Search results for: corporate credit rating prediction

Authors: Aadityaa Singla

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The big five personality traits are as follows: openness, conscientiousness, extraversion, agreeableness, and neuroticism. In order to get an insight into their personality, many flocks to these categories, which each have different meanings/characteristics. This information is important not only to individuals but also to career professionals and psychologists who can use this information for candidate assessment or job recruitment. The links between AI and psychology have been well studied in cognitive science, but it is still a rather novel development. It is possible for various AI classification models to accurately predict a personality question via ten input questions. This would contrast with the hundred questions that normal humans have to answer to gain a complete picture of their five personality traits. In order to approach this problem, various AI classification models were used on a dataset to predict what a user may answer. From there, the model's prediction was compared to its actual response. Normally, there are five answer choices (a 20% chance of correct guess), and the models exceed that value to different degrees, proving their significance. By utilizing an MLP classifier, decision tree, linear model, and K-nearest neighbors, they were able to obtain a test accuracy of 86.643, 54.625, 47.875, and 52.125, respectively. These approaches display that there is potential in the future for more nuanced predictions to be made regarding personality.

Keywords: machine learning, personally, big five personality traits, cognitive science

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Authors: Elise Machline

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Policy instruments have been developed worldwide to reduce the energy demand of buildings. Two types of such instruments have been green building rating systems and energy efficiency standards for buildings -such as Green Star (Australia), LEED (United States, Leadership in Energy and Environmental Design), Energy Star (United States), and BREEAM (United Kingdom, Building Research Establishment Environmental Assessment Method). The popularity of the idea of sustainable development has allowed the actors to consider the potential value generated by the environmental performance of buildings, labeled “green value” in the literature. Sustainable performances of buildings are expected to improve their attractiveness, increasing their value. A growing number of empirical studies demonstrate that green buildings yield rental/sale premia, as well as higher occupancy rates and thus higher asset values. The results suggest that green buildings are not affordable to all and that their construction tends to have a gentrifying effect. An increasing number of countries are institutionalizing green strategies for affordable housing. In that sense, making green buildings affordable to all will depend on government policies. That research aims to investigate whether green building fosters inequality in Israel, under the banner of sustainability. The method is comparison (of the market value). This method involves comparing the green buildings sale prices with non-certified buildings of the same type that have undergone recent transactions. The “market value” is deduced from those sources by analogy. The results show that, in Israel, green building projects are usually addressed to the middle to upper classes. The green apartment’s sale premium is about 19% (comparing to non-certified dwelling). There is a link between energy and/or environmental performance and the financial value of the dwellings. Moreover, price differential is much higher than the value of energy savings. This perpetuates socio-spatial and socio-economic inequality as well as ecological vulnerability for the poor and other socially marginal groups. Moreover, there are no green affordable housings and the authorities do not subsidy green building or retrofitting.

Keywords: green building, gentrification, social housing, green value, green building certification

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Authors: Ugbede Onalo, Mohd Lizam, Ahmad Kaseri

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In view of dearth of studies on changes in accounting standards and banks’ earnings management particularly in the context of emerging economies, and the recent Malaysia and Nigeria change from their respective local GAAP to IFRS, this study deemed it overwhelming to investigate the effects of the switch on banks’ earnings management focusing on LLP as the manipulative device. This study employed judgmental sampling to select twenty eight banks- eight Malaysia and twenty Nigeria banks as sample covering period 2008-2013. To provide an empirical research setting in pursuant of the objective of this study, the study period is further partitioned into pre (2008, 2009, 2010) and post (2011, 2012, 2013) IFRS adoption periods. This study consistent with previous studies models a LLP regression model to investigate specific discretionary accruals of banks. Findings suggest that Malaysia and Nigeria banks individually use LLP to manage reported earnings more prior to IFRS implementation. Comparative overall results evidenced that the pre IFRS adoption or domestic GAAP era for both Malaysia and Nigeria sample banks is associated with higher prevalent earnings management through LLP than the corresponding post IFRS adoption era in diverse magnitude but in favour of Malaysia banks for both periods. With results demonstrating that IFRS adoption is linked to lower earnings management via LLP, this study therefore recommends the global adoption of IFRS as reporting framework. This study also endorses that Nigeria banks embrace and borrow a leaf from Malaysia banks good corporate governance practices.

Keywords: accounting standards, IFRS, FRS, SAS, LLP, earnings management

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Authors: Çiğdem Bakır, Mecit Yüzkat

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With the increasing emphasis on water quality worldwide, the search for and expanding the market for new and intelligent monitoring systems has increased. The current method is the laboratory process, where samples are taken from bodies of water, and tests are carried out in laboratories. This method is time-consuming, a waste of manpower, and uneconomical. To solve this problem, we used machine learning methods to detect water pollution in our study. We created decision trees with the Orange3 software we used in our study and tried to determine all the factors that cause water pollution. An automatic prediction model based on water quality was developed by taking many model inputs such as water temperature, pH, transparency, conductivity, dissolved oxygen, and ammonia nitrogen with machine learning methods. The proposed approach consists of three stages: preprocessing of the data used, feature detection, and classification. We tried to determine the success of our study with different accuracy metrics and the results. We presented it comparatively. In addition, we achieved approximately 98% success with the decision tree.

Keywords: decision tree, water quality, water pollution, machine learning

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Authors: Mohammad Reza Bagherzadeh, Mohammad Hossein Taheri

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Knowledge management serves as one of the great breakthroughs in information and knowledge era and given its outstanding features, successful organizations tends to adopt it. Therefore, to deal with knowledge management establishment in universities is of special importance. In this regard, the present research aims to shed lights on factors background knowledge management establishment at Islamic Azad University, Behshahr Branch (Northern Iran). Considering three factors information technology system, knowledge process system and organizational culture as a fundamental of knowledge management infrastructure, foregoing factors were evaluated individually. The present research was conducted in descriptive-survey manner and participants included all staffs and faculty members, so that according to Krejcie & Morgan table a sample size proportional to the population size was considered. The measurement tools included survey questionnaire whose reliability was calculated to 0.83 according to Cronbachs alpha. To data analysis, descriptive statistics such as frequency and its percentage tables, column charts, mean, standard deviation and as for inferential statistics Kolomogrov- Smirnov test and single T-test were used. The findings show that despite the good corporate culture as one of the three factors background the establishment of the knowledge management at Islamic Azad University Behshahr Branch, other two ones, including IT systems, and knowledge processes systems are characterized with adverse status. As a result, these factors have caused no necessary conditions for the establishment of Knowledge Management in the university provided.

Keywords: knowledge management, information technology, knowledge processes, organizational culture, educational institutions

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Authors: Abdul Hakim Chikho

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A simple method of calculating satisfactory of the effect of instability on the distribution of in-plane bending moments in unbraced semi-rigidly multistory steel framed structures is presented in this paper. This method, which is a modified form of the current amplified sway method of BS5950: part1:2000, uses an approximate load factor at elastic instability in each storey of a frame which in turn dependent up on the axial loads acting in the columns. The calculated factors are then used to represent the geometrical deformations due to the presence of axial loads, acting in that storey. Only a first order elastic analysis is required to accomplish the calculation. Comparison of the prediction of the proposed method and the current BS5950 amplified sway method with an accurate second order elastic computation shows that the proposed method leads to predictions which are markedly more accurate than the current approach of BS5950.

Keywords: improved amplified sway method, steel frames, semi-rigid connections, secondary effects

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Authors: Bhavita S. Dave, Jaimin Vaidya, Chandresh H. Solanki, Atul K.

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To measure the permeability of a soil specimen, one of the basic assumptions of Darcy's law is that the soil sample should be saturated. Unlike saturated soils, the permeability of unsaturated soils cannot be found using conventional methods as it does not follow Darcy's law. Many empirical models, such as the Van Genuchten Model and Fredlund-Xing Model were suggested to predict permeability value for unsaturated soil. Such models use data from the soil-freezing characteristic curve to find fitting parameters for frozen unsaturated soils. In this study, soil specimens were subjected to 0, 1, 3, and 5 freezing-thawing (F-T) cycles for different degrees of saturation to have a wide range of suction, and its soil freezing characteristic curves were formulated for all F-T cycles. Changes in fitting parameters and relative permeability with subsequent F-T cycles are presented in this paper for both models.

Keywords: frozen unsaturated soil, Fredlund Xing model, soil-freezing characteristic curve, Van Genuchten model

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Authors: Bronwen Wade

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Over the last half-century, child welfare systems have increasingly relied on quantitative risk assessment tools, such as actuarial or predictive risk tools. These tools are developed by performing statistical analysis of how attributes captured in administrative data are related to future child maltreatment. Some scholars argue that attributes in administrative data can serve as proxies for race and that quantitative risk assessment tools reify racial bias in decision-making. Others argue that these tools provide more “objective” and “scientific” guides for decision-making instead of subjective social worker judgment. This study performs a systematic review of the literature on the impact of quantitative risk assessment tools on racial disproportionality; it examines methodological biases in work on this topic, summarizes key findings, and provides suggestions for further work. A search of CINAHL, PsychInfo, Proquest Social Science Premium Collection, and the ProQuest Dissertations and Theses Collection was performed. Academic and grey literature were included. The review includes studies that use quasi-experimental methods and development, validation, or re-validation studies of quantitative risk assessment tools. PROBAST (Prediction model Risk of Bias Assessment Tool) and CHARMS (CHecklist for critical Appraisal and data extraction for systematic Reviews of prediction Modelling Studies) were used to assess the risk of bias and guide data extraction for risk development, validation, or re-validation studies. ROBINS-I (Risk of Bias in Non-Randomized Studies of Interventions) was used to assess for bias and guide data extraction for the quasi-experimental studies identified. Due to heterogeneity among papers, a meta-analysis was not feasible, and a narrative synthesis was conducted. 11 papers met the eligibility criteria, and each has an overall high risk of bias based on the PROBAST and ROBINS-I assessments. This is deeply concerning, as major policy decisions have been made based on a limited number of studies with a high risk of bias. The findings on racial disproportionality have been mixed and depend on the tool and approach used. Authors use various definitions for racial equity, fairness, or disproportionality. These concepts of statistical fairness are connected to theories about the reason for racial disproportionality in child welfare or social definitions of fairness that are usually not stated explicitly. Most findings from these studies are unreliable, given the high degree of bias. However, some of the less biased measures within studies suggest that quantitative risk assessment tools may worsen racial disproportionality, depending on how disproportionality is mathematically defined. Authors vary widely in their approach to defining and addressing racial disproportionality within studies, making it difficult to generalize findings or approaches across studies. This review demonstrates the power of authors to shape policy or discourse around racial justice based on their choice of statistical methods; it also demonstrates the need for improved rigor and transparency in studies of quantitative risk assessment tools. Finally, this review raises concerns about the impact that these tools have on child welfare systems and racial disproportionality.

Keywords: actuarial risk, child welfare, predictive risk, racial disproportionality

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Authors: O. Behar, A. Khellaf, K. Mohammedi, S. Ait Kaci

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Up to now, most validation studies have been based on the MBE and RMSE, and therefore, focused only on long and short terms performance to test and classify solar radiation models. This traditional analysis does not take into account the quality of modeling and linearity. In our analysis we have tested 22 solar radiation models that are capable to provide instantaneous direct and global radiation at any given location Worldwide. We introduce a new indicator, which we named Global Accuracy Indicator (GAI) to examine the linear relationship between the measured and predicted values and the quality of modeling in addition to long and short terms performance. Note that the quality of model has been represented by the T-Statistical test, the model linearity has been given by the correlation coefficient and the long and short term performance have been respectively known by the MBE and RMSE. An important founding of this research is that the use GAI allows avoiding default validation when using traditional methodology that might results in erroneous prediction of solar power conversion systems performances.

Keywords: solar radiation model, parametric model, performance analysis, Global Accuracy Indicator (GAI)

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Authors: Mei Xuan Tan, Eng Ying Bong

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Academic discussion during and after instructional teaching is an integral part of learning. Such discussion between the instructor and student or peer-to-peer discussion can be in several different forms. It could be face-to-face discussion, via email and use of online discussion forum. In this study, the effectiveness of using WhatsApp for academic discussion for a first year half-credit Chemistry course was examined. This study was run over two years with two different batches of students. Participation in the study was voluntary and student volunteers were recruited within the first week of the term. The activity in the WhatsApp group was monitored by two instructors teaching the course. At the end of the course, the students participated in an online survey to evaluate their experience of using WhatsApp for academic discussion. There were a total of 26 questions. The survey had a total of 4 sections with regards to the use of WhatsApp for academic discussion: 1) Familiarity with WhatsApp, 2) Effectiveness of using WhatsApp for discussion, 3) Challenges and 4) Overall experience. The main purpose of using an IM platform for academic discussion was to encourage after-class discussion amongst the students. 32% of the participants had used other online platform, such as Piazza and forums in Learning Management System (LMS), for after-class academic discussion with their instructors and peers. This was a low percentage considering that some courses use such online platform as their main forum amongst instructors and students. At the end of our study, over 83% of the participants felt that WhatsApp was a more effective platform compared to other online forum. One interesting finding was the effect of WhatsApp discussion on face-to-face interaction with instructors. 28% of the students agreed that the use of WhatsApp as a discussion forum had encouraged them to approach their instructors during or after class. 51% of students answered neutral. This could be interpreted that the use of WhatsApp had not affected the frequent (or lack of) face-to-face interaction with their instructors. A second survey question, similar but phrased differently from the first, was also asked to evaluate the aspect of face-to-face interaction with instructors. 34% disagreed that the use of WhatsApp had reduced the frequency of face-to-face interaction. This could imply that the frequency remained the same or might have increased. The 38% who agreed to a decrease in face-to-face interaction have either asked the questions in WhatsApp or had their questions answered by a query from another student in the group chat. These outcomes suggested that the use of technology aided and complemented face-to-face interaction between instructors and students. The study also looked at the challenges of using WhatsApp for academic discussion. Some challenges included difficulty in referring back to previous discussion and students finding some discussions irrelevant to them. In conclusion, the use of IM platform for academic discussion was desirable for the students, but it should not be the only channel as face-to-face consultation and online forum for lengthy discussion are still important for after-class learning of students.

Keywords: chemistry, pedogogy, technological tools, undergraduate

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Authors: Mohamed Hafid, Marcel Lacroix

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This study presents an inverse analysis for predicting the thermal conductivities and the heat flux of a high-temperature metallurgical reactor simultaneously. Once these thermal parameters are predicted, the time-varying thickness of the protective phase-change bank that covers the inside surface of the brick walls of a metallurgical reactor can be calculated. The enthalpy method is used to solve the melting/solidification process of the protective bank. The inverse model rests on the Levenberg-Marquardt Method (LMM) combined with the Broyden method (BM). A statistical analysis for the thermal parameter estimation is carried out. The effect of the position of the temperature sensors, total number of measurements and measurement noise on the accuracy of inverse predictions is investigated. Recommendations are made concerning the location of temperature sensors.

Keywords: inverse heat transfer, phase change, metallurgical reactor, Levenberg–Marquardt method, Broyden method, bank thickness

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Authors: Ardalan Tofighi Soleimandarabi

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Artificial intelligence has revolutionized the concrete construction industry and improved processes by increasing efficiency, accuracy, and sustainability. This article examines the applications of artificial intelligence in predicting the compressive strength of concrete, optimizing mixing plans, and improving structural health monitoring systems. Artificial intelligence-based models, such as artificial neural networks (ANN) and combined machine learning techniques, have shown better performance than traditional methods in predicting concrete properties. In addition, artificial intelligence systems have made it possible to improve quality control and real-time monitoring of structures, which helps in preventive maintenance and increases the life of infrastructure. Also, the use of artificial intelligence plays an effective role in sustainable construction by optimizing material consumption and reducing waste. Although the implementation of artificial intelligence is associated with challenges such as high initial costs and the need for specialized training, it will create a smarter, more sustainable, and more affordable future for concrete structures.

Keywords: artificial intelligence, concrete construction, compressive strength prediction, structural health monitoring, stability

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Authors: S. Mousavian, A. Abedianpour, A. Khanmohammadi, S. Hematian, Gh. Eidi Veisi

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Ionic liquids are finding a wide range of applications from reaction media to separations and materials processing. In these applications, Vapor–Liquid equilibrium (VLE) is the most important one. VLE for six systems at 353 K and activity coefficients at infinite dilution 〖(γ〗_i^∞) for various solutes (alkanes, alkenes, cycloalkanes, cycloalkenes, aromatics, alcohols, ketones, esters, ethers, and water) in the ionic liquids (1-ethyl-3-methylimidazolium bis (trifluoromethylsulfonyl)imide [EMIM][BTI], 1-hexyl-3-methyl imidazolium bis (trifluoromethylsulfonyl) imide [HMIM][BTI], 1-octyl-3-methylimidazolium bis(trifluoromethylsulfonyl) imide [OMIM][BTI], and 1-butyl-1-methylpyrrolidinium bis (trifluoromethylsulfonyl) imide [BMPYR][BTI]) have been used to train neural networks in the temperature range from (303 to 333) K. Densities of the ionic liquids, Hildebrant constant of substances, and temperature were selected as input of neural networks. The networks with different hidden layers were examined. Networks with seven neurons in one hidden layer have minimum error and good agreement with experimental data.

Keywords: ionic liquid, neural networks, VLE, dilute solution

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Authors: José Leandro Melgar Néris, Claudinéia Brazil, Luciane Teresa Salvi, Isabel Cristina Damin

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The impact the climate change is not recent, the main variable in the hydrological cycle is the sequence and shortage of a drought, which has a significant impact on the socioeconomic, agricultural and environmental spheres. This study aims to characterize and quantify, based on precipitation climatic projections, the rainy and dry events in the region of the Uruguay River Basin, through the Standardized Precipitation Index (SPI). The database is the image that is part of the Intercomparison of Model Models, Phase 5 (CMIP5), which provides condition prediction models, organized according to the Representative Routes of Concentration (CPR). Compared to the normal set of climates in the Uruguay River Watershed through precipitation projections, seasonal precipitation increases for all proposed scenarios, with a low climate trend. From the data of this research, the idea is that this article can be used to support research and the responsible bodies can use it as a subsidy for mitigation measures in other hydrographic basins.

Keywords: climate change, climatic model, dry events, precipitation projections

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Authors: Chin-Hsiang Chu

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This article review the literature in the field among the marketing and aesthetics, the current market and customer-oriented product sales, and gradually from the practical functionality, transformed into the visual appearance of the concept note and the importance of marketing experience substance 'economic Aesthetics' trend. How to introduce the concept of aesthetic and differentiate products have become an important content of marketing management in for an organization in marketing.In previous studies,marketing aesthetic related researches are rare.Therefore, the purpose of this study to explore the connection between aesthetics and marketing of the market economy, and aggregated content through literature review, trying to find related research implications for the management of marketing aesthetics, market-oriented and customer value and development of the product. In this study, the problem statement and background, the development of the theory of evolution, as well as methods and results of discovery stage, literature review was conducted to explore. The results found: (1) Study of Aesthetics will help deepen the shopping environment and service environment commonly understood. (2) the perceived value of products imported aesthetic, consumer willingness to buy, and even premium products will be more attractive. (3) marketing personnel for general marketing management with a high degree of aesthetic identity. (4) management in marketing aesthetics connotation, aesthetic characteristics of five elements is greatly valued by the real-time, complex, specificity, attract sexual and richness. (5) allows consumers to experience through the process due to stimulate the senses, the mind and thinking with the corporate brand or have a deeper link. Results of this study can be used as business in a competitive market, new product development and design of the guide.

Keywords: marketing aesthetics, aesthetics economic, aesthetic, experiential marketing

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Authors: Pinqiao Wang

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Mindfulness, derived from Buddhism, has been developed to improve individuals' well-being, first in the West and then gaining growing popularity in Asia. Numerous research studies have proven the effectiveness of mindfulness among clinical groups and the public all over the world. However, as enthusiasm surges, reflections on mindfulness and its commodification and instrumentalization arise. Hong Kong was seen as the model of a free market by neoliberal economists. The relationships between its socioeconomic neoliberalism, Western-inspired democracy aspiration, and political harmonization with China Mainland have been fraught with tensions, which have been further exacerbated by socio-political changes since the 2010s. Under such circumstances, mental health problems have come into the spotlight in Hong Kong recently. Mindfulness has gained growing popularity in Hong Kong, with its influence reaching from primary schools to corporate settings. A more comprehensive socio-political analysis of mindfulness within the Hong Kong context warrants further exploration. Drawing on interview responses from mindfulness practitioners, we examine the connections between the ideologies underlying mindfulness and contemporary capitalist society. On the one hand, mindfulness focuses on the present moment and self-improvement, representing neoliberal capitalist spirituality and reinforcing existing power relations. On the other hand, mindfulness fosters the acceptance of difference, which is argued to demonstrate the potential for advancing democracy at both the individual and community levels. Academically, this research provides empirical evidence to advance the current discussions and debates surrounding the socio-political potential of mindfulness. Practically, it serves as a reflection on mindfulness practices to optimize their impact on individuals and society.

Keywords: neoliberal subjectivity, qualitative analysis, social construction, technologies of the self, therapeutic culture

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Authors: Mohammad Javad Seddighi, Avar Almukhtar

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Sustainable urban planning and design (SUPD) play a critical role in achieving the United Nations Sustainable Development Goals (UN SDGs). While there are many rating systems and standards available to assess the sustainability of the built environment, there is still a lack of a comprehensive framework that can assess the quality of SUPD in a specific context. In this paper, we present a framework for assessing the quality of SUPD in Iranian cities, considering their unique cultural, social, and environmental contexts. The aim of this study is to develop a framework for assessing the quality of SUPD in Iranian cities. To achieve this aim, the following objectives are pursued review and synthesis of relevant literature on SUPD, identification of key indicators and criteria for assessing the quality of SUPD in Iranian cities application of the framework to case studies of Iranian cities and evaluation and refinement of the framework based on the results of the case studies. The framework is developed based on a review and synthesis of relevant literature on SUPD, and the identification of key indicators and criteria for assessing the quality of SUPD in Iranian cities. The framework is then applied to case studies of Iranian cities and the results are evaluated and refined. The data for this study are collected through a review of relevant literature on SUPD, including academic journals, conference proceedings, and books. The case studies of Iranian cities are selected based on their relevance and availability of data. The data are collected through interviews, site visits, and document analysis. This paper presents a framework for assessing the quality of SUPD in Iranian cities. The framework is developed based on a review and synthesis of relevant literature, identification of key indicators and criteria, application to case studies, and evaluation and refinement. The framework provides a comprehensive and context-specific approach to assessing the quality of SUPD in Iranian cities. It can be used by urban planners, designers, and policymakers to improve the sustainability and liveability of Iranian cities, and it can be adapted for use in other contexts.

Keywords: sustainable urban planning and design, framework, quality assessment, Iranian cities, case studies

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Authors: Sheetla Prasad

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The objective of this study is ‘discovering the real psyche of human beings for prediction of mode, direction and strength of the potential of actions of the individual. The human face was taken as a source of central point to search for the route of real psyche. Analysis of the face architecture (shape and salient features of face) was done by three directional photographs ( 600 left and right and camera facing) of human beings. The shapes and features of the human face were scaled in 177 units on the basis of face–features locations (FFL). The mathematical analysis was done of FFLs by self developed and standardized formula. At this phase, 800 samples were taken from the population of students, teachers, advocates, administrative officers, and common persons. The finding shows that real psyche has two external rings (ER). These ER are itself generator of two independent psyches (manifested and manipulated). Prima-facie, it was proved that micro differences in FFLs have potential to predict the state of art of the human psyche. The potential of psyches was determined by the saving and distribution of mental energy. It was also mathematically proved.

Keywords: face architecture, psyche, potential, face functional ratio, external rings

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Authors: Sagir M. Yusuf, Chris Baber

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We describe issues bedeviling the coordination of heterogeneous (different sensors carrying agents) multi-agent missions such as belief conflict, situation reasoning, etc. We applied Bayesian and agents' presumptions inferential reasoning to solve the outlined issues with the heterogeneous multi-agent belief variation and situational-base reasoning. Bayesian Belief Network (BBN) was used in modeling the agents' belief conflict due to sensor variations. Simulation experiments were designed, and cases from agents’ missions were used in training the BBN using gradient descent and expectation-maximization algorithms. The output network is a well-trained BBN for making inferences for both agents and human experts. We claim that the Bayesian learning algorithm prediction capacity improves by the number of training data and argue that it enhances multi-agents robustness and solve agents’ sensor conflicts.

Keywords: distributed constraint optimization problem, multi-agent system, multi-robot coordination, autonomous system, swarm intelligence

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Authors: Suliman Al Balawi

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Food waste is a significant problem in the Kingdom of Saudi Arabia (KSA). About SR13 billion worth of food is wasted per year in the KSA. From moral, social, and economic perspectives, it is essential to reduce the wastage of food. Although studies have identified the amount of food waste in the KSA, there is a lack of research on why people in the KSA waste food; thus, it is difficult to design efficient intervention programs to reduce food waste. This research investigates the key factors that influence the food waste behavior of the people of the KSA. A food waste behavior model is proposed in this study that has moral disengagement at the center of the model. Following a literature survey, it is hypothesised that religiosity, hedonic value, frugality, and trait cynicism are the antecedents of moral disengagement that are likely to impact the food waste behavior of the people of the KSA. The study further posits that an intervention strategy in the form of a social marketing campaign that focuses on lowering the level of moral disengagement could reduce the food waste behavior of the people of the KSA. This study will apply a pre-test/post-test experimental design (control group). A random sampling method will be used to select participants from the (employees of a chosen firm) in the KSA. The social marketing campaign will be run for six months through the Corporate Social Responsibility Department of the Company, and to analyse the experimental data, structural equation modeling (SEM) will be used. The outcomes of the study will demonstrate the effectiveness of a social marketing campaign for improving the food waste behavior of the people of the KSA and will ultimately lay the foundation for designing efficient intervention programs in the future. This study will contribute to the knowledge on food waste behavior by testing a newly proposed food waste behavior model in the KSA.

Keywords: food waste, social marketing, Saudi Arabia, moral disengagement

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Authors: L. S. Chathurika

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Early prediction of student performance is an important factor to be gained academic excellence. Whatever the study stream in secondary education, students lay the foundation for higher studies during the first year of their degree or diploma program in Sri Lanka. The information technology (IT) field has certain improvements in the education domain by selecting specialization areas to show the talents and skills of students. These specializations can be software engineering, network administration, database administration, multimedia design, etc. After completing the first-year, students attempt to select the best path by considering numerous factors. The purpose of this experiment is to predict the best study path using machine learning algorithms. Five classification algorithms: decision tree, support vector machine, artificial neural network, Naïve Bayes, and logistic regression are selected and tested. The support vector machine obtained the highest accuracy, 82.4%. Then affecting features are recognized to select the best study path.

Keywords: algorithm, classification, evaluation, features, testing, training

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Authors: Ajoy Kumar Das, Prasenjit Dey

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Heat transfer due to forced convection of copper water based nanofluid has been predicted by Artificial Neural network (ANN). The present nanofluid is formed by mixing copper nano particles in water and the volume fractions are considered here are 0% to 15% and the Reynolds number are kept constant at 100. The back propagation algorithm is used to train the network. The present ANN is trained by the input and output data which has been obtained from the numerical simulation, performed in finite volume based Computational Fluid Dynamics (CFD) commercial software Ansys Fluent. The numerical simulation based results are compared with the back propagation based ANN results. It is found that the forced convection heat transfer of water based nanofluid can be predicted correctly by ANN. It is also observed that the back propagation ANN can predict the heat transfer characteristics of nanofluid very quickly compared to standard CFD method.

Keywords: forced convection, square cylinder, nanofluid, neural network

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Authors: Noor Azlina Mohamed Yunus, Baharom Abd Rahman, Abdul Kadir Othman, Narehan Hassan, Rohana Mat Som, Ibhrahim Zakaria

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Customer satisfaction and customer loyalty are the most important outcomes of marketing in which both elements serve various stages of consumer buying behavior. Excellent service quality has become a major corporate goal as more companies gradually struggle for quality for their products and services. Therefore, the main purpose of this study is to investigate the influence of service quality on customer satisfaction and customer loyalty at one telecommunication company in Malaysia which is Telekom Malaysia. The scope of this research is to evaluate satisfaction on the products or services at TMpoint Bukit Raja, Malaysia. The data are gathered through the distribution of questionnaires to a total of 306 respondents who visited and used the products or services. By using correlation and multiple regression analyses, the result revealed that there was a positive and significant relationship between service quality and customer satisfaction. The most influential factor on customer satisfaction was empathy followed by reliability, assurance and tangibles. However, there was no significant influence between responsiveness and customer satisfaction. The result also showed there was a positive and significant relationship between service quality and customer loyalty. The most influential factor on customer loyalty was assurance followed by reliability and tangibles. TMpoint Bukit Raja is recommended to device excellent strategies to satisfy customers’ needs and to adopt action-oriented approach by focusing on what the customers wanted. It is also recommended that similar study can be carried out in other industries using different methodologies such as longitudinal method, enlarge the sample size and use a qualitative approach.

Keywords: customer satisfaction, customer loyalty, service quality, telecommunication company

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Authors: Mahnaz Jafari, Parisa Izadpanahi, Francesco Mancini, Muhammad Qureshi

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The advancement in Information Technology (IT) has been an intrinsic element in the developments of the 21st century bringing benefits such as increased economic productivity. However, its widespread application has also been associated with inadvertent negative impacts on society and the environment necessitating selective interventions to mitigate these impacts. This study responded to this need by developing a Green IT Rating Tool (GIRT) for higher education institutions (HEI) in Australia to evaluate the sustainability of IT-related practices from an environmental, social, and economic perspective. Each dimension must be considered equally to achieve sustainability. The development of the GIRT was informed by the views of interviewed IT professionals whose opinions formed the basis of a framework listing Green IT initiatives in order of their importance as perceived by the interviewed professionals. This framework formed the base of the GIRT, which identified Green IT initiatives (such as videoconferencing as a substitute for long-distance travel) and the associated weighting of each practice. The proposed sustainable Green IT model could be integrated into existing IT systems, leading to significant reductions in carbon emissions and e-waste and improvements in energy efficiency. The development of the GIRT and the findings of this study have the potential to inspire other organizations to adopt sustainable IT practices, positively impact the environment, and be used as a reference by IT professionals and decision-makers to evaluate IT-related sustainability practices. The GIRT could also serve as a benchmark for HEIs to compare their performance with other institutions and to track their progress over time. Additionally, the study's results suggest that virtual and cloud-based technologies could reduce e-waste and energy consumption in the higher education sector. Overall, this study highlights the importance of incorporating Green IT practices into the IT systems of HEI to contribute to a more sustainable future.

Keywords: green information technology, international higher-educational institution, sustainable solutions, environmentally friendly IT systems

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Authors: Maryam Kiani, Abdul Basit Kiani

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At larger scales, the performance of cementitious materials is impacted by processes occurring at the nanometer scale. These materials boast intricate hierarchical structures with random features that span from the nanometer to millimeter scale. It is fascinating to observe how the nanoscale processes influence the overall behavior and characteristics of these materials. By delving into and manipulating these processes, scientists and engineers can unlock the potential to create more durable and sustainable infrastructure and construction materials. It's like unraveling a hidden tapestry of secrets that hold the key to building stronger and more resilient structures. The present work employs simulations as the computational modeling methodology to predict mechanical properties for carbon/silica based cementitious materials at the molecular/nano scale level. Studies focused on understanding the effect of higher mechanical properties of cementitious materials with carbon silica nanoparticles via Material Studio materials modeling.

Keywords: nanomaterials, SiO₂, carbon black, mechanical properties

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Authors: Sobhan Sobhani

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This study examined the behavioral patterns of student and their determinants according to the "symbolic interaction" sociological perspective in the form of 7 hypotheses. Behavioral patterns of students were classified in 8 categories: religious, scientific, political, artistic, sporting, national, parents and teachers. They were evaluated by student opinions by a five-point Likert rating scale. The statistical population included all male and female students of Islamic Azad University, Behabahan branch, among which 600 patients (268 females and 332 males) were selected randomly. The following statistical methods were used: frequency and percentage, mean, t-test, Pearson correlation coefficient and multi-way analysis of variance. The results obtained from statistical analysis showed that: 1-There is a significant difference between male and female students in terms of disposition to religious figures, artists, teachers and parents. 2-There is a significant difference between students of urban and rural areas in terms of assuming behavioral patterns of religious, political, scientific, artistic, national figures and teachers. 3-The most important criterion for selecting behavioral patterns of students is intellectual understanding with the pattern. 4-The most important factor influencing the behavioral patterns of male and female students is parents followed by friends. 5-Boys are affected by teachers, the Internet and satellite programs more than girls. Girls assume behavioral patterns from books more than boys. 6-There is a significant difference between students in human sciences, technical, medical and engineering disciplines in terms of selecting religious and political figures as behavioral patterns. 7-There is a significant difference between students belonging to different subcultures in terms of assuming behavioral patterns of religious, scientific and cultural figures. 8-Between the first and fourth year students in terms of selecting behavioral patterns, there is a significant difference only in selecting religious figures. 9-There is a significant negative correlation between the education level of parents and the selection of religious and political figures and teachers. 10-There is a significant negative correlation between family income and the selection of political and religious figures.

Keywords: behavioral patterns, behavioral patterns, male and female students, Islamic Azad University

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Authors: Armineh Nourbakhsh, Sameena Shah, Carolyn Rose

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Layout-aware language models have been used to create multimodal representations for documents that are in image form, achieving relatively high accuracy in document understanding tasks. However, the large number of parameters in the resulting models makes building and using them prohibitive without access to high-performing processing units with large memory capacity. We propose an alternative approach that can create efficient representations without the need for a neural visual backbone. This leads to an 80% reduction in the number of parameters compared to the smallest SOTA model, widely expanding applicability. In addition, our layout embeddings are pre-trained on spatial and visual cues alone and only fused with text embeddings in downstream tasks, which can facilitate applicability to low-resource of multi-lingual domains. Despite using 2.5% of training data, we show competitive performance on two form understanding tasks: semantic labeling and link prediction.

Keywords: layout understanding, form understanding, multimodal document understanding, bias-augmented attention

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Authors: Komol Phaisarn, Anuphan Suttimarn, Vitchanan Keawtong, Kittisak Thongyoun, Chaiyos Jamsawang

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This article is intended to analyze insurance information which contains information on the customer decision when purchasing life insurance pay package. The data were analyzed in order to present new customers with Life Insurance Perfect Pay package to meet new customers’ needs as much as possible. The basic data of insurance pay package were collect to get data mining; thus, reducing the scattering of information. The data were then classified in order to get decision model or decision tree using Algorithm C4.5 (J-48). In the classification, WEKA tools are used to form the model and testing datasets are used to test the decision tree for the accurate decision. The validation of this model in classifying showed that the accurate prediction was 68.43% while 31.25% were errors. The same set of data were then tested with other models, i.e. Naive Bayes and Zero R. The results showed that J-48 method could predict more accurately. So, the researcher applied the decision tree in writing the program used to introduce the product to new customers to persuade customers’ decision making in purchasing the insurance package that meets the new customers’ needs as much as possible.

Keywords: decision tree, data mining, customers, life insurance pay package

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Authors: Stefanie Behncke

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This paper analyses the effects of different macroprudential policy measures that have recently been implemented in Switzerland. Among them is the activation and the increase of the countercyclical capital buffer (CCB) and a tightening of loan-to-value (LTV) requirements. These measures were introduced to limit systemic risks in the Swiss mortgage and real estate markets. They were meant to affect mortgage growth, mortgage risks, and banks’ capital buffers. Evaluation of their quantitative effects provides insights for Swiss policymakers when reassessing their policy. It is also informative for policymakers in other countries who plan to introduce macroprudential instruments. We estimate the effects of the different macroprudential measures with a Differences-in-Differences estimator. Banks differ with respect to the relative importance of mortgages in their portfolio, their riskiness, and their capital buffers. Thus, some of the banks were more affected than others by the CCB, while others were more affected by the LTV requirements. Our analysis is made possible by an unusually informative bank panel data set. It combines data on newly issued mortgage loans and quantitative risk indicators such as LTV and loan-to-income (LTI) ratios with supervisory information on banks’ capital and liquidity situation and balance sheets. Our results suggest that the LTV cap of 90% was most effective. The proportion of new mortgages with a high LTV ratio was significantly reduced. This result does not only apply to the 90% LTV, but also to other threshold values (e.g. 80%, 75%) suggesting that the entire upper part of the LTV distribution was affected. Other outcomes such as the LTI distribution, the growth rates of mortgages and other credits, however, were not significantly affected. Regarding the activation and the increase of the CCB, we do not find any significant effects: neither LTV/LTI risk parameters nor mortgage and other credit growth rates were significantly reduced. This result may reflect that the size of the CCB (1% of relevant residential real estate risk-weighted assets at activation, respectively 2% at the increase) was not sufficiently high enough to trigger a distinct reaction between the banks most likely to be affected by the CCB and those serving as controls. Still, it might be have been effective in increasing the resilience in the overall banking system. From a policy perspective, these results suggest that targeted macroprudential policy measures can contribute to financial stability. In line with findings by others, caps on LTV reduced risk taking in Switzerland. To fully assess the effectiveness of the CCB, further experience is needed.

Keywords: banks, financial stability, macroprudential policy, mortgages

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Authors: Moustafa Osman

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The paper describes and analyses different good practice examples of protective levels, and initiatives actions (“framework conditions”) and encourages the uptake of environmental management systems (EMSs) to small and medium-sized enterprises (SMEs). Most of industries tend to take EMS as tools leading towards sustainability planning. The application of these tools has numerous environmental obligations that neither suggests decision nor recommends what a company should achieve ultimately. These set up clearly defined criteria to evaluate environmental protective action (EEPA) into sustainability indicators. The physical integration will evaluate how to incorporate traditional knowledge into baseline information, preparing impact prediction, and planning mitigation measures in monitoring conditions. Thereby efforts between the government, industry and community led protective action to concern with present needs for future generations, meeting the goal of sustainable development. The paper discusses how to set out distinct aspects of sustainable indicators and reflects inputs, outputs, and modes of impact on the environment.

Keywords: environmental management, sustainability, indicators, protective action

Procedia PDF Downloads 443