Search results for: unified theory of acceptance and use of technology (UTAUT) model

Authors: R. T. Aggangan

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Woodfuels continue to be a major component of the energy supply mix of the Philippines due to increasing demand for energy that are not adequately met by decreasing supply and increasing prices of fuel oil such as liquefied petroleum gas (LPG) and kerosene. The Development Academy of the Philippines projects the demand of woodfuels in 2016 as 28.3 million metric tons in the household sector and about 105.4 million metric tons combined supply potentials of both forest and non-forest lands. However, the Revised Master Plan for Forestry Development projects a demand of about 50 million cu meters of fuelwood in 2016 but the capability to supply from local sources is only about 28 million cu meters indicating a 44 % deficiency. Household demand constitutes 82% while industries demand is 18%. Domestic household demand for energy is for cooking needs while the industrial demand is for steam power generation, curing barns of tobacco: brick, ceramics and pot making; bakery; lime production; and small scale food processing. Factors that favour increased use of wood-based energy include the relatively low prices (increasing oil-based fuel prices), availability of efficient wood-based energy utilization technology, increasing supply, and increasing population that cannot afford conventional fuels. Moreover, innovations in combustion technology and cogeneration of heat and power from biomass for modern applications favour biomass energy development. This paper recommends policies and strategic directions for the development of the woodfuel industry with the twin goals of sustainably supplying the energy requirements of households and industry.

Keywords: biomass energy development, fuelwood, households and industry, innovations in combustion technology, supply and demand

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Authors: Satya P. Dubey, Hrushikesh A Abhyankar, Veronica Marchante, James L. Brighton, Björn Bergmann

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Aims: To develop a mathematical model that simulates the ROP of PLA taking into account the effect of alternative energy to be implemented in a continuous reactive extrusion production process of PLA. Introduction: The production of large amount of waste is one of the major challenges at the present time, and polymers represent 70% of global waste. PLA has emerged as a promising polymer as it is compostable, biodegradable thermoplastic polymer made from renewable sources. However, the main limitation for the application of PLA is the traces of toxic metal catalyst in the final product. Thus, a safe and efficient production process needs to be developed to avoid the potential hazards and toxicity. It has been found that alternative energy sources (LASER, ultrasounds, microwaves) could be a prominent option to facilitate the ROP of PLA via continuous reactive extrusion. This process may result in complete extraction of the metal catalysts and facilitate less active organic catalysts. Methodology: Initial investigation were performed using the data available in literature for the reaction mechanism of ROP of PLA based on conventional metal catalyst stannous octoate. A mathematical model has been developed by considering significant parameters such as different initial concentration ratio of catalyst, co-catalyst and impurity. Effects of temperature variation and alternative energies have been implemented in the model. Results: The validation of the mathematical model has been made by using data from literature as well as actual experiments. Validation of the model including alternative energies is in progress based on experimental data for partners of the InnoREX project consortium. Conclusion: The model developed reproduces accurately the polymerisation reaction when applying alternative energy. Alternative energies have a great positive effect to increase the conversion and molecular weight of the PLA. This model could be very useful tool to complement Ludovic® software to predict the large scale production process when using reactive extrusion.

Keywords: polymer, poly-lactic acid (PLA), ring opening polymerization (ROP), metal-catalyst, bio-degradable, renewable source, alternative energy (AE)

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Authors: Kanchan Mondal, Dasharath Koulage, Dattatray Manerikar, Asmita Ghate

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This paper presents an additive reliability model using warranty data and Finite Element Analysis (FEA) data. Warranty data for any product gives insight to its underlying issues. This is often used by Reliability Engineers to build prediction model to forecast failure rate of parts. But there is one major limitation in using warranty data for prediction. Warranty periods constitute only a small fraction of total lifetime of a product, most of the time it covers only the infant mortality and useful life zone of a bathtub curve. Predicting with warranty data alone in these cases is not generally provide results with desired accuracy. Failure rate of a mechanical part is driven by random issues initially and wear-out or usage related issues at later stages of the lifetime. For better predictability of failure rate, one need to explore the failure rate behavior at wear out zone of a bathtub curve. Due to cost and time constraints, it is not always possible to test samples till failure, but FEA-Fatigue analysis can provide the failure rate behavior of a part much beyond warranty period in a quicker time and at lesser cost. In this work, the authors proposed an Additive Weibull Model, which make use of both warranty and FEA fatigue analysis data for predicting failure rates. It involves modeling of two data sets of a part, one with existing warranty claims and other with fatigue life data. Hazard rate base Weibull estimation has been used for the modeling the warranty data whereas S-N curved based Weibull parameter estimation is used for FEA data. Two separate Weibull models’ parameters are estimated and combined to form the proposed Additive Weibull Model for prediction.

Keywords: bathtub curve, fatigue, FEA, reliability, warranty, Weibull

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Authors: L. Al Ahmad, C. Latrille, D. Hainos, D. Blanc, M. Clausse

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A two-dimensional finite volume axisymmetric model is developed to predict the simultaneous heat and mass transfers during the drying of industrial sludge. The simulations were run using COMSOL-Multiphysics 3.5a. The input parameters of the numerical model were acquired from a preliminary experimental work. Results permit to establish correlations describing the evolution of the various parameters as a function of the drying temperature and the sludge water content. The selection and coupling of the equation are validated based on the drying kinetics acquired experimentally at a temperature range of 45-65 °C and absolute pressure range of 200-1000 mbar. The model, incorporating the heat and mass transfer mechanisms at different operating conditions, shows simulated values of temperature and water content. Simulated results are found concordant with the experimental values, only at the first and last drying stages where sludge shrinkage is insignificant. Simulated and experimental results show that sludge drying is favored at high temperatures and low pressure. As experimentally observed, the drying time is reduced by 68% for drying at 65 °C compared to 45 °C under 1 atm. At 65 °C, a 200-mbar absolute pressure vacuum leads to an additional reduction in drying time estimated by 61%. However, the drying rate is underestimated in the intermediate stage. This rate underestimation could be improved in the model by considering the shrinkage phenomena that occurs during sludge drying.

Keywords: industrial sludge drying, heat transfer, mass transfer, mathematical modelling

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Authors: Yan Yan, Erhong Sun, Lin Peng, Xuchun Ye

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Aims: The present study aimed to explore Intensive Care Unit(ICU) nurses’ mental workload (MWL) and associated factors with it in performing human-machine tasks. Background: A wide range of emerging technologies have penetrated widely in the field of health care, and ICU nurses are facing a dramatic increase in nursing human-machine tasks. However, there is still a paucity of literature reporting on the general MWL of ICU nurses performing human-machine tasks and the associated influencing factors. Methods: A cross-sectional survey was employed. The data was collected from January to February 2021 from 9 tertiary hospitals in 6 provinces (Shanghai, Gansu, Guangdong, Liaoning, Shandong, and Hubei). Two-stage sampling was used to recruit eligible ICU nurses (n=427). The data were collected with an electronic questionnaire comprising sociodemographic characteristics and the measures of MWL, self-efficacy, system usability, and task difficulty. The univariate analysis, two-way analysis of variance(ANOVA), and a linear mixed model were used for data analysis. Results: Overall, the mental workload of ICU nurses in performing human-machine tasks was medium (score 52.04 on a 0-100 scale). Among the typical nursing human-machine tasks selected, the MWL of ICU nurses in completing first aid and life support tasks (‘Using a defibrillator to defibrillate’ and ‘Use of ventilator’) was significantly higher than others (p < .001). And ICU nurses’ MWL in performing human-machine tasks was also associated with age (p = .001), professional title (p = .002), years of working in ICU (p < .001), willingness to study emerging technology actively (p = .006), task difficulty (p < .001), and system usability (p < .001). Conclusion: The MWL of ICU nurses is at a moderate level in the context of a rapid increase in nursing human-machine tasks. However, there are significant differences in MWL when performing different types of human-machine tasks, and MWL can be influenced by a combination of factors. Nursing managers need to develop intervention strategies in multiple ways. Implications for practice: Multidimensional approaches are required to perform human-machine tasks better, including enhancing nurses' willingness to learn emerging technologies actively, developing training strategies that vary with tasks, and identifying obstacles in the process of human-machine system interaction.

Keywords: mental workload(MWL), nurse, ICU, human-machine, tasks, cross-sectional study, linear mixed model, China

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Authors: Massimiliano Frezza, Sergio Bianchi, Augusto Pianese

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Introduced by Shannon in 1948 in the field of information theory as the average rate at which information is produced by a stochastic set of data, the concept of entropy has gained much attention as a measure of uncertainty and unpredictability associated with a dynamical system, eventually depicted by a stochastic process. In particular, the Shannon entropy measures the degree of order/disorder of a given signal and provides useful information about the underlying dynamical process. It has found widespread application in a variety of fields, such as, for example, cryptography, statistical physics and finance. In this regard, many contributions have employed different measures of entropy in an attempt to characterize the financial time series in terms of market efficiency, market crashes and/or financial crises. The Shannon entropy has also been considered as a measure of the risk of a portfolio or as a tool in asset pricing. This work investigates the theoretical link between the Shannon entropy and the multifractional Brownian motion (mBm), stochastic process which recently is the focus of a renewed interest in finance as a driving model of stochastic volatility. In particular, after exploring the current state of research in this area and highlighting some of the key results and open questions that remain, we show a well-defined relationship between the Shannon (log)entropy and the memory function H(t) of the mBm. In details, we allow both the length of time series and time scale to change over analysis to study how the relation modify itself. On the one hand, applications are developed after generating surrogates of mBm trajectories based on different memory functions; on the other hand, an empirical analysis of several international stock indexes, which confirms the previous results, concludes the work.

Keywords: Shannon entropy, multifractional Brownian motion, Hurst–Holder exponent, stock indexes

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Authors: Shayla He

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Background and Purpose: According to Chamie (2017), it’s estimated that no less than 150 million people, or about 2 percent of the world’s population, are homeless. The homeless population in the United States has grown rapidly in the past four decades. In New York City, the sheltered homeless population has increased from 12,830 in 1983 to 62,679 in 2020. Knowing the trend on the homeless population is crucial at helping the states and the cities make affordable housing plans, and other community service plans ahead of time to better prepare for the situation. This study utilized the data from New York City, examined the key factors associated with the homelessness, and developed systematic modeling to predict homeless populations of the future. Using the best model developed, named HP-RNN, an analysis on the homeless population change during the months of 2020 and 2021, which were impacted by the COVID-19 pandemic, was conducted. Moreover, HP-RNN was tested on the data from Seattle. Methods: The methodology involves four phases in developing robust prediction methods. Phase 1 gathered and analyzed raw data of homeless population and demographic conditions from five urban centers. Phase 2 identified the key factors that contribute to the rate of homelessness. In Phase 3, three models were built using Linear Regression, Random Forest, and Recurrent Neural Network (RNN), respectively, to predict the future trend of society's homeless population. Each model was trained and tuned based on the dataset from New York City for its accuracy measured by Mean Squared Error (MSE). In Phase 4, the final phase, the best model from Phase 3 was evaluated using the data from Seattle that was not part of the model training and tuning process in Phase 3. Results: Compared to the Linear Regression based model used by HUD et al (2019), HP-RNN significantly improved the prediction metrics of Coefficient of Determination (R2) from -11.73 to 0.88 and MSE by 99%. HP-RNN was then validated on the data from Seattle, WA, which showed a peak %error of 14.5% between the actual and the predicted count. Finally, the modeling results were collected to predict the trend during the COVID-19 pandemic. It shows a good correlation between the actual and the predicted homeless population, with the peak %error less than 8.6%. Conclusions and Implications: This work is the first work to apply RNN to model the time series of the homeless related data. The Model shows a close correlation between the actual and the predicted homeless population. There are two major implications of this result. First, the model can be used to predict the homeless population for the next several years, and the prediction can help the states and the cities plan ahead on affordable housing allocation and other community service to better prepare for the future. Moreover, this prediction can serve as a reference to policy makers and legislators as they seek to make changes that may impact the factors closely associated with the future homeless population trend.

Keywords: homeless, prediction, model, RNN

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Authors: Hamitri-Guerfi Fatiha, Mekimene Lekhder, Madani Khodir, Youyou Ahcene

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Virgin olive oil is appreciated by consumers, the quality of the oil is regulated by the international olive oil council depends on its chemical composition, so, the correct packing conditions are a prerequisite to preserve oil color, flavor, and nutriments, from production to consumption. The contact of food with various materials of packaging, since the production, until their consumption constitutes one of the essential aspects of food safety (directive 76/833/CEE). In Algeria, plastic bottles, although, they are economic and light are largely used at packaging olive oil but not used in other countries. This is due to migration phenomena that can occur from these materials. Thus, the goal of this work is to examine the physicochemical behavior of the couple packaging plastic-oil during their exposure to three temperatures corresponding to the conditions of storage applied in Algeria. Like, it is difficult to compare blowers of bottles which are heavy engineering, it comes out from this study that the effect of heat, the absorption of water, the constraints of storage of acidity, as well as the composition of oil, the PET bottles showed a remarkable structural instability, this defect of quality was confirmed by the analysis of morphology by electronic scan microscopy. These bottles present a total migration significantly higher than the threshold of acceptance. Moreover, a metal contamination of oil by its packaging was confirmed by the spectroscopy of atomic absorption and a microanalysis. The differences observed between the results of the microanalysis applied and the mechanical characterizations of the various bottles are reported, showing the reality of the container-contents exchanges.

Keywords: interaction, stability, pet, virgin olive oil

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Authors: Naga Velamakuri, Jyothi K. Reddy

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Quality must be designed into a product and not inspected has become the main motto of all the companies globally. Due to the rapidly increasing technology in the past few decades, the nature of demands from the consumers has become more sophisticated. To sustain this global revolution of innovation in production systems, companies have to take steps to accommodate this technology growth. In this process of understanding the customers' expectations, all the firms globally take steps to deliver a perfect output. Most of these techniques also concentrate on the consistent development and optimization of the product to exceed the expectations. Quality Function Deployment(QFD) and Modular Function Deployment(MFD) are such techniques which rely on the voice of the customer and help deliver the needs. In this paper, Quality Function Deployment and Modular Function Deployment techniques which help in converting the quantitative descriptions to qualitative outcomes are discussed. The area of interest would be to understand the scope of each of the techniques and the application range in product development when these are applied together to any problem. The research question would be mainly aimed at comprehending the limitations using modularity in product development.

Keywords: quality function deployment, modular function deployment, house of quality, methodology

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Authors: Mohammed Islam, Jungyong Wang, Dong Cheol Seo

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The Smoothed Particle Hydrodynamics (SPH) method is a novel, meshless, and Lagrangian technique based numerical method that has shown promises to accurately predict the hydrodynamics of water and structure interactions in violent flow conditions. The main goal of this study is to build confidence on the versatility of the Smoothed Particle Hydrodynamics (SPH) based tool, to use it as a complementary tool to the physical model testing capabilities and support research need for the performance evaluation of ships and offshore platforms exposed to an extreme and harsh environment. In the current endeavor, an open-sourced SPH-based tool was used and validated for modeling and predictions of the hydrodynamic interactions of a 6-DOF ship and bergy bits. The study involved the modeling of a modern generic drillship and simplified bergy bits in floating and towing scenarios and in regular and irregular wave conditions. The predictions were validated using the model-scale measurements on a moored ship towed at multiple oblique angles approaching a floating bergy bit in waves. Overall, this study results in a thorough comparison between the model scale measurements and the prediction outcomes from the SPH tool for performance and accuracy. The SPH predicted ship motions and forces were primarily within ±5% of the measurements. The velocity and pressure distribution and wave characteristics over the free surface depicts realistic interactions of the wave, ship, and the bergy bit. This work identifies and presents several challenges in preparing the input file, particularly while defining the mass properties of complex geometry, the computational requirements, and the post-processing of the outcomes.

Keywords: SPH, ship and bergy bit, hydrodynamic interactions, model validation, physical model testing

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Authors: Alpha Bolinao, Francine Rose De Castro, Jessie Kate Lumba, Raztine Mae Paeste, Hannah Grace Tosio

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The present study aimed to know the role of verbal bullying in the lives of obese teenagers exposed to it. The study employed a qualitative design specifically the phenomenological approach that focuses on the obese teenagers’ verbal bullying experiences. The study also used the social constructivism approach wherein it described the obese teenagers’ verbal bullying experiences as they interact with the social world. Through purposive and referral sampling technique, the researchers were able to choose twelve (12) respondents from different schools around the City of Manila, enrolled in the School Year 2015-2016, ages 16-21 years old, has experienced verbal bullying for the last ten (10) years and with the Body Mass Index (BMI) of equal to or greater than 30. Upon the consent of the respondents, ethical considerations were ensured. In-depth one (1) hour interviews were guided by the researchers’ aide memoir. The recorded interviews were transcribed into a field text and the responses were thoroughly analyzed through Thematic Analysis and Kelly’s Repertory Grid. It was found that the role of verbal bullying in the lives of obese teenagers exposed to it is a process and is best described through a syringe, or the 5S Responses of Obese Teenagers in Bullying, with five conceptual themes which also signify the experiences and the process that obese teenagers have gone through after experiencing verbal bullying. The themes conceptualized were: Suffering, self-doubt, suppression, self-acceptance and sanguineness. This paper may serve as a basis for a counseling program to help the obese teenagers cope with their bullying experiences.

Keywords: obesity, obese teenagers, bullying, experiences

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Authors: Abbas Ghahremani

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One of the most fundamental management issues in organizations and companies is the recruiting of efficient staff and compiling exact and perfect criteria for testing the applicants,which is guided and practiced by the manager of human resources of the organization. Obviously, each part of the organization seeks special features and abilities in the people apart from common features among all the staff in all units,which are called principal duties and abilities,and we will study them more. This article is trying to find out how we can identify the most efficient people among the applicants of employment by using proper methods of testing appropriate for the needs of different of employment by using proper methods of testing appropriate for the needs of different units of the organization and recruit efficient staff. Acceptable method for recruiting is to closely identify their characters from various aspects such as ability to communicate, flexibility, stress management, risk acceptance, tolerance, vision to future, familiarity with the art, amount of creativity and different thinking and by raising proper questions related with the above named features and presenting a questionnaire, evaluate them from various aspect in order to gain the proper result. According to the above explanations, it can be concluded which aspects of abilities and characteristics of a person must be evaluated in order to reduce any mistake in recruitment and approach an ideal result and ultimately gain an organized system according to the standards and avoid waste of energy for unprofessional personnel which is a marginal issue in the organizations.

Keywords: human resources management, staff recuiting, employment factors, efficient staff

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Authors: Roxana Poushang Baghery, Matthew D. Reyes

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This paper presents a comprehensive investigation into jobsite safety orientation programs within the US construction industry. Through interviews with industry professionals, this paper explores the domains of safety roles, daily safety practices, safety culture, and experts’ insights. This study underscores the pivotal significance of safety orientation programs, addressing their content, coordination, technology integration, and emergency procedures. Key findings emphasize the influential roles of leadership, language, and technology in the enhancement of these programs. Advocating for a paradigm shift, this paper calls for a multifaceted approach rooted in engagement, leadership commitment, clear communication, technological integration, simplicity, and a persistent pursuit of improvement in safety orientations. This study significantly contributes to the ongoing evolution and enhancement of safety practices, ensuring the safety and success of construction projects and, above all, the safeguarding of its workforce.

Keywords: jobsite safety orientation, construction industry, safety culture, workplace incidents

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Authors: Wichian Sriprachan, Chutikarn Sriviboon

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The objectives of this research were to study the management of local towns and to develop a better model of town management according to the Philosophy of Sufficiency Economy. This study utilized qualitative research, field research, as well as documentary research at the same time. A total of 10 local towns or Tambons of Supanburi province, Thailand were selected for an in-depth interview. The findings revealed that the model of local town management according to Philosophy of Sufficient Economy was in a level of “good” and the model of management has the five basic guidelines: 1) ability to manage budget information and keep it up-to-date, 2) ability to decision making according to democracy rules, 3) ability to use check and balance system, 4) ability to control, follow, and evaluation, and 5) ability to allow the general public to participate. In addition, the findings also revealed that the human resource management according to Philosophy of Sufficient Economy includes obeying laws, using proper knowledge, and having integrity in five areas: plan, recruit, select, train, and maintain human resources.

Keywords: management, local town (Tambon), principles of sufficiency economy, marketing management

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Authors: Prakash Chandra Subedi

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Family farming is the family based farming activities, where the farmers cultivate their farm themselves and all the members of the family are engaged in farming as per their skill, age, and physical strength. This study was conducted to examine the food sufficiency level of family farmers and, was carried in the four VDCs of Kavrepalanchowk district -Jaisithok Mandan, Mahadevsthan Mandan and Gairi Bisouna Deupur. A total of 115 households determined as the sample size from each of the four VDCs were randomly visited for interview in the study. The size of land holding was found to be very small and fragmented. The quality of soil was fertile and could yield high production if irrigation existed. The labour used patterns were significant number of family labour but due to high youth migration there were labour shortage. The rate of adoption of agri-technology was low but the households adopting insectides/pesticides and chemical fertilizers were found to be high without any knowledge regarding its using techniques. In conclusion, the study highpoint that the crop production and food sufficiency level of the family farmers of the Kavrepalanchowk district is decreasing. Many farmers were leaving their farming and started seeking opportunity to go for foreign employment or engaged in non-agricultural activities in urban areas. If no action is taken timely, there may come situation that we will have to depend on imports for all the food requirements. Thus, the study reveals that the family farming could act as an agent for ensuring food sufficiency for all, if proper policies is promoted to family farmers with legal titles to their land or promoted with sustainable agriculture methods or provided with proper agri-technology or given their share of respect and responsibilities that farming as honorable profession.

Keywords: family farming, technology transfer, crop production, food sufficiency

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Authors: Golnush Masghati-Amoli, Paul Chin

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Over the past recent years, with the rapid increases in data availability and computing power, Machine Learning (ML) techniques have been called on in a range of different industries for their strong predictive capability. However, the use of Machine Learning in commercial banking has been limited due to a special challenge imposed by numerous regulations that require lenders to be able to explain their analytic models, not only to regulators but often to consumers. In other words, although Machine Leaning techniques enable better prediction with a higher level of accuracy, in comparison with other industries, they are adopted less frequently in commercial banking especially for scoring purposes. This is due to the fact that Machine Learning techniques are often considered as a black box and fail to provide information on why a certain risk score is given to a customer. In order to bridge this gap between the explain-ability and performance of Machine Learning techniques, a Hybrid Model is developed at Dun and Bradstreet that is focused on blending Machine Learning algorithms with traditional approaches such as scorecards. The Hybrid Model maximizes efficiency of traditional scorecards by merging its practical benefits, such as explain-ability and the ability to input domain knowledge, with the deep insights of Machine Learning techniques which can uncover patterns scorecard approaches cannot. First, through development of Machine Learning models, engineered features and latent variables and feature interactions that demonstrate high information value in the prediction of customer risk are identified. Then, these features are employed to introduce observed non-linear relationships between the explanatory and dependent variables into traditional scorecards. Moreover, instead of directly computing the Weight of Evidence (WoE) from good and bad data points, the Hybrid Model tries to match the score distribution generated by a Machine Learning algorithm, which ends up providing an estimate of the WoE for each bin. This capability helps to build powerful scorecards with sparse cases that cannot be achieved with traditional approaches. The proposed Hybrid Model is tested on different portfolios where a significant gap is observed between the performance of traditional scorecards and Machine Learning models. The result of analysis shows that Hybrid Model can improve the performance of traditional scorecards by introducing non-linear relationships between explanatory and target variables from Machine Learning models into traditional scorecards. Also, it is observed that in some scenarios the Hybrid Model can be almost as predictive as the Machine Learning techniques while being as transparent as traditional scorecards. Therefore, it is concluded that, with the use of Hybrid Model, Machine Learning algorithms can be used in the commercial banking industry without being concerned with difficulties in explaining the models for regulatory purposes.

Keywords: machine learning algorithms, scorecard, commercial banking, consumer risk, feature engineering

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Authors: Amir Jalalian-Khakshour, T. N. Croft

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Vertical Axis Wind Turbine (VAWT) systems are becoming increasingly popular as they have a number of advantages over traditional wind turbines. The advantages are reliability, ease of transportation and manufacturing. These attributes could make these technologies useful in developing economies. The performance characteristics of a VAWT are different from a horizontal axis wind turbine, which can be attributed to the low tip speed ratio operation. To unlock the potential of these VAWT systems, the operational behaviour in a number of system topologies and environmental conditions needs to be understood. In this study, a non-linear dynamic simulation method was developed in Matlab and validated against in field data of a large scale, 8-meter rotor diameter prototype. This simulation method has been utilised to determine the performance characteristics of a number of control methods and system topologies. The motivation for this research was to develop a simulation method which accurately captures the operating behaviour and is computationally inexpensive. The model was used to evaluate the performance through parametric studies and optimisation techniques. The study gave useful insights into the applications and energy generation potential of this technology.

Keywords: power generation, renewable energy, rotordynamics, wind energy

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Authors: Marcin Debowski, Marcin Zielinski, Miroslaw Krzemieniewski, Agata Glowacka-Gil, Paulina Rusanowska, Magdalena Zielinska, Agnieszka Cydzik-Kwiatkowska

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Technologies of biogas upgrading are now perceived as competitive solution combustion and production of electricity and heat. Biomethane production will ensure broader application as energy carrier than biogas. Biomethane can be used as fuel in internal combustion engines or introduced into the natural gas transmission network. Therefore, there is a need to search for innovative, economically and technically justified methods for biogas enrichment. The aim of this paper is to present a technology solution for biogas upgrading with immobilized algae biomass. Reactor for biogas upgrading with immobilized algae biomass can be used for removing CO₂ from the biogas, flue gases and the waste gases especially coming from different industry sectors, e.g. from the food industry from yeast production process, biogas production systems, liquid and gaseous fuels combustion systems, hydrocarbon processing technology. The basis for the technological assumptions of presented technology were laboratory works and analyses that tested technological variants of biogas upgrading. The enrichment of biogas with a methane content of 90-97% pointed to technological assumptions for installation on a technical scale. Reactor for biogas upgrading with algae biomass is characterized by a significantly lower cubature in relation to the currently used solutions which use CO₂ removal processes. The invention, by its structure, assumes achieving a very high concentration of biomass of algae through its immobilization in capsules. This eliminates the phenomenon of lowering the pH value, i.e. acidification of the environment in which algae grow, resulting from the introduction of waste gases at a high CO₂ concentration. The system for introducing light into algae capsules is characterized by a higher degree of its use, due to lower losses resulting from the phenomenon of absorption of light energy by water. The light from the light source is continuously supplied to the formed biomass of algae or cyanobacteria in capsules by the light tubes. The light source may be sunlight or a light generator of a different wavelength of light from 300 nm to 800 nm. A portion of gas containing CO₂, accumulated in the tank and conveyed by the pump is periodically introduced into the housing of the photobioreactor tank. When conveying the gas that contains CO₂, it penetrates the algal biomass in capsules through the outer envelope, displacing, from the algal biomass, gaseous metabolic products which are discharged by the outlet duct for gases. It contributes to eliminating the negative impact of this factor on CO₂ binding processes. As a result of the cyclic dosing of gases containing carbon dioxide, gaseous metabolic products of algae are displaced and removed outside the technological system. Technology for biogas upgrading with immobilized algae biomass is suitable for the small biogas plant. The advantages of this technology are high efficiency as well as useful algae biomass which can be used mainly as animal feed, fertilizers and in the power industry. The construction of the device allows effective removal of carbon dioxide from gases at a high CO₂ concentration.

Keywords: biogas, carbon dioxide, immobilised biomass, microalgae, upgrading

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Authors: Barbara Vojvodikova, Katerina Jupova, Iva Ticha

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Cities in their historical evolution have always adapted their internal structure to the needs of society (for example protective city walls during classicism era lost their defense function, became unnecessary, were demolished and gave space for new features such as roads, museums or parks). Today it is necessary to modify the internal structure of the city in order to minimize the impact of climate changes on the environment of the population. This article discusses the results of the Urban Climate model owned by VITO, which was carried out as part of a project from the European Union's Horizon grant agreement No 730004 Pan-European Urban Climate Services Climate-Fit city. The use of the model was aimed at changes in land use and land cover in cities related to urban heat islands (UHI). The task of the application was to evaluate possible land use change scenarios in connection with city requirements and ideas. Two pilot areas in the Czech Republic were selected. One is Ostrava and the other Hodonín. The paper provides a demonstration of the application of the model for various possible future development scenarios. It contains an assessment of the suitability or inappropriateness of scenarios of future development depending on the temperature increase. Cities that are preparing to reconstruct the public space are interested in eliminating proposals that would lead to an increase in temperature stress as early as in the assignment phase. If they have evaluation on the unsuitability of some type of design, they can limit it into the proposal phases. Therefore, especially in the application of models on Local level - in 1 m spatial resolution, it was necessary to show which type of proposals would create a significant temperature island in its implementation. Such a type of proposal is considered unsuitable. The model shows that the building itself can create a shady place and thus contribute to the reduction of the UHI. If it sensitively approaches the protection of existing greenery, this new construction may not pose a significant problem. More massive interventions leading to the reduction of existing greenery create a new heat island space.

Keywords: climate model, heat islands, Hodonin, land use changes, Ostrava

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Authors: Lyka Selene Magnayi, Marcos Vinas, Roseanne Ramos

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As the real estate industry continually grows in the Philippines, Geographic Information Systems (GIS) provide advantages in generating spatial databases for efficient delivery of information and services. The real estate sector is not only providing qualitative data about real estate properties but also utilizes various spatial aspects of these properties for different applications such as hazard mapping and assessment. In this study, a three-dimensional (3D) model and a spatial database of real estate properties in Fort Bonifacio, Taguig City are developed using GIS and SketchUp. Spatial datasets include political boundaries, buildings, road network, digital terrain model (DTM) derived from Interferometric Synthetic Aperture Radar (IFSAR) image, Google Earth satellite imageries, and hazard maps. Multiple model layers were created based on property listings by a partner real estate company, including existing and future property buildings. Actual building dimensions, building facade, and building floorplans are incorporated in these 3D models for geovisualization. Hazard model layers are determined through spatial overlays, and different scenarios of hazards are also presented in the models. Animated maps and walkthrough videos were created for company presentation and evaluation. Model evaluation is conducted through client surveys requiring scores in terms of the appropriateness, information content, and design of the 3D models. Survey results show very satisfactory ratings, with the highest average evaluation score equivalent to 9.21 out of 10. The output maps and videos obtained passing rates based on the criteria and standards set by the intended users of the partner real estate company. The methodologies presented in this study were found useful and have remarkable advantages in the real estate industry. This work may be extended to automated mapping and creation of online spatial databases for better storage, access of real property listings and interactive platform using web-based GIS.

Keywords: geovisualization, geographic information systems, GIS, real estate, spatial database, three-dimensional model

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Authors: Sergio Curilef, Boris Atenas

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Systems with long-range interactions are very common in nature. They are observed from the atomic scale to the astronomical scale and exhibit anomalies, such as inequivalence of ensembles, negative heat capacity, ergodicity breaking, nonequilibrium phase transitions, quasistationary states, and anomalous diffusion. These anomalies are exacerbated when special initial conditions are imposed; in particular, we use the so-called water bag initial conditions that stand for a uniform distribution. Several theoretical and practical implications are discussed here. A potential energy inspired by dipole-dipole interactions is proposed to build the dipole-type Hamiltonian mean-field model. As expected, the dynamics is novel and general to the behavior of systems with long-range interactions, which is obtained through molecular dynamics technique. Two plateaus sequentially emerge before arriving at equilibrium, which are corresponding to two different quasistationary states. The first plateau is a type of quasistationary state the lifetime of which depends on a power law of N and the second plateau seems to be a true quasistationary state as reported in the literature. The general behavior of the model according to its dynamics and thermodynamics is described. Using numerical simulation we characterize the mean kinetic energy, caloric curve, and the diffusion law through the mean square of displacement. The present challenge is to characterize the distributions in phase space. Certainly, the equilibrium state is well characterized by the Gaussian distribution, but quasistationary states in general depart from any Gaussian function.

Keywords: dipole-type interactions, dynamics and thermodynamics, mean field model, quasistationary states

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Authors: Bright Emeni

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The project is a system that allows users to locate their misplaced or lost devices by using Bluetooth technology. It utilizes the DFRobot Bettle BLE Arduino microcontroller as its main component for communication and control. By interfacing it with an LED and a buzzer, the system provides visual and auditory signals to assist in locating the target device. The search process can be initiated through an Android application, by which the system creates a Bluetooth connection between the microcontroller and the target device, permitting the exchange of signals for tracking purposes. When the device is within range, the LED indicator illuminates, and the buzzer produces audible alerts, guiding the user to the device's location. The application also provides an estimated distance of the object using Bluetooth signal strength. The project’s goal is to offer a practical and efficient solution for finding misplaced devices, leveraging the capabilities of Bluetooth technology and microcontroller-based control systems.

Keywords: Bluetooth finder, object finder, Bluetooth tracking, tracker

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Authors: Saniye Çeşmecioğlu

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The importance of project sustainability and success has become increasingly significant due to the proliferation of external environmental factors that have decreased project resistance in contemporary times. The primary approach to forestall the failure of projects is to ensure their long-term viability through the strategic selection of projects as creating judicious project selection framework within the organization. Decision-makers require precise decision contexts (models) that conform to the company's business objectives and sustainability expectations during the project selection process. The establishment of a rational model for project selection enables organizations to create a distinctive and objective framework for the selection process. Additionally, for the optimal implementation of this decision-making model, it is crucial to establish a Project Management Office (PMO) team and Project Steering Committee within the organizational structure to oversee the framework. These teams enable updating project selection criteria and weights in response to changing conditions, ensuring alignment with the company's business goals, and facilitating the selection of potentially viable projects. This paper presents a multi-criteria decision model for selecting project sustainability and project success criteria that ensures timely project completion and retention. The model was developed using MACBETH (Measuring Attractiveness by a Categorical Based Evaluation Technique) and was based on broadcaster companies’ expectations. The ultimate results of this study provide a model that endorses the process of selecting the appropriate project objectively by utilizing project selection and sustainability criteria along with their respective weights for organizations. Additionally, the study offers suggestions that may ascertain helpful in future endeavors.

Keywords: project portfolio management, project selection, multi-criteria decision making, project sustainability and success criteria, MACBETH

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Authors: Tapas Acharya, Monalisa Mitra

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Overlay modeling is the most widely used conventional analysis for spatial decision support system. Overlay modeling requires a set of themes with different weightage computed in varied manners, which gives a resultant input for further integrated analysis. In spite of the popularity and most widely used technique; it gives inconsistent and erroneous results for similar inputs while processed in various GIS overlay techniques. This study is an attempt to compare and analyse the differences in the outputs of different overlay methods using GIS platform with same set of themes of the Precambrian metamorphic to obtain groundwater prospecting in Precambrian metamorphic rocks. The objective of the study is to emphasize the most suitable overlay method for groundwater prospecting in older Precambrian metamorphics. Seven input thematic layers like slope, Digital Elevation Model (DEM), soil thickness, lineament intersection density, average groundwater table fluctuation, stream density and lithology have been used in the spatial overlay models of fuzzy overlay, weighted overlay and weighted sum overlay methods to yield the suitable groundwater prospective zones. Spatial concurrence analysis with high yielding wells of the study area and the statistical comparative studies among the outputs of various overlay models using RStudio reveal that the Weighted Overlay model is the most efficient GIS overlay model to delineate the groundwater prospecting zones in the Precambrian metamorphic rocks.

Keywords: fuzzy overlay, GIS overlay model, groundwater prospecting, Precambrian metamorphics, weighted overlay, weighted sum overlay

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Authors: Assil Ghariri

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This article studies the process of rewriting the self through memory in Kazuo Ishiguro’s novel, the Unconsoled (1995). It deals with the journey that the protagonist Mr. Ryder takes through the unconscious, in search for his real self, in which trauma stands as an obstacle. The article uses Carl Jung’s theory of archetypes. Trauma, in this article, is discussed as one of the true obstacles of the unconscious that prevent people from realizing the truth about their selves.

Keywords: Carl Jung, Kazuo Ishiguro, memory, trauma

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Authors: Dana Pugach, Michal Tamir

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Most criminal cases end with a plea agreement, an issue whose many aspects have been discussed extensively in legal literature. One important feature, however, has gained little notice, and that is crime victims’ place in plea agreements following the federal Crime Victims Rights Act of 2004. This law has provided victims some meaningful and potentially revolutionary rights, including the right to be heard in the proceeding and a right to appeal against a decision made while ignoring the victim’s rights. While victims’ rights literature has always emphasized the importance of such right, references to this provision in the general literature about plea agreements are sparse, if existing at all. Furthermore, there are a few cases only mentioning this right. This article purports to bridge between these two bodies of legal thinking – the vast literature concerning plea agreements and victims’ rights research– by using behavioral economics. The article will, firstly, trace the possible structural reasons for the failure of this right to be materialized. Relevant incentives of all actors involved will be identified as well as their inherent consequential processes that lead to the victims’ rights malfunction. Secondly, the article will use nudge theory in order to suggest solutions that will enhance incentives for the repeat players in the system (prosecution, judges, defense attorneys) and lead to the strengthening of weaker group’s interests – the crime victims. Behavioral psychology literature recognizes that the framework in which an individual confronts a decision can significantly influence his decision. Richard Thaler and Cass Sunstein developed the idea of ‘choice architecture’ - ‘the context in which people make decisions’ - which can be manipulated to make particular decisions more likely. Choice architectures can be changed by adjusting ‘nudges,’ influential factors that help shape human behavior, without negating their free choice. The nudges require decision makers to make choices instead of providing a familiar default option. In accordance with this theory, we suggest a rule, whereby a judge should inquire the victim’s view prior to accepting the plea. This suggestion leaves the judge’s discretion intact; while at the same time nudges her not to go directly to the default decision, i.e. automatically accepting the plea. Creating nudges that force actors to make choices is particularly significant when an actor intends to deviate from routine behaviors but experiences significant time constraints, as in the case of judges and plea bargains. The article finally recognizes some far reaching possible results of the suggestion. These include meaningful changes to the earlier stages of criminal process even before reaching court, in line with the current criticism of the plea agreements machinery.

Keywords: plea agreements, victims' rights, nudge theory, criminal justice

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Authors: Elena Pozdnyakova

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“Government Relations” is a field of knowledge presently taught at the majority of universities around the globe. English as the default language can become the language of teaching since the issues discussed are both global and national in character. However for this field of knowledge key concepts and their word representations in English don’t often coincide with those in other languages. International master’s degree students abroad as well as students, taught the course in English at their national universities, are exposed to difficulties, connected with correct conceptualizing of terminology of GR in British and American academic traditions. The study was carried out during the GR English language course elaboration (pilot research: 2013 -2015) at Moscow State Institute of Foreign Relations (University), Russian Federation. Within this period, English language instructors designed and elaborated the three-semester course of GR. Methodologically the course design was based on elaboration model with the special focus on conceptual elaboration sequence and theoretical elaboration sequence. The course designers faced difficulties in concept selection and theoretical elaboration sequence. To improve the results and eliminate the problems with concept selection, a new, corpus-based approach was worked out. The computer-based tool WordSmith 6.0 was used with the aim to build a model of key concept selection. The corpus of GR English texts consisted of 1 million words (the study corpus). The approach was based on measuring effect size, i.e. the percent difference of the frequency of a word in the study corpus when compared to that in the reference corpus. The results obtained proved significant improvement in the process of concept selection. The corpus-based model also facilitated theoretical elaboration of teaching materials.

Keywords: corpus-based study, English as the default language, key concepts, measuring effect size, model of key concept selection

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Authors: Rabiul Islam

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The study was in order to assess soil erosion at plot scale Universal Soil Loss Equation (USLE) erosion model and Geographic Information System (GIS) technique have been used for the study 8 plots in Guthrie Corridor Expressway, Selangor, Malaysia. The USLE model estimates an average soil loss soil integrating several factors such as rainfall erosivity factor(R ), Soil erodibility factor (K), slope length and steepness factor (LS), vegetation cover factor as well as conservation practice factor (C &P) and Results shows that the four plots have very low rates of soil loss, i.e. NLDNM, NDNM, PLDM, and NDM having an average soil loss of 0.059, 0.106, 0.386 and 0.372 ton/ha/ year, respectively. The NBNM, PLDNM and NLDM plots had a relatively higher rate of soil loss, with an average of 0.678, 0.757 and 0.493ton/ha/year. Whereas, the NBM is one of the highest rate of soil loss from 0.842 ton/ha/year to maximum 16.466 ton/ha/year. The NBM plot was located at bare the land; hence the magnitude of C factor(C=0.15) was the highest one.

Keywords: USLE model, GIS, Guthrie Corridor Expressway (GCE), Malaysia

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Authors: Sumaira Ashraf, Elisabete G.S. Félix, Zélia Serrasqueiro

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Traditional financial distress prediction models performed well to predict bankrupt and insolvent firms of the developed markets. Previous studies particularly focused on the predictability of financial distress, financial failure, and bankruptcy of firms. This paper contributes to the literature by extending the definition of financial distress with the inclusion of early warning signs related to quotation of face value, dividend/bonus declaration, annual general meeting, and listing fee. The study used five well-known distress prediction models to see if they have the ability to predict early warning signs of financial distress. Results showed that the predictive ability of the models varies over time and decreases specifically for the sample with early warning signs of financial distress. Furthermore, the study checked the differences in the predictive ability of the models with respect to the financial crisis. The results conclude that the predictive ability of the traditional financial distress prediction models decreases for the firms with early warning signs of financial distress and during the time of financial crisis. The study developed a new model comprising significant variables from the five models and one new variable earning response. This new model outperforms the old distress prediction models before, during and after the financial crisis. Thus, it can be used by researchers, organizations and all other concerned parties to indicate early warning signs for the emerging markets.

Keywords: financial distress, emerging market, prediction models, Z-Score, logit analysis, probit model

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Authors: Neda Nabid

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Friction-based supplemental devices have been extensively used for seismic protection and strengthening of structures, however, the conventional use of these dampers may not necessarily lead to an efficient structural performance. Conventionally designed friction dampers follow a uniform height-wise distribution pattern of slip load values for more practical simplicity. This can lead to localizing structural damage in certain story levels, while the other stories accommodate a negligible amount of relative displacement demand. A practical performance-based optimization methodology is developed to tackle with structural damage localization of RC frame buildings with friction energy dissipation devices under severe earthquakes. The proposed methodology is based on the concept of uniform damage distribution theory. According to this theory, the slip load values of the friction dampers redistribute and shift from stories with lower relative displacement demand to the stories with higher inter-story drifts to narrow down the discrepancy between the structural damage levels in different stories. In this study, the efficacy of the proposed design methodology is evaluated through the seismic performance of five different low to high-rise RC frames equipped with friction wall dampers under six real spectrum-compatible design earthquakes. The results indicate that compared to the conventional design, using the suggested methodology to design friction wall systems can lead to, by average, up to 40% reduction of maximum inter-story drift; and incredibly more uniform height-wise distribution of relative displacement demands under the design earthquakes.

Keywords: friction damper, nonlinear dynamic analysis, RC structures, seismic performance, structural damage

Procedia PDF Downloads 213