Search results for: rule ranking

Authors: Hassan Younis

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Purpose: The objective of this study is to review influential papers in the sustainability and supply chain studies domain, leveraging insights from this review to develop a structured framework for academics and researchers. This framework aims to assist scholars in identifying the most impactful publications for their scholarly pursuits. Subsequently, the study will apply and trial the developed framework on selected scholarly articles within the sustainability and supply chain studies domain to evaluate its efficacy, practicality, and reliability. Design/Methodology/Approach: Utilizing the "Publish or Perish" tool, a search was conducted to locate papers incorporating "sustainability" and "supply chain" in their titles. After rigorous filtering steps, a panel of university professors identified five crucial criteria for evaluating research robustness: average yearly citation counts (25%), scholarly contribution (25%), alignment of findings with objectives (15%), methodological rigor (20%), and journal impact factor (15%). These five evaluation criteria are abbreviated as “ACMAJ" framework. Each paper then received a tiered score (1-3) for each criterion, normalized within its category, and summed using weighted averages to calculate a Final Normalized Score (FNS). This systematic approach allows for objective comparison and ranking of the research based on its impact, novelty, rigor, and publication venue. Findings: The study's findings highlight the lack of structured frameworks for assessing influential sustainability research in supply chain management, which often results in a dependence on citation counts. A complete model that incorporates five essential criteria has been suggested as a response. By conducting a methodical trial on specific academic articles in the field of sustainability and supply chain studies, the model demonstrated its effectiveness as a tool for identifying and selecting influential research papers that warrant additional attention. This work aims to fill a significant deficiency in existing techniques by providing a more comprehensive approach to identifying and ranking influential papers in the field. Practical Implications: The developed framework helps scholars identify the most influential sustainability and supply chain publications. Its validation serves the academic community by offering a credible tool and helping researchers, students, and practitioners find and choose influential papers. This approach aids field literature reviews and study suggestions. Analysis of major trends and topics deepens our grasp of this critical study area's changing terrain. Originality/Value: The framework stands as a unique contribution to academia, offering scholars an important and new tool to identify and validate influential publications. Its distinctive capacity to efficiently guide scholars, learners, and professionals in selecting noteworthy publications, coupled with the examination of key patterns and themes, adds depth to our understanding of the evolving landscape in this critical field of study.

Keywords: supply chain management, sustainability, framework, model

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Authors: Hung-Chi Chang

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For an extended EPQ model with random yield, the existent study revealed that both the disaggregating and consolidating shipment policies for the imperfect quality items are independent of holding cost, and recommended a model with economic benefit by comparing the least total cost for each of the three models investigated. To better capture the real situation, we generalize the existent study to include different holding costs for perfect and imperfect quality items. Through analysis, we show that the above shipment policies are dependent on holding costs. Furthermore, we derive a simple decision rule solely based on the thresholds of problem parameters to select a superior model. The results are illustrated analytically and numerically.

Keywords: consolidating shipments, disaggregating shipments, EPQ, imperfect quality, inventory

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Authors: Gurleen Kour, Mowkshi Khullar, B. K. Chandan, Parvinder Pal Singh, Kushalava Reddy Yumpalla, Gurunadham Munagala, Ram A. Vishwakarma, Zabeer Ahmed

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New chemotherapeutic compounds against multidrug-resistant Mycobacterium tuberculosis (Mtb) are urgently needed to combat drug resistance in tuberculosis (TB). Apart from in-vitro potency against the target, physiochemical properties and pharmacokinetic properties play an imperative role in the process of drug discovery. We have identified novel nitroimidazole derivatives with potential activity against mycobacterium tuberculosis. One lead candidates, MCD-017, which showed potent activity against H37Rv strain (MIC=0.5µg/ml) and was further evaluated in the process of drug development. Methods: Basic physicochemical parameters like solubility and lipophilicity (LogP) were evaluated. Thermodynamic solubility was determined in PBS buffer (pH 7.4) using LC/MS-MS. The partition coefficient (Log P) of the compound was determined between octanol and phosphate buffered saline (PBS at pH 7.4) at 25°C by the microscale shake flask method. The compound followed Lipinski’s rule of five, which is predictive of good oral bioavailability and was further evaluated for metabolic stability. In-vitro metabolic stability was determined in rat liver microsomes. The hepatotoxicity of the compound was also determined in HepG2 cell line. In vivo pharmacokinetic profile of the compound after oral dosing was also obtained using balb/c mice. Results: The compound exhibited favorable solubility and lipophilicity. The physical and chemical properties of the compound were made use of as the first determination of drug-like properties. The compound obeyed Lipinski’s rule of five, with molecular weight < 500, number of hydrogen bond donors (HBD) < 5 and number of hydrogen bond acceptors(HBA) not more then 10. The log P of the compound was less than 5 and therefore the compound is predictive of exhibiting good absorption and permeation. Pooled rat liver microsomes were prepared from rat liver homogenate for measuring the metabolic stability. 99% of the compound was not metabolized and remained intact. The compound did not exhibit cytoxicity in hepG2 cells upto 40 µg/ml. The compound revealed good pharmacokinetic profile at a dose of 5mg/kg administered orally with a half life (t1/2) of 1.15 hours, Cmax of 642ng/ml, clearance of 4.84 ml/min/kg and a volume of distribution of 8.05 l/kg. Conclusion : The emergence of multi drug resistance (MDR) and extensively drug resistant (XDR) Tuberculosis emphasize the requirement of novel drugs active against tuberculosis. Thus, the need to evaluate physicochemical and pharmacokinetic properties in the early stages of drug discovery is required to reduce the attrition associated with poor drug exposure. In summary, it can be concluded that MCD-017 may be considered a good candidate for further preclinical and clinical evaluations.

Keywords: mycobacterium tuberculosis, pharmacokinetics, physicochemical properties, hepatotoxicity

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Authors: Gitanjali Pagare, Hansa Devi, S. P. Sanyal

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Full-potential linearized augmented plane wave (FLAPW) method has been employed within the generalized gradient approximation (GGA) and local spin density approximation (LSDA) as the exchange correlation potential to investigate elastic properties of LaX (X = Cd and Hg) in their B2-type (CsCl) crystal structure. The calculated ground state properties such as lattice constant (a0), bulk modulus (B) and pressure derivative of bulk modulus (B') agree well with the available experimental results. The second order elastic constants (C11, C12 and C44) have been calculated. The ductility or brittleness of these intermetallic compounds is predicted by using Pugh’s rule B/GH and Cauchy’s pressure (C12-C44). The calculated results indicate that LaHg is the ductile whereas LaCd is brittle in nature.

Keywords: ductility/brittleness, elastic constants, equation of states, FP-LAPW method, intermetallics

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Authors: Jane E. Hill

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Many variables led to the changes in the insanity defense since the Wild Beast Standard of 1723 until the Federal Insanity Defense Reform Act of 1984. The insanity defense is used in criminal trials and argued that the defendant is ‘not guilty by reason of insanity’ because the individual was unable to distinguish right from wrong during the time they were breaking the law. The issue that surrounds whether or not to use the insanity defense in the criminal court depends on the mental state of the defendant at the time the criminal act was committed. This leads us to the question of did the defendant know right from wrong when they broke the law? In 1723, The Wild Beast Test stated that to be exempted from punishment the individual is totally deprived of their understanding and memory and doth not know what they are doing. The Wild Beast Test became the standard in England for over seventy-five years. In 1800, James Hadfield attempted to assassinate King George III. He only made the attempt because he was having delusional beliefs. The jury and the judge gave a verdict of not guilty. However, to legal confine him; the Criminal Lunatics Act was enacted. Individuals that were deemed as ‘criminal lunatics’ and were given a verdict of not guilty would be taken into custody and not be freed into society. In 1843, the M'Naghten test required that the individual did not know the quality or the wrongfulness of the offense at the time they committed the criminal act(s). Daniel M'Naghten was acquitted on grounds of insanity. The M'Naghten Test is still a modern concept of the insanity defense used in many courts today. The Irresistible Impulse Test was enacted in the United States in 1887. The Irresistible Impulse Test suggested that offenders that could not control their behavior while they were committing a criminal act were not deterrable by the criminal sanctions in place; therefore no purpose would be served by convicting the offender. Due to the criticisms of the latter two contentions, the federal District of Columbia Court of Appeals ruled in 1954 to adopt the ‘product test’ by Sir Isaac Ray for insanity. The Durham Rule also known as the ‘product test’, stated an individual is not criminally responsible if the unlawful act was the product of mental disease or defect. Therefore, the two questions that need to be asked and answered are (1) did the individual have a mental disease or defect at the time they broke the law? and (2) was the criminal act the product of their disease or defect? The Durham courts failed to clearly define ‘mental disease’ or ‘product.’ Therefore, trial courts had difficulty defining the meaning of the terms and the controversy continued until 1972 when the Durham rule was overturned in most places. Therefore, the American Law Institute combined the M'Naghten test with the irresistible impulse test and The United States Congress adopted an insanity test for the federal courts in 1984.

Keywords: insanity defense, psychology law, The Federal Insanity Defense Reform Act of 1984, The Wild Beast Standard in 1723

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Authors: Revoti Prasad Bora, Nikita Katyal, Saurabh Yadav

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Pre-processing plays an important role in various image processing applications. Most of the time due to the similar nature of images, a particular pre-processing or a set of pre-processing steps are sufficient to produce the desired results. However, in the education domain, there is a wide variety of images in various aspects like images with line-based diagrams, chemical formulas, mathematical equations, etc. Hence a single pre-processing or a set of pre-processing steps may not yield good results. Therefore, a Deep Learning based approach for dynamically selecting a relevant pre-processing technique for each image is proposed. The proposed method works as a classifier to detect hidden patterns in the images and predicts the relevant pre-processing technique needed for the image. This approach experimented for an image similarity matching problem but it can be adapted to other use cases too. Experimental results showed significant improvement in average similarity ranking with the proposed method as opposed to static pre-processing techniques.

Keywords: deep-learning, classification, pre-processing, computer vision, image processing, educational data mining

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Authors: Mahdi Ebrahimi

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One of the most effective factors that can empower and modernize the Islamic government according to the needs of society is the institution of expediency in Islamic governance. At the same time, not paying attention to the foundations and principles of Islamic governance may cause this factor to create the basis for corruption and totalitarianism of the rulers, which ultimately causes a gap between the people and the rulers and the emergence of whole government corruption and dictatorship. Meanwhile, there are specific principles in the doctrine of Islamic Governance that can prevent such an event from happening. Principles such as: remaining popular and pious by the Ulama, Amr Bil-Maroof Va Nahy An Al-Munkar (commanding the good and preventing the bad) by the individuals, the rule of frank criticism with loud voices and clarification and accountability in the fields that cause the corruption of those in charge. In this research, these principles are presented along with their Islamic basis. It is also stated what effect each of these cases will have on preserving Islam in the ruling system.

Keywords: expediency, Islamic ruling, Islamic principles, Islam

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Authors: Yahaya Salihu Emeje, Amuchie Austine Anthony

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The topic examined the prospects of entrepreneurship as an emerging dynamic and strategic tool in the upliftment of human and non-human resources in the Nigerian university system, with a view of showcasing the abundant positive impact, on the Nigerian University system in particular and Nigerian economy at large. It is end at bringing out the benefits of entrepreneurship in the university system which includes, namely cultivating the culture of enterprise in University system; improvement in the quality and quantity of both human and non-human resources; innovative and creative methods of production; new employment strategies in the University system; improved sources of internal generated revenue; entrepreneurship as the culture of sustainability within and outside the university system. Secondary data was used in analyzing entrepreneurship as a productivity tool in the Nigeria University system. From the findings, the university system could be enriched through innovative ideas and technical revenue and employment generation; sustainable financial and economic base; university autonomy and improved international ranking of Nigerian Universities system; therefore, recommended that entrepreneurship is necessary therapy for reviving the ailing, Nigerian universities system.

Keywords: entrepreneurship, strategic, productivity, universities

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Authors: Nawab Yousuf Ali, S. Golam, A. Ameer, Ashok Toru Roy

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This paper develops new morphological rules suitable for Bangla repetition words to be incorporated into an inter lingua representation called Universal Networking Language (UNL). The proposed rules are to be used to combine verb roots and their inflexions to produce words which are then combined with other similar types of words to generate repetition words. This paper outlines the format of morphological rules for different types of repetition words that come from verb roots based on the framework of UNL provided by the UNL centre of the Universal Networking Digital Language (UNDL) foundation.

Keywords: Universal Networking Language (UNL), universal word (UW), head word (HW), Bangla-UNL Dictionary, morphological rule, enconverter (EnCo)

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Authors: Shuen-Tai Wang, Yu-Ching Lin, Hsi-Ya Chang

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Cloud computing and virtualization technology have brought an innovative way for people to develop and use software nowadays. However, conventional virtualization comes at the expense of performance loss for applications. Container-based virtualization could be an option as it potentially reduces overhead and minimizes performance decline of the service platform. In this paper, we introduce a system framework and present an implementation of resource broker for dynamic cloud service deployment on the container-based platform to facilitate the efficient execution and improve the utilization. We target the load-aware service deployment approach for task ranking scenario. This proposed effort can collaborate with resource management system to adaptively deploy services according to the different requests. In particular, our approach relies on composing service immediately onto appropriate container according to user’s requirement in order to conserve the waiting time. Our evaluation shows how efficient of the service deployment is and how to expand its applicability to support the variety of cloud service.

Keywords: cloud computing, container-based virtualization, resource broker, service deployment

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Authors: Huan Lin, Liwen Pang

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In order to reduce the ambiguity and uncertainty of product form bionic design, a product form bionic design method based on eye tracking is proposed. The eye-tracking experiment is designed to calculate the average time ranking of the specific parts of the bionic shape that the subjects are looking at. Key bionic shape is explored through the experiment and then applied to a desk lamp bionic design. During the design case, FAHP (Fuzzy Analytic Hierachy Process) and SD (Semantic Differential) method are firstly used to identify consumer emotional perception model toward desk lamp before product design. Through investigating different desk lamp design elements and consumer views, the form design factors on the desk lamp product are reflected and all design schemes are sequenced after caculation. Desk lamp form bionic design method is combined the key bionic shape extracted from eye-tracking experiment and priority of desk lamp design schemes. This study provides an objective and rational method to product form bionic design.

Keywords: Bionic design; Form; Eye tracking; FAHP; Desk lamp

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Authors: Wei-Neng Wang, Jhy-Yuan Shieh, Jhy-Hwa Chen, Juin-Jen Chang

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This paper incorporate tax evasion into a one-sector real business cycle (RBC) model to explores the quantitative interrelations between income tax rate and equilibrium (in)determinacy, and income tax rate is endogenously determined in order to balance the government budget. We find that the level of the effective income tax rate is key factor for equilibrium (in)determinacy, instead of the level of income tax rate in a tax evasion economy. Under an economy with tax evasion, the higher income tax rate is not sufficiently to lead to equilibrium indeterminate, it must combine with a necessary condition which is the lower fraction of tax evasion and that can result in agents' optimistic expectations to become self-fulfilling and sunspot fluctuation more likely to occur. On the other hand, an economy with tax evasion can see its macroeconomy become more stabilize, and a higher fraction of income tax evasion may has a stronger stabilizing effect.

Keywords: tax evasion, balanced-budget rule, equlibirium (in)determinacy, effective income tax rate

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Authors: Natalia Efremova, Sergey Tarasenko

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We propose a novel neural network architecture for visual saliency detections, which utilizes neuro physiologically plausible mechanisms for extraction of salient regions. The model has been significantly inspired by recent findings from neuro physiology and aimed to simulate the bottom-up processes of human selective attention. Two types of features were analyzed: color and direction of maximum variance. The mechanism we employ for processing those features is PCA, implemented by means of normalized Hebbian learning and the waves of spikes. To evaluate performance of our model we have conducted psychological experiment. Comparison of simulation results with those of experiment indicates good performance of our model.

Keywords: neural network models, visual saliency detection, normalized Hebbian learning, Oja's rule, psychological experiment

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Authors: Serkan Aras, Emrah Gulay

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Combining various forecasting models is an important tool for researchers to attain more accurate forecasts. A great number of papers have shown that selecting single models as dissimilar models, or methods based on different information as possible leads to better forecasting performances. However, there is not a certain rule regarding the number of single models to be used in any combining methods. This study focuses on determining the optimal or near optimal number for single models with the help of statistical tests. An extensive experiment is carried out by utilizing some well-known time series data sets from diverse fields. Furthermore, many rival forecasting methods and some of the commonly used combining methods are employed. The obtained results indicate that some statistically significant performance differences can be found regarding the number of the single models in the combining methods under investigation.

Keywords: combined forecast, forecasting, M-competition, time series

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Authors: Yonas Shuke Kitawa

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Background: Although malaria incidence has substantially fallen sharply over the past few years, the rate of decline varies by district, time, and malaria type. Despite this turn-down, malaria remains a major public health threat in various districts of Ethiopia. Consequently, the present study is aimed at developing a predictive model that helps to identify the spatio-temporal variation in malaria risk by multiple plasmodium species. Methods: We propose a multivariate spatio-temporal Bayesian model to obtain a more coherent picture of the temporally varying spatial variation in disease risk. The spatial autocorrelation in such a data set is typically modeled by a set of random effects that assign a conditional autoregressive prior distribution. However, the autocorrelation considered in such cases depends on a binary neighborhood matrix specified through the border-sharing rule. Over here, we propose a graph-based optimization algorithm for estimating the neighborhood matrix that merely represents the spatial correlation by exploring the areal units as the vertices of a graph and the neighbor relations as the series of edges. Furthermore, we used aggregated malaria count in southern Ethiopia from August 2013 to May 2019. Results: We recognized that precipitation, temperature, and humidity are positively associated with the malaria threat in the area. On the other hand, enhanced vegetation index, nighttime light (NTL), and distance from coastal areas are negatively associated. Moreover, nonlinear relationships were observed between malaria incidence and precipitation, temperature, and NTL. Additionally, lagged effects of temperature and humidity have a significant effect on malaria risk by either species. More elevated risk of P. falciparum was observed following the rainy season, and unstable transmission of P. vivax was observed in the area. Finally, P. vivax risks are less sensitive to environmental factors than those of P. falciparum. Conclusion: The improved inference was gained by employing the proposed approach in comparison to the commonly used border-sharing rule. Additionally, different covariates are identified, including delayed effects, and elevated risks of either of the cases were observed in districts found in the central and western regions. As malaria transmission operates in a spatially continuous manner, a spatially continuous model should be employed when it is computationally feasible.

Keywords: disease mapping, MSTCAR, graph-based optimization algorithm, P. falciparum, P. vivax, waiting matrix

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Authors: Dim En Nyaung, Thin Lai Lai Thein

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Due to the rapid increase of Internet, web opinion sources dynamically emerge which is useful for both potential customers and product manufacturers for prediction and decision purposes. These are the user generated contents written in natural languages and are unstructured-free-texts scheme. Therefore, opinion mining techniques become popular to automatically process customer reviews for extracting product features and user opinions expressed over them. Since customer reviews may contain both opinionated and factual sentences, a supervised machine learning technique applies for subjectivity classification to improve the mining performance. In this paper, we dedicate our work is the task of opinion summarization. Therefore, product feature and opinion extraction is critical to opinion summarization, because its effectiveness significantly affects the identification of semantic relationships. The polarity and numeric score of all the features are determined by Senti-WordNet Lexicon. The problem of opinion summarization refers how to relate the opinion words with respect to a certain feature. Probabilistic based model of supervised learning will improve the result that is more flexible and effective.

Keywords: opinion mining, opinion summarization, sentiment analysis, text mining

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Authors: Fereshteh Ahmadi, Önver Cetrez, Said Zandi, Sharareh Akhavan

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In this paper, we have mapped the coping methods used to address the coronavirus pandemic by members of the academic community. We conducted an anonymous survey of a convenient sample of 674 faculty/staff members and students from September to December 2020. A modified version of the RCOPE scale was used for data collection. The results indicate that both religious and existential coping methods were used by respondents. The study also indicates that even though 71% of in-formants believed in God or another religious figure, 61% reported that they had tried to gain control of the situation directly without the help of God or another religious figure. The ranking of the coping strategies used indicates that the first five methods used by informants were all non-religious coping methods (i.e., secular existential coping methods): regarding life as a part of a greater whole, regarding nature as an important resource, listening to the sound of surrounding nature, being alone and con-templating, and walking/engaging in any activities outdoors giving a spiritual feeling. Our results contribute to the new area of research on academic community’s coping with pandemic-related stress and challenges.

Keywords: academic staff, academics, coping strategies, coronavirus epidemic, higher education.

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Authors: Azadeh Bashiri

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

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

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Authors: Dino Carpentras, Paul J. Maher, Caoimhe O'Reilly, Michael Quayle

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Opinion dynamics is a sub-field of agent-based modeling that focuses on people’s opinions and their evolutions over time. Despite the rapid increase in the number of publications in this field, it is still not clear how to apply these models to real-world scenarios. Indeed, there is no agreement on how people update their opinion while interacting. Furthermore, it is not clear if different topics will show the same dynamics (e.g., more polarized topics may behave differently). These problems are mostly due to the lack of experimental validation of the models. Some previous studies started bridging this gap in the literature by directly measuring people’s opinions before and after the interaction. However, these experiments force people to express their opinion as a number instead of using natural language (and then, eventually, encoding it as numbers). This is not the way people normally interact, and it may strongly alter the measured dynamics. Another limitation of these studies is that they usually average all the topics together, without checking if different topics may show different dynamics. In our work, we collected data from 200 participants on 5 unpolarized topics. Participants expressed their opinions in natural language (“agree” or “disagree”). We also measured the certainty of their answer, expressed as a number between 1 and 10. However, this value was not shown to other participants to keep the interaction based on natural language. We then showed the opinion (and not the certainty) of another participant and, after a distraction task, we repeated the measurement. To make the data compatible with opinion dynamics models, we multiplied opinion and certainty to obtain a new parameter (here called “continuous opinion”) ranging from -10 to +10 (using agree=1 and disagree=-1). We firstly checked the 5 topics individually, finding that all of them behaved in a similar way despite having different initial opinions distributions. This suggested that the same model could be applied for different unpolarized topics. We also observed that people tend to maintain similar levels of certainty, even when they changed their opinion. This is a strong violation of what is suggested from common models, where people starting at, for example, +8, will first move towards 0 instead of directly jumping to -8. We also observed social influence, meaning that people exposed with “agree” were more likely to move to higher levels of continuous opinion, while people exposed with “disagree” were more likely to move to lower levels. However, we also observed that the effect of influence was smaller than the effect of random fluctuations. Also, this configuration is different from standard models, where noise, when present, is usually much smaller than the effect of social influence. Starting from this, we built an opinion dynamics model that explains more than 80% of data variance. This model was also able to show the natural conversion of polarization from unpolarized states. This experimental approach offers a new way to build models grounded on experimental data. Furthermore, the model offers new insight into the fundamental terms of opinion dynamics models.

Keywords: experimental validation, micro-dynamics rule, opinion dynamics, update rule

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Authors: Tzipi Eshet

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The primary objectives of this work are the examination of public preferences and attributed importance to different characteristics of coastal cliff protection alternatives, and drawing conclusions about the applicable alternative in Beit-Yanai beach. Erosion of coastal cliffs is a natural phenomenon that occurs in many places in the world. This creates problems along the coastlines, which are densely populated areas with highly developed economic activity. In recent years, various aspects of the aeolianite cliffs along the Israeli coast have been studied extensively. There is a consensus among researchers regarding a general trend of cliff retreat. This affects civilian infrastructure, wildlife habitats and heritage values, as well as Increases the risk to human life. The Israeli government, committed to the integrated coastal zones management approach, decided on a policy and guidelines to deal with cliff erosion, which includes establishing physical protection on land and in the sea, sand nourishment and runoff drainage. Physical protection solutions to reduce the rate of retreat of the cliffs are considerably important both for planning authorities and visitors to the beach. Direct costs of different protection alternatives, as well as external costs and benefits, may vary, thus affecting consumer preferences. Planning and execution of sustainable coastal cliff protection alternatives must take into account the different characteristics and their impact on aspects of economics, environment and leisure. The rocky shore of Beit-Yanai Beach was chosen as a case study to examine the nature of the influence of various protective solutions on consumer preferences. This beach is located in the center of Israel's coastline, and acts as a focus of attraction for recreation, land and sea sports, and educational activities as well. If no action will be taken, cliff retreat will continue. A survey was conducted to reveal the importance of coastal protection alternatives characteristics and the visual preferences to visitors at beach Beit-Yanai and residents living on the cliff (N=287). Preferences and willingness-to-pay were explored using Contingent-Ranking and Choice-Experiments techniques. Results show that visitors’ and residents’ willingness-to-pay for coastal cliff protection alternatives is affected both by financial and environmental aspects, as well as leisure. They prefer coastal cliff protection alternatives that are not visible and do not need constant maintenance, do not affect the quality of seawater or the habitats of wildlife and do not lower the security level of the swimmers. No significant difference was found comparing willingness-to-pay among local and non-local users. Additionally, they mostly prefer a protection solution which is integrated in the coastal landscape and maintains the natural appearance of the beach. Of the possible protection alternatives proposed for the protection of the cliff in Beit Yanai beach are two techniques that meet public preferences: rock revetments and submerged detached breakwaters. Results indicate that the visiting public prefer the implementation of these protection alternatives and will be willing to pay for them. Future actions to reduce retreat rate in Beit-Yanai have to consider implications on the economic, environmental and social conditions, along with weighting public interest against the interest of the individual.

Keywords: contingent-ranking, choice-experiments, coastal cliff protection, erosion of coastal cliffs, environment

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Authors: Abdulah Hamads Alatiah

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The green architecture represents the essence of the sustainability process and the fundamental rule in the desert areas' reconstruction seeking to maintain the environmental balance. This study is based on the analytical descriptive approach, to extract the objectives of green architecture in the desert areas, and reveal the most important principles that contribute to highlight its economic, social, and environmental importance, in addition to standing on the most important technical standards that can be relied upon to deal with its environmental problems. The green architecture aims: making use of the alternative energy, reducing the conventional energy consumption, addressing its negative effects, adapting to the climate, innovation in design, providing the individuals' welfare and rationalizing the use of the available resources to maintain its environmental sustainability.

Keywords: green architecture, the warm-dry climate, natural lighting, environmental quality, renewable energy, weather changes

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Authors: M. Hadji, A. Haddad, Y. Hadji

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The effects of boronizing treatment on the friction coefficient and wear behavior of Ti2AlC were investigated. In order to modify the surface properties of Ti2AlC, boronizing treatment was carried out through powder pack cementation in the 1150-1350 °C temperature range. After boronizing treatment, one mixture layer, composed of TiB2 and SiC, forms on the surface of Ti2AlC. The growth of the coating is processed by inward diffusion of Boron and obeys a linear rule. The Boronizing treatment increases the hardness of Ti2AlC from 6 GPa to 13GPa. In the pin-on-disc test, it was found that the material undergoes a steady-state coefficient of friction of around 0.8 and 0.45 in case of Ti2AlC/Al2O3 tribocouple under 7N load for the non treated and the boronized samples, respectively. The wear resistance of Ti2AlC under Al2O3 ball sliding has been significantly improved, which indicated that the boronizing treatment is a promising surface modification way of Ti2AlC.

Keywords: MAX phase, wear, hardness, boronizing

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Authors: Sadegh Abedi, Ali Yaghoubi, Hamidreza Mashatzadegan

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This paper proposes an approach to identify key processes required by an organization in the field of knowledge management and aligning them with organizational objectives. For this purpose, first, organization’s most important non-financial objectives which are impacted by knowledge management processes are identified and then, using a quality house, are linked with knowledge management processes which are regarded as technical elements. Using this method, processes that are in need of improvement and more attention are prioritized based on their significance. This means that if a process has more influence on organization’s objectives and is in a dire situation comparing to others, is prioritized for choice and improvement. In this research process dominance is considered to be an influential element in process ranking (in addition to communication matrix). This is the reason for utilizing DEA techniques for prioritizing processes in quality house. Results of implementing the method in Khuzestan steel company represents this method’s capability of identifying key processes that require improvements in organization’s knowledge management system.

Keywords: knowledge management, organizational performance, fuzzy data, envelopment analysis

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Authors: Kreangkri Ratchagit

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This paper is concerned with exponential stability of switched linear systems with interval time-varying delays. The time delay is any continuous function belonging to a given interval, in which the lower bound of delay is not restricted to zero. By constructing a suitable augmented Lyapunov-Krasovskii functional combined with Leibniz-Newton’s formula, a switching rule for the exponential stability of switched linear systems with interval time-varying delays and new delay-dependent sufficient conditions for the exponential stability of the systems are first established in terms of LMIs. Finally, some examples are exploited to illustrate the effectiveness of the proposed schemes.

Keywords: exponential stability, hybrid systems, timevarying delays, Lyapunov-Krasovskii functional, Leibniz-Newton’s formula

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Authors: R. Niranchana, K. Meena Alias Jeyanthi

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As a result of the present climate change dilemma, the energy balancing strategy is to construct a sustainable environment has become a top concern for researchers worldwide. The environment itself has always been a solution from the earliest days of human evolution. Carbon capture begins with its accurate estimation and monitoring credit inventories, and its efficient use. Sustainable urban planning with deliverables of re-use energy models might benefit from assessment methods like biomass carbon credit ranking. The term "biomass energy" refers to the various ways in which living organisms can potentially be converted into a source of energy. The approaches that can be applied to biomass and an algorithm for evaluating carbon credits are presented in this paper. The micro-climate evaluation using Computational Fluid dynamics was carried out across the location (1 km x1 km) at Dindigul, India (10°24'58.68" North, 77°54.1.80 East). Sustainable Urban design must be carried out considering environmental and physiological convection, conduction, radiation and evaporative heat exchange due to proceeding solar access and wind intensities.

Keywords: biomass, climate assessment, urban planning, multi-regression, carbon estimation algorithm

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Authors: Hans Marquez Ramos, Cesar Hernandez, Ingrid Páez

Abstract:

This paper develops a multiple channel assignment model, which allows to take advantage in most efficient way, spectrum opportunities in cognitive radio networks. Developed scheme allows make several available and frequency adjacent channel assignments, which require a bigger wide band, under an equality environment. The hybrid assignment model it is made by to algorithms, one who makes the ranking and select available frequency channels and the other one in charge of establishing an equality criteria, in order to not restrict spectrum opportunities for all other secondary users who wish to make transmissions. Measurements made were done for average bandwidth, average delay, as well fairness computation for several channel assignment. Reached results were evaluated with experimental spectrum occupational data from GSM frequency band captured. Developed model, shows evidence of improvement in spectrum opportunity use and a wider average transmit bandwidth for each secondary user, maintaining equality criteria in channel assignment.

Keywords: bandwidth, fairness, multichannel, secondary users

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Authors: Khoi A. Nguyen, Rodney A. Stewart, Hong Zhang

Abstract:

‘Water-related energy’ is energy use which is directly or indirectly influenced by changes to water use. Informatics applying a range of mathematical, statistical and rule-based approaches can be used to reveal important information on demand from the available data provided at second, minute or hourly intervals. This study aims to combine these two concepts to improve the current water end use disaggregation problem through applying a wide range of most advanced pattern recognition techniques to analyse the concurrent high-resolution water-energy consumption data. The obtained results have shown that recognition accuracies of all end-uses have significantly increased, especially for mechanised categories, including clothes washer, dishwasher and evaporative air cooler where over 95% of events were correctly classified.

Keywords: deep learning network, smart metering, water end use, water-energy data

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Authors: Yasser F. Hassan

Abstract:

The reduction or removal of noise in a color image is an essential part of image processing, whether the final information is used for human perception or for an automatic inspection and analysis. This paper describes the modeling system based on the rough neural network model to adaptive cellular automata for various image processing tasks and noise remover. In this paper, we consider the problem of object processing in colored image using rough neural networks to help deriving the rules which will be used in cellular automata for noise image. The proposed method is compared with some classical and recent methods. The results demonstrate that the new model is capable of being trained to perform many different tasks, and that the quality of these results is comparable or better than established specialized algorithms.

Keywords: rough sets, rough neural networks, cellular automata, image processing

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Authors: A. Rajabpour, A. Hadizadeh Kheirkhah

Abstract:

Heat transfer is of great importance to biological systems in order to function properly. In the present study, specific heat capacity as one of the most important heat transfer properties is calculated for a soluble in water Lysozyme protein. Using equilibrium molecular dynamics (MD) simulation, specific heat capacities of pure water, dry lysozyme, and lysozyme-water solution are calculated at 300K for different weight fractions. It is found that MD results are in good agreement with ideal binary mixing rule at small weight fractions. Results of all simulations have been validated with experimental data.

Keywords: specific heat capacity, molecular dynamics simulation, lysozyme protein, equilibrium

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Authors: Olalekan Bamidele Aruleba

Abstract:

This research assessed the impact of manpower training and development in the construction industry. The aim is to determine the effect of training and development on employees for effective organizational growth in the construction industry to identify the training method for each category of employee in the construction industry, challenges to training and development of workers in the construction industry and impact of manpower training and development on employees and employers. Data for the study were obtained through a well-structured questionnaire administered to building professionals in Nigeria construction firm. Eighty (80) questionnaires were distributed among building professionals in three selected local governments within Ondo State and sixty-four (64) were returned. Data collected were analysed using descriptive statistics and ranking. Findings of the study revealed that in house training and in-service training methods were preferred by most construction industry. It concluded that the attitude of top management and lack of fund was seen as the significant challenges militating against training of employees. The study recommended that manpower training and development must be sustained by all stakeholders in the industry in order to improve workers' productivity; the organization should adopt the right method in training each category of employees and carry out the need assessment for training to avoid training wrong employees.

Keywords: construction, development, manpower, training

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