Search results for: adaptive thermal comfort model

Authors: A. Shoiynbek, K. Kozhakhmet, P. Menezes, D. Kuanyshbay, D. Bayazitov

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Speech emotion recognition has received increasing research interest all through current years. There was used emotional speech that was collected under controlled conditions in most research work. Actors imitating and artificially producing emotions in front of a microphone noted those records. There are four issues related to that approach, namely, (1) emotions are not natural, and it means that machines are learning to recognize fake emotions. (2) Emotions are very limited by quantity and poor in their variety of speaking. (3) There is language dependency on SER. (4) Consequently, each time when researchers want to start work with SER, they need to find a good emotional database on their language. In this paper, we propose the approach to create an automatic tool for speech emotion extraction based on facial emotion recognition and describe the sequence of actions of the proposed approach. One of the first objectives of the sequence of actions is a speech detection issue. The paper gives a detailed description of the speech detection model based on a fully connected deep neural network for Kazakh and Russian languages. Despite the high results in speech detection for Kazakh and Russian, the described process is suitable for any language. To illustrate the working capacity of the developed model, we have performed an analysis of speech detection and extraction from real tasks.

Keywords: deep neural networks, speech detection, speech emotion recognition, Mel-frequency cepstrum coefficients, collecting speech emotion corpus, collecting speech emotion dataset, Kazakh speech dataset

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Authors: Djalal Hamed

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The aim of this paper is to perform an analytic solution of steady state natural convection in a narrow rectangular channel between two vertical parallel MTR-type fuel plates, imposed under a cosine shape heat flux to determine the margin of the nuclear core power at which the natural convection cooling mode can ensure a safe core cooling, where the cladding temperature should not be reach the specific safety limits (90 °C). For this purpose, a simple computer program is developed to determine the principal parameter related to the nuclear core safety such as the temperature distribution in the fuel plate and in the coolant (light water) as a function of the reactor power. Our results are validated throughout a comparison against the results of another published work, which is considered like a reference of this study.

Keywords: buoyancy force, friction force, natural convection, thermal hydraulic analysis, vertical heated rectangular channel

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Authors: Balwinder Singh

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The present research is a paper on the characterization of aluminum alloy-6063 hybrid metal matrix composites using three different reinforcement materials (SiC, red mud, and fly ash) through stir casting method. The red mud was used in solid form, and particle size range varies between 103-150 µm. During this investigation, fly ash is received from Guru Nanak Dev Thermal Plant (GNDTP), Bathinda. The study has been done by using Taguchi’s L9 orthogonal array by taking fraction wt.% (SiC 5%, 7.5%, and 10% and Red Mud and Fly Ash 2%, 4%, and 6%) as input parameters with their respective levels. The study of the mechanical properties (tensile strength, impact strength, and microhardness) has been done by using Analysis of Variance (ANOVA) with the help of MINITAB 17 software. It is revealed that silicon carbide is the most significant parameter followed by red mud and fly ash affecting the mechanical properties, respectively. The fractured surface morphology of the composites using Field Emission Scanning Electron Microscope (FESEM) shows that there is a good mixing of reinforcement particles in the matrix. Energy-dispersive X-ray spectroscopy (EDS) was performed to know the presence of the phases of the reinforced material.

Keywords: reinforcement, silicon carbide, fly ash, red mud

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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: 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

Procedia PDF Downloads 127

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: Vicente Espinola, Luis Torres, Christhian Gonzalez

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Entrepreneurship is a topic of current interest in Mexico and the World, which has been fostered through public policies with great impact on its generation. The strategies used in Mexico have not been successful, being motivational strategies aimed at the masses with the intention that someone in the process generates a venture. The strategies used for its development have been "picking of winners" favoring those who have already overcome the initial stages of undertaking without effective support. This situation shows a disarticulation that appears even more in social entrepreneurship; due to this, it is relevant to research on those elements that could develop them and thus integrate a model of entrepreneurship and social innovation for Mexico. Social entrepreneurship should be generating social innovation, which is translated into business models in order to make the benefits reach the population. These models are proposed putting the social impact before the economic impact, without forgetting its sustainability in the medium and long term. In this work, we present a simple model of innovation and social entrepreneurship for Guanajuato, Mexico. This algorithm was based on how social innovation could be generated in a systemic way for Mexico through different institutions that promote innovation. In this case, the technological parks of the state of Guanajuato were studied because these are considered one of the areas of Mexico where its main objectives are to make technology transfer to companies but overlooking the social sector and entrepreneurs. An experimental design of n = 60 was carried out with potential entrepreneurs to identify their perception of the social approach that the enterprises should have, the skills they consider required to create a venture, as well as their interest in generating ventures that solve social problems. This experiment had a 2K design, the value of k = 3 and the computational simulation was performed in R statistical language. A simple model of interconnected variables is proposed, which allows us to identify where it is necessary to increase efforts for the generation of social enterprises. The 96.67% of potential entrepreneurs expressed interest in ventures that solve social problems. In the analysis of the variables interaction, it was identified that the isolated development of entrepreneurial skills would only replicate the generation of traditional ventures. The variable of social approach presented positive interactions, which may influence the generation of social entrepreneurship if this variable was strengthened and permeated in the processes of training and development of entrepreneurs. In the future, it will be necessary to analyze the institutional actors that are present in the social entrepreneurship ecosystem, in order to analyze the interaction necessary to strengt the innovation and social entrepreneurship ecosystem.

Keywords: social innovation, model, entrepreneurship, technological parks

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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: Ying Xin, Shigeki Kametani

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This paper deals the energy saving performance of GHP (Gas engine heat pump) air conditioning system has improved with time-series variation. There are two types of air conditioning systems, VRF (Variable refrigerant flow) and central cooling and heating system. VRF is classified as EHP (Electric driven heat pump) and GHP. EHP drives the compressor with electric motor. GHP drives the compressor with the gas engine. The electric consumption of GHP is less than one tenth of EHP does. In this study, the energy consumption data of GHP installed the junior high schools was collected. An annual and monthly energy consumption per rated thermal output power of each apparatus was calculated, and then their energy efficiency was analyzed. From these data, we investigated improvement of the energy saving of the GHP air conditioning system by the change in the generation.

Keywords: energy-saving, variable refrigerant flow, gas engine heat pump, electric driven heat pump, air conditioning system

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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

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Authors: Youn-Hwan Kim, Jae-Won Moon, Hae-Joong Kim

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This paper introduces the study on the method of accelerated life test to electrical rotating system. In recent years, as well as efficiency for motors and generators, there is a growing need for research on the life expectancy. It is considered impossible to calculate the acceleration coefficient by increasing the rotational load or temperature load as the acceleration stress in the motor system because the temperature of the copper exceeds the wire thermal class rating. In this paper, the accelerated life test methods of the electrical rotating system are classified according to the application. This paper describes the development of the test procedure for the highly accelerated life test (HALT) of the 100kW permanent magnet synchronous motor (PMSM) of electric vehicle. Finally, it explains how to select acceleration load for vibration, temperature, bearing load, etc. for accelerated life test.

Keywords: acceleration coefficient, electric vehicle motor, HALT, life expectancy, vibration

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Authors: David Gottlieb, Jason Yoder

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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: V. Ravindra, P. A. Saikiran, M. Ramgopal

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This paper presents an energy analysis of a solar assisted trigeneration system using an Ejector for dairy applications. The working fluid in the trigeneration loop is Supercritical CO₂. The trigeneration system is a combination of Brayton cycle and ejector based vapor compression refrigeration cycle. The heating and cooling outputs are used for simultaneous pasteurization and chilling of the milk. The electrical power is used to drive the auxiliary equipment in the dairy plant. A numerical simulation is done with Engineering Equation Solver (EES), and a parametric analysis is performed by varying the operating variables over a meaningful range. The results show that the overall performance index decreases with increase in ambient temperature. For an ejector based system, the compressor work and cooling output are significant output quantities. An increase in total mass flow rate of the refrigerant (primary + secondary) results in an increase in the compressor work and cooling output.

Keywords: trigeneration, solar thermal, supercritical CO₂, ejector

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

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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: Nemes Alexandra

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The aim of the research is to develop an optimum microstructure of steel coatings on aluminum surfaces for application on the crankcase cylinder bores. For the proper design of the microstructure of the coat, it is important to control the plasma gun unit properly. The maximum operating time was determined while the plasma gun could optimally work before its destruction. Objectives: The aim of the research is to determine the optimal operating time of the plasma gun between renovations (the renovation shall involve the replacement of the test components of the plasma gun: electrode, nozzle plate, powder injector. Methodology: Plasma jet and particle flux analysis with PFI (PFI is a diagnostic tool for all kinds of thermal spraying processes), CT reconstruction and analysis on the new and the used plasma guns, failure analysis of electrodes, nozzle plates, and powder injectors, microscopic examination of the microstructure of the coating. Contributions: As the result of the failure analysis detailed above, the use of the plasma gun was maximized at 100 operating hours in order to get optimal microstructure for the coat.

Keywords: APS, air plasma spray, failure analysis, electrode, nozzle plate, powder injector

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

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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

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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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Authors: Aman Patidar, Dipankar Sarkar, Manish Pal

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Due to rapid development, increase in the traffic load, higher traffic volume and seasonal variation in temperature, asphalt pavement shows distresses like rutting, fatigue and thermal cracking etc. because of this pavement fails during service life so that bitumen needs to be modified with some additive. In this study VG30 grade bitumen modify with addition of nanosilica with 1% to 5% (increment of 1%) by weight of bitumen. Hot mix asphalt (HMA) have higher mixing, laying and rolling temperatures which leads to higher consumption of fuel. To address this issue, a nano material named ZycoTherm which is chemical warm mix asphalt (WMA) additive is added to bitumen. Nanosilica modification (NSMB) results in the increase in stability compared to unmodified bitumen (UMB). WMA modified mix shows slightly higher stability than UMB and NSMB in a lower bitumen content. The Retained stability and tensile strength ratio (TSR) is more than 75% and 80% respectively for both mixes. Nanosilica with WMA has more resistant to temperature susceptibility, moisture susceptibility and short term aging than NSMB.

Keywords: HMA, nanosilica, NSMB, temperature, TSR, UMB, WMA

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Authors: Carolin Lutz, Jörg Matthes, Patrick Waibel, Ulrich Precht, Krassimir Garbev, Günter Beuchle, Uwe Schweike, Peter Stemmermann, Hubert B. Keller

Abstract:

Online measurement of the product quality is a challenging task in cement production, especially in the production of Celitement, a novel environmentally friendly hydraulic binder. The mineralogy and chemical composition of clinker in ordinary Portland cement production is measured by X-ray diffraction (XRD) and X ray fluorescence (XRF), where only crystalline constituents can be detected. But only a small part of the Celitement components can be measured via XRD, because most constituents have an amorphous structure. This paper describes the development of algorithms suitable for an on-line monitoring of the final processing step of Celitement based on NIR-data. For calibration intermediate products were dried at different temperatures and ground for variable durations. The products were analyzed using XRD and thermogravimetric analyses together with NIR-spectroscopy to investigate the dependency between the drying and the milling processes on one and the NIR-signal on the other side. As a result, different characteristic parameters have been defined. A short overview of the Celitement process and the challenging tasks of the online measurement and evaluation of the product quality will be presented. Subsequently, methods for systematic development of near-infrared calibration models and the determination of the final calibration model will be introduced. The application of the model on experimental data illustrates that NIR-spectroscopy allows for a quick and sufficiently exact determination of crucial process parameters.

Keywords: calibration model, celitement, cementitious material, NIR spectroscopy

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Authors: Shri Krishna Mishra

Abstract:

In an educational context, technology can prompt interactive plight only when it is used in conjunction with interactive plight methods. This study, therefore, examines the relationships among components that contribute to higher levels of interactive plight and execution, such as interactive Plight methods, technology, intrinsic motivation and deep learning. 526 students participated in this study. With structural equation modelling, the authors test the conceptual model and identify satisfactory model fit. The results indicate that interactive Plight methods, technology and intrinsic motivation have significant relationship with interactive Plight; deep learning mediates the relationships of the other variables with Execution.

Keywords: searching the relationship among components, contribute to interactive plight, educational execution, intrinsic motivation

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Authors: Y. Okumuş, A. Tuna, A. T. Seyhan, H. Çelebi

Abstract:

Useful carbon fibers were derived from chicken feathers (PCFs) based on a two-step pyrolysis method. The collected PCFs were cleaned and categorized as black, white and brown. Differential scanning calorimeter (DSC) and thermo-gravimetric analyzer (TGA) were systemically used to design the pyrolysis steps. Depending on colors, feathers exhibit different glass transition (Tg) temperatures. Long-time heat treatment applied to the feathers emerged influential on the surface quality of the resulting carbon fibers. Fourier Transformation Infrared (FTIR) examination revealed that the extent of disulfide bond cleavage is highly associated with the feather melting stability. Scanning electron microscopy (SEM) examinations were employed to evaluate the morphological changes of feathers after pyrolysis. Of all, brown feathers were found to be the most promising to turn into useful carbon fibers without any trace of melting and shape distortion when pyrolysis was carried out at 230°C for 24 hours and at 450°C for 1 hour.

Keywords: poultry chicken feather, keratin protein fiber, pyrolysis, high carbonaceous fibers

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Authors: Zhaojun Wang, Zongdi Sun, Zhiyuan Liu

Abstract:

First of all, the carbon trading price and trading volume in Shanghai are transformed by Fourier transform, and the frequency response diagram is obtained. Then, the frequency response diagram is analyzed and the Blackman filter is designed. The Blackman filter is used to filter, and the carbon trading time domain and frequency response diagram are obtained. After wavelet analysis, the carbon trading data were processed; respectively, we got the average value for each 5 days, 10 days, 20 days, 30 days, and 60 days. Finally, the data are used as input of the Back Propagation Neural Network model for prediction.

Keywords: Shanghai carbon trading, carbon trading price, carbon trading volume, wavelet analysis, BP neural network model

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Authors: Hritwik Ghosh, Irfan Sadiq Rahat, Sachi Nandan Mohanty, J. V. R. Ravindra

Abstract:

In the rapidly evolving landscape of medical diagnostics, the early detection and accurate classification of skin cancer remain paramount for effective treatment outcomes. This research delves into the transformative potential of Artificial Intelligence (AI), specifically Deep Learning (DL), as a tool for discerning and categorizing various skin conditions. Utilizing a diverse dataset of 3,000 images representing nine distinct skin conditions, we confront the inherent challenge of class imbalance. This imbalance, where conditions like melanomas are over-represented, is addressed by incorporating class weights during the model training phase, ensuring an equitable representation of all conditions in the learning process. Our pioneering approach introduces a hybrid model, amalgamating the strengths of two renowned Convolutional Neural Networks (CNNs), VGG16 and ResNet50. These networks, pre-trained on the ImageNet dataset, are adept at extracting intricate features from images. By synergizing these models, our research aims to capture a holistic set of features, thereby bolstering classification performance. Preliminary findings underscore the hybrid model's superiority over individual models, showcasing its prowess in feature extraction and classification. Moreover, the research emphasizes the significance of rigorous data pre-processing, including image resizing, color normalization, and segmentation, in ensuring data quality and model reliability. In essence, this study illuminates the promising role of AI and DL in revolutionizing skin cancer diagnostics, offering insights into its potential applications in broader medical domains.

Keywords: artificial intelligence, machine learning, deep learning, skin cancer, dermatology, convolutional neural networks, image classification, computer vision, healthcare technology, cancer detection, medical imaging

Procedia PDF Downloads 80