of these findings, the study concludes that there is a crisis of reciprocity in the CSR process in Mhondoro-Ngezi, and that a situation where the conceptualisation of local development needs and the deployment of specific development tools seems to be driven by one stakeholder almost to the exclusion of all others, can only present contradictory development outcomes. The significance of this study is that it allows for the development of a more nuanced and robust CSR discourse. Rather than focusing on the corporate and stakeholder perspectives and outcomes of CSR initiatives, this study examines the CSR- development nexus by interrogating the idea of reciprocal responsibility as a sin qua non to CSR success. This analytical strategy and focus allow the researcher to gain a clear understanding of how stakeholder relationships and duties influence CSR processes and also the overall outcome. At a more practical level, the findings of the study should help to shape the policy on corporate community relationships with a view to enhancing the role of mining in development.

Keywords: community development, processes, reciprocity, stakeholders

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Authors: Shai Sarussi

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Let S be an integral domain with field of fractions F and let A be an F-algebra. An S-subalgebra R of A is called S-nice if R∩F = S and the localization of R with respect to S \{0} is A. Denoting by W the set of all S-nice subalgebras of A, and defining a notion of open sets on W, one can view W as a T0-Alexandroff space. Thus, the algebraic structure of W can be viewed from the point of view of topology. It is shown that every nonempty open subset of W has a maximal element in it, which is also a maximal element of W. Moreover, a supremum of an irreducible subset of W always exists. As a notable connection with valuation theory, one considers the case in which S is a valuation domain and A is an algebraic field extension of F; if S is indecomposed in A, then W is an irreducible topological space, and W contains a greatest element.

Keywords: integral domains, Alexandroff topology, prime spectrum of a ring, valuation domains

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Authors: Shao-Ying Wang, Shin-I Shih, Chi-Cheng Wu

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Background: By following to the maturity theory about age, the manifestation of depression in different age groups under occupational stressors still remains unclear. Therefore, the aim of this study was to examine the depression within four main symptoms clusters: cognition, affect, physical complaints and interpersonal difficulty among the different age groups. Additionally, this study also used the stress appraisal theory, through the examination of challenge and hindrance appraisals, the effects of cognitive factors were expected to give therapeutic indication for the future treatment of depression under abusive leadership. Methods (Participants and Procedure): The data were collected in two waves from employees of local companies in Taiwan. The participants (58 males and 167 females) were native Chinese speakers, ranging in age from 20 to 59 years (M= 36.51). Up to 80% educational level of participants were above senior high. The married population was approximately at 43%. Measures; 1. Abusive Leadership: To measure abusive leadership, we used 15-item scale of abusive supervision which anchored on a 7-point Likert-type scale. (α= .96) 2. Depression: We used Taiwanese Depression Scale to measure the 4 clusters (cognition, affect, physical complaints and interpersonal difficulty) of symptoms. Participants responded for depression anchored on a 7-point Likert-type scale (α= .96). 3. Stress Appraisal Scale: To measure challenge and hindrance types of appraisal, participants responded to 33-item measure anchored on a 7-point Likert-type scale. (Challenge appraisal; α= .90; hindrance appraisal α= .87). Results: The results of correlation showed that there was a significant and negative correlation between abusive leadership and age (r = - .21, p < .01). Abusive leadership was positive correlated significantly with hindrance appraisal (r = .52, p < .01) and depression (r = .20, p < .01). The results also showed that hindrance appraisal was correlated to depression positively (r = .36, p < .01). A one-way ANOVA was conducted to compare the effect of lower/middle/order age groups on each cluster of depressive symptoms. The results showed that the effect of age groups on cognition was significant F (2, 157) =3.66, P < .05. Older age group (M=13.43 SD=6.84) reported less cognitive symptoms of depression than the middle (M=16.77 SD=7.49) and lower age (M=16.91 SD=6.97) groups. Besides, the effect of age groups on affect was also significant F (2,157)= 4.09 P < .05. Older age group (M=18.68 SD=8.98) reported less affective symptoms of depression than the middle (M=22.01 SD=7.96) and lower age (M=23.56 SD=7.67) groups. Moreover, the main effect of hindrance appraisal was found F (2, 157) =3.81, P < .05. Older age group (M=9.44 SD=2.89) reported fewer score on hindrance appraisals than the middle (M=11.06 SD=4.02) and lower age (M=9.62 SD=3.17) groups. To conclude, the severity of depression symptoms varies across different age groups. Maturity seems to be the protective factor to depression, accompanying with lower hindrance appraisals.

Keywords: abusive leadership, affective commitment, depression symptoms, psychological well-being

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Authors: Thilini M. Yatanwala

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CCTV (Closed-Circuit-Television) Surveillance System is being used in public places over decades and a large variety of data is being produced every moment. However, most of the CCTV data is stored in isolation without having integrity. As a result, identification of the behavior of suspicious people along with their location has become strenuous. This research was conducted to acquire more accurate and reliable timely information from the CCTV video records. The implemented system can identify human objects in public places based on outfit colors. Inter-process communication technologies were used to implement the CCTV camera network to track people in the premises. The research was conducted in three stages and in the first stage human objects were filtered from other movable objects available in public places. In the second stage people were uniquely identified based on their outfit colors and in the third stage an individual was continuously tracked in the CCTV network. A face detection algorithm was implemented using cascade classifier based on the training model to detect human objects. HAAR feature based two-dimensional convolution operator was introduced to identify features of the human face such as region of eyes, region of nose and bridge of the nose based on darkness and lightness of facial area. In the second stage outfit colors of human objects were analyzed by dividing the area into upper left, upper right, lower left, lower right of the body. Mean color, mod color and standard deviation of each area were extracted as crucial factors to uniquely identify human object using histogram based approach. Color based measurements were written in to XML files and separate directories were maintained to store XML files related to each camera according to time stamp. As the third stage of the approach, inter-process communication techniques were used to implement an acknowledgement based CCTV camera network to continuously track individuals in a network of cameras. Real time analysis of XML files generated in each camera can determine the path of individual to monitor full activity sequence. Higher efficiency was achieved by sending and receiving acknowledgments only among adjacent cameras. Suspicious incidents such as a person staying in a sensitive area for a longer period or a person disappeared from the camera coverage can be detected in this approach. The system was tested for 150 people with the accuracy level of 82%. However, this approach was unable to produce expected results in the presence of group of people wearing similar type of outfits. This approach can be applied to any existing camera network without changing the physical arrangement of CCTV cameras. The study of human identification and suspicious incident detection using outfit color analysis can achieve higher level of accuracy and the project will be continued by integrating motion and gait feature analysis techniques to derive more information from CCTV videos.

Keywords: CCTV surveillance, human detection and identification, image processing, inter-process communication, security, suspicious detection

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Authors: Sami Baraketi, Jean Marie Garcia, Olivier Brun

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Wavelength Division Multiplexing (WDM) is the dominant transport technology used in numerous high capacity backbone networks, based on optical infrastructures. Given the importance of costs (CapEx and OpEx) associated to these networks, resource management is becoming increasingly important, especially how the optical circuits, called “lightpaths”, are routed throughout the network. This requires the use of efficient algorithms which provide routing strategies with the lowest cost. We focus on the lightpath routing and wavelength assignment problem, known as the RWA problem, while optimizing wavelength fragmentation over the network. Wavelength fragmentation poses a serious challenge for network operators since it leads to the misuse of the wavelength spectrum, and then to the refusal of new lightpath requests. In this paper, we first establish a new Integer Linear Program (ILP) for the problem based on a node-link formulation. This formulation is based on a multilayer approach where the original network is decomposed into several network layers, each corresponding to a wavelength. Furthermore, we propose an efficient heuristic for the problem based on a greedy algorithm followed by a post-treatment procedure. The obtained results show that the optimal solution is often reached. We also compare our results with those of other RWA heuristic methods.

Keywords: WDM, lightpath, RWA, wavelength fragmentation, optimization, linear programming, heuristic

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Authors: Clinton Adas

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Industrial animal farming contributes to numerous problems that humans face, and among these, antimicrobial resistance (AMR) has been identified by the World Health Organisation as a real possibility for the 21st Century. While numerous factors contribute to AMR, one of them is industrial animal farming and its effect on the food chain and environment. In 2017, livestock were given around 73% of all antibiotics worldwide to make them grow faster for profit purposes, to prevent illness caused by unhealthy living conditions, and to treat disease when it breaks out. Many of the antibiotics used provide little benefit to animals, and most are the same as those used by humans - including many deemed critical to human health that should be used sparingly. AMR contributes to millions of illnesses, and in 2019 was responsible for around 4.95 million deaths worldwide. It costs Europe around nine billion euros per year, while it costs the United States (US) around 20 billion dollars per year. While not a simple or quick solution, one way to begin to address the challenge of AMR and other harms from this type of farming is to focus on animal welfare as part of a One Health and Welfare approach, as better welfare requires less antibiotics usage, which may begin to break the cycle.

Keywords: animal and human welfare, industrial animal farming, antimicrobial resistance, one health and welfare, sustainable development goals

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Authors: Payman Tajalli, Steven Segal

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Applied ethics is an area of ethics which is looked upon most favorably as the most appropriate and useful for educational purposes; after all if ethics finds no application would any investment of time, effort and finance by the educational institutions be warranted? The current approaches to ethics in business and management often entail appealing to various types of moral theories and to this end almost every major philosophical approach has been enlisted. In this paper, we look at ethics through the philosophy of Emmanuel Levinas to argue that since ethics is ‘first philosophy’ it can neither be rule-based nor rule-governed, not something that can be worked out first and then applied to a given situation, hence the overwhelming emphasis on ‘applied ethics’ as a field of study in business and management education is unjustified. True ethics is not applied ethics. This assertion does not mean that teaching ethical theories and philosophies need to be abandoned rather it is the acceptance of the fact that an increase in cognitive awareness of such theories and ethical models and frameworks, or the mastering of techniques and procedures for ethical decision making, will not affect the desired ethical transformation in our students. Levinas himself argued for an ethics without a foundation, not one that required us to go ‘beyond good and evil’ as Nietzsche contended, rather an ethics which necessitates going ‘before good and evil'. Such an ethics does not provide us with a set of methods or techniques or a decision tree that enable us determine the rightness of an action and what we ought to do, rather it is about a way of being, an ethical posture or approach one takes in the inter-subjective relationship with the other that holds the promise of ethical conduct. Ethics in this Levinasian sense then is one of infinite and unconditional responsibility for the other person in relationship, an ethics which is not subject to negotiation, calculation or reciprocity, and as such it could neither be applied nor taught through conventional pedagogy with its focus on knowledge transfer from the teacher to student, and to this end Levinas offers a non-maieutic, non-conventional approach to pedagogy. The paper concludes that from a Levinasian perspective on ethics and education, we may need to guide our students to move away from the clear and objective professionalism of the management and applied ethics towards the murky individual spiritualism. For Levinas, this is ‘the Copernican revolution’ in ethics.

Keywords: business ethics, ethics education, Levinas, maieutic teaching, ethics without foundation

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Authors: Azzam Alosaimi

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Different countries attempt to reduce energy demands and Greenhouse Gas (GHG) emissions to mitigate global warming potential. They set different building codes to regulate excessive building’s energy losses. Energy losses occur due to pressure difference between the indoor and outdoor environments, and thus, heat transfers from one region to another. One major sources of energy loss is known as building airtightness. Building airtightness is the fundamental feature of the building envelope that directly impacts infiltration. Most of international building codes require minimum performance for new construction to ensure acceptable airtightness. The execution of airtightness required standards has become more challenging in recent years due to a lack of expertise and equipment, making it costly and time-consuming. Hence, researchers have developed predictive models to predict buildings infiltration rates to meet building codes and to reduce energy and cost. This research applies a theoretical modeling approach using Matlab software to predict mean infiltration rate distributions and total heat loss of Saudi Arabia’s housing stock.

Keywords: infiltration rate, energy demands, heating loss, cooling loss, carbon emissions

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Authors: Mohammad Alshawaf, Rahmat Poudineh, Nawaf Alhajeri

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The power generated from photovoltaic (PV) modules is non-dispatchable on demand due to the stochastic nature of solar radiation. The random variations in the measured intensity of solar irradiance are due to clouds and, in the case of arid regions, dust storms which decrease the intensity of intensity of solar irradiance. Therefore, modeling PV power output using average, maximum, or minimum solar irradiance values is inefficient to predict power generation reliably. The overall objective of this paper is to predict the power output of PV modules using Monte Carlo approach based the weather and solar conditions measured in Kuwait. Given the 250 Wp PV module used in study, the average daily power output is 1021 Wh/day. The maximum power was generated in April and the minimum power was generated in January 1187 Wh/day and 823 Wh/day respectively. The certainty of the daily predictions varies seasonally and according to the weather conditions. The output predictions were far more certain in the summer months, for example, the 80% certainty range for August is 89 Wh/day, whereas the 80% certainty range for April is 250 Wh/day.

Keywords: Monte Carlo, solar energy, variable renewable energy, Kuwait

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Authors: Mehrdad Abkenari, Mehmet Kunt, Mahdi Nourollahi

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Evaluating the environmental risk factors is a combination of analysis of transportation effects. Various definitions for risk can be found in different scientific sources. Each definition depends on a specific and particular perspective or dimension. The effects of potential risks present along the new proposed routes and existing infrastructures of large transportation projects like railways should be studied under comprehensive engineering frameworks. Despite various definitions provided for ‘risk’, all include a uniform concept. Two obvious aspects, loss and unreliability, have always been pointed in all definitions of this term. But, selection as the third aspect is usually implied and means how one notices it. Currently, conducting engineering studies on the environmental effects of railway projects have become obligatory according to the Environmental Assessment Act in developing countries. Considering the longitudinal nature of these projects and probable passage of railways through various ecosystems, scientific research on the environmental risk of these projects have become of great interest. Although many areas of expertise such as road construction in developing countries have not seriously committed to these studies yet, attention to these subjects in establishment or implementation of different systems have become an inseparable part of this wave of research. The present study used environmental risks identified and existing in previous studies and stations to use in next step. The second step proposes a new hybrid approach of analytical network process (ANP) and DEMATEL in fuzzy conditions for assessment of determined risks. Since evaluation of identified risks was not an easy touch, mesh structure was an appropriate approach for analyzing complex systems which were accordingly employed for problem description and modeling. Researchers faced the shortage of real space data and also due to the ambiguity of experts’ opinions and judgments, they were declared in language variables instead of numerical ones. Since fuzzy logic is appropriate for ambiguity and uncertainty, formulation of experts’ opinions in the form of fuzzy numbers seemed an appropriate approach. Fuzzy DEMATEL method was used to extract the relations between major and minor risk factors. Considering the internal relations of risk major factors and its sub-factors in the analysis of fuzzy network, the weight of risk’s main factors and sub-factors were determined. In general, findings of the present study, in which effective railway environmental risk indicators were theoretically identified and rated through the first usage of combined model of DEMATEL and fuzzy network analysis, indicate that environmental risks can be evaluated more accurately and also employed in railway projects.

Keywords: DEMATEL, ANP, fuzzy, risk

Procedia PDF Downloads 405