Search results for: capability maturity model integration

Authors: Mohanaad Talal Shakir

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This paper tries to propose educational design by using multimedia technology for Engineering of computer Technology, Alma'ref University College in Iraq. This paper evaluates the acceptance, cognition, and interactiveness of the proposed model by students by using the statistical relationship to determine the stage of the model. Objectives of proposed education design are to develop a user-friendly software for education purposes using multimedia technology and to develop animation for 3D model to simulate assembling and disassembling process of high-speed flow.

Keywords: CAL, multimedia, shock tunnel, interactivity, engineering education

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Authors: Xuan Dinh Vu, Elmar Csaplovics

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There has been an increasing need for methods to define priority areas for biodiversity conservation since the effectiveness of biodiversity conservation in protected areas largely depends on the availability of material resources. The identification of priority areas requires the integration of biodiversity data together with social data on human pressures and responses. However, the deficit of comprehensive data and reliable methods becomes a key challenge in zoning where the demand for conservation is most urgent and where the outcomes of conservation strategies can be maximized. In order to fill this gap, the study applied an environmental model Condition–Pressure–Response to suggest a set of criteria to identify priority areas for biodiversity conservation. Our empirical data has been compiled from 185 respondents, categorizing into three main groups: governmental administration, research institutions, and protected areas in Vietnam by using a well - designed questionnaire. Then, the Analytic Hierarchy Process (AHP) theory was used to identify the weight of all criteria. Our results have shown that priority level for biodiversity conservation could be identified by three main indicators: condition, pressure, and response with the value of the weight of 26%, 41%, and 33%, respectively. Based on the three indicators, 7 criteria and 15 sub-criteria were developed to support for defining priority areas for biodiversity conservation and zoning protected areas. In addition, our study also revealed that the groups of governmental administration and protected areas put a focus on the 'Pressure' indicator while the group of Research Institutions emphasized the importance of 'Response' indicator in the evaluation process. Our results provided recommendations to apply the developed criteria for identifying priority areas for biodiversity conservation in Vietnam.

Keywords: biodiversity conservation, condition–pressure–response model, criteria, priority areas, protected areas

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Authors: Prasad Kalagura, B. Veeresh kumar

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We constructed an interface system that would allow a similarly paralyzed user to interact with a computer with almost full functional capability. A real-time tracking algorithm is implemented based on adaptive skin detection and motion analysis. The clicking of the mouse is activated by the user's eye blinking through a sensor. The keyboard function is implemented by voice recognition kit.

Keywords: embedded ARM7 processor, mouse pointer control, voice recognition

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Authors: Alireza Saidi

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Aside from injuries due to direct contact with hot or cold substances or objects, exposure to extreme temperatures in the workplace involves physical hazards to workers. On the other hand, a poorly acclimatized worker may have reduced performance and alertness and may, therefore, be more vulnerable to the risk of accidents and injuries. Due to the incompatibility of the standards put in place with certain workplaces and the lack of thermoregulation in many protective equipments, thermal strains remain among the physical risks most present in many work sectors. However, many of these problems can be overcome thanks to the potential of intelligent textile technologies allowing intelligent thermoregulation in protective equipment. Nowadays, technologies such as heating elements, cooling elements are applied in products intended for sport and leisure, and research work has been carried out in the integration of temperature sensors and thermal stress detectors in personal protective equipment. However, the usage of all of these technologies in personal protective equipment remains very marginal. This article presents a portrait of the current state of intelligent thermoregulation systems by carrying out a synthesis of technical developments, which is accompanied by a gap analysis of current developments. Thus, the research work necessary for the adaptation and integration of intelligent thermoregulation systems with personal protective equipment is discussed in order to offer a perspective of future developments.

Keywords: personal protective equipment, smart textiles, thermoregulation, thermal strain

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Authors: Shreyas Kumar, Mili Shangari

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Integrating artificial intelligence (AI) in the cyber insurance sector represents a significant advancement, offering the potential to revolutionize risk assessment, fraud detection, and claims processing. However, this integration introduces a range of regulatory and economic challenges that must be addressed to ensure responsible and effective deployment of AI technologies. This paper examines the multifaceted regulatory landscape governing AI in cyber insurance and explores the economic implications of compliance, innovation, and market dynamics. AI's capabilities in processing vast amounts of data and identifying patterns make it an invaluable tool for insurers in managing cyber risks. Yet, the application of AI in this domain is subject to stringent regulatory scrutiny aimed at safeguarding data privacy, ensuring algorithmic transparency, and preventing biases. Regulatory bodies, such as the European Union with its General Data Protection Regulation (GDPR), mandate strict compliance requirements that can significantly impact the deployment of AI systems. These regulations necessitate robust data protection measures, ethical AI practices, and clear accountability frameworks, all of which entail substantial compliance costs for insurers. The economic implications of these regulatory requirements are profound. Insurers must invest heavily in upgrading their IT infrastructure, implementing robust data governance frameworks, and training personnel to handle AI systems ethically and effectively. These investments, while essential for regulatory compliance, can strain financial resources, particularly for smaller insurers, potentially leading to market consolidation. Furthermore, the cost of regulatory compliance can translate into higher premiums for policyholders, affecting the overall affordability and accessibility of cyber insurance. Despite these challenges, the potential economic benefits of AI integration in cyber insurance are significant. AI-enhanced risk assessment models can provide more accurate pricing, reduce the incidence of fraudulent claims, and expedite claims processing, leading to overall cost savings and increased efficiency. These efficiencies can improve the competitiveness of insurers and drive innovation in product offerings. However, balancing these benefits with regulatory compliance is crucial to avoid legal penalties and reputational damage. The paper also explores the potential risks associated with AI integration, such as algorithmic biases that could lead to unfair discrimination in policy underwriting and claims adjudication. Regulatory frameworks need to evolve to address these issues, promoting fairness and transparency in AI applications. Policymakers play a critical role in creating a balanced regulatory environment that fosters innovation while protecting consumer rights and ensuring market stability. In conclusion, the integration of AI in cyber insurance presents both regulatory and economic challenges that require a coordinated approach involving regulators, insurers, and other stakeholders. By navigating these challenges effectively, the industry can harness the transformative potential of AI, driving advancements in risk management and enhancing the resilience of the cyber insurance market. This paper provides insights and recommendations for policymakers and industry leaders to achieve a balanced and sustainable integration of AI technologies in cyber insurance.

Keywords: artificial intelligence (AI), cyber insurance, regulatory compliance, economic impact, risk assessment, fraud detection, cyber liability insurance, risk management, ransomware

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Authors: Zhidong Zhang, Yingchen Yang

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In this study, a diagnostic assessment model for Mastery Engineering Learning was established based on a group of undergraduate students who studied in an engineering course. A diagnostic assessment model can examine both students' learning process and report achievement results. One very unique characteristic is that the diagnostic assessment model can recognize the errors and anything blocking students in their learning processes. The feedback is provided to help students to know how to solve the learning problems with alternative strategies and help the instructor to find alternative pedagogical strategies in the instructional designs. Dynamics is a core course in which is a common course being shared by several engineering programs. This course is a very challenging for engineering students to solve the problems. Thus knowledge acquisition and problem-solving skills are crucial for student success. Therefore, developing an effective and valid assessment model for student learning are of great importance. Diagnostic assessment is such a model which can provide effective feedback for both students and instructor in the mastery of engineering learning.

Keywords: diagnostic assessment, mastery learning, engineering, bayesian network model, learning processes

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Authors: Elizelle Juanee Cilliers

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Recent planning thinking has laid the foundations for a general sense of best practice that aims to enhance the quality of life, suggesting an open and participatory process. It is accepted that integration of top-down and bottom-up approaches may lead to efficient action in environments and sustainable planning and development, although it is also accepted that such an integrated approach has various challenges of implementation. A flexible framework in which the strengths of both the top-down and bottom-up approaches were explored in this research, based on the EU Interreg VALUE Added project and five case studies where student education and student involvement played a crucial role within the participation process of the redesign of the urban environment. It was found that international student workshops were an effective tool to integrate bottom-up and top-down structures, as it acted as catalyst for communication, interaction, creative design, quick transformation from planning to implementation, building social cohesion, finding mutual ground between stakeholders and thus enhancing overall quality of life and quality of environments. It offered a good alternative to traditional participation modes and created a platform for an integrative planning approach. The role and importance of education and integration within the urban environment were emphasized.

Keywords: top-down, bottom-up, flexible, student involvement

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Authors: Ion Smeureanu, Adriana Reveiu, Marian Dardala, Titus Felix Furtuna, Roman Kanala

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This paper proposes a linear model for optimizing domestic energy consumption, in Romania. Both techno-economic and consumer behavior approaches have been considered, in order to develop the model. The proposed model aims to reduce the energy consumption, in households, by assembling in a unitary model, aspects concerning: residential lighting, space heating, hot water, and combined space heating – hot water, space cooling, and passenger transport. This paper focuses on space heating domestic energy consumption model, and quantify not only technical-economic issues, but also consumer behavior impact, related to people decision to envelope and insulate buildings, in order to minimize energy consumption.

Keywords: consumer behavior, open source energy modeling system (OSeMOSYS), MARKAL/TIMES Romanian energy model, virtual technologies

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Authors: Cristina Schreiner, Romeo Ciobanu, Marius Pislaru

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This paper aims to build a system based on fuzzy models that can be implemented in the assessment of ecological systems, to determine appropriate methods of action for reducing adverse effects on environmental and implicit the population. The model proposed provides new perspective for environmental assessment, and it can be used as a practical instrument for decision-making.

Keywords: ecosystem model, environmental security, fuzzy logic, sustainability of habitable regions

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Authors: Hassan Al Salman

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We consider a nonlinear parabolic cross diffusion model arising in applied mathematics. A fully practical piecewise linear finite element approximation of the model is studied. By using entropy-type inequalities and compactness arguments, existence of a global weak solution is proved. Providing further regularity of the solution of the model, some uniqueness results and error estimates are established. Finally, some numerical experiments are performed.

Keywords: cross diffusion model, entropy-type inequality, finite element approximation, numerical analysis

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Authors: Rui Mao, Heming Ji, Xiaoyu Wang

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Keystroke dynamics are widely used in identity recognition. It has the advantage that the individual typing rhythm is difficult to imitate. It also supports continuous authentication through the keyboard without extra devices. The existing keystroke dynamics authentication methods based on machine learning have a drawback in supporting relatively complex scenarios with massive data. There are drawbacks to both feature extraction and model optimization in these methods. To overcome the above weakness, an authentication model of keystroke dynamics based on deep learning is proposed. The model uses feature vectors formed by keystroke content and keystroke time. It ensures efficient continuous authentication by cooperating attention mechanisms with the combination of CNN and Bi-LSTM. The model has been tested with Open Data Buffalo dataset, and the result shows that the FRR is 3.09%, FAR is 3.03%, and EER is 4.23%. This proves that the model is efficient and accurate on continuous authentication.

Keywords: keystroke dynamics, identity authentication, deep learning, CNN, LSTM

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Authors: Anwar Jarndal

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In this paper, a genetic-neural-network (GNN) based large-signal model for GaN HEMTs is presented along with its parameters extraction procedure. The model is easy to construct and implement in CAD software and requires only DC and S-parameter measurements. An improved decomposition technique is used to model self-heating effect. Two GNN models are constructed to simulate isothermal drain current and power dissipation, respectively. The two model are then composed to simulate the drain current. The modeling procedure was applied to a packaged GaN-on-Si HEMT and the developed model is validated by comparing its large-signal simulation with measured data. A very good agreement between the simulation and measurement is obtained.

Keywords: GaN HEMT, computer-aided design and modeling, neural networks, genetic optimization

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Authors: Betty Chiyangwa

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This is a work in progress project focused on exploring the complexities surrounding the second generation Mozambican migrant youth’s experiences to construct their identity and develop a sense of belonging in post-apartheid, Bushbuckridge in South Africa. Established in 1884, Bushbuckridge is one of the earliest districts to accommodate Mozambicans who migrated to South Africa in the 1970s. Bushbuckridge as a destination for Mozambican migrants is crucial to their search for social freedom and space to “belong to.” The action of deliberately seeking freedom is known as an act of agency. Four major objectives govern the paper. The first objective observes how second-generation Mozambican migrant youth living in South Africa negotiate and construct their own identities. Secondly, it explores second-generation Mozambican migrant youth narratives regarding their sense of belonging in South Africa. Thirdly, the study intends to understand how social processes of identity and belonging influence second-generation Mozambican migrant youth experiences and future aspirations in South Africa. The last objective examines how Sen’s Capability approach is relevant in understanding second-generation Mozambican migrant youth identity and belonging in South Africa. This is a single case study informed by data from semi-structured interviews and narratives with youth between the ages of 18 and 34 who are born and raised in South Africa to at least one former Mozambican refugee parent living in Bushbuckridge. Drawing from Crenshaw’s Intersectionality and Sen’s Capability approaches, this study significantly contributes to the existing body of knowledge on South to South migration by demonstrating how both approaches can be operationalized towards understanding complex experiences and capabilities of the disadvantaged group simultaneously. The subject of second-generation migrants is often under-researched in South African migration; thus, their perspectives have been marginalized in Social Science research.

Keywords: second-generation, Mozambican, migrant, youth, bushbuckridge

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Authors: Abdulrazzak Akroot, Lutfu Namli

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Solid oxide fuel cells (SOFCs) are one of the most promising technologies since they can produce electricity directly from fuel and generate a lot of waste heat that is generally used in the gas turbines to promote the general performance of the thermal power plant. In this study, the energy, and exergy analysis of a solid oxide fuel cell/gas turbine hybrid system was proceed in MATLAB to examine the performance characteristics of the hybrid system in two different configurations: anode-supported model and electrolyte-supported model. The obtained results indicate that if the fuel utilization factor reduces from 0.85 to 0.65, the overall efficiency decreases from 64.61 to 59.27% for the anode-supported model whereas it reduces from 58.3 to 56.4% for the electrolyte-supported model. Besides, the overall exergy reduces from 53.86 to 44.06% for the anode-supported model whereas it reduces from 39.96 to 33.94% for the electrolyte-supported model. Furthermore, increasing the air utilization factor has a negative impact on the electrical power output and the efficiencies of the overall system due to the reduction in the O₂ concentration at the cathode-electrolyte interface.

Keywords: solid oxide fuel cell, anode-supported model, electrolyte-supported model, energy analysis, exergy analysis

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Authors: Mustapha Kamel Mihoubi, Hocine Dahmani

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The purpose of work is to study the phenomenon of agitation of storm waves at basin caused by different directions of waves relative to the current provision thrown numerical model based on the equation in shallow water using Boussinesq model MIKE 21 BW. According to the diminishing effect of penetration of a wave optimal solution will be available to be reproduced in reduced model. Another alternative arrangement throws will be proposed to reduce the agitation and the effects of the swell reflection caused by the penetration of waves in the harbor.

Keywords: agitation, Boussinesq equations, combination, harbor

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Authors: Matthew Perkins-McVey

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The pharmacological arm of mental health treatment is in a state of crisis. The promises of the Prozac century have fallen short; the number of different therapeutically significant medications that successfully complete development shrinks with every passing year, and the demand for better treatments only grows. Answering these hardships is a renewed optimism concerning the efficacy of controlled psychedelic therapy, a renaissance that has seen the return of a familiar concept: intoxication as a model psychosis. First appearing in the mid-19th century and featuring in an array of 20th century efforts in psychedelic research, model psychosis has, once more, come to the foreground of psychedelic research. And yet, little has been made of where this peculiar, perhaps even intoxicatingly mad, the idea originates. This paper seeks to uncover the conceptual foundations underlying the early emergence of model psychosis. This narrative will explore the conceptual foundations behind their independent development of the concept of model psychosis, considering their similarities and differences. In the course of this examination, it becomes apparent that the definition of endogenous psychosis, which formed in the mid-19th century, is the direct product of emerging understandings of exogenous psychosis, or model psychosis. Ultimately, the goal is not merely to understand how and why model psychosis became thinkable but to examine how seemingly secondary concept changes can engender new ways of being a psychiatric subject.

Keywords: history of psychiatry, model psychosis, history of medicine, history of science

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Authors: Jang kyun Cho, Jeong-dong Lee

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The advent of the Internet, mobile communications, and social network services has stimulated social interactions among consumers, allowing people to affect one another’s innovation adoptions by exchanging information more frequently and more quickly. Previous diffusion models, such as the Bass model, however, face limitations in reflecting such recent phenomena in society. These models are weak in their ability to model interactions between agents; they model aggregated-level behaviors only. The agent based model, which is an alternative to the aggregate model, is good for individual modeling, but it is still not based on an economic perspective of social interactions so far. This study assumes the presence of social utility from other consumers in the adoption of innovation and investigates the effect of individual interactions on innovation diffusion by developing a new model called the interaction-based diffusion model. By comparing this model with previous diffusion models, the study also examines how the proposed model explains innovation diffusion from the perspective of economics. In addition, the study recommends the use of a small-world network topology instead of cellular automata to describe innovation diffusion. This study develops a model based on individual preference and heterogeneous social interactions using utility specification, which is expandable and, thus, able to encompass various issues in diffusion research, such as reservation price. Furthermore, the study proposes a new framework to forecast aggregated-level market demand from individual level modeling. The model also exhibits a good fit to real market data. It is expected that the study will contribute to our understanding of the innovation diffusion process through its microeconomic theoretical approach.

Keywords: innovation diffusion, agent based model, small-world network, demand forecasting

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Authors: Srikanth Pandurangi, Basheer Mohammed, Nezar Al Sayegh

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In order to meet the increasing demand for housing care for Kuwaiti citizens, the government authorities in Kuwait are undertaking a series of projects in the form of new large cities, outside the current urban area. Al Mutlaa City located to the north-west of the Kuwait Metropolitan Area is one such project out of the 15 planned new cities. The city accommodates a wide variety of residential developments, employment opportunities, commercial, recreational, health care and institutional uses. This paper examines the application of comprehensive transportation demand modeling works undertaken in VISUM platform to understand the future intracity and intercity travel distribution patterns in Kuwait. The scope of models developed varied in levels of detail: strategic model update, sub-area models representing future demand of Al Mutlaa City, sub-area models built to estimate the demand in the residential neighborhoods of the city. This paper aims at offering model update framework that facilitates easy integration between sub-area models and strategic national models for unified traffic forecasts. This paper presents the transportation demand modeling results utilized in informing the planning of multi-modal transportation system for Al Mutlaa City. This paper also presents the household survey data collection efforts undertaken using GPS devices (first time in Kuwait) and notebook computer based digital survey forms for interviewing representative sample of citizens and residents. The survey results formed the basis of estimating trip generation rates and trip distribution coefficients used in the strategic base year model calibration and validation process.

Keywords: innovative methods in transportation data collection, integrated public transportation system, traffic forecasts, transportation modeling, travel behavior

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Authors: M. Rafiur Rahman, M. Mezbah Uddin, Mohammad Irfan Uddin, M. Moinul Islam

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With a rapid development of offshore renewable energy industry, the research activities in regards of harnessing power from offshore wind and wave energy are increasing day by day. Integration of wind turbines and wave energy converters into one combined semi-submersible platform might be a cost-economy and beneficial option. In this paper, the coupled integrated dynamic analysis in the time domain (TD) of a simplified semi-submersible flap type concept (SFC) is accomplished via state-of-the-art numerical code referred as Simo-Riflex-Aerodyn (SRA). This concept is a combined platform consisting of a semi-submersible floater supporting a 5 MW horizontal axis wind turbine (WT) and three elliptical shaped flap type wave energy converters (WECs) on three pontoons. The main focus is to validate the numerical model of SFC with experimental results and perform the frequency domain (FD) and TD response analysis. The numerical analysis is performed using potential flow theory for hydrodynamics and blade element momentum (BEM) theory for aerodynamics. A variety of environmental conditions encompassing the functional & survival conditions for short-term sea (1-hour simulation) are tested to evaluate the sustainability of the SFC. The numerical analysis is performed in full scale. Finally, the time domain analysis of heave, pitch & surge motions is performed numerically using SRA and compared with the experimental results. Due to the simplification of the model, there are some discrepancies which are discussed in brief.

Keywords: coupled integrated dynamic analysis, SFC, time domain analysis, wave energy converters

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Authors: Yuchao Hua, Lingai Luo

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Thermal energy storage is of critical importance for the highly-efficient utilization of renewable energy sources. Over the past decades, single-tank thermocline technology has attracted much attention owing to its high cost-effectiveness. In the present work, we investigate the influence of the filler porosity’s non-uniform distribution on the thermal performance of the packed-bed sensible heat thermocline storage tanks on the basis of the analytical model obtained by the Laplace transform. It is found that when the total amount of filler materials (i.e., the integration of porosity) is fixed, the different porosity distributions can result in the significantly-different behaviors of outlet temperature and thus the varied charging and discharging efficiencies. Our results indicate that a non-uniform distribution of the fillers with the proper design can improve the heat storage performance without changing the total amount of the filling materials.

Keywords: energy storage, heat thermocline storage tank, packed bed, transient thermal analysis

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Authors: Retius Chifurira

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Logistic regression model is the most used regression model to predict meteorological drought probabilities. When the dependent variable is extreme, the logistic model fails to adequately capture drought probabilities. In order to adequately predict drought probabilities, we use the generalized linear model (GLM) with the quantile function of the generalized extreme value distribution (GEVD) as the link function. The method maximum likelihood estimation is used to estimate the parameters of the generalized extreme value (GEV) regression model. We compare the performance of the logistic and the GEV regression models in predicting drought probabilities for Zimbabwe. The performance of the regression models are assessed using the goodness-of-fit tests, namely; relative root mean square error (RRMSE) and relative mean absolute error (RMAE). Results show that the GEV regression model performs better than the logistic model, thereby providing a good alternative candidate for predicting drought probabilities. This paper provides the first application of GLM derived from extreme value theory to predict drought probabilities for a drought-prone country such as Zimbabwe.

Keywords: generalized extreme value distribution, general linear model, mean annual rainfall, meteorological drought probabilities

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Authors: Glauco M. M. M. Lustosa, João Paulo C. Costa, Sonia M. Zanetti, Mario Cilense, Leinig Antônio Perazolli, Maria Aparecida Zaghete

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The contamination of the environment has been one of the biggest problems of our time, mostly due to developments of many industries. SnO2 is an n-type semiconductor with band gap about 3.5 eV and has its electrical conductivity dependent of type and amount of modifiers agents added into matrix ceramic during synthesis process, allowing applications as sensing of gaseous pollutants on ambient. The chemical synthesis by polymeric precursor method consists in a complexation reaction between tin ion and citric acid at 90 °C/2 hours and subsequently addition of ethyleneglycol for polymerization at 130 °C/2 hours. It also prepared polymeric resin of zinc, cobalt and niobium ions. Stoichiometric amounts of the solutions were mixed to obtain the systems (Zn, Nb)-SnO2 and (Co, Nb) SnO2 . The metal immobilization reduces its segregation during the calcination resulting in a crystalline oxide with high chemical homogeneity. The resin was pre-calcined at 300 °C/1 hour, milled in Atritor Mill at 500 rpm/1 hour, and then calcined at 600 °C/2 hours. X-Ray Diffraction (XDR) indicated formation of SnO2 -rutile phase (JCPDS card nº 41-1445). The characterization by Scanning Electron Microscope of High Resolution showed spherical ceramic powder nanostructured with 10-20 nm of diameter. 20 mg of SnO2 -based powder was kept in 20 ml of isopropyl alcohol and then taken to an electrophoretic deposition (EPD) system. The EPD method allows control the thickness films through the voltage or current applied in the electrophoretic cell and by the time used for deposition of ceramics particles. This procedure obtains films in a short time with low costs, bringing prospects for a new generation of smaller size devices with easy integration technology. In this research, films were obtained in an alumina substrate with interdigital electrodes after applying 2 kV during 5 and 10 minutes in cells containing alcoholic suspension of (Zn, Nb)-SnO2 and (Co, Nb) SnO2 of powders, forming a sensing layer. The substrate has designed integrated micro hotplates that provide an instantaneous and precise temperature control capability when a voltage is applied. The films were sintered at 900 and 1000 °C in a microwave oven of 770 W, adapted by the research group itself with a temperature controller. This sintering is a fast process with homogeneous heating rate which promotes controlled growth of grain size and also the diffusion of modifiers agents, inducing the creation of intrinsic defects which will change the electrical characteristics of SnO2 -based powders. This study has successfully demonstrated a microfabricated system with an integrated micro-hotplate for detection of CO and NO2 gas at different concentrations and temperature, with self-heating SnO2 - based nanoparticles films, being suitable for both industrial process monitoring and detection of low concentrations in buildings/residences in order to safeguard human health. The results indicate the possibility for development of gas sensors devices with low power consumption for integration in portable electronic equipment with fast analysis. Acknowledgments The authors thanks to the LMA-IQ for providing the FEG-SEM images, and the financial support of this project by the Brazilian research funding agencies CNPq, FAPESP 2014/11314-9 and CEPID/CDMF- FAPESP 2013/07296-2.

Keywords: chemical synthesis, electrophoretic deposition, self-heating, gas sensor

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Authors: Ashhar Ahmed Shaikh, Ayush Tandon

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The swift reduction of fossil fuels from nature has crucial need for alternative energy sources to cater vital demand. It is essential to boost alternative energy sources to cover the continuously increasing demand for energy while minimizing the negative environmental impacts. Solar energy is one of the reliable sources that can generate energy. Solar energy is freely available in nature and is completely eco-friendly, and they are considered as the most promising power generating sources due to their easy availability and other advantages for the local power generation. This paper is to review the implementation of power electronic devices through Solar Energy Grid Integration System (SEGIS) to increase the efficiency. This paper will also concentrate on the future grid infrastructure and various other applications in order to make the grid smart. Development and implementation of a power electronic devices such as PV inverters and power controllers play an important role in power supply in the modern energy economy. Solar Energy Grid Integration System (SEGIS) opens pathways for promising solutions for new electronic and electrical components such as advanced innovative inverter/controller topologies and their functions, economical energy management systems, innovative energy storage systems with equipped advanced control algorithms, advanced maximum-power-point tracking (MPPT) suited for all PV technologies, protocols and the associated communications. In addition to advanced grid interconnection capabilities and features, the new hardware design results in small size, less maintenance, and higher reliability. The SEGIS systems will make the 'advanced integrated system' and 'smart grid' evolutionary processes to run in a better way. Since the last few years, there was a major development in the field of power electronics which led to more efficient systems and reduction of the cost per Kilo-watt. The inverters became more efficient and had reached efficiencies in excess of 98%, and commercial solar modules have reached almost 21% efficiency.

Keywords: solar energy grid integration systems, smart grid, advanced integrated system, power electronics

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Authors: Dorota Miroslaw-Swiatek, Mateusz Grygoruk, Sylwia Szporak

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We applied a two-dimensional surface water flow model with irregular wet boundaries. In this model, flow equations are in the form of a 2-D, non-linear diffusion equations which allows to account spatial variations in flow resistance and topography. Calculation domain to simulate the flow pattern in the floodplain is congruent with a Digital Elevation Model (DEM) grid. The rate and direction of sheet flow in wetlands is affected by vegetation type and density, therefore the developed model take into account spatial distribution vegetation resistance to the water flow. The model was tested in a part of the Biebrza Valley, of an outstanding heterogeneity in the elevation and flow resistance distributions due to various ecohydrological conditions and management measures. In our approach we used the highest-possible quality of the DEM in order to obtain hydraulic slopes and vegetation distribution parameters for the modelling. The DEM was created from the cloud of points measured in the LiDAR technology. The LiDAR reflects both the land surface as well as all objects on top of it such as vegetation. Depending on the density of vegetation cover the ability of laser penetration is variable. Therefore to obtain accurate land surface model the “vegetation effect” was corrected using data collected in the field (mostly the vegetation height) and satellite imagery such as Ikonos (to distinguish different vegetation types of the floodplain and represent them spatially). Model simulation was performed for the spring thaw flood in 2009.

Keywords: floodplain flow, Biebrza valley, model simulation, 2D surface flow model

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Authors: Young-Hyun Seo, Hyunwoo Park, Dong-Kyu Kim, Seung-Young Kho

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The purpose of this study is providing an improved mode choice model considering parameters including age grouping of prime-aged and old age. In this study, 2010 Household Travel Survey data were used and improper samples were removed through the analysis. Chosen alternative, date of birth, mode, origin code, destination code, departure time, and arrival time are considered from Household Travel Survey. By preprocessing data, travel time, travel cost, mode, and ratio of people aged 45 to 55 years, 55 to 65 years and over 65 years were calculated. After the manipulation, the mode choice model was constructed using LIMDEP by maximum likelihood estimation. A significance test was conducted for nine parameters, three age groups for three modes. Then the test was conducted again for the mode choice model with significant parameters, travel cost variable and travel time variable. As a result of the model estimation, as the age increases, the preference for the car decreases and the preference for the bus increases. This study is meaningful in that the individual and households characteristics are applied to the aggregate model.

Keywords: age grouping, aging, mode choice model, multinomial logit model

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Authors: Li Xiaoge, Wang Chaodong

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We introduce the first Chinese Coreference Resolution Model based on BERT (CCRM-BERT) and show that it significantly outperforms all previous work. The key idea is to consider the features of the mention, such as part of speech, width of spans, distance between spans, etc. And the influence of each features on the model is analyzed. The model computes mention embeddings that combine BERT with features. Compared to the existing state-of-the-art span-ranking approach, our model significantly improves accuracy on the Chinese OntoNotes benchmark.

Keywords: BERT, coreference resolution, deep learning, nature language processing

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Authors: Awol Seid Ebrie

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HIV results as an incurable disease, AIDS. After a person is infected with virus, the virus gradually destroys all the infection fighting cells called CD4 cells and makes the individual susceptible to opportunistic infections which cause severe or fatal health problems. Several studies show that the CD4 cells count is the most determinant indicator of the effectiveness of the treatment or progression of the disease. The objective of this paper is to investigate the progression of the disease over time among patient under HAART treatment. Two main approaches of the generalized multilevel ordinal models; namely the proportional odds model and the nonproportional odds model have been applied to the HAART data. Also, the multilevel part of both models includes random intercepts and random coefficients. In general, four models are explored in the analysis and then the models are compared using the deviance information criteria. Of these models, the random coefficients nonproportional odds model is selected as the best model for the HAART data used as it has the smallest DIC value. The selected model shows that the progression of the disease increases as the time under the treatment increases. In addition, it reveals that gender, baseline clinical stage and functional status of the patient have a significant association with the progression of the disease.

Keywords: nonproportional odds model, proportional odds model, random coefficients model, random intercepts model

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Authors: Babak Bashari Rad

Abstract:

A metamorphic computer virus uses different code transformation techniques to mutate its body in duplicated instances. Characteristics and function of new instances are mostly similar to their parents, but they cannot be easily detected by the majority of antivirus in market, as they depend on string signature-based detection techniques. The purpose of this research is to propose a Hidden Markov Model for classification of metamorphic viruses in executable files. In the proposed solution, portable executable files are inspected to extract the instructions opcodes needed for the examination of code. A Hidden Markov Model trained on portable executable files is employed to classify the metamorphic viruses of the same family. The proposed model is able to generate and recognize common statistical features of mutated code. The model has been evaluated by examining the model on a test data set. The performance of the model has been practically tested and evaluated based on False Positive Rate, Detection Rate and Overall Accuracy. The result showed an acceptable performance with high average of 99.7% Detection Rate.

Keywords: malware classification, computer virus classification, metamorphic virus, metamorphic malware, Hidden Markov Model

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Authors: Somoshree Datta, Chithra A. V., Sandeep Nithyanandan, Smitha K. K.

Abstract:

Space exploration has always been at the forefront of technological innovation, pushing the boundaries of human knowledge and capabilities. In recent years, the integration of Artificial Intelligence (AI) has revolutionized the field, offering unprecedented opportunities to enhance the efficiency, autonomy and intelligence of space missions. This survey paper aims to provide a comprehensive overview of the multifaceted applications of AI in space exploration, exploring the evolution of this synergy and its impact on mission success, scientific discovery, and the future of space endeavors. Indian Space Research Organization (ISRO) has achieved great feats in the recent moon mission (Chandrayaan-3) and sun mission (Aditya L1) by using artificial intelligence to enhance moon navigation as well as help young scientists to study the Sun even before the launch by creating AI-generated image visualizations. Throughout this survey, we will review key advancements, challenges and prospects in the intersection of AI and space exploration. As humanity continues its quest to explore the cosmos, the integration of AI promises to unlock new frontiers, reshape mission architectures, and redefine our understanding of the universe. This survey aims to serve as a comprehensive resource for researchers, engineers and enthusiasts interested in the dynamic and evolving landscape of AI applications in space exploration.

Keywords: artificial intelligence, space exploration, space missions, deep learning

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Authors: Heung Sun Yoon, Jong Tae Kim

Abstract:

In this paper, we present an activity diagram model for double-loop control self-adaptive braking system. Since activity diagram helps to improve visibility of self-adaption, we can easily find where improvement is needed on double-loop control. Double-loop control is adopted since the design conditions and actual conditions can be different. The system is reconfigured in runtime by using double-loop control. We simulated to verify and validate our model by using MATLAB. We compared single-loop control model with double-loop control model. Simulation results show that double-loop control provides more consistent brake power control than single-loop control.

Keywords: activity diagram, automotive, braking system, double-loop, self-adaptive, UML, vehicle

Procedia PDF Downloads 396