Search results for: Hidden Markov Model (HMM)

Authors: Purnomo Yustianto, Robin Doss, Novianto B. Kurniawan Suhardi

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Since its inception, the design activities of Service Oriented Architecture (SOA) has been guided with aspects from the Service Design Principles (SDP), such as cohesion, granularity, loose coupling, discoverability, and autonomy, etc. The goal of this paper is two folds. The first is to examine the position of SDP within the context of software quality, and the second is to reframe the aspects of SDP into a more concise terms and relations. This paper is divided into four parts, in which after the introduction, a review on related software quality is provided to determine the quality context of SDP. The third part reviews the original SDP and offers a relation model among the SDP aspects. The fourth part explores the design quality metrics available for SOA and proposes a relationship representing the design quality. Among the aspects of design principles, the cohesion and coupling aspect is determined to be the two important aspects for achieving reusability of a service.

Keywords: SOA, software quality, service design principle, reusability, cohesion, coupling

Procedia PDF Downloads 171

Authors: Zhaoming Yang, Qi Xiang, Qian He, Michael Havbro Faber, Enrico Zio, Huai Su, Jinjun Zhang

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Resilience is one of the key factors for system safety assessment and optimization, and resilience studies of natural gas pipeline systems (NGPS), especially in terms of process descriptions, are still being explored. Based on the three main stages, which are function loss process, recovery process, and waiting process, the paper has built functions and models which are according to the practical characteristics of NGPS and mainly analyzes the characteristics of deterministic interruptions. The resilience of NGPS also considers the threshold of the system function or users' satisfaction. The outcomes, which quantify the resilience of NGPS in different evaluation views, can be combined with the max flow and shortest path methods, help with the optimization of extra gas supplies and gas routes as well as pipeline maintenance strategies, the quick analysis of disturbance effects and the improvement of NGPS resilience evaluation accuracy.

Keywords: natural gas pipeline system, resilience, process modeling, deterministic disturbance

Procedia PDF Downloads 126

Authors: Ishu Surender, M. Amez Khair, Ishan Singh

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Urbanization is a multidimensional phenomenon. It is an indication of the long-term process for the shift of economics to industrial from rural. The significance of urbanization in modernization, socio-economic development, and poverty eradication is relevant in modern times. This paper aims to study the urbanization index model in the capital of India, Delhi using aspects such as demographic aspect, infrastructural development aspect, and economic development aspect. The urbanization index of all the nine districts of Delhi will be determined using multiple parameters such as population density and the availability of health and education facilities. The definition of the urban area varies from city to city and requires periodic classification which makes direct comparisons difficult. The urbanization index calculated in this paper can be employed to measure the urbanization of a district and compare the level of urbanization in different districts.

Keywords: multiparameter, population density, multiple regression, normalized urbanization index

Procedia PDF Downloads 114

Authors: Ismael Ávila, José Reynaldo F. Filho, Vasco Varanda Picchi

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The ever-growing consumer awareness of food provenance in Brazil is driving the creation of a trusted ecosystem around the animal protein supply chain. The traceability and accountability requirements of such an ecosystem demand a blockchain layer to strengthen the weak links in that chain. For that, direct involvement of the companies in the blockchain transactions, including as validator nodes of the network, implies formalizing a partnership with the consortium behind the ecosystem. Yet, their compliance standards usually require that a formal governance structure is in place before they agree with any membership terms. In light of such a strategic role of blockchain governance, the paper discusses a framework for tailoring a governance model for a blockchain-based solution aimed at the meat supply chain and evaluates principles and attributes in terms of their relevance to the development of a robust trust ecosystem.

Keywords: blockchain, governance, trust ecosystem, supply chain, traceability

Procedia PDF Downloads 120

Authors: Yuang Guo, Dewancker Bart

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The primary energy consumption of buildings throughout China was approximately 814 million tons of coal equivalents in 2014, which accounts for 19.12% of China's total primary energy consumption. Also, the energy consumption of public buildings takes a bigger share than urban residential buildings and rural residential buildings among the total energy consumption. To improve the level of energy demand, various design parameters were chosen. Meanwhile, a series of simulations by Energy Plus (EP-Launch) is performed using a base case model established in Open Studio. Through the results, 16%-23% of total energy demand reductions can be found in the severe cold zone of China, and it can also provide a reference for the architectural design of other similar climate zones.

Keywords: energy consumption, design parameters, indoor thermal comfort, simulation study, severe cold climate zone

Procedia PDF Downloads 156

Authors: Ummu Salma Al Azizah, Herri Mulyono, Anisa Mauliata Suryana

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The significance of corporate governance regarding to the agency problem have been transparent. This study examine the impact of corporate governance on the performance of Islamic banking in Indonesia. By using fixed effect model and added some control variable, the current study try to explore the correlation between the theoretical framework on corporate governance, such as agency theory and risk management theory. The bank performance (Return on Asset and Return on Equity) which are operational performance and financial performance. And Corporate governance based on Board size, CEO duality, Audit committee and Shariah supervisory board. The limitation of this study only focus on the Islamic banks performance from year 2015 to 2020. The study fill the gap in the literature by addressing the issue of corporate governance on Islamic banks performance in Indonesia.

Keywords: corporate governance, financial performance, islamic banks, listed companies, Indonesia

Procedia PDF Downloads 127

Authors: Robert Caulk

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A generalized framework for adaptive machine learning deployments in algorithmic trading is introduced, tested, and released as open-source code. The presented software aims to test the hypothesis that recent data contains enough information to form a probabilistically favorable short-term price prediction. Further, the framework contains various adaptive machine learning techniques that are geared toward generating profit during strong trends and minimizing losses during trend changes. Results demonstrate that this adaptive machine learning approach is capable of capturing trends and generating profit. The presentation also discusses the importance of defining the parameter space associated with the dynamic training data-set and using the parameter space to identify and remove outliers from prediction data points. Meanwhile, the generalized architecture enables common users to exploit the powerful machinery while focusing on high-level feature engineering and model testing. The presentation also highlights common strengths and weaknesses associated with the presented technique and presents a broad range of well-tested starting points for feature set construction, target setting, and statistical methods for enforcing risk management and maintaining probabilistically favorable entry and exit points. The presentation also describes the end-to-end data processing tools associated with FreqAI, including automatic data fetching, data aggregation, feature engineering, safe and robust data pre-processing, outlier detection, custom machine learning and statistical tools, data post-processing, and adaptive training backtest emulation, and deployment of adaptive training in live environments. Finally, the generalized user interface is also discussed in the presentation. Feature engineering is simplified so that users can seed their feature sets with common indicator libraries (e.g. TA-lib, pandas-ta). The user also feeds data expansion parameters to fill out a large feature set for the model, which can contain as many as 10,000+ features. The presentation describes the various object-oriented programming techniques employed to make FreqAI agnostic to third-party libraries and external data sources. In other words, the back-end is constructed in such a way that users can leverage a broad range of common regression libraries (Catboost, LightGBM, Sklearn, etc) as well as common Neural Network libraries (TensorFlow, PyTorch) without worrying about the logistical complexities associated with data handling and API interactions. The presentation finishes by drawing conclusions about the most important parameters associated with a live deployment of the adaptive learning framework and provides the road map for future development in FreqAI.

Keywords: machine learning, market trend detection, open-source, adaptive learning, parameter space exploration

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Authors: Faruk Ortes, Baris Sayin, Tarik Serhat Bozkurt, Cemil Akcay

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The technique using near-surface mounted (NSM) carbon fiber-reinforced polymer (CFRP) composites has proved to be an reliable strengthening technique. However, the effects of different parameters for the use of NSM CFRP are not fully developed yet. This study focuses on the development of a numerical modeling that can predict the behavior of reinforced concrete (RC) beams strengthened with NSM FRP rods exposed to bending loading and the efficiency of various parameters such as CFRP rod size and filling material type are evaluated by using prepared models. For this purpose, three different models are developed and implemented in the ANSYS® software using Finite Element Analysis (FEA). The numerical results indicate that CFRP rod size and filling material type are significant factors in the behavior of the analyzed RC beams.

Keywords: numerical model, FEA, RC beam, NSM technique, CFRP rod, filling material

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Authors: Terence Soule, Tami Al Ghamdi

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To study how to transfer knowledge from multiple source problems to the target problem, we modeled the Transfer Learning (TL) process using Genetic Algorithms as the model solver. TL is the process that aims to transfer learned data from one problem to another problem. The TL process aims to help Machine Learning (ML) algorithms find a solution to the problems. The Genetic Algorithms (GA) give researchers access to information that we have about how the old problem is solved. In this paper, we have five different source problems, and we transfer the knowledge to the target problem. We studied different scenarios of the target problem. The results showed combined knowledge from multiple source problems improves the GA performance. Also, the process of combining knowledge from several problems results in promoting diversity of the transferred population.

Keywords: transfer learning, genetic algorithm, evolutionary computation, source and target

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Authors: S. Turkan

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In this paper, the Turkey’s Top 500 Industrial Enterprises data in 2014 were analyzed by data envelopment analysis. Data envelopment analysis is used to detect efficient decision-making units such as universities, hospitals, schools etc. by using inputs and outputs. The decision-making units in this study are enterprises. To detect efficient enterprises, some financial ratios are determined as inputs and outputs. For this reason, financial indicators related to productivity of enterprises are considered. The efficient foreign weighted owned capital enterprises are detected via super efficiency model. According to the results, it is said that Mercedes-Benz is the most efficient foreign weighted owned capital enterprise in Turkey.

Keywords: data envelopment analysis, super efficiency, logistic regression, financial ratios

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Authors: Min-Tsai Lai, Taqwa Hariguna

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This paper presents a periodical replacement model for a system, considering the concept of single and cumulative repair cost limits simultaneously. The failures are divided into two types. Minor failure can be corrected by minimal repair and serious failure makes the system breakdown completely. When a minor failure occurs, if the repair cost is less than a single repair cost limit L1 and the accumulated repair cost is less than a cumulative repair cost limit L2, then minimal repair is executed, otherwise, the system is preventively replaced. The system is also replaced at time T or at serious failure. The optimal period T minimizing the long-run expected cost per unit time is verified to be finite and unique under some specific conditions.

Keywords: repair-cost limit, cumulative repair-cost limit, minimal repair, periodical replacement policy

Procedia PDF Downloads 365

Authors: Ai Fujii, Kan Shimazaki

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Bicycle users must ride on the street according the law in Japan, but in practice, many bicycle users ride on the sidewalk. Drivers generally feel that bicycles riding in the street are in the way. In contrast, pedestrians generally feel that bicycles riding on the sidewalk are in the way. That seems to make sense. What, then, is the difference between riding a bicycle on the sidewalk or in the street by usual traveling means. We made 3D computer graphics models of pedestrians, a car, and a bicycle at an intersection. The bicycle was positioned to choose between advancing to the sidewalk or the street after a few seconds. We then made a 2D stimulus picture by changing the point of view of the 3DCG model pictures. Attitudes were surveyed using this 2D stimulus picture, and we compared attitudes between three groups, people traveling by car, on foot, or by bicycle. Here we report the survey result.

Keywords: bicycle, sidewalk, pedestrians, driver, intersection, safety

Procedia PDF Downloads 180

Authors: Tushar Bhardwaj

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Internet of Things (IoT) possesses a dynamic network where the network nodes (mobile devices) are added and removed constantly and randomly, hence the traffic distribution in the network is quite variable and irregular. The basic but very important part in any network is route searching. We have many conventional route searching algorithms like link-state, and distance vector algorithms but they are restricted to the static point to point network topology. In this paper we propose a model that uses the Ant Colony Algorithm for route searching. It is dynamic in nature and has positive feedback mechanism that conforms to the route searching. We have also embedded the concept of Non-Deterministic Finite Automata [NDFA] minimization to reduce the network to increase the performance. Results show that Ant Colony Algorithm gives the shortest path from the source to destination node and NDFA minimization reduces the broadcasting storm effectively.

Keywords: routing, ant colony algorithm, NDFA, IoT

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Authors: Navah Z. Ratzon, Rachel Shichrur

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Background: Many studies have assessed and identified the risk factors of safe driving, but there is relatively little research-based evidence concerning the ability to improve the driving skills of drivers in general and in particular of bus drivers, who are defined as a population at risk. Accidents involving bus drivers can endanger dozens of passengers and cause high direct and indirect damages. Objective: To examine the effectiveness of a metacognitive-functional intervention program for the reduction of risk factors among professional drivers relative to a control group. Methods: The study examined 77 bus drivers working for a large public company in the center of the country, aged 27-69. Twenty-one drivers continued to the intervention stage; four of them dropped out before the end of the intervention. The intervention program we developed was based on previous driving models and the guiding occupational therapy practice framework model in Israel, while adjusting the model to the professional driving in public transportation and its particular risk factors. Treatment focused on raising awareness to safe driving risk factors identified at prescreening (ergonomic, perceptual-cognitive and on-road driving data), with reference to the difficulties that the driver raises and providing coping strategies. The intervention has been customized for each driver and included three sessions of two hours. The effectiveness of the intervention was tested using objective measures: In-Vehicle Data Recorders (IVDR) for monitoring natural driving data, traffic accident data before and after the intervention, and subjective measures (occupational performance questionnaire for bus drivers). Results: Statistical analysis found a significant difference between the degree of change in the rate of IVDR perilous events (t(17)=2.14, p=0.046), before and after the intervention. There was significant difference in the number of accidents per year before and after the intervention in the intervention group (t(17)=2.11, p=0.05), but no significant change in the control group. Subjective ratings of the level of performance and of satisfaction with performance improved in all areas tested following the intervention. The change in the ‘human factors/person’ field, was significant (performance : t=- 2.30, p=0.04; satisfaction with performance : t=-3.18, p=0.009). The change in the ‘driving occupation/tasks’ field, was not significant but showed a tendency toward significance (t=-1.94, p=0.07,). No significant differences were found in driving environment-related variables. Conclusions: The metacognitive-functional intervention significantly improved the objective and subjective measures of safety of bus drivers’ driving. These novel results highlight the potential contribution of occupational therapists, using metacognitive functional treatment, to preventing car accidents among the healthy drivers population and improving the well-being of these drivers. This study also enables familiarity with advanced technologies of IVDR systems and enriches the knowledge of occupational therapists in regards to using a wide variety of driving assessment tools and making the best practice decisions.

Keywords: bus drivers, IVDR, human risk factors, metacognitive-functional intervention

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Authors: Cheila Pereira, Sara C. Cunha, Miguel A. Faria, José O. Fernandes

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The increasing world population brings several concerns, one of which is food security and sustainability. To meet this challenge, aquaculture, the farming of aquatic animals and plants, including fish, mollusks, bivalves, and algae, has experienced sustained growth and development in recent years. Recent advances in this industry have focused on reducing its economic and environmental costs, for example, the substitution of protein sources in fish feed. Plant-based proteins are now a common approach, and while it is a greener alternative to animal-based proteins, there are some disadvantages, such as their putative content and intoxicants such as mycotoxins. These are naturally occurring plant contaminants, and their exposure in fish can cause health problems, stunted growth or even death, resulting in economic losses for the producers and health concerns for the consumers. Different works have demonstrated the presence of both AFB1 (aflatoxin B1) and ENNB1 (enniatin B1) in fish feed and their capacity to be absorbed and bioaccumulate in the fish organism after digestion, further reaching humans through fish ingestion. The aim of this work was to evaluate the bioaccessibility of both mycotoxins in samples of Sparus aurata muscle using a static digestion model based on the INFOGEST protocol. The samples were subjected to different cooking procedures – raw, grilled and fried – and different seasonings – none, thyme and ginger – in order to evaluate their potential reduction effect on mycotoxins bioaccessibility, followed by the evaluation of the intestinal transport of both compounds with an in vitro cell model composed of Caco-2/HT-29 co-culture monolayers, simulating the human intestinal epithelium. The bioaccessible fractions obtained in the digestion studies were used in the transport studies for a more realistic approach to bioavailability evaluation. Results demonstrated the effect of the use of different cooking procedures and seasoning on the toxin's bioavailability. Sparus aurata was chosen in this study for its large production in aquaculture and high consumption in Europe. Also, with the continued evolution of fish farming practices and more common usage of novel feed ingredients based on plants, there is a growing concern about less studied contaminants in aquaculture and their consequences for human health. In pair with greener advances in this industry, there is a convergence towards alternative research methods, such as in vitro applications. In the case of bioavailability studies, both in vitro digestion protocols and intestinal transport assessment are excellent alternatives to in vivo studies. These methods provide fast, reliable and comparable results without ethical restraints.

Keywords: AFB1, aquaculture, bioaccessibility, ENNB1, intestinal transport.

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Authors: James Moir

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The mainstay of Big Data is prediction in that it allows practitioners, researchers, and policy analysts to predict trends based upon the analysis of large and varied sources of data. These can range from changing social and political opinions, patterns in crimes, and consumer behaviour. Big Data has therefore shifted the criterion of success in science from causal explanations to predictive modelling and simulation. The 19th-century science sought to capture phenomena and seek to show the appearance of it through causal mechanisms while 20th-century science attempted to save the appearance and relinquish causal explanations. Now 21st-century science in the form of Big Data is concerned with the prediction of appearances and nothing more. However, this pulls social science back in the direction of a more rule- or law-governed reality model of science and away from a consideration of the internal nature of rules in relation to various practices. In effect Big Data offers us no more than a world of surface appearance and in doing so it makes disappear any context-specific conceptual sensitivity.

Keywords: big data, appearance, disappearance, surface, epistemology

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Authors: Alexandre Gurchumelia, Luca Sorriso-Valvo, David Burgess, Khatuna Elbakidze, Oleg Kharshiladze, Diana Kvaratskhelia

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The terrestrial magnetosheath is a highly turbulent medium, with a high level of magnetic1field fluctuations throughout a broad range of scales. These often include an inertial range where a2magnetohydrodynamic turbulent cascade is observed. The multifractal properties of the turbulent3cascade, strictly related to intermittency, are observed here during the transition from quasi-parallel to4quasi-perpendicular magnetic field with respect to the bow-shock normal. The different multifractal5behavior in the two regions is analyzed. A standard coarse-graining technique has been used6to evaluate the generalized dimensions and the corresponding multifractal spectrumf(α). A7p-model fit provided a quantitative measure of multifractality and intermittency, to be compared with8standard indicators: the width of the multifractal spectrum, the peak of the kurtosis, and its scaling9exponent. Results show a clear transition and sharp differences in the intermittency properties for the two regions.

Keywords: magnetos heath, turbulence, multifractal, instabilities

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Authors: Junjie Fu

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This paper explores the cultural evolution of the "city-mountain" landscape in ancient Chinese cities, tracing its origins in the regional mountain and town division within the national system. It delves into the cultural archetype of "city-mountain" landscape divine imagery and its spatial characteristics, drawing from the spatial conception of mountain worship and divine order in the model of Kunlun and Penglai. Furthermore, it examines the shift from religious to daily life influences, leading to a poetic aesthetic turn in the "city-mountain" landscape. The paper also discusses the organizational structure of the "city-mountain" poetic landscape and its role as a space for enjoyment. By studying the cultural connotations, evolving relationships, and power mechanisms of the "city-mountain" landscape, this research provides theoretical insights for the construction and development of "city-mountain" landscapes and mountain cities.

Keywords: city-mountain landscape, cultural image, divinity, landscape image, poetry

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Authors: Ahmed Bakry, Moustafa Ahmed

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We model and simulate the combined effect of fiber dispersion and frequency chirp of a directly modulated high-speed laser diode on the figures of merit of a non-amplified 40-Gbps optical fiber link. We consider both the return to zero (RZ) and non-return to zero (NRZ) patterns of the pseudorandom modulation bits. The performance of the fiber communication system is assessed by the fiber-length limitation due to the fiber dispersion. We study the influence of replacing standard single-mode fibers by non-zero dispersion-shifted fibers on the maximum fiber length and evaluate the associated power penalty. We introduce new dispersion tolerances for 1-dB power penalty of the RZ and NRZ 40-Gbps optical fiber links.

Keywords: bit error rate, dispersion, frequency chirp, fiber communications, semiconductor laser

Procedia PDF Downloads 641

Authors: Bernard Polednik, Adam Piotrowicz, Lukasz Guz, Marzenna Dudzinska

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Transportation is considered to be responsible for increased exposure of road users – i.e., drivers, car passengers, and pedestrians as well as inhabitants of houses located near roads - to pollutants emitted from vehicles. Accurate estimates are, however, difficult as exposure depends on many factors such as traffic intensity or type of fuel as well as the topography and the built-up area around the individual routes. The season and weather conditions are also of importance. In the case of inhabitants of houses located near roads, their exposure depends on the distance from the road, window tightness and other factors that decrease pollutant infiltration. This work reports the variations of particle concentrations along a selected road in Lublin, Poland. Their impact on the exposure for road users as well as for inhabitants of houses located near the road is also presented. Mobile and fixed-site measurements were carried out in peak (around 8 a.m. and 4 p.m.) and off-peak (12 a.m., 4 a.m., and 12 p.m.) traffic times in all 4 seasons. Fixed-site measurements were performed in 12 measurement points along the route. The number and mass concentration of particles was determined with the use of P-Trak model 8525, OPS 3330, DustTrak DRX model 8533 (TSI Inc. USA) and Grimm Aerosol Spectrometer 1.109 with Nano Sizer 1.321 (Grimm Aerosol Germany). The obtained results indicated that the highest concentrations of traffic-related pollution were measured near 4-way traffic intersections during peak hours in the autumn and winter. The highest average number concentration of ultrafine particles (PN0.1), and mass concentration of fine particles (PM2.5) in fixed-site measurements were obtained in the autumn and amounted to 23.6 ± 9.2×10³ pt/cm³ and 135.1 ± 11.3 µg/m³, respectively. The highest average number concentration of submicrometer particles (PN1) was measured in the winter and amounted to 68 ± 26.8×10³ pt/cm³. The estimated doses of particles deposited in the commuters’ and pedestrians’ lungs within an hour near 4-way TIs in peak hours in the summer amounted to 4.3 ± 3.3×10⁹ pt/h (PN0.1) and 2.9 ± 1.4 µg/h (PM2.5) and 3.9 ± 1.1×10⁹ pt/h (PN0.1) or 2.5 ± 0.4 µg/h (PM2.5), respectively. While estimating the doses inhaled by the inhabitants of premises located near the road one should take into account different fractional penetration of particles from outdoors to indoors. Such doses assessed for the autumn and winter are up to twice as high as the doses inhaled by commuters and pedestrians in the summer. In the winter traffic-related ultrafine particles account for over 70% of all ultrafine particles deposited in the pedestrians’ lungs. The share of traffic-related PM10 particles was estimated at approximately 33.5%. Concluding, the results of the particle concentration measurements along a road in Lublin indicated that the concentration is mainly affected by the traffic intensity and weather conditions. Further detailed research should focus on how the season and the metrological conditions affect concentration levels of traffic-related pollutants and the exposure of commuters and pedestrians as well as the inhabitants of houses located near traffic routes.

Keywords: air quality, deposition dose, health effects, vehicle emissions

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Authors: Magno Enrique Mendoza Meza

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This paper deals with the comparison of three control techniques: the hysteresis on-off control (HyOOC), the hybrid on-off control (HOOC) and the simple Structured Treatment Interruptions (sSTI). These techniques are applied to the mathematical model developed by Kirschner and Webb. To compare these techniques we use a cost functional that minimize the wild-type virus population and the mutant virus population, but the main objective is to minimize the systemic cost of treatment and maximize levels of healthy CD4+ T cells. HyOOC, HOOC, and sSTI are applied to the drug therapies using a reverse transcriptase and protease inhibitors; simulations show that these controls maintain the uninfected cells in a small, bounded neighborhood of a pre-specified level. The controller HyOOC and HOOC are designed by appropriate choice of virtual equilibrium points.

Keywords: virus dynamics, on-off control, hysteresis, multi-drug therapies

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Authors: Burcu Kaya, Jan-Martin Kaiser, Karl-Friedrich Becker, Tanja Braun, Klaus-Dieter Lang

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Quality of the molded packages is strongly influenced by the process parameters of the transfer molding. To achieve a better package quality and a stable transfer molding process, it is necessary to understand the influence of the process parameters on the package quality. This work aims to comprehend the relationship between the process parameters, and to identify the optimum process parameters for the transfer molding process in order to achieve less voids and wire sweep. To achieve this, a DoE is executed for process optimization and a regression analysis is carried out. A systematic approach is represented to generate models which enable an estimation of the number of voids and wire sweep. Validation experiments are conducted to verify the model and the results are presented.

Keywords: dielectric analysis, electronic packages, epoxy molding compounds, transfer molding process

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Authors: Abdollah Kavousi Fard

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This paper addresses the optimal scheduling of hybrid reconfigurable microgrids considering hybrid electric vehicle charging demands. A stochastic framework based on unscented transform to model the high uncertainties of renewable energy sources including wind turbine and photovoltaic panels, as well as the hybrid electric vehicles’ charging demand. In order to get to the optimal scheduling, the network reconfiguration is employed as an effective tool for changing the power supply path and avoiding possible congestions. The simulation results are analyzed and discussed in three different scenarios including coordinated, uncoordinated and smart charging demand of hybrid electric vehicles. A typical grid-connected microgrid is employed to show the satisfying performance of the proposed method.

Keywords: microgrid, renewable energy sources, reconfiguration, optimization

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Authors: Roberta Martino, Viviana Ventre

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Intertemporal choices are choices under conditions of uncertainty in which the consequences are distributed over time. The Discounted Utility Model is the essential reference for describing the individual in the context of intertemporal choice. The model is based on the idea that the individual selects the alternative with the highest utility, which is calculated by multiplying the cardinal utility of the outcome, as if the reception were instantaneous, by the discount function that determines a decrease in the utility value according to how the actual reception of the outcome is far away from the moment the choice is made. Initially, the discount function was assumed to have an exponential trend, whose decrease over time is constant, in line with a profile of a rational investor described by classical economics. Instead, empirical evidence called for the formulation of alternative, hyperbolic models that better represented the actual actions of the investor. Attitudes that do not comply with the principles of classical rationality are termed anomalous, i.e., difficult to rationalize and describe through normative models. The development of behavioral finance, which describes investor behavior through cognitive psychology, has shown that deviations from rationality are due to the limited rationality condition of human beings. What this means is that when a choice is made in a very difficult and information-rich environment, the brain does a compromise job between the cognitive effort required and the selection of an alternative. Moreover, the evaluation and selection phase of the alternative, the collection and processing of information, are dynamics conditioned by systematic distortions of the decision-making process that are the behavioral biases involving the individual's emotional and cognitive system. In this paper we present an original decomposition of the discount function to investigate the psychological principles of hyperbolic discounting. It is possible to decompose the curve into two components: the first component is responsible for the smaller decrease in the outcome as time increases and is related to the individual's impatience; the second component relates to the change in the direction of the tangent vector to the curve and indicates how much the individual perceives the indeterminacy of the future indicating his or her aversion to uncertainty. This decomposition allows interesting conclusions to be drawn with respect to the concept of impatience and the emotional drives involved in decision-making. The contribution that neuroscience can make to decision theory and inter-temporal choice theory is vast as it would allow the description of the decision-making process as the relationship between the individual's emotional and cognitive factors. Neurofinance is a discipline that uses a multidisciplinary approach to investigate how the brain influences decision-making. Indeed, considering that the decision-making process is linked to the activity of the prefrontal cortex and amygdala, neurofinance can help determine the extent to which abnormal attitudes respect the principles of rationality.

Keywords: impatience, intertemporal choice, neurofinance, rationality, uncertainty

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Authors: T. S. Terence Ma, Irene T. Ho

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Conducting adequate assessment of the challenges students with ASD (Autism Spectrum Disorder) face and the support they need is imperative for promoting their school adjustment. Students with ASD often show deficits in communication, social interaction, emotional regulation, and self-management in learning. While targeting these areas in intervention is often helpful, we argue that not enough attention has been paid to weak self-regulation being a key factor underlying their manifest difficulty in all these areas. Self-regulation refers to one’s ability to moderate their behavioral or affective responses without assistance from others. Especially for students with high functioning autism, who often show problems not so much in acquiring the needed skills but rather in applying those skills appropriately in everyday problem-solving, self-regulation becomes a key to successful adjustment in daily life. Therefore, a greater understanding of the construct of self-regulation, its relationship with other daily skills, and its role in school functioning for students with ASD would generate insights on how students’ school adjustment could be promoted more effectively. There were two focuses in this study. Firstly, we examined the extent to which self-regulation is a distinct construct that is differentiable from other daily skills and the most salient indicators of this construct. Then we tested a model of relationships between self-regulation and other daily school skills as well as their relative and combined effects on school adjustment. A total of 1,345 Grade1 to Grade 6 students with ASD attending mainstream schools in Hong Kong participated in the research. In the first stage of the study, teachers filled out a questionnaire consisting of 136 items assessing a wide range of student skills in social, emotional and learning areas. Results from exploratory factor analysis (EFA) with 673 participants and subsequent confirmatory factor analysis (CFA) with another group of 672 participants showed that there were five distinct factors of school skills, namely (1) communication skills, (2) pro-social behavior, (3) emotional skills, (4) learning management, and (5) self-regulation. Five scales representing these skill dimensions were generated. In the second stage of the study, a model postulating the mediating role of self-regulation for the effects of the other four types of skills on school adjustment was tested with structural equation modeling (SEM). School adjustment was defined in terms of the extent to which the student is accepted well in school, with high engagement in school life and self-esteem as well as good interpersonal relationships. A 5-item scale was used to assess these aspects of school adjustment. Results showed that communication skills, pro-social behavior, emotional skills and learning management had significant effects on school adjustment only indirectly through self-regulation, and their total effects were found to be not high. The results indicate that support rendered to students with ASD focusing only on the training of well-defined skills is not adequate for promoting their inclusion in school. More attention should be paid to the training of self-management with an emphasis on the application of skills backed by self-regulation. Also, other non-skill factors are important in promoting inclusive education.

Keywords: autism, assessment, factor analysis, self-regulation, school adjustment

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Authors: Nader Mohamed

Abstract:

The Late Cretaceous deposits are well developed through-out Egypt. This is due to a ‎transgression phase associated with the subsidence caused by the neo-Tethyan rift event that ‎took place across the northern margin of Africa, resulting in a period of dominantly marine ‎deposits in the Gulf of Suez. The Late Cretaceous Nezzazat Group represents the Cenomanian, ‎Turonian and clastic sediments of the Lower Senonian. The Nezzazat Group has been divided ‎into four formations namely, from base to top, the Raha Formation, the Abu Qada Formation, ‎the Wata Formation and the Matulla Formation. The Cenomanian Raha and the Lower Senonian ‎Matulla formations are the most important clastic sequence in the Nezzazat Group because they ‎provide the highest net reservoir thickness and the highest net/gross ratio. This study emphasis ‎on Matulla formation located in the eastern part of the Gulf of Suez. The three stratigraphic ‎surface sections (Wadi Sudr, Wadi Matulla and Gabal Nezzazat) which represent the exposed ‎Coniacian-Santonian sediments in Sinai are used for correlating Matulla sediments of Ras ‎Budran field. Cutting description, petrographic examination, log behaviors, biostratigraphy with ‎outcrops are used to identify the reservoir characteristics, lithology, facies environment logs and ‎subdivide the Matulla formation into three units. The lower unit is believed to be the main ‎reservoir where it consists mainly of sands with shale and sandy carbonates, while the other ‎units are mainly carbonate with some streaks of shale and sand. Reservoir modeling is an ‎effective technique that assists in reservoir management as decisions concerning development ‎and depletion of hydrocarbon reserves, So It was essential to model the Matulla reservoir as ‎accurately as possible in order to better evaluate, calculate the reserves and to determine the ‎most effective way of recovering as much of the petroleum economically as possible. All ‎available data on Matulla formation are used to build the reservoir structure model, lithofacies, ‎porosity, permeability and water saturation models which are the main parameters that describe ‎the reservoirs and provide information on effective evaluation of the need to develop the oil ‎potentiality of the reservoir. This study has shown the effectiveness of; 1) the integration of ‎geological data to evaluate and subdivide Matulla formation into three units. 2) Lithology and ‎facies environment interpretation which helped in defining the nature of deposition of Matulla ‎formation. 3) The 3D reservoir modeling technology as a tool for adequate understanding of the ‎spatial distribution of property and in addition evaluating the unlocked new reservoir areas of ‎Matulla formation which have to be drilled to investigate and exploit the un-drained oil. 4) This ‎study led to adding a new room of production and additional reserves to Ras Budran field. ‎

Keywords: geology, oil and gas, geoscience, sequence stratigraphy

Procedia PDF Downloads 106

Authors: Mary Fargher

Abstract:

This paper examines the opportunities of using a more hierarchical approach to geospatial enquiry in using GIS in school geography. A case is made that it is not just the lack of teacher technological knowledge that is stopping some teachers from using GIS in the classroom but that there is a gap in their understanding of how to link GIS use more specifically to the pedagogy of teaching geography with GIS. Using a hierarchical approach to geospatial enquiry as a theoretical framework, the analysis shows clearly how concepts of spatial distribution, interaction, relation, comparison, and temporal relationships can be used by teachers more explicitly to capitalise on the analytical power of GIS and to construct what can be interpreted as powerful geographical knowledge. An exemplar illustrating this approach on the topic of geo-hazards is then presented for critical analysis and discussion. Recommendations are then made for a model of progression for geography teacher education with GIS through hierarchical geospatial enquiry that takes into account beginner, intermediate, and more advanced users.

Keywords: digital geography, GIS, education, hierarchical geospatial enquiry, powerful geographical knowledge

Procedia PDF Downloads 153

Authors: Jiahe Liu, Hongyang Yu, Miao Luo, Feng Qian

Abstract:

The widespread application of 3D human body reconstruction spans various fields. Smplify-X, an algorithm reliant on single-image input, employs three distinct body parameter templates, necessitating gender classification of individuals within the input image. Researchers employed a ResNet18 network to train a gender classifier within the Smplify-X framework, setting the threshold at 0.9, designating images falling below this threshold as having neutral gender. This model achieved 62.38% accurate predictions and 7.54% incorrect predictions. Our improvement involved refining the MobileNet network, resulting in a raised threshold of 0.97. Consequently, we attained 78.89% accurate predictions and a mere 0.2% incorrect predictions, markedly enhancing prediction precision and enabling more precise 3D human body reconstruction.

Keywords: SMPLX, mobileNet, gender classification, 3D human reconstruction

Procedia PDF Downloads 100

Authors: Wafa’ Alma'Aitah, Khaled Almakadmeh

Abstract:

this study presents an information retrieval system of using genetic algorithm to increase information retrieval efficiency. Using vector space model, information retrieval is based on the similarity measurement between query and documents. Documents with high similarity to query are judge more relevant to the query and should be retrieved first. Using genetic algorithms, each query is represented by a chromosome; these chromosomes are fed into genetic operator process: selection, crossover, and mutation until an optimized query chromosome is obtained for document retrieval. Results show that information retrieval with adaptive crossover probability and single point type crossover and roulette wheel as selection type give the highest recall. The proposed approach is verified using (242) proceedings abstracts collected from the Saudi Arabian national conference.

Keywords: genetic algorithm, information retrieval, optimal queries, crossover

Procedia PDF Downloads 293

Authors: Saeedeh Barzegar Khalilsaraei, Manoocheher Kelarestaghi, Farshad Eshghi

Abstract:

The vehicle color, as a prominent and stable feature, helps to identify a vehicle more accurately. As a result, vehicle color recognition is of great importance in intelligent transportation systems. Unlike conventional methods which use only a single Convolutional Neural Network (CNN) for feature extraction or classification, in this paper, four CNNs, with different architectures well-performing in different classes, are trained to extract various features from the input image. To take advantage of the distinct capability of each network, the multiple outputs are combined using a stack generalization algorithm as an ensemble technique. As a result, the final model performs better than each CNN individually in vehicle color identification. The evaluation results in terms of overall average accuracy and accuracy variance show the proposed method’s outperformance compared to the state-of-the-art rivals.

Keywords: Vehicle Color Recognition, Ensemble Algorithm, Stack Generalization, Convolutional Neural Network

Procedia PDF Downloads 85