Search results for: cluster model approach

Authors: Smriti, Ajeet Kumar

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We present a variant of the Irving-Kirkwood procedure to obtain the microscopic expressions of the cross-section averaged continuum fields such as internal force and moment in one-dimensional nanostructures in the non-equilibrium setting. In one-dimensional continuum theories for slender bodies, we deal with quantities such as mass, linear momentum, angular momentum, and strain energy densities, all defined per unit length. These quantities are obtained by integrating the corresponding pointwise (per unit volume) quantities over the cross-section of the slender body. However, no well-defined cross-section exists for these nanostructures at finite temperature. We thus define the cross-section of a nanorod to be an infinite plane which is fixed in space even when time progresses and defines the above continuum quantities by integrating the pointwise microscopic quantities over this infinite plane. The method yields explicit expressions of both the potential and kinetic parts of the above quantities. We further specialize in these expressions for helically repeating one-dimensional nanostructures in order to use them in molecular dynamics study of extension, torsion, and bending of such nanostructures. As, the Irving-Kirkwood procedure does not yield expressions of stiffnesses, we resort to a thermodynamic equilibrium approach to obtain the expressions of axial force, twisting moment, bending moment, and the associated stiffnesses by taking the first and second derivatives of the Helmholtz free energy with respect to conjugate strain measures. The equilibrium approach yields expressions independent of kinetic terms. We then establish the equivalence of the expressions obtained using the two approaches. The derived expressions are used to understand the extension, torsion, and bending of single-walled carbon nanotubes at non-zero temperatures.

Keywords: thermoelasticity, molecular dynamics, one dimensional nanostructures, nanotube buckling

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Authors: Chansheng He, Zhongfu Wang, Xiao Bai, Jie Tian, Xin Jin

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Heterogeneity of soil hydraulic properties directly affects hydrological processes at different scales. Understanding heterogeneity of soil hydraulic properties such as soil moisture is therefore essential for modeling watershed ecohydrological processes, particularly in hard to access, topographically complex mountainous watersheds. This study maps spatial variations of soil moisture by in situ observation network that consists of sampling points, zones, and tributaries, and monitors corresponding hydrological variables of air and soil temperatures, evapotranspiration, infiltration, and runoff in the Upper Reach of the Heihe River Watershed, a second largest inland river (terminal lake) with a drainage area of over 128,000 km² in Northwest China. Subsequently, the study uses a hydrological model, SWAT (Soil and Water Assessment Tool) to simulate the effects of heterogeneity of soil moisture on watershed hydrological processes. The spatial clustering method, Full-Order-CLK was employed to derive five soil heterogeneous zones (Configuration 97, 80, 65, 40, and 20) for soil input to SWAT. Results show the simulations by the SWAT model with the spatially clustered soil hydraulic information from the field sampling data had much better representation of the soil heterogeneity and more accurate performance than the model using the average soil property values for each soil type derived from the coarse soil datasets. Thus, incorporating detailed field sampling soil heterogeneity data greatly improves performance in hydrologic modeling.

Keywords: heterogeneity, soil moisture, SWAT, up-scaling

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Authors: Kumbharkhane Ashok

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The time domain dielectric relaxation spectroscopy (TDRS) probes the interaction of a macroscopic sample with a time-dependent electrical field. The resulting complex permittivity spectrum, characterizes amplitude (voltage) and time scale of the charge-density fluctuations within the sample. These fluctuations may arise from the reorientation of the permanent dipole moments of individual molecules or from the rotation of dipolar moieties in flexible molecules, like polymers. The time scale of these fluctuations depends on the sample and its relative relaxation mechanism. Relaxation times range from some picoseconds in low viscosity liquids to hours in glasses, Therefore the DRS technique covers an extensive dynamical process, its corresponding frequency range from 10-4 Hz to 1012 Hz. This inherent ability to monitor the cooperative motion of molecular ensemble distinguishes dielectric relaxation from methods like NMR or Raman spectroscopy which yield information on the motions of individual molecules. An experimental set up for Time Domain Reflectometry (TDR) technique from 10 MHz to 30 GHz has been developed for the aqueous solutions. This technique has been very simple and covers a wide band of frequencies in the single measurement. Dielectric Relaxation Spectroscopy is especially sensitive to intermolecular interactions. The complex permittivity spectra of aqueous solutions have been fitted using Cole-Davidson (CD) model to determine static dielectric constants and relaxation times for entire concentrations. The heterogeneous molecular interactions in aqueous solutions have been discussed through Kirkwood correlation factor and excess properties.

Keywords: liquid, aqueous solutions, time domain reflectometry

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Authors: Gonzalez Carlos, Martinez Fransisco

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The creation of a seismic prediction model that considers all the regional variations and perfectly adjusts its results to the response spectra is very complicated. To achieve statistically acceptable results, it is necessary to process a sufficiently robust data set, and even if high efficiencies are achieved, this model will only work properly in this region. However, when using it in other regions, differences are found due to different parameters that have not been calibrated to other regions, such as the site effect. The fact that impedance contrasts, as well as other factors belonging to the site, have a great influence on the local response is well known, which is why this work, using the residual method, is intended to establish a regional calibration of the corresponding parameters site effect for the Spain region in the global GMPM BSSA 14.

Keywords: GMPM, seismic prediction equations, residual method, response spectra, impedance contrast

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Authors: Mahsaossadat Pourrahmati Khelejan

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The purpose of this research was to identify and prioritize the sustainable development of sports venues using new and degradable energies with using the AHP Hierarchical Analysis approach. The research method is a descriptive strategy with regard to the direction of implementation and is a hierarchical research with a practical purpose. In this study, 30 experts (physical education faculty members, geography professors, accredited sports venues managers, and renewable energy engineers) were selected using purposeful sampling method as the research population. The research tool was a researcher-made questionnaire on the factors affecting the sustainable development of sports venues by using new technologies and degradable energy. Finally, the research questionnaire was designed with four components and 21 items. All steps were performed by using Expert Choice software. The importance of indicators that influence the sustainable development of sports venues is highlighted by the use of clean and degradable energy, for example: 1. Economic factor, weighing 0.420 2. Environmental index, weighing 0. 320 3. Physical index, weighing 0.148 4. Social index, weighing 0.122.

Keywords: Sports Venues, Sustainable Development, Degradable Energies, Prioritize

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Authors: Firas A. Al Laban, Mohamed Chabi, Sammani Danwawu Abdullahi

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There are a real needs to integrate types of Open Educational Resources (OER) with an intelligent system to extract information and knowledge in the semantic searching level. Those needs raised because most of current learning standard adopted web based learning and the e-learning systems does not always serve all educational goals. Semantic Web systems provide educators, students, and researchers with intelligent queries based on a semantic knowledge management learning system. An ontology-based learning system is an advanced system, where ontology plays the core of the semantic web in a smart learning environment. The objective of this paper is to discuss the potentials of ontologies and mapping different kinds of ontologies; heterogeneous or homogenous to manage and control different types of Open Educational Resources. The important contribution of this research is to approach a methodology uses logical rules and conceptual relations to map between ontologies of different educational resources. We expect from this methodology to establish for an intelligent educational system supporting student tutoring, self and lifelong learning system.

Keywords: knowledge management systems, ontologies, semantic web, open educational resources

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Authors: Mohamed Othmani, Yassine Khlifi

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This paper presents a technique for compact three dimensional (3D) object model reconstruction using wavelet networks. It consists to transform an input surface vertices into signals,and uses wavelet network parameters for signal approximations. To prove this, we use a wavelet network architecture founded on several mother wavelet families. POLYnomials WindOwed with Gaussians (POLYWOG) wavelet families are used to maximize the probability to select the best wavelets which ensure the good generalization of the network. To achieve a better reconstruction, the network is trained several iterations to optimize the wavelet network parameters until the error criterion is small enough. Experimental results will shown that our proposed technique can effectively reconstruct an irregular 3D object models when using the optimized wavelet network parameters. We will prove that an accurateness reconstruction depends on the best choice of the mother wavelets.

Keywords: 3d object, optimization, parametrization, polywog wavelets, reconstruction, wavelet networks

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Authors: Feng-Tsung Cheng, Shu-Li Wang, Mei-Fang Wu, , Hui-Yu Chuang

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Due to the rapid development of modern technology, the widespread usage of the Internet makes business environment changing quickly. In order to be a leader in the global competitive market and to pursuit survive, “changing” becomes an unspoken rules need to follow for the company survival. The purpose of this paper is to build change model by using SWOT, strategy map, and balance scorecard, KPI and change management theory. The research findings indicate that organizational change plan formulated by the case company should require the employee to resist change factors and performance management system issues into consideration and must be set organizational change related programs, such as performance appraisal reward system, consulting and counseling mechanisms programs to improve motivation and reduce staff negative emotions. Then according to the model revised strategy maps and performance indicators proposed in this paper, such as strategy maps add and modify corporate culture, improve internal processes management, increase the growth rate of net income and other strategies. The performance indicators are based on strategy maps new and modified by adding net income growth rate, to achieve target production rate, manpower training achievement rates and other indicators, through amendments to achieve the company’s goal, be a leading brand of precision machinery industry.

Keywords: organizational change, SWOT analysis, strategy maps, performance indicators

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Authors: Pongsatorn Tantrabundit, Lersak Phothong, Ong-art Chanprasitchai

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Due to the emergence of the Internet, it has extended the traditional Word-of-Mouth (WOM) to a new form called “Electronic Word-of-Mouth (eWOM).” Unlike traditional WOM, eWOM is able to present information in various ways by applying different components. Each eWOM component generates different effects on online consumer behavior. This research investigates the effects of Webcare (responding message) from product/ service providers on negative eWOM by applying two types of products (search and experience). The proposed conceptual model was developed based on the combination of the stages in consumer decision-making process, theory of reasoned action (TRA), theory of planned behavior (TPB), the technology acceptance model (TAM), the information integration theory and the elaboration likelihood model. The methodology techniques used in this study included multivariate analysis of variance (MANOVA) and multiple regression analysis. The results suggest that Webcare does slightly increase Thai online consumer’s perceptions on perceived eWOM trustworthiness, information diagnosticity and quality. For negative eWOM, we also found that perceived eWOM Trustworthiness, perceived eWOM diagnosticity and quality have a positive relationship with eWOM influence whereas perceived valence has a negative relationship with eWOM influence in Thai online consumers.

Keywords: consumer behavior, electronic word-of-mouth, online review, online word-of-mouth, Thai online consumer, webcare

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Authors: Taehan Lee

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We consider a network design problem which has shortest routing restriction based on the values determined by the installed facilities on each arc. In conventional multicommodity network design problem, a commodity can be routed through any possible path when the capacity is available. But, we consider a problem in which the commodity between two nodes must be routed on a path which has shortest metric value and the link metric value is determined by the installed facilities on the link. By this routing restriction, the problem has a distinct characteristic. We present an integer programming formulation containing the primal-dual optimality conditions to the shortest path routing. We give some computational results for the model.

Keywords: integer programming, multicommodity network design, routing, shortest path

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Authors: Salem Alsanusi, Loubna Bentaher

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Response Surface Methods (RSM) provide statistically validated predictive models that can then be manipulated for finding optimal process configurations. Variation transmitted to responses from poorly controlled process factors can be accounted for by the mathematical technique of propagation of error (POE), which facilitates ‘finding the flats’ on the surfaces generated by RSM. The dual response approach to RSM captures the standard deviation of the output as well as the average. It accounts for unknown sources of variation. Dual response plus propagation of error (POE) provides a more useful model of overall response variation. In our case, we implemented this technique in predicting compressive strength of concrete of 28 days in age. Since 28 days is quite time consuming, while it is important to ensure the quality control process. This paper investigates the potential of using design of experiments (DOE-RSM) to predict the compressive strength of concrete at 28th day. Data used for this study was carried out from experiment schemes at university of Benghazi, civil engineering department. A total of 114 sets of data were implemented. ACI mix design method was utilized for the mix design. No admixtures were used, only the main concrete mix constituents such as cement, coarse-aggregate, fine aggregate and water were utilized in all mixes. Different mix proportions of the ingredients and different water cement ratio were used. The proposed mathematical models are capable of predicting the required concrete compressive strength of concrete from early ages.

Keywords: mix proportioning, response surface methodology, compressive strength, optimal design

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Authors: Durga Toshniwal, Lokesh Agrawal

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As the web continues to play an increasing role in information exchange, and conducting daily activities, computer users have become the target of miscreants which infects hosts with malware or adware for financial gains. Unfortunately, even a single visit to compromised web site enables the attacker to detect vulnerabilities in the user’s applications and force the downloading of multitude of malware binaries. We provide an approach to effectively scan the so-called drive-by downloads on the Internet. Drive-by downloads are result of URLs that attempt to exploit their visitors and cause malware to be installed and run automatically. To scan the web for malicious pages, the first step is to use a crawler to collect URLs that live on the Internet, and then to apply fast prefiltering techniques to reduce the amount of pages that are needed to be examined by precise, but slower, analysis tools (such as honey clients or antivirus programs). Although the technique is effective, it requires a substantial amount of resources. A main reason is that the crawler encounters many pages on the web that are legitimate and needs to be filtered. In this paper, to characterize the nature of this rising threat, we present implementation of a web crawler on Python, an approach to search the web more efficiently for pages that are likely to be malicious, filtering benign pages and passing remaining pages to antivirus program for detection of malwares. Our approaches starts from an initial seed of known, malicious web pages. Using these seeds, our system generates search engines queries to identify other malicious pages that are similar to the ones in the initial seed. By doing so, it leverages the crawling infrastructure of search engines to retrieve URLs that are much more likely to be malicious than a random page on the web. The results shows that this guided approach is able to identify malicious web pages more efficiently when compared to random crawling-based approaches.

Keywords: web crawler, malwares, seeds, drive-by-downloads, security

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Authors: Michael Tilahun Mulugeta

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Pedestrians are the most vulnerable road users as they are more exposed to the risk of collusion. Pedestrian safety at road intersections still remains the most vital and yet unsolved issue in Addis Ababa, Ethiopia. One of the critical points in pedestrian safety is the occurrence of conflict between turning vehicle and pedestrians at un-signalized intersection. However, a better understanding of the factors that affect the likelihood of the conflicts would help provide direction for countermeasures aimed at reducing the number of crashes. This paper has sorted to explore a model to describe the relation between traffic conflicts and influencing factors using Multiple Linear regression methodology. In this research the main focus is to study the interaction of turning (left & right) vehicle with pedestrian at unsignalized intersections. The specific objectives also to determine factors that affect the number of potential conflicts and develop a model of potential conflict.

Keywords: potential, regression analysis, pedestrian, conflicts

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Authors: Chen Xi, Lao Xuerui, Li Junjie, Jiang Yike, Wang Hanwei, Zeng Zihao

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To further promote the development of smart cities, the microscopic "nerve endings" of the City Intelligent Model (CIM) are extended to be more sensitive. In this paper, we develop a pedestrian trajectory twin terminal based on the CIM and CNN technology. It also uses 5G networks, architectural and geoinformatics technologies, convolutional neural networks, combined with deep learning networks for human behaviour recognition models, to provide empirical data such as 'pedestrian flow data and human behavioural characteristics data', and ultimately form spatial performance evaluation criteria and spatial performance warning systems, to make the empirical data accurate and intelligent for prediction and decision making.

Keywords: urban planning, urban governance, CIM, artificial intelligence, convolutional neural network

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Authors: Marziyeh Khavari

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In recent decades, climate change, global warming, and the growing population worldwide face some challenges, such as increasing food consumption and shortage of resources. Assessing how climate change could disturb crops, especially hazelnut production, seems crucial for sustainable agriculture production. For hazelnut cultivation in the mid-warm condition, such as in Iran, here we present an investigation of climate parameters and how much they are effective on fertility and nut production of hazelnut trees. Therefore, the climate change of the northern zones in Iran has investigated (1960-2017) and was reached an uptrend in temperature. Furthermore, the descriptive analysis performed on six cultivars during seven years shows how this small-scale survey could demonstrate the effects of climate change on hazelnut production and stability. Results showed that some climate parameters are more significant on nut production, such as solar radiation, soil temperature, relative humidity, and precipitation. Moreover, some cultivars have produced more stable production, for instance, Negret and Segorbe, while the Mervill de Boliver recorded the most variation during the study. Another aspect that needs to be met is training and predicting an actual model to simulate nut production through a neural network and linear regression simulation. The study developed and estimated the ANN model's generalization capability with different criteria such as RMSE, SSE, and accuracy factors for dependent and independent variables (environmental and yield traits). The models were trained and tested while the accuracy of the model is proper to predict hazelnut production under fluctuations in weather parameters.

Keywords: climate change, neural network, hazelnut, global warming

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Authors: Didiosky Benítez-Erice, Frederik Questier, Dalgys Pérez-Luján

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This paper aims to present two models around the production of students’ experiential knowledge in the teaching-learning process of higher education: the teacher-centered production model and the student-centered production model. From a range of knowledge management and experiential learning theories, the paper elaborates into the nature of students’ experiential knowledge and proposes further adjustments of existing second-generation knowledge management theories taking into account the particularities of higher education. Despite its theoretical nature the paper can be relevant for future studies that stress student-driven improvement and innovation at higher education institutions.

Keywords: experiential knowledge, higher education, knowledge management, teaching-learning process

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Authors: Helen S. Ghali, Engy Serag, A. Samer Ezeldin

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In many countries, the construction industry relies heavily on outsourcing models in executing their projects and expanding their businesses to fit in the diverse market. Such extensive integration of subcontractors is becoming an influential factor in contractor’s cash flow management. Accordingly, subcontractors’ financial terms are important phenomena and pivotal components for the well-being of the contractor’s cash flow. The aim of this research is to study the contractor’s cash flow with respect to the owner and subcontractor’s payment management plans, considering variable advance payment, payment frequency, and lag and retention policies. The model is developed to provide contractors with a decision support tool that can assist in selecting the optimum subcontracting plan to minimize the contractor’s financing limits and optimize the profit values. The model is built using Microsoft Excel VBA coding, and the genetic algorithm is utilized as the optimization tool. Three objective functions are investigated, which are minimizing the highest negative overdraft value, minimizing the net present worth of overdraft, and maximizing the project net profit. The model is validated on a full-scale project which includes both self-performed and subcontracted work packages. The results show potential outputs in optimizing the contractor’s negative cash flow values and, in the meantime, assisting contractors in selecting suitable subcontractors to achieve the objective function.

Keywords: cash flow optimization, payment plan, procurement management, subcontracting plan

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Authors: Gulnara Moldasheva

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The research explores the relationship between management responsibility and corporate governance of listed companies in Kazakhstan. This research employs firm level data of randomly selected listed non-financial firms and firm level data “operational” financial sector, consisted from banking sector, insurance companies and accumulated pension funds using multivariate regression analysis under fixed effect model approach. Ownership structure includes institutional ownership, managerial ownership and private investor’s ownership. Management responsibility of the firm is expressed by the decision of the firm on amount of leverage. Results of the cross sectional panel study for non-financial firms showed that only institutional shareholding is significantly negatively correlated with debt to equity ratio. Findings from “operational” financial sector show that leverage is significantly affected only by the CEO/Chair duality and the size of financial institutions, and insignificantly affected by ownership structure. Also, the findings show, that there is a significant negative relationship between profitability and the debt to equity ratio for non-financial firms, which is consistent with pecking order theory. Generally, the found results suggest that corporate governance and a management responsibility play important role in corporate performance of listed firms in Kazakhstan.

Keywords: ownership, corporate governance, debt to equity ratio, corporate performance

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Authors: Anastasia K. Eleftheriadou, Athanasios Sfetsos, Nikolaos Gounaris

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The present work examines the suitability of a seasonal forecasting model downscaled with a very high spatial resolution in order to assess the energy performance and requirements of buildings. The application of the developed model is applied on Greece for a period and with a forecast horizon of 5 months in the future. Greece, as a country in the middle of a financial crisis and facing serious societal challenges, is also very sensitive to climate changes. The commonly used method for the correlation of climate change with the buildings energy consumption is the concept of Degree Days (DD). This method can be applied to heating and cooling systems for a better management of environmental, economic and energy crisis, and can be used as medium (3-6 months) planning tools in order to predict the building needs and country’s requirements for residential energy use.

Keywords: downscaled seasonal models, degree days, energy performance

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Authors: Lourenco Camnahas, Eileen Willis, Greg Fisher, Jessie Gunson, Pascale Dettwiller, Charlene Thornton

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Stock-out of pharmaceuticals is a common issue at all level of health services in Timor-Leste, a small post-conflict country. This lead to the research questions: what are the current methods used to quantify pharmaceutical supplies; what factors contribute to the on-going pharmaceutical stock-out? The study examined factors that influence the pharmaceutical supply chain system. Methodology: Privett and Goncalvez dependency model has been adopted for the design of the qualitative interviews. The model examines pharmaceutical supply chain management at three management levels: management of individual pharmaceutical items, health facilities, and health systems. The interviews were conducted in order to collect information on inventory management, logistics management information system (LMIS) and the provision of pharmaceuticals. Andersen' behavioural model for healthcare utilization also informed the interview schedule, specifically factors linked to environment (healthcare system and external environment) and the population (enabling factors). Forty health professionals (bureaucrats, clinicians) and six senior officers from a United Nations Agency, a global multilateral agency and a local non-governmental organization were interviewed on their perceptions of factors (healthcare system/supply chain and wider environment) impacting on stock out. Additionally, policy documents for the entire healthcare system, along with population data were collected. Findings: An analysis using Pozzebon’s critical interpretation identified a range of difficulties within the system from poor coordination to failure to adhere to policy guidelines along with major difficulties with inventory management, quantification, forecasting, and budgetary constraints. Weak logistics management information system, lack of capacity in inventory management, monitoring and supervision are additional organizational factors that also contributed to the issue. There were various methods of quantification of pharmaceuticals applied in the government sector, and non-governmental organizations. Lack of reliable data is one of the major problems in the pharmaceutical provision. Global Fund has the best quantification methods fed by consumption data and malaria cases. There are other issues that worsen stock-out: political intervention, work ethic and basic infrastructure such as unreliable internet connectivity. Major issues impacting on pharmaceutical quantification have been identified. However, current data collection identified limitations within the Andersen model; specifically, a failure to take account of predictors in the healthcare system and the environment (culture/politics/social. The next step is to (a) compare models used by three non-governmental agencies with the government model; (b) to run the Andersen explanatory model for pharmaceutical expenditure for 2 to 5 drug items used by these three development partners in order to see how it correlates with the present model in terms of quantification and forecasting the needs; (c) to repeat objectives (a) and (b) using the government model; (d) to draw a conclusion about the strength.

Keywords: inventory management, pharmaceutical forecasting and quantification, pharmaceutical stock-out, pharmaceutical supply chain management

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Authors: Abimbola M. Enitan, J. Adeyemo

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Anaerobic modeling is a useful tool to describe and simulate the condition and behaviour of anaerobic treatment units for better effluent quality and biogas generation. The present investigation deals with the anaerobic treatment of brewery wastewater with varying organic loads. The chemical oxygen demand (COD) and total suspended solids (TSS) of the influent and effluent of the bioreactor were determined at various retention times to generate data for kinetic coefficients. The bio-kinetic coefficients in the modified Stover–Kincannon kinetic and methane generation models were determined to study the performance of anaerobic digestion process. At steady-state, the determination of the kinetic coefficient (K), the endogenous decay coefficient (Kd), the maximum growth rate of microorganisms (µmax), the growth yield coefficient (Y), ultimate methane yield (Bo), maximum utilization rate constant Umax and the saturation constant (KB) in the model were calculated to be 0.046 g/g COD, 0.083 (dˉ¹), 0.117 (d-¹), 0.357 g/g, 0.516 (L CH4/gCODadded), 18.51 (g/L/day) and 13.64 (g/L/day) respectively. The outcome of this study will help in simulation of anaerobic model to predict usable methane and good effluent quality during the treatment of industrial wastewater. Thus, this will protect the environment, conserve natural resources, saves time and reduce cost incur by the industries for the discharge of untreated or partially treated wastewater. It will also contribute to a sustainable long-term clean development mechanism for the optimization of the methane produced from anaerobic degradation of waste in a close system.

Keywords: brewery wastewater, methane generation model, environment, anaerobic modeling

Procedia PDF Downloads 240

Authors: Roberto M. G. Velásquez, Jonas R. Gazoli, Nelson Ponce Jr, Valério L. Borges, Alessandro Sete, Fernanda M. C. Tomé, Julian D. Hunt, Heitor C. Lira, Cristiano L. de Souza, Fabio T. Bindemann, Wilmar Wounnsoscky

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Nowadays, society is working toward reducing energy losses and greenhouse gas emissions, as well as seeking clean energy sources, as a result of the constant increase in energy demand and emissions. Energy loss occurs in the gas pressure reduction stations at the delivery points in natural gas distribution systems (city gates). Installing pressure reduction turbines (PRT) parallel to the static reduction valves at the city gates enhances the energy efficiency of the system by recovering the enthalpy of the pressurized natural gas, obtaining in the pressure-lowering process shaft work and generating electrical power. Currently, the Brazilian natural gas transportation network has 9,409 km in extension, while the system has 16 national and 3 international natural gas processing plants, including more than 143 delivery points to final consumers. Thus, the potential of installing PRT in Brazil is 66 MW of power, which could yearly avoid the emission of 235,800 tons of CO2 and generate 333 GWh/year of electricity. On the other hand, an economic viability analysis of these energy efficiency projects is commonly carried out based on estimates of the project's cash flow obtained from several variables forecast. Usually, the cash flow analysis is performed using representative values of these variables, obtaining a deterministic set of financial indicators associated with the project. However, in most cases, these variables cannot be predicted with sufficient accuracy, resulting in the need to consider, to a greater or lesser degree, the risk associated with the calculated financial return. This paper presents an approach applied to the technical-economic viability analysis of PRTs projects that explicitly considers the uncertainties associated with the input parameters for the financial model, such as gas pressure at the delivery point, amount of energy generated by TRP, the future price of energy, among others, using sensitivity analysis techniques, scenario analysis, and Monte Carlo methods. In the latter case, estimates of several financial risk indicators, as well as their empirical probability distributions, can be obtained. This is a methodology for the financial risk analysis of PRT projects. The results of this paper allow a more accurate assessment of the potential PRT project's financial feasibility in Brazil. This methodology will be tested at the Cuiabá thermoelectric plant, located in the state of Mato Grosso, Brazil, and can be applied to study the potential in other countries.

Keywords: pressure reduction turbine, natural gas pressure drop station, energy efficiency, electricity generation, monte carlo methods

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Authors: Sitaram Dahal

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Sustainable Development, a universal need for the present generation and the future generation, is an accepted way to assure intra and inter-generational equity. International movements like Rio Earth Summit 1992, Stockholm Conference 1972, Kyoto Protocol, Sustainable Development Goals (SDGs) proclaim the need of sustainable globe. The socio- economic disparity prevailing in the society shows that the indigenous peoples are living life far below poverty line. These indigenous people, aboriginal social groups sharing common cultural values and with a unique identity, are away from development being merely focused on the growth. Though studies suggest that most of the indigenous practices are often environment-friendly, alert about the plunging trend of the practices. This study explores the trend of intergenerational transmission of indigenous profession of pottery making of Kumal community (Meghauli Village Development Committee of Chitwan district) and factors affecting the trend. The SD indicators - contribution of IP to well-being of pottery makers had been query in the study. The study reveals that the pottery making profession can stand sustainable in terms of environment and socio-economic capital compared to modern technologies. However, the number of practitioners has been decreasing and youths hardly show interest to continue their indigenous profession. The new generations are not in a stage of accepting pottery in complete profession, that challenges the social and cultural sustainability of the profession. Indigenous profession demand people investments over modern technology and innovations. The relative investment of human labour is dramatically high with the indigenous profession. In addition, the fashion and innovations of market rule challenge the sustainability of the pottery making profession. The practice is limited to small cluster as a show piece at present. The study illustrates the market driven unsustainability of indigenous profession of Kumal community.

Keywords: professional unsustainability, pottery making, Kumal Community, Indigenous Professoin

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Authors: Samar M. Alqhtani, Suhuai Luo, Brian Regan

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Data fusion technology can be the best way to extract useful information from multiple sources of data. It has been widely applied in various applications. This paper presents a data fusion approach in multimedia data for event detection in twitter by using Dempster-Shafer evidence theory. The methodology applies a mining algorithm to detect the event. There are two types of data in the fusion. The first is features extracted from text by using the bag-ofwords method which is calculated using the term frequency-inverse document frequency (TF-IDF). The second is the visual features extracted by applying scale-invariant feature transform (SIFT). The Dempster - Shafer theory of evidence is applied in order to fuse the information from these two sources. Our experiments have indicated that comparing to the approaches using individual data source, the proposed data fusion approach can increase the prediction accuracy for event detection. The experimental result showed that the proposed method achieved a high accuracy of 0.97, comparing with 0.93 with texts only, and 0.86 with images only.

Keywords: data fusion, Dempster-Shafer theory, data mining, event detection

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Authors: David Gottlieb, Jason Yoder

Abstract:

The feeling of loneliness is not uncommon in modern society, and yet, there is a fundamental lack of understanding in its origins and purpose in nature. One interpretation of loneliness is that it is a subjective experience that punishes a lack of social behavior, and thus its emergence in human evolution is seemingly tied to the survival of early human tribes. Still, a common counterintuitive response to loneliness is a state of hypervigilance, resulting in social withdrawal, which may appear maladaptive to modern society. So far, no computational model of loneliness’ effect during evolution yet exists; however, agent-based models (ABM) can be used to investigate social behavior, and applying evolution to agents’ behaviors can demonstrate selective advantages for particular behaviors. We propose an ABM where each agent contains four social behaviors, and one goal-seeking behavior, letting evolution select the best behavioral patterns for resource allocation. In our paper, we use an algorithm similar to the boid model to guide the behavior of agents, but expand the set of rules that govern their behavior. While we use cohesion, separation, and alignment for simple social movement, our expanded model adds goal-oriented behavior, which is inspired by particle swarm optimization, such that agents move relative to their personal best position. Since agents are given the ability to form connections by interacting with each other, our final behavior guides agent movement toward its social connections. Finally, we introduce a mechanism to represent a state of loneliness, which engages when an agent's perceived social involvement does not meet its expected social involvement. This enables us to investigate a minimal model of loneliness, and using evolution we attempt to elucidate its value in human survival. Agents are placed in an environment in which they must acquire resources, as their fitness is based on the total resource collected. With these rules in place, we are able to run evolution under various conditions, including resource-rich environments, and when disease is present. Our simulations indicate that there is strong selection pressure for social behavior under circumstances where there is a clear discrepancy between initial resource locations, and against social behavior when disease is present, mirroring hypervigilance. This not only provides an explanation for the emergence of loneliness, but also reflects the diversity of response to loneliness in the real world. In addition, there is evidence of a richness of social behavior when loneliness was present. By introducing just two resource locations, we observed a divergence in social motivation after agents became lonely, where one agent learned to move to the other, who was in a better resource position. The results and ongoing work from this project show that it is possible to glean insight into the evolutionary advantages of even simple mechanisms of loneliness. The model we developed has produced unexpected results and has led to more questions, such as the impact loneliness would have at a larger scale, or the effect of creating a set of rules governing interaction beyond adjacency.

Keywords: agent-based, behavior, evolution, loneliness, social

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Authors: Jean Marie Tshimula, Atsushi Togashi

Abstract:

We develop a data-science approach for providing an interactive visualization and predictive models to find insights into the projects' historical data in order for stakeholders understand some unseen opportunities in the African market that might escape them behind the online project portfolio of the African Development Bank. This machine learning-based web application identifies the market trend of the fastest growing economies across the continent as well skyrocketing sectors which have a significant impact on the future of business in Africa. Owing to this, the approach is tailored to predict where the investment needs are the most required. Moreover, we create a corpus that includes the descriptions of over more than 1,200 projects that approximately cover 14 sectors designed for some of 53 African countries. Then, we sift out this large amount of semi-structured data for extracting tiny details susceptible to contain some directions to follow. In the light of the foregoing, we have applied the combination of Latent Dirichlet Allocation and Random Forests at the level of the analysis module of our methodology to highlight the most relevant topics that investors may focus on for investing in Africa.

Keywords: machine learning, topic modeling, natural language processing, big data

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Authors: Intan Maisarah Abd Rahim, Herlina Abdul Rahim, Rashidah Ghazali

Abstract:

Diabetes is a medical condition that can lead to various diseases such as stroke, heart disease, blindness and obesity. In clinical practice, the concern of the diabetic patients towards the blood glucose examination is rather alarming as some of the individual describing it as something painful with pinprick and pinch. As for some patient with high level of glucose level, pricking the fingers multiple times a day with the conventional glucose meter for close monitoring can be tiresome, time consuming and painful. With these concerns, several non-invasive techniques were used by researchers in measuring the glucose level in blood, including ultrasonic sensor implementation, multisensory systems, absorbance of transmittance, bio-impedance, voltage intensity, and thermography. This paper is discussing the application of the near-infrared (NIR) spectroscopy as a non-invasive method in measuring the glucose level and the implementation of the linear system identification model in predicting the output data for the NIR measurement. In this study, the wavelengths considered are at the 1450 nm and 1950 nm. Both of these wavelengths showed the most reliable information on the glucose presence in blood. Then, the linear Autoregressive Moving Average Exogenous model (ARMAX) model with both un-regularized and regularized methods was implemented in predicting the output result for the NIR measurement in order to investigate the practicality of the linear system in this study. However, the result showed only 50.11% accuracy obtained from the system which is far from the satisfying results that should be obtained.

Keywords: diabetes, glucose level, linear, near-infrared, non-invasive, prediction system

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Authors: Virakti Dhaval Shah

Abstract:

Advances in technology and the changes in lifestyle and work expectations amid the COVID-19 pandemic are requiring changes to vocational assessment, provision of vocational training, and identification of job matches for individuals with intellectual disability. Vocational assessment involves the assessment of interests, skills, abilities, and strengths/weaknesses, as well as a detailed understanding of healthcare, familial, social, community, workplace-related and policy-level protective and risk factors impacting the individual. In India, vocational assessment procedures such as interviews play a major role in vocational placement today. Unfortunately, many of the most widely used vocational assessment instruments in India were developed in the 1970s to 2000s and have not been revised since. Hence, there is a dire need to update existing tools and prepare a structured approach for vocational service providers to meet the unique employment needs of individuals with intellectual disabilities. To address this need, this project designed a multi-domain assessment toolkit for a structured approach to vocational assessment, training, and job placement for individuals with intellectual disabilities in India. Methods included conducting an empirical review of the available tools currently in use in India for the vocational assessment of persons with intellectual disabilities. Domains addressed in the instrument review were organized into a structured system, and additional items related to contemporary technology, pandemic-related experiences of persons with disabilities, and changes in lifestyle and work expectations due to the pandemic were added. Items assessing behaviors, provision of vocational training, and identification of job matches for individuals with intellectual disabilities were developed. The proposed tool has the potential to benefit organizations working with and preparing individuals with intellectual disabilities to find successful employment by undertaking a structured approach to vocational assessment, rehabilitation, training, and placement. It can be particularly useful for guiding new professionals doing vocational rehabilitation in India.

Keywords: intellectual disability, rehabilitation, vocational assessment, vocational rehabilitation

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Authors: Han-Taw Chen, Chung-Hou Lai, Tzu-Hsiang Lin, Ge-Jang He

Abstract:

This study applies the inverse method and three-dimensional CFD commercial software in conjunction with the experimental temperature data to investigate the heat transfer and fluid flow characteristics of the plate-fin heat sink in a closed rectangular enclosure for various values of fin height. The inverse method with the finite difference method and the experimental temperature data is applied to determine the heat transfer coefficient. The k-ε turbulence model is used to obtain the heat transfer and fluid flow characteristics within the fins. To validate the accuracy of the results obtained, the comparison of the average heat transfer coefficient is made. The calculated temperature at selected measurement locations on the plate-fin is also compared with experimental data.

Keywords: inverse method, FLUENT, k-ε model, heat transfer characteristics, plate-fin heat sink

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Authors: H. Daaou Nedjari, O. Guerri, M. Saighi

Abstract:

A numerical study was conducted to optimize the positioning of wind turbines over complex terrains. Thus, a two-dimensional disk model was used to calculate the flow velocity deficit in wind farms for both flat and complex configurations. The wind turbine wake was assessed using the hybrid methods that combine CFD (Computational Fluid Dynamics) with the actuator disc model. The wind turbine rotor has been defined with a thrust force, coupled with the Navier-Stokes equations that were resolved by an open source computational code (Code_Saturne V3.0 developed by EDF) The simulations were conducted in atmospheric boundary layer condition considering a two-dimensional region located at the north of Algeria at 36.74°N longitude, 02.97°E latitude. The topography elevation values were collected according to a longitudinal direction of 1km downwind. The wind turbine sited over topography was simulated for different elevation variations. The main of this study is to determine the topography effect on the behavior of wind farm wake flow. For this, the wake model applied in complex terrain needs to selects the singularity effects of topography on the vertical wind flow without rotor disc first. This step allows to determine the existence of mixing scales and friction forces zone near the ground. So, according to the ground relief the wind flow waS disturbed by turbulence and a significant speed variation. Thus, the singularities of the velocity field were thoroughly collected and thrust coefficient Ct was calculated using the specific speed. In addition, to evaluate the land effect on the wake shape, the flow field was also simulated considering different rotor hub heights. Indeed, the distance between the ground and the hub height of turbine (Hhub) was tested in a flat terrain for different locations as Hhub=1.125D, Hhub = 1.5D and Hhub=2D (D is rotor diameter) considering a roughness value of z0=0.01m. This study has demonstrated that topographical farm induce a significant effect on wind turbines wakes, compared to that on flat terrain.

Keywords: CFD, wind turbine wake, k-epsilon model, turbulence, complex topography

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