Search results for: utility model
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 17328

Search results for: utility model

17208 A 3-Dimensional Memory-Based Model for Planning Working Postures Reaching Specific Area with Postural Constraints

Authors: Minho Lee, Donghyun Back, Jaemoon Jung, Woojin Park

Abstract:

The current 3-dimensional (3D) posture prediction models commonly provide only a few optimal postures to achieve a specific objective. The problem with such models is that they are incapable of rapidly providing several optimal posture candidates according to various situations. In order to solve this problem, this paper presents a 3D memory-based posture planning (3D MBPP) model, which is a new digital human model that can analyze the feasible postures in 3D space for reaching tasks that have postural constraints and specific reaching space. The 3D MBPP model can be applied to the types of works that are done with constrained working postures and have specific reaching space. The examples of such works include driving an excavator, driving automobiles, painting buildings, working at an office, pitching/batting, and boxing. For these types of works, a limited amount of space is required to store all of the feasible postures, as the hand reaches boundary can be determined prior to perform the task. This prevents computation time from increasing exponentially, which has been one of the major drawbacks of memory-based posture planning model in 3D space. This paper validates the utility of 3D MBPP model using a practical example of analyzing baseball batting posture. In baseball, batters swing with both feet fixed to the ground. This motion is appropriate for use with the 3D MBPP model since the player must try to hit the ball when the ball is located inside the strike zone (a limited area) in a constrained posture. The results from the analysis showed that the stored and the optimal postures vary depending on the ball’s flying path, the hitting location, the batter’s body size, and the batting objective. These results can be used to establish the optimal postural strategies for achieving the batting objective and performing effective hitting. The 3D MBPP model can also be applied to various domains to determine the optimal postural strategies and improve worker comfort.

Keywords: baseball, memory-based, posture prediction, reaching area, 3D digital human models

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17207 Theta-Phase Gamma-Amplitude Coupling as a Neurophysiological Marker in Neuroleptic-Naive Schizophrenia

Authors: Jun Won Kim

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Objective: Theta-phase gamma-amplitude coupling (TGC) was used as a novel evidence-based tool to reflect the dysfunctional cortico-thalamic interaction in patients with schizophrenia. However, to our best knowledge, no studies have reported the diagnostic utility of the TGC in the resting-state electroencephalographic (EEG) of neuroleptic-naive patients with schizophrenia compared to healthy controls. Thus, the purpose of this EEG study was to understand the underlying mechanisms in patients with schizophrenia by comparing the TGC at rest between two groups and to evaluate the diagnostic utility of TGC. Method: The subjects included 90 patients with schizophrenia and 90 healthy controls. All patients were diagnosed with schizophrenia according to the criteria of Diagnostic and Statistical Manual of Mental Disorders, 4th edition (DSM-IV) by two independent psychiatrists using semi-structured clinical interviews. Because patients were either drug-naïve (first episode) or had not been taking psychoactive drugs for one month before the study, we could exclude the influence of medications. Five frequency bands were defined for spectral analyses: delta (1–4 Hz), theta (4–8 Hz), slow alpha (8–10 Hz), fast alpha (10–13.5 Hz), beta (13.5–30 Hz), and gamma (30-80 Hz). The spectral power of the EEG data was calculated with fast Fourier Transformation using the 'spectrogram.m' function of the signal processing toolbox in Matlab. An analysis of covariance (ANCOVA) was performed to compare the TGC results between the groups, which were adjusted using a Bonferroni correction (P < 0.05/19 = 0.0026). Receiver operator characteristic (ROC) analysis was conducted to examine the discriminating ability of the TGC data for schizophrenia diagnosis. Results: The patients with schizophrenia showed a significant increase in the resting-state TGC at all electrodes. The delta, theta, slow alpha, fast alpha, and beta powers showed low accuracies of 62.2%, 58.4%, 56.9%, 60.9%, and 59.0%, respectively, in discriminating the patients with schizophrenia from the healthy controls. The ROC analysis performed on the TGC data generated the most accurate result among the EEG measures, displaying an overall classification accuracy of 92.5%. Conclusion: As TGC includes phase, which contains information about neuronal interactions from the EEG recording, TGC is expected to be useful for understanding the mechanisms the dysfunctional cortico-thalamic interaction in patients with schizophrenia. The resting-state TGC value was increased in the patients with schizophrenia compared to that in the healthy controls and had a higher discriminating ability than the other parameters. These findings may be related to the compensatory hyper-arousal patterns of the dysfunctional default-mode network (DMN) in schizophrenia. Further research exploring the association between TGC and medical or psychiatric conditions that may confound EEG signals will help clarify the potential utility of TGC.

Keywords: quantitative electroencephalography (QEEG), theta-phase gamma-amplitude coupling (TGC), schizophrenia, diagnostic utility

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17206 Tobacco Taxation and the Heterogeneity of Smokers' Responses to Price Increases

Authors: Simone Tedeschi, Francesco Crespi, Paolo Liberati, Massimo Paradiso, Antonio Sciala

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This paper aims at contributing to the understanding of smokers’ responses to cigarette prices increases with a focus on heterogeneity, both across individuals and price levels. To do this, a stated preference quasi-experimental design grounded in a random utility framework is proposed to evaluate the effect on smokers’ utility of the price level and variation, along with social conditioning and health impact perception. The analysis is based on individual-level data drawn from a unique survey gathering very detailed information on Italian smokers’ habits. In particular, qualitative information on the individual reactions triggered by changes in prices of different magnitude and composition are exploited. The main findings stemming from the analysis are the following; the average price elasticity of cigarette consumption is comparable with previous estimates for advanced economies (-.32). However, the decomposition of this result across five latent-classes of smokers, reveals extreme heterogeneity in terms of price responsiveness, implying a potential price elasticity that ranges between 0.05 to almost 1. Such heterogeneity is in part explained by observable characteristics such as age, income, gender, education as well as (current and lagged) smoking intensity. Moreover, price responsiveness is far from being independent from the size of the prospected price increase. Finally, by comparing even and uneven price variations, it is shown that uniform across-brand price increases are able to limit the scope of product substitutions and downgrade. Estimated price-response heterogeneity has significant implications for tax policy. Among them, first, it provides evidence and a rationale for why the aggregate price elasticity is likely to follow a strictly increasing pattern as a function of the experienced price variation. This information is crucial for forecasting the effect of a given tax-driven price change on tax revenue. Second, it provides some guidance on how to design excise tax reforms to balance public health and revenue goals.

Keywords: smoking behaviour, preference heterogeneity, price responsiveness, cigarette taxation, random utility models

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17205 The Role of Organizational Identity in Disaster Response, Recovery and Prevention: A Case Study of an Italian Multi-Utility Company

Authors: Shanshan Zhou, Massimo Battaglia

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Identity plays a critical role when an organization faces disasters. Individuals reflect on their working identities and identify themselves with the group and the organization, which facilitate collective sensemaking under crisis situations and enable coordinated actions to respond to and recover from disasters. In addition, an organization’s identity links it to its regional community, which fosters the mobilization of resources and contributes to rapid recovery. However, identity is also problematic for disaster prevention because of its persistence. An organization’s ego-defenses system prohibits the rethink of its identity and a rigid identity obstructs disaster prevention. This research aims to tackle the ‘problem’ of identity by study in-depth a case of an Italian multi–utility which experienced the 2012 Northern Italy earthquakes. Collecting data from 11 interviews with top managers and key players in the local community and archived materials, we find that the earthquakes triggered the rethink of the organization’s identity, which got reinforced afterward. This research highlighted the importance of identity in disaster response and recovery. More importantly, it explored the solution of overcoming the barrier of ego-defense that is to transform the organization into a learning organization which constantly rethinks its identity.

Keywords: community identity, disaster, identity, organizational learning

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17204 Customer Segmentation Revisited: The Case of the E-Tailing Industry in Emerging Market

Authors: Sanjeev Prasher, T. Sai Vijay, Chandan Parsad, Abhishek Banerjee, Sahakari Nikhil Krishna, Subham Chatterjee

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With rapid rise in internet retailing, the industry is set for a major implosion. Due to the little difference among competitors, companies find it difficult to segment and target the right shoppers. The objective of the study is to segment Indian online shoppers on the basis of the factors – website characteristics and shopping values. Together, these cover extrinsic and intrinsic factors that affect shoppers as they visit web retailers. Data were collected using questionnaire from 319 Indian online shoppers, and factor analysis was used to confirm the factors influencing the shoppers in their selection of web portals. Thereafter, cluster analysis was applied, and different segments of shoppers were identified. The relationship between income groups and online shoppers’ segments was tracked using correspondence analysis. Significant findings from the study include that web entertainment and informativeness together contribute more than fifty percent of the total influence on the web shoppers. Contrary to general perception that shoppers seek utilitarian leverages, the present study highlights the preference for fun, excitement, and entertainment during browsing of the website. Four segments namely Information Seekers, Utility Seekers, Value Seekers and Core Shoppers were identified and profiled. Value seekers emerged to be the most dominant segment with two-fifth of the respondents falling for hedonic as well as utilitarian shopping values. With overlap among the segments, utilitarian shopping value garnered prominence with more than fifty-eight percent of the total respondents. Moreover, a strong relation has been established between the income levels and the segments of Indian online shoppers. Web shoppers show different motives from being utility seekers to information seekers, core shoppers and finally value seekers as income levels increase. Companies can strategically use this information for target marketing and align their web portals accordingly. This study can further be used to develop models revolving around satisfaction, trust and customer loyalty.

Keywords: online shopping, shopping values, effectiveness of information content, web informativeness, web entertainment, information seekers, utility seekers, value seekers, core shoppers

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17203 Improving Forecasting Demand for Maintenance Spare Parts: Case Study

Authors: Abdulaziz Afandi

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Minimizing the inventory cost, optimizing the inventory quantities, and increasing system operational availability are the main motivations to enhance forecasting demand of spare parts in a major power utility company in Medina. This paper reports in an effort made to optimize the orders quantities of spare parts by improving the method of forecasting the demand. The study focuses on equipment that has frequent spare parts purchase orders with uncertain demand. The pattern of the demand considers a lumpy pattern which makes conventional forecasting methods less effective. A comparison was made by benchmarking various methods of forecasting based on experts’ criteria to select the most suitable method for the case study. Three actual data sets were used to make the forecast in this case study. Two neural networks (NN) approaches were utilized and compared, namely long short-term memory (LSTM) and multilayer perceptron (MLP). The results as expected, showed that the NN models gave better results than traditional forecasting method (judgmental method). In addition, the LSTM model had a higher predictive accuracy than the MLP model.

Keywords: neural network, LSTM, MLP, forecasting demand, inventory management

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17202 Analyzing the Impact of Migration on HIV and AIDS Incidence Cases in Malaysia

Authors: Ofosuhene O. Apenteng, Noor Azina Ismail

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The human immunodeficiency virus (HIV) that causes acquired immune deficiency syndrome (AIDS) remains a global cause of morbidity and mortality. It has caused panic since its emergence. Relationships between migration and HIV/AIDS have become complex. In the absence of prospectively designed studies, dynamic mathematical models that take into account the migration movement which will give very useful information. We have explored the utility of mathematical models in understanding transmission dynamics of HIV and AIDS and in assessing the magnitude of how migration has impact on the disease. The model was calibrated to HIV and AIDS incidence data from Malaysia Ministry of Health from the period of 1986 to 2011 using Bayesian analysis with combination of Markov chain Monte Carlo method (MCMC) approach to estimate the model parameters. From the estimated parameters, the estimated basic reproduction number was 22.5812. The rate at which the susceptible individual moved to HIV compartment has the highest sensitivity value which is more significant as compared to the remaining parameters. Thus, the disease becomes unstable. This is a big concern and not good indicator from the public health point of view since the aim is to stabilize the epidemic at the disease-free equilibrium. However, these results suggest that the government as a policy maker should make further efforts to curb illegal activities performed by migrants. It is shown that our models reflect considerably the dynamic behavior of the HIV/AIDS epidemic in Malaysia and eventually could be used strategically for other countries.

Keywords: epidemic model, reproduction number, HIV, MCMC, parameter estimation

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17201 Water Supply and Demand Analysis for Ranchi City under Climate Change Using Water Evaluation and Planning System Model

Authors: Pappu Kumar, Ajai Singh, Anshuman Singh

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There are different water user sectors such as rural, urban, mining, subsistence and commercial irrigated agriculture, commercial forestry, industry, power generation which are present in the catchment in Subarnarekha River Basin and Ranchi city. There is an inequity issue in the access to water. The development of the rural area, construction of new power generation plants, along with the population growth, the requirement of unmet water demand and the consideration of environmental flows, the revitalization of small-scale irrigation schemes is going to increase the water demands in almost all the water-stressed catchment. The WEAP Model was developed by the Stockholm Environment Institute (SEI) to enable evaluation of planning and management issues associated with water resources development. The WEAP model can be used for both urban and rural areas and can address a wide range of issues including sectoral demand analyses, water conservation, water rights and allocation priorities, river flow simulation, reservoir operation, ecosystem requirements and project cost-benefit analyses. This model is a tool for integrated water resource management and planning like, forecasting water demand, supply, inflows, outflows, water use, reuse, water quality, priority areas and Hydropower generation, In the present study, efforts have been made to access the utility of the WEAP model for water supply and demand analysis for Ranchi city. A detailed works have been carried out and it was tried to ascertain that the WEAP model used for generating different scenario of water requirement, which could help for the future planning of water. The water supplied to Ranchi city was mostly contributed by our study river, Hatiya reservoir and ground water. Data was collected from various agencies like PHE Ranchi, census data of 2011, Doranda reservoir and meteorology department etc. This collected and generated data was given as input to the WEAP model. The model generated the trends for discharge of our study river up to next 2050 and same time also generated scenarios calculating our demand and supplies for feature. The results generated from the model outputs predicting the water require 12 million litter. The results will help in drafting policies for future regarding water supplies and demands under changing climatic scenarios.

Keywords: WEAP model, water demand analysis, Ranchi, scenarios

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17200 Contrasted Mean and Median Models in Egyptian Stock Markets

Authors: Mai A. Ibrahim, Mohammed El-Beltagy, Motaz Khorshid

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Emerging Markets return distributions have shown significance departure from normality were they are characterized by fatter tails relative to the normal distribution and exhibit levels of skewness and kurtosis that constitute a significant departure from normality. Therefore, the classical Markowitz Mean-Variance is not applicable for emerging markets since it assumes normally-distributed returns (with zero skewness and kurtosis) and a quadratic utility function. Moreover, the Markowitz mean-variance analysis can be used in cases of moderate non-normality and it still provides a good approximation of the expected utility, but it may be ineffective under large departure from normality. Higher moments models and median models have been suggested in the literature for asset allocation in this case. Higher moments models have been introduced to account for the insufficiency of the description of a portfolio by only its first two moments while the median model has been introduced as a robust statistic which is less affected by outliers than the mean. Tail risk measures such as Value-at Risk (VaR) and Conditional Value-at-Risk (CVaR) have been introduced instead of Variance to capture the effect of risk. In this research, higher moment models including the Mean-Variance-Skewness (MVS) and Mean-Variance-Skewness-Kurtosis (MVSK) are formulated as single-objective non-linear programming problems (NLP) and median models including the Median-Value at Risk (MedVaR) and Median-Mean Absolute Deviation (MedMAD) are formulated as a single-objective mixed-integer linear programming (MILP) problems. The higher moment models and median models are compared to some benchmark portfolios and tested on real financial data in the Egyptian main Index EGX30. The results show that all the median models outperform the higher moment models were they provide higher final wealth for the investor over the entire period of study. In addition, the results have confirmed the inapplicability of the classical Markowitz Mean-Variance to the Egyptian stock market as it resulted in very low realized profits.

Keywords: Egyptian stock exchange, emerging markets, higher moment models, median models, mixed-integer linear programming, non-linear programming

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17199 Design and Implementation of Machine Learning Model for Short-Term Energy Forecasting in Smart Home Management System

Authors: R. Ramesh, K. K. Shivaraman

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The main aim of this paper is to handle the energy requirement in an efficient manner by merging the advanced digital communication and control technologies for smart grid applications. In order to reduce user home load during peak load hours, utility applies several incentives such as real-time pricing, time of use, demand response for residential customer through smart meter. However, this method provides inconvenience in the sense that user needs to respond manually to prices that vary in real time. To overcome these inconvenience, this paper proposes a convolutional neural network (CNN) with k-means clustering machine learning model which have ability to forecast energy requirement in short term, i.e., hour of the day or day of the week. By integrating our proposed technique with home energy management based on Bluetooth low energy provides predicted value to user for scheduling appliance in advanced. This paper describes detail about CNN configuration and k-means clustering algorithm for short-term energy forecasting.

Keywords: convolutional neural network, fuzzy logic, k-means clustering approach, smart home energy management

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17198 Urinary Volatile Organic Compound Testing in Fast-Track Patients with Suspected Colorectal Cancer

Authors: Godwin Dennison, C. E. Boulind, O. Gould, B. de Lacy Costello, J. Allison, P. White, P. Ewings, A. Wicaksono, N. J. Curtis, A. Pullyblank, D. Jayne, J. A. Covington, N. Ratcliffe, N. K. Francis

Abstract:

Background: Colorectal symptoms are common but only infrequently represent serious pathology, including colorectal cancer (CRC). A large number of invasive tests are presently performed for reassurance. We investigated the feasibility of urinary volatile organic compound (VOC) testing as a potential triage tool in patients fast-tracked for assessment for possible CRC. Methods: A prospective, multi-centre, observational feasibility study was performed across three sites. Patients referred on NHS fast-track pathways for potential CRC provided a urine sample which underwent Gas Chromatography Mass Spectrometry (GC-MS), Field Asymmetric Ion Mobility Spectrometry (FAIMS) and Selected Ion Flow Tube Mass Spectrometry (SIFT-MS) analysis. Patients underwent colonoscopy and/or CT colonography and were grouped as either CRC, adenomatous polyp(s), or controls to explore the diagnostic accuracy of VOC output data supported by an artificial neural network (ANN) model. Results: 558 patients participated with 23 (4.1%) CRC diagnosed. 59% of colonoscopies and 86% of CT colonographies showed no abnormalities. Urinary VOC testing was feasible, acceptable to patients, and applicable within the clinical fast track pathway. GC-MS showed the highest clinical utility for CRC and polyp detection vs. controls (sensitivity=0.878, specificity=0.882, AUROC=0.884). Conclusion: Urinary VOC testing and analysis are feasible within NHS fast-track CRC pathways. Clinically meaningful differences between patients with cancer, polyps, or no pathology were identified therefore suggesting VOC analysis may have future utility as a triage tool. Acknowledgment: Funding: NIHR Research for Patient Benefit grant (ref: PB-PG-0416-20022).

Keywords: colorectal cancer, volatile organic compound, gas chromatography mass spectrometry, field asymmetric ion mobility spectrometry, selected ion flow tube mass spectrometry

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17197 GPRS Based Automatic Metering System

Authors: Constant Akama, Frank Kulor, Frederick Agyemang

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All over the world, due to increasing population, electric power distribution companies are looking for more efficient ways of reading electricity meters. In Ghana, the prepaid metering system was introduced in 2007 to replace the manual system of reading which was fraught with inefficiencies. However, the prepaid system in Ghana is not capable of integration with online systems such as e-commerce platforms and remote monitoring systems. In this paper, we present a design framework for an automatic metering system that can be integrated with e-commerce platforms and remote monitoring systems. The meter was designed using ADE 7755 which reads the energy consumption and the reading is processed by a microcontroller connected to Sim900 General Packet Radio Service module containing a GSM chip provisioned with an Access Point Name. The system also has a billing server and a management server located at the premises of the utility company which communicate with the meter over a Virtual Private Network and GPRS. With this system, customers can buy credit online and the credit will be transferred securely to the meter. Also, when a fault is reported, the utility company can log into the meter remotely through the management server to troubleshoot the problem.

Keywords: access point name, general packet radio service, GSM, virtual private network

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17196 Political Economy and Human Rights Engaging in Conversation

Authors: Manuel Branco

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This paper argues that mainstream economics is one of the reasons that can explain the difficulty in fully realizing human rights because its logic is intrinsically contradictory to human rights, most especially economic, social and cultural rights. First, its utilitarianism, both in its cardinal and ordinal understanding, contradicts human rights principles. Maximizing aggregate utility along the lines of cardinal utility is a theoretical exercise that consists in ensuring as much as possible that gains outweigh losses in society. In this process an individual may get worse off, though. If mainstream logic is comfortable with this, human rights' logic does not. Indeed, universality is a key principle in human rights and for this reason the maximization exercise should aim at satisfying all citizens’ requests when goods and services necessary to secure human rights are at stake. The ordinal version of utilitarianism, in turn, contradicts the human rights principle of indivisibility. Contrary to ordinal utility theory that ranks baskets of goods, human rights do not accept ranking when these goods and services are necessary to secure human rights. Second, by relying preferably on market logic to allocate goods and services, mainstream economics contradicts human rights because the intermediation of money prices and the purpose of profit may cause exclusion, thus compromising the principle of universality. Finally, mainstream economics sees human rights mainly as constraints to the development of its logic. According to this view securing human rights would, then, be considered a cost weighing on economic efficiency and, therefore, something to be minimized. Fully realizing human rights needs, therefore, a different approach. This paper discusses a human rights-based political economy. This political economy, among other characteristics should give up mainstream economics narrow utilitarian approach, give up its belief that market logic should guide all exchanges of goods and services between human beings, and finally give up its view of human rights as constraints on rational choice and consequently on good economic performance. Giving up mainstream’s narrow utilitarian approach means, first embracing procedural utility and human rights-aimed consequentialism. Second, a more radical break can be imagined; non-utilitarian, or even anti-utilitarian, approaches may emerge, then, as alternatives, these two standpoints being not necessarily mutually exclusive, though. Giving up market exclusivity means embracing decommodification. More specifically, this means an approach that takes into consideration the value produced outside the market and an allocation process no longer necessarily centered on money prices. Giving up the view of human rights as constraints means, finally, to consider human rights as an expression of wellbeing and a manifestation of choice. This means, in turn, an approach that uses indicators of economic performance other than growth at the macro level and profit at the micro level, because what we measure affects what we do.

Keywords: economic and social rights, political economy, economic theory, markets

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17195 Task Value and Research Culture of Southern Luzon State University

Authors: Antonio V. Romana, Rizaide A. Salayo, Maria Lavinia E. Fetalino

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This study assessed the subjective task value and research culture of SLSU faculty. It used the sequential explanatory mixed-method research design. For the quantitative phase, a questionnaire on the research culture and task value were used. While in the qualitative phase, the data was coded and thematized to interpret the focus group discussion outcome. Results showed that the dimensions of the subjective task value, intrinsic, got the highest rank while the utility value got the lowest. It is worth mentioning that all subjective task values were "Agreed." From the FGD, faculty members valued research and wanted to be involved in this undertaking. However, the limited number of faculty researchers, heavy teaching workload, inadequate information on the research process, lack of self-confidence, and low incentives received from research hindered their writing and engagement with research. Thus, a policy brief was developed. It is recommended that the institution may conduct a series of research seminar workshops for the faculty members, plan regular research idea exchange activities, and revisit the university's research thrust and agenda for faculties specialization and expertise alignment. In addition, the university may also lessen the workload and hire additional faculty members so that educators may focus on their research work. Finally, cash incentives may still be considered upon knowing that the faculty members have varied experiences in doing research tasks.

Keywords: task value, interest value, attainment value, utility value, research culture

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17194 Quantifying Uncertainties in an Archetype-Based Building Stock Energy Model by Use of Individual Building Models

Authors: Morten Brøgger, Kim Wittchen

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Focus on reducing energy consumption in existing buildings at large scale, e.g. in cities or countries, has been increasing in recent years. In order to reduce energy consumption in existing buildings, political incentive schemes are put in place and large scale investments are made by utility companies. Prioritising these investments requires a comprehensive overview of the energy consumption in the existing building stock, as well as potential energy-savings. However, a building stock comprises thousands of buildings with different characteristics making it difficult to model energy consumption accurately. Moreover, the complexity of the building stock makes it difficult to convey model results to policymakers and other stakeholders. In order to manage the complexity of the building stock, building archetypes are often employed in building stock energy models (BSEMs). Building archetypes are formed by segmenting the building stock according to specific characteristics. Segmenting the building stock according to building type and building age is common, among other things because this information is often easily available. This segmentation makes it easy to convey results to non-experts. However, using a single archetypical building to represent all buildings in a segment of the building stock is associated with loss of detail. Thermal characteristics are aggregated while other characteristics, which could affect the energy efficiency of a building, are disregarded. Thus, using a simplified representation of the building stock could come at the expense of the accuracy of the model. The present study evaluates the accuracy of a conventional archetype-based BSEM that segments the building stock according to building type- and age. The accuracy is evaluated in terms of the archetypes’ ability to accurately emulate the average energy demands of the corresponding buildings they were meant to represent. This is done for the buildings’ energy demands as a whole as well as for relevant sub-demands. Both are evaluated in relation to the type- and the age of the building. This should provide researchers, who use archetypes in BSEMs, with an indication of the expected accuracy of the conventional archetype model, as well as the accuracy lost in specific parts of the calculation, due to use of the archetype method.

Keywords: building stock energy modelling, energy-savings, archetype

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17193 Amplifying Sine Unit-Convolutional Neural Network: An Efficient Deep Architecture for Image Classification and Feature Visualizations

Authors: Jamshaid Ul Rahman, Faiza Makhdoom, Dianchen Lu

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Activation functions play a decisive role in determining the capacity of Deep Neural Networks (DNNs) as they enable neural networks to capture inherent nonlinearities present in data fed to them. The prior research on activation functions primarily focused on the utility of monotonic or non-oscillatory functions, until Growing Cosine Unit (GCU) broke the taboo for a number of applications. In this paper, a Convolutional Neural Network (CNN) model named as ASU-CNN is proposed which utilizes recently designed activation function ASU across its layers. The effect of this non-monotonic and oscillatory function is inspected through feature map visualizations from different convolutional layers. The optimization of proposed network is offered by Adam with a fine-tuned adjustment of learning rate. The network achieved promising results on both training and testing data for the classification of CIFAR-10. The experimental results affirm the computational feasibility and efficacy of the proposed model for performing tasks related to the field of computer vision.

Keywords: amplifying sine unit, activation function, convolutional neural networks, oscillatory activation, image classification, CIFAR-10

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17192 Risk Reassessment Using GIS Technologies for the Development of Emergency Response Management Plans for Water Treatment Systems

Authors: Han Gul Lee

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When water treatments utilities are designed, an initial construction site risk assessment is conducted. This helps us to understand general safety risks that each utility needs to be complemented in the designing stage. Once it’s built, an additional risk reassessment process secures and supplements its disaster management and response plan. Because of its constantly changing surroundings with city renovation and developments, the degree of various risks that each facility has to face changes. Therefore, to improve the preparedness for spill incidents or disasters, emergency managers should run spill simulations with the available scientific technologies. This research used a two-dimensional flow routing model to simulate its spill disaster scenario based on its digital elevation model (DEM) collected with drone technologies. The results of the simulations can help emergency managers to supplement their response plan with concrete situational awareness in advance. Planning based on this simulation model minimizes its potential loss and damage when an incident like earthquakes man-made disaster happens, which could eventually be a threat in a public health context. This pilot research provides an additional paradigm to increase the preparedness to spill disasters. Acknowledgment: This work was supported by Korea Environmental Industry & Technology Institute (KEITI) through Environmental R&D Project on the Disaster Prevention of Environmental Facilities Program funded by Korea Ministry of Environment (MOE) (No.202002860001).

Keywords: risk assessment, disaster management, water treatment utilities, situational awareness, drone technologies

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17191 Development of a Scale for Evaluating the Efficacy of Vacationing

Authors: Ju Yeon Lee, Seol Ah Oh, Hong il Kim, Hae Yong Do, Sung Won Choi

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The purpose of this study was to develop a Well-being and Moments Scale (WAMS) for evaluating the efficacy of ‘vacationing’ as a form of mental health recuperation. ‘Vacationing’ is defined as a going outside one’s usual environment to seek refreshment and relief from one’s daily life. To develop WAMS, we followed recommended procedures for scale development, including reviewing related studies, conducting focus group interviews to elucidate the need for this assessment area, and modifying items based on expert opinion. Through this process, we developed the WAMS. The psychometric properties of the WAMS were then tested in two separate samples. Exploratory factor analysis (EFA) was conducted using 1.41 participants (mean age = 30.45 years; range: 20-50 years) to identify the underlying 3-factor structure of 'Positive Emotions', 'Life Satisfaction' and 'Self-Confidence.' The 26 items retained based on the EFA procedures were associated with excellent reliability (i.e., α = 0.93). Confirmatory factor analysis was then conducted using 200 different participants (mean age = 29.51 years; range: 20-50 years) and revealed good model fit for our hypothesized 3-factor model. Convergent validity tests also revealed correlations with other scales in the expected direction and range. Study limitations as well as the importance and utility of WMAS are also discussed.

Keywords: vacationing, positive affect, life satisfaction, self-confidence, WAMS

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17190 Utility of Cardiac Biomarkers in Combination with Exercise Stress Testing in Patients with Suspected Ischemic Heart Disease

Authors: Rawa Delshada, Sanaa G. Hamab, Rastee D. Koyeec

Abstract:

Eighty patients with suspected ischemic heart disease were enrolled in the present study. They were classified into two groups: patients with positive exercise stress test results (n=40) and control group with negative exercise stress test results (n=40). Serum concentration of troponin I, Heart-type Fatty Acid Binding Protein (H-FABP) and Ischemia Modified Albumin (IMA) were measured one hour after performing stress test. Enzyme Linked Immunosorbent Assay was used to measure both troponin I, H-FABP levels, while IMA levels were measured by albumin cobalt binding test. There was no statistically significant difference in the mean concentration of troponin I between two groups (0.75±0.55ng/ml) for patients with positive test result vs. (0.71±0.55ng/ml) for negative test result group with P>0.05. Contrary to our expectation, mean IMA level was slightly higher among control group (70.88±39.76U/ml) compared to (62.7±51.9U/ml) in positive test result group, but still with no statistically significant difference (P>0.05). Median H-FABP level was also higher among negative exercise stress testing group compared the positive one (2ng/ml vs. 1.9ng/ml respectively), but failed to reach statistically significant difference (P>0.05). When quartiles model used to explore the possible association between each study biomarkers with the others; serum H-FABP level was lowest (1.7ng/ml) in highest quartile of IMA and lowest H-FABP (1.8ng/ml) in highest quartile of troponin I but with no statistically significant association (P>0.05). Myocardial ischemia, more likely occurred after exercise stress test, is not capable of causing troponin I release. Furthermore, an increase in H-FABP and IMA levels after stress test are not reflecting myocardial ischemia. Moreover, the combination of troponin I, H-FABP and IMA after measuring their post exercise levels does not improve the diagnostic utility of exercise stress test enormously.

Keywords: cardiac biomarkers, ischemic heart disease, troponin I, ischemia modified albumin, heart-type fatty acid binding protein, exercise stress testing

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17189 Mathematical Model to Quantify the Phenomenon of Democracy

Authors: Mechlouch Ridha Fethi

Abstract:

This paper presents a recent mathematical model in political sciences concerning democracy. The model is represented by a logarithmic equation linking the Relative Index of Democracy (RID) to Participation Ratio (PR). Firstly the meanings of the different parameters of the model were presented; and the variation curve of the RID according to PR with different critical areas was discussed. Secondly, the model was applied to a virtual group where we show that the model can be applied depending on the gender. Thirdly, it was observed that the model can be extended to different language models of democracy and that little use to assess the state of democracy for some International organizations like UNO.

Keywords: democracy, mathematic, modelization, quantification

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17188 The Effect of Socio-Economic Factors on Electric Vehicle Charging Behavior: An Investigation

Authors: Judith Mwakalonge, Geophrey Mbatta, Cuthbert Ruseruka, Gurcan Comert, Saidi Siuhi

Abstract:

Recent advancements in technology have fostered the development of Electric Vehicles (EVs) that provides relief from transportation dependence on natural fossil fuels as sources of energy. It is estimated that more than 50% of petroleum is used for transportation, which accounts for 28% of annual energy use. Vehicles make up about 82% of all transportation energy use. It is also estimated that about 22% of global Carbon dioxide (CO2) emissions are produced by the transportation sector, therefore, it raises environmental concerns. Governments worldwide, including the United States, are investing in developing EVs to resolve the issues related to the use of natural fossil fuels, such as air pollution due to emissions. For instance, the Bipartisan Infrastructure Law (BIL) that was signed by President Biden on November 15th, 2021, sets aside about $5 billion to be apportioned to all 50 states, the District of Columbia, and Puerto Rico for the development of EV chargers. These chargers should be placed in a way that maximizes their utility. This study aims at studying the charging behaviors of Electric Vehicle (EV) users to establish factors to be considered in the selection of charging locations. The study will focus on social-economic and land use data by studying the relationship between charging time and charging locations. Local factors affecting the charging time and the chargers’ utility will be investigated.

Keywords: electric vehicles, EV charging stations, social economic factors, charging networks

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17187 The Achievement Model of University Social Responsibility

Authors: Le Kang

Abstract:

On the research question of 'how to achieve USR', this contribution reflects the concept of university social responsibility, identify three achievement models of USR as the society - diversified model, the university-cooperation model, the government - compound model, also conduct a case study to explore characteristics of Chinese achievement model of USR. The contribution concludes with discussion of how the university, government and society balance demands and roles, make necessarily strategic adjustment and innovative approach to repair the shortcomings of each achievement model.

Keywords: modern university, USR, achievement model, compound model

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17186 Analyzing Electricity Demand Multipliers in the Malaysian Economy

Authors: Hussain Ali Bekhet, Tuan Ab Rashid Bin Tuan Abdullah, Tahira Yasmin

Abstract:

It is very important for electric utility to determine dominant sectors which have more impacts on electricity consumption in national economy system. The aim of this paper is to examine the electricity demand multipliers in Malaysia for (2005-2014) period. Malaysian Input-output tables, 2005 and 2010 are used. Besides, a new concept, electricity demand multiplier (EDM), is presented to identify key sectors imposing great impacts on electricity demand quantitatively. In order to testify the effectiveness of the Malaysian energy policies, it notes that there is fluctuation of the ranking sectors between 2005 and 2010. This could be reflected that there is efficiency with pace of development in Malaysia. This can be good indication for decision makers for designing future energy policies.

Keywords: input-output model, demand multipliers, electricity, key sectors, Malaysia

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17185 Optimum Locations for Intercity Bus Terminals with the AHP Approach: Case Study of the City of Esfahan

Authors: Mehrdad Arabi, Ehsan Beheshtitabar, Bahador Ghadirifaraz, Behrooz Forjanizadeh

Abstract:

Interaction between human, location and activity defines space. In the framework of these relations, space is a container for current specifications in relations of the 3 mentioned elements. The change of land utility considered with average performance range, urban regulations, society requirements etc. will provide welfare and comfort for citizens. From an engineering view it is fundamental that choosing a proper location for a specific civil activity requires evaluation of locations from different perspectives. The debate of desirable establishment of municipal service elements in urban regions is one of the most important issues related to urban planning. In this paper, the research type is applicable based on goal, and is descriptive and analytical based on nature. Initially existing terminals in Esfahan are surveyed and then new locations are presented based on evaluated criteria. In order to evaluate terminals based on the considered factors, an AHP model is used at first to estimate weight of different factors and then existing and suggested locations are evaluated using Arc GIS software and AHP model results. The results show that existing bus terminals are located in fairly proper locations. Further results of this study suggest new locations to establish terminals based on urban criteria.

Keywords: Arc GIS, Esfahan city, optimum locations, terminals

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17184 Criticality Assessment Model for Water Pipelines Using Fuzzy Analytical Network Process

Authors: A. Assad, T. Zayed

Abstract:

Water networks (WNs) are responsible of providing adequate amounts of safe, high quality, water to the public. As other critical infrastructure systems, WNs are subjected to deterioration which increases the number of breaks and leaks and lower water quality. In Canada, 35% of water assets require critical attention and there is a significant gap between the needed and the implemented investments. Thus, the need for efficient rehabilitation programs is becoming more urgent given the paradigm of aging infrastructure and tight budget. The first step towards developing such programs is to formulate a Performance Index that reflects the current condition of water assets along with its criticality. While numerous studies in the literature have focused on various aspects of condition assessment and reliability, limited efforts have investigated the criticality of such components. Critical water mains are those whose failure cause significant economic, environmental or social impacts on a community. Inclusion of criticality in computing the performance index will serve as a prioritizing tool for the optimum allocating of the available resources and budget. In this study, several social, economic, and environmental factors that dictate the criticality of a water pipelines have been elicited from analyzing the literature. Expert opinions were sought to provide pairwise comparisons of the importance of such factors. Subsequently, Fuzzy Logic along with Analytical Network Process (ANP) was utilized to calculate the weights of several criteria factors. Multi Attribute Utility Theories (MAUT) was then employed to integrate the aforementioned weights with the attribute values of several pipelines in Montreal WN. The result is a criticality index, 0-1, that quantifies the severity of the consequence of failure of each pipeline. A novel contribution of this approach is that it accounts for both the interdependency between criteria factors as well as the inherited uncertainties in calculating the criticality. The practical value of the current study is represented by the automated tool, Excel-MATLAB, which can be used by the utility managers and decision makers in planning for future maintenance and rehabilitation activities where high-level efficiency in use of materials and time resources is required.

Keywords: water networks, criticality assessment, asset management, fuzzy analytical network process

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17183 Assessment and Prediction of Vehicular Emissions in Commonwealth Avenue, Quezon City at Various Policy and Technology Scenarios Using Simple Interactive Model (SIM-Air)

Authors: Ria M. Caramoan, Analiza P. Rollon, Karl N. Vergel

Abstract:

The Simple Interactive Models for Better Air Quality (SIM-air) is an integrated approach model that allows the available information to support the integrated urban air quality management. This study utilized the vehicular air pollution information system module of SIM-air for the assessment of vehicular emissions in Commonwealth Avenue, Quezon City, Philippines. The main objective of the study is to assess and predict the contribution of different types of vehicles to the vehicular emissions in terms of PM₁₀, SOₓ, and NOₓ at different policy and technology scenarios. For the base year 2017, the results show vehicular emissions of 735.46 tons of PM₁₀, 108.90 tons of SOₓ, and 2,101.11 tons of NOₓ. Motorcycle is the major source of particulates contributing about 52% of the PM₁₀ emissions. Meanwhile, Public Utility Jeepneys contribute 27% of SOₓ emissions and private cars using gasoline contribute 39% of NOₓ emissions. Ambient air quality monitoring was also conducted in the study area for the standard parameters of PM₁₀, S0₂, and NO₂. Results show an average of 88.11 µg/Ncm, 47.41 µg/Ncm and 22.54 µg/Ncm for PM₁₀, N0₂, and SO₂, respectively, all were within the DENR National Ambient Air Quality Guideline Values. Future emissions of PM₁₀, NOₓ, and SOₓ are estimated at different scenarios. Results show that in the year 2030, PM₁₀ emissions will be increased by 186.2%. NOₓ emissions and SOₓ emissions will also be increased by 38.9% and 5.5%, without the implementation of the scenarios.

Keywords: ambient air quality, emissions inventory, mobile air pollution, vehicular emissions

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17182 Microscopic Simulation of Toll Plaza Safety and Operations

Authors: Bekir O. Bartin, Kaan Ozbay, Sandeep Mudigonda, Hong Yang

Abstract:

The use of microscopic traffic simulation in evaluating the operational and safety conditions at toll plazas is demonstrated. Two toll plazas in New Jersey are selected as case studies and were developed and validated in Paramics traffic simulation software. In order to simulate drivers’ lane selection behavior in Paramics, a utility-based lane selection approach is implemented in Paramics Application Programming Interface (API). For each vehicle approaching the toll plaza, a utility value is assigned to each toll lane by taking into account the factors that are likely to impact drivers’ lane selection behavior, such as approach lane, exit lane and queue lengths. The results demonstrate that similar operational conditions, such as lane-by-lane toll plaza traffic volume can be attained using this approach. In addition, assessment of safety at toll plazas is conducted via a surrogate safety measure. In particular, the crash index (CI), an improved surrogate measure of time-to-collision (TTC), which reflects the severity of a crash is used in the simulation analyses. The results indicate that the spatial and temporal frequency of observed crashes can be simulated using the proposed methodology. Further analyses can be conducted to evaluate and compare various different operational decisions and safety measures using microscopic simulation models.

Keywords: microscopic simulation, toll plaza, surrogate safety, application programming interface

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17181 Data-Driven Insights Into Juvenile Recidivism: Leveraging Machine Learning for Rehabilitation Strategies

Authors: Saiakhil Chilaka

Abstract:

Juvenile recidivism presents a significant challenge to the criminal justice system, impacting both the individuals involved and broader societal safety. This study aims to identify the key factors influencing recidivism and successful rehabilitation outcomes by utilizing a dataset of over 25,000 individuals from the NIJ Recidivism Challenge. We employed machine learning techniques, particularly Random Forest Classification, combined with SHAP (SHapley Additive exPlanations) for model interpretability. Our findings indicate that supervision risk score, percent days employed, and education level are critical factors affecting recidivism, with higher levels of supervision, successful employment, and education contributing to lower recidivism rates. Conversely, Gang Affiliation emerged as a significant risk factor for reoffending. The model achieved an accuracy of 68.8%, highlighting its utility in identifying high-risk individuals and informing targeted interventions. These results suggest that a comprehensive approach involving personalized supervision, vocational training, educational support, and anti-gang initiatives can significantly reduce recidivism and enhance rehabilitation outcomes for juveniles, providing critical insights for policymakers and juvenile justice practitioners.

Keywords: juvenile, justice system, data analysis, SHAP

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17180 Psychological Contract Violation and Occupational Stressors amongst UK Police Officers

Authors: Fazeelat Duran, Darren Bishopp, Jessica Woodhams

Abstract:

Psychological contract refers to the perceptions of an employee and their employer regarding their mutual obligations towards each other. The rationale for applying the psychological contract theory in UK policing was to investigate its impact on their wellbeing because the psychological contract is a useful tool in identifying factors having a negative effect on the wellbeing of employees. The paper will report on a study, which examined how occupational stressors and psychological contract violation may influence the wellbeing (e.g. Physical Stress and General Health) of a sample of police officers (N=127). The design of the study was cross-sectional and based on data collected through a self-report survey. The results of hierarchical regression analyses and structural equation model, suggest that occupational stressors and psychological contract violation play a critical role in both physical and psychological health. The implications of these findings and the utility of considering the psychological contract will be discussed.

Keywords: police officers, psychological contract, occupational stressors, wellbeing

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17179 The Meta–Evaluation of Master Degree Theses in Science Program of Evaluation Methodology, Srinakharinwirot University

Authors: Panwasn Mahalawalert

Abstract:

The objective of this study was to meta-evaluation of Master Degree theses in Science Program of Evaluation Methodology at Srinakharinwirot University, published during 2008-2011. This study was summative meta-evaluation that evaluated all theses of Master Degree in Science Program of Evaluation Methodology. Data were collected using the theses characteristics recording form and the evaluation meta-evaluation checklist. The collected data were analyzed by two parts: 1) Quantitative data were analyzed by descriptive statistics presented in frequency, percentages, mean, and standard deviation and 2) Qualitative data were analyzed by content analysis. The results of this study were found the theses characteristics was results revealed that most of theses were published in 2011. The largest group of theses researcher were female and were from the government office. The evaluation model of all theses were Decision-Oriented Evaluation Model. The objective of all theses were evaluate the project or curriculum. The most sampling technique were used the multistage random sampling technique. The most tool were used to gathering the data were questionnaires. All of the theses were analysed by descriptive statistics. The meta-evaluation results revealed that most of theses had fair on Utility Standards and Feasibility Standards, good on Propriety Standards and Accuracy Standards.

Keywords: meta-evaluation, evaluation, master degree theses, Srinakharinwirot University

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