Search results for: data access

Authors: Mohammad Hadi Khorashadi Zadeh

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Many new applications and internet services have been emerged since the innovation of mobile networks and devices. However, these applications have problems of security, management, and performance in business environments. Cloud systems provide information transfer, management facilities, and security for virtual environments. Therefore, an innovative internet service and a business model are proposed in the present study for creating a secure and consolidated environment for managing the mobile information of organizations based on cloud virtual phones (CVP) infrastructures. Using this method, users can run Android and web applications in the cloud which enhance performance by connecting to other CVP users and increases privacy. It is possible to combine the CVP with distributed protocols and central control which mimics the behavior of human societies. This mix helps in dealing with sensitive data in mobile devices and facilitates data management with less application overhead.

Keywords: BYOD, mobile cloud computing, mobile security, information management

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Authors: Duncan Wallace, M-Tahar Kechadi

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In recent years, Machine Learning (ML) approaches have been successfully applied to an analysis of patient symptom data in the context of disease diagnosis, at least where such data is well codified. However, much of the data present in Electronic Health Records (EHR) are unlikely to prove suitable for classic ML approaches. Furthermore, as scores of data are widely spread across both hospitals and individuals, a decentralized, computationally scalable methodology is a priority. The focus of this paper is to develop a method to predict outliers in an out-of-hours healthcare provision center (OOHC). In particular, our research is based upon the early identification of patients who have underlying conditions which will cause them to repeatedly require medical attention. OOHC act as an ad-hoc delivery of triage and treatment, where interactions occur without recourse to a full medical history of the patient in question. Medical histories, relating to patients contacting an OOHC, may reside in several distinct EHR systems in multiple hospitals or surgeries, which are unavailable to the OOHC in question. As such, although a local solution is optimal for this problem, it follows that the data under investigation is incomplete, heterogeneous, and comprised mostly of noisy textual notes compiled during routine OOHC activities. Through the use of Deep Learning methodologies, the aim of this paper is to provide the means to identify patient cases, upon initial contact, which are likely to relate to such outliers. To this end, we compare the performance of Long Short-Term Memory, Gated Recurrent Units, and combinations of both with Convolutional Neural Networks. A further aim of this paper is to elucidate the discovery of such outliers by examining the exact terms which provide a strong indication of positive and negative case entries. While free-text is the principal data extracted from EHRs for classification, EHRs also contain normalized features. Although the specific demographical features treated within our corpus are relatively limited in scope, we examine whether it is beneficial to include such features among the inputs to our neural network, or whether these features are more successfully exploited in conjunction with a different form of a classifier. In this section, we compare the performance of randomly generated regression trees and support vector machines and determine the extent to which our classification program can be improved upon by using either of these machine learning approaches in conjunction with the output of our Recurrent Neural Network application. The output of our neural network is also used to help determine the most significant lexemes present within the corpus for determining high-risk patients. By combining the confidence of our classification program in relation to lexemes within true positive and true negative cases, with an inverse document frequency of the lexemes related to these cases, we can determine what features act as the primary indicators of frequent-attender and non-frequent-attender cases, providing a human interpretable appreciation of how our program classifies cases.

Keywords: artificial neural networks, data-mining, machine learning, medical informatics

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Authors: Izabel Cristina Zattar, Gilberto Passos Lima, Guilherme Schünemann de Oliveira

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In Brazil, there are several institutions committed to the development of new businesses based on product innovation. Among them are business incubators, universities and science institutes. Business incubators can be defined as nurseries for new companies, which may be in the technology segment, discussed in this article. Business incubators provide services related to infrastructure, such as physical space and meeting rooms. Besides these services, incubators also offer assistance in the form of information and communication, access to finance, relationship networks and business monitoring and mentoring processes. Business incubators support not all technology companies. One of the business incubators tasks is to assess the nature and feasibility of new business proposals. To assist this goal, this paper proposes a methodology for evaluating new business using the Analytic Hierarchy Process (AHP). This paper presents the concepts used in the assessing methodology application for new business, concepts that have been tested with positive results in practice. This study counts on three main steps: first, a hierarchy was built, based on new business manuals used by the business incubators. These books and manuals relate business selection requirements, such as the innovation status and other technological aspects. Then, a questionnaire was generated, in order to guide incubator experts in the parity comparisons at all hierarchy levels. The weights of each requirement are calculated from information obtained from the questionnaire responses. Finally, the proposed method was applied to evaluate five new business proposals, which were applying to be part of a company incubator. The main result is the classification of these new businesses, which helped the incubator experts to decide what companies were more eligible to work with. This classification may also be helpful to the decision-making process of business incubators in future selection processes.

Keywords: Analytic Hierarchy Process (AHP), Brazilian companies incubators, technology companies, incubator

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Authors: Dimitriu Corneliu-Ioan, Gheorghe FrațIlă

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Romania has one of the highest rates of road deaths among European Union Member States, and there is a concern that the country will not meet its goal of "zero deaths" by 2050. The European Union also aims to halve the number of people seriously injured in road accidents by 2030. Therefore, there is a need to improve road infrastructure safety management in Romania. The aim of this study is to analyze road accident data through statistical methods to assess the current state of road infrastructure safety in Bucharest. The study also aims to identify trends and make forecasts regarding serious road accidents and their consequences. The objective is to provide insights that can help prioritize measures to increase road safety, particularly in urban areas. The research utilizes statistical analysis methods, including exploratory analysis and descriptive statistics. Databases from the Traffic Police and the Romanian Road Authority are analyzed using Excel. Road risks are compared with the main causes of road accidents to identify correlations. The study emphasizes the need for better quality and more diverse collection of road accident data for effective analysis in the field of road infrastructure engineering. The research findings highlight the importance of prioritizing measures to improve road safety in urban areas, where serious accidents and their consequences are more frequent. There is a correlation between the measures ordered by road safety auditors and the main causes of serious accidents in Bucharest. The study also reveals the significant social costs of road accidents, amounting to approximately 3% of GDP, emphasizing the need for collaboration between local and central administrations in allocating resources for road safety. This research contributes to a clearer understanding of the current road infrastructure safety situation in Romania. The findings provide critical insights that can aid decision-makers in allocating resources efficiently and institutionally cooperating to achieve sustainable road safety. The data used for this study are collected from the Traffic Police and the Romanian Road Authority. The data processing involves exploratory analysis and descriptive statistics using the Excel tool. The analysis allows for a better understanding of the factors contributing to the current road safety situation and helps inform managerial decisions to eliminate or reduce road risks. The study addresses the state of road infrastructure safety in Bucharest and analyzes the trends and forecasts regarding serious road accidents and their consequences. It studies the correlation between road safety measures and the main causes of serious accidents. To improve road safety, cooperation between local and central administrations towards joint financial efforts is important. This research highlights the need for statistical data processing methods to substantiate managerial decisions in road infrastructure management. It emphasizes the importance of improving the quality and diversity of road accident data collection. The research findings provide a critical perspective on the current road safety situation in Romania and offer insights to identify appropriate solutions to reduce the number of serious road accidents in the future.

Keywords: road death rate, strategic objective, serious road accidents, road safety, statistical analysis

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Authors: Rudan Xue, Annika Moscati, Rehel Zeleke Kebede, Peter Johansson

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Successful buildings’ simulation and analysis inevitably require information exchange between multiple building information modeling (BIM) software. The BIM infor-mation exchange based on IFC is widely used. However, Industry Foundation Classifi-cation (IFC) files are not always reliable and information can get lost when using dif-ferent software for modeling and simulations. In this research, interviews with lighting simulation experts and a case study provided by a company producing lighting devices have been the research methods used to identify the necessary steps and data for suc-cessful information exchange between lighting simulation tools and authoring design tools. Model creation, information exchange, and model simulation have been identi-fied as key aspects for the success of information exchange. The paper concludes with recommendations for improved information exchange and more reliable simulations that take all the needed parameters into consideration.

Keywords: BIM, data exchange, interoperability issues, lighting simulations

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Authors: Paschal Arsein Mugabe

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This paper examines sustainable development planning in the context of environmental concerns in rural areas of the Tanzania. It challenges mainstream approaches to development, focusing instead upon transformative action for environmental justice. The goal is to help shape future sustainable development agendas in local government, international agencies and civil society organisations. Research methods: The approach of the study is geographical, but also involves various Trans-disciplinary elements, particularly from development studies, sociology and anthropology, management, geography, agriculture and environmental science. The research methods included thematic and questionnaire interviews, participatory tools such as focus group discussion, participatory research appraisal and expert interviews for primary data. Secondary data were gathered through the analysis of land use/cover data and official documents on climate, agriculture, marketing and health. Also several earlier studies that were made in the area provided an important reference base. Findings: The findings show that, agricultural sustainability in Tanzania appears likely to deteriorate as a consequence of climate change. Noteworthy differences in impacts across households are also present both by district and by income category. Also food security cannot be explained by climate as the only influencing factor. A combination of economic, political and socio-cultural context of the community are crucial. Conclusively, it is worthy knowing that people understand their relationship between climate change and their livelihood.

Keywords: agriculture, climate change, environment, sustainable development

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Authors: Ezra Yehuwalashet, Alireza Malehmir

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Blötberget mining area in central Sweden, part of the Bergslagen mineral district, is well known for its various type of mineralization particularly iron-oxide deposits since the 1600. To shed lights on the knowledge of the host rock structures, depth extent and tonnage of the mineral deposits and support deep mineral exploration potential in the study area, new ground gravity and existing aeromagnetic data (from the Geological Survey of Sweden) were used for interpretations and modelling. A major boundary separating a gravity low from a gravity high in the southern part of the study area is noticeable and likely representing a fault boundary separating two different lithological units. Gravity data and modeling offers a possible new target area in the southeast of the known mineralization while suggesting an excess high-density region down to 800 m depth.

Keywords: gravity, magnetics, ore deposit, geophysics

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Authors: Dhiraj Neupane

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Decentralized policy and practices have largely concentrated on the transformation of decision-making authorities from central to local institutions (or people) in the developing world. Such policy and practices always aimed for the equitable and efficient management of resources in the line of poverty reduction. The transformation of forest decision-making autonomy has also glorified as the best forest management alternatives to maximize the forest benefits and improve the livelihood of local people living nearby the forests. However, social heterogeneity and poor decision-making capacity of local institutions (or people) pose a nexus while managing the resources and sharing the forest benefits among the user households despite the policy objectives. The situation is severe in the lowland of Nepal, where forest resources have higher economic potential and user households have heterogeneous socio-economic conditions. The study discovered that utilizing the power of decision-making autonomy, user households were putting low values of timber considering the equitable access of timber to all user households as it is the most valuable product of community forest. Being the society is heterogeneous by socio-economic conditions, households of better economic conditions were always taking higher amount of forest benefits. The low valuation of timber has negative consequences on equitable benefit sharing and poor support to livelihood improvement of user households. Moreover, low valuation has possibility to increase the local demands of timber and increase the human pressure on forests.

Keywords: decentralized forest policy, Nepal, poverty, social heterogeneity, Terai

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Authors: Debra L. Stanley, Gabriela Wasileski

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Offenders face many challenges as they transition from being incarcerated to the community, ranging from housing and employment needs to long standing problems with addictions and mental health issues. A lack of appropriate behavioral health services in the more remote parts of the United States has led to a significant illegal substance abuse problem, housing instability, and unaddressed mental health and trauma issues. High rates of poverty and unemployment exacerbate the growing behavioral health issues, drug overdoses, co-occurring disorders, and crime that are so prevalent across rural communities. This study examines the challenges of rural jail reentry faced by offenders in a treatment capacity. The client-centered evidence-based program is uniquely designed to provide continuity of care that focuses on issues which affect rural communities. Prior to release from jail, individuals go through comprehensive assessment screenings to measure mental health and substance use disorder as well as trauma and prior crime victimization histories; the assessments help to target client-specific services. The quasi-experimental research design tracks clients throughout their recovery and reintegration into the community. Individuals in a rural program often do not have the benefit of easy access or peer mentoring that is so often found in urban recovery programs. Therefore, much of the support is provided through telehealth and e-services. The goal of this study is to explore the nature of rural reentry programs and measures of recidivism, drug overdoses, and other behavioral health needs and successful reentry to include stable housing and employment.

Keywords: jail reentry, rehabilitation, behavioral health, drug abuse, recidivism

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Authors: Silvia Arrate, Waldo Salud, Eloy París

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The wear of cutting tools is one of the most decisive elements when planning tunneling works, programming the maintenance stops and saving the optimum stock of spare parts during the evolution of the excavation. Being able to predict the behavior of cutting tools can give a very competitive advantage in terms of costs and excavation performance, optimized to the needs of the TBM itself. The incredible evolution of data science in recent years gives the option to implement it at the time of analyzing the key and most critical parameters related to machinery with the purpose of knowing how the cutting head is performing in front of the excavated ground. Taking this as a case study, Metro Line 3 of Guadalajara in Mexico will develop the feasibility of using Specific Energy versus data science applied over parameters of Torque, Penetration, and Contact Force, among others, to predict the behavior and status of cutting tools. The results obtained through both techniques are analyzed and verified in the function of the wear and the field situations observed in the excavation in order to determine its effectiveness regarding its predictive capacity. In conclusion, the possibilities and improvements offered by the application of digital tools and the programming of calculation algorithms for the analysis of wear of cutting head elements compared to purely empirical methods allow early detection of possible damage to cutting tools, which is reflected in optimization of excavation performance and a significant improvement in costs and deadlines.

Keywords: cutting tools, data science, prediction, TBM, wear

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Authors: Ankit Tyagi, Reet Kamal Tiwari, Naveen James

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Landslide is the major geo-environmental problem of Himalaya because of high ridges, steep slopes, deep valleys, and complex system of streams. They are mainly triggered by rainfall and earthquake and causing severe damage to life and property. In Uttarakhand, the Tehri reservoir rim area, which is situated in the lesser Himalaya of Garhwal hills, was selected for landslide hazard zonation (LHZ). The study utilized different types of data, including geological maps, topographic maps from the survey of India, Landsat 8, and Cartosat DEM data. This paper presents the use of a weighted overlay method in LHZ using fourteen causative factors. The various data layers generated and co-registered were slope, aspect, relative relief, soil cover, intensity of rainfall, seismic ground shaking, seismic amplification at surface level, lithology, land use/land cover (LULC), normalized difference vegetation index (NDVI), topographic wetness index (TWI), stream power index (SPI), drainage buffer and reservoir buffer. Seismic analysis is performed using peak horizontal acceleration (PHA) intensity and amplification factors in the evaluation of the landslide hazard index (LHI). Several digital image processing techniques such as topographic correction, NDVI, and supervised classification were widely used in the process of terrain factor extraction. Lithological features, LULC, drainage pattern, lineaments, and structural features are extracted using digital image processing techniques. Colour, tones, topography, and stream drainage pattern from the imageries are used to analyse geological features. Slope map, aspect map, relative relief are created by using Cartosat DEM data. DEM data is also used for the detailed drainage analysis, which includes TWI, SPI, drainage buffer, and reservoir buffer. In the weighted overlay method, the comparative importance of several causative factors obtained from experience. In this method, after multiplying the influence factor with the corresponding rating of a particular class, it is reclassified, and the LHZ map is prepared. Further, based on the land-use map developed from remote sensing images, a landslide vulnerability study for the study area is carried out and presented in this paper.

Keywords: weighted overlay method, GIS, landslide hazard zonation, remote sensing

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Authors: Sofia Hartati

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This research is aimed at describing training in early childhood education program empirically, describing teachers ability to plan lessons empirically, and acquiring empirical data as well as analyzing the influence of guided and independent training toward teachers competence in planning early childhood learning program. The method used is an experiment. It collected data with a population of 76 early childhood educators in Tunjung Teja Sub District area through random sampling technique and grouped into two namely 38 people in an experiment class and 38 people in a controlled class. The technique used for data collections is a test. The result of the research shows that there is a significant influence between training for guided educators toward Teachers Ability toward Planning Early Childhood Learning Program. Guided training has been proven to improve the ability to comprehend planning a learning program. The ability to comprehend planning a learning program owned by teachers of early childhood program comprises of 1) determining the characteristics and competence of students prior to learning; 2) formulating the objective of the learning; 3) selecting materials and its sequences; 4) selecting teaching methods; 5) determining the means or learning media; 6) selecting evaluation strategy as a part of teachers pedagogic competence. The result of this research describes a difference in the competence level of teachers who have joined guided training which is relatively higher than the teachers who joined the independent training. Guided training is one of an effective way to improve the knowledge and competence of early childhood educators.

Keywords: competence, planning, teachers, training

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Authors: Tannia Vindel, Carlos Mejia, Damaris Araujo, Carlos Velasquez, Darlin Trejo

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The DWDM (Dense Wavelenght Division Multiplexing) is in constant growth around the world by consumer demand to meet their needs. Since its inception in this operation arises the need for a system which enable us to expand the communication of an entire nation to improve the computing trends of their societies according to their customs and geographical location. The Honduran Company of Telecommunications (HONDUTEL), provides the internet services and data transport technology with a PDH and SDH, which represents in the Republic of Honduras C. A., the option of viability for the consumer in terms of purchase value and its ease of acquisition; but does not have the efficiency in terms of technological advance and represents an obstacle that limits the long-term socio-economic development in comparison with other countries in the region and to be able to establish a competition between telecommunications companies that are engaged in this heading. For that reason we propose to establish a new technological trend implemented in Europe and that is applied in our country that allows us to provide a data transfer in broadband as it is DWDM, in this way we will have a stable service and quality that will allow us to compete in this globalized world, and that must be replaced by one that would provide a better service and which must be in the forefront. Once implemented the DWDM is build upon the existing resources, such as the equipment used, and you will be given life to a new stage providing a business image to the Republic of Honduras C,A, as a nation, to ensure the data transport and broadband internet to a meaningful relationship. Same benefits in the first instance to existing customers and to all the institutions were bidden to these public and private need of such services.

Keywords: demultiplexers, light detectors, multiplexers, optical amplifiers, optical fibers, PDH, SDH

Procedia PDF Downloads 269

Authors: Lan Wu

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The declared transformation towards a ‘new electricity system dominated by renewable energy’ by China requires a cleaner electricity consumption mix with high shares of renewable energy sourced-electricity (RES-E). Unfortunately, integration of RES-E into Chinese electricity markets remains a problem pending more robust legal support, evidenced by the curtailment of wind and solar power as a consequence of integration constraints. The upcoming energy law of the PRC (energy law) is expected to provide such long-awaiting support and coordinate the existing diverse sector-specific laws to deal with the weak implementation that dampening the delivery of their desired regulatory effects. However, in the shadow of the COVID-19 crisis, it remains uncertain how this new energy law brings synergies to RES-E integration, mindful of the significant impacts of the pandemic. Through the theoretical lens of the interplay between China’s electricity reform and legislative development, the present paper investigates whether there is a paradigm shift in energy law regarding renewable energy integration compared with the existing sector-specific energy laws. It examines the 2020 draft for comments on the energy law and analyses its relationship with sector-specific energy laws focusing on RES-E integration. The comparison is drawn upon five key aspects of the RES-E integration issue, including the status of renewables, marketisation, incentive schemes, consumption mechanisms, access to power grids, and dispatching. The analysis shows that it is reasonable to expect a more open and well-organized electricity market enabling absorption of high shares of RES-E. The present paper concludes that a period of prosperous development of RES-E in the post-COVID-19 era can be anticipated with the legal support by the upcoming energy law. It contributes to understanding the signals China is sending regarding the transition towards a cleaner energy future.

Keywords: energy law, energy transition, electricity market reform, renewable energy integration

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Authors: Vanja Skoric

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The paper examines whether the impacts of artificial intelligence (AI) can be meaningfully addressed through the rights-based approach to AI design, investigating in particular how the inclusive, participatory process of assessing the AI impact would make this viable. There is a significant gap between envisioning rights-based AI systems and their practical application. Plausibly, internalizing human rights approach within AI design process might be achieved through identifying and assessing implications of AI features human rights, especially considering the case of vulnerable individuals and communities. However, there is no clarity or consensus on how such an instrument should be operationalised to usefully identify the impact, mitigate harms and meaningfully ensure relevant stakeholders’ participation. In practice, ensuring the meaningful inclusion of those individuals, groups, or entire communities who are affected by the use of the AI system is a prerequisite for a process seeking to assess human rights impacts and risks. Engagement in the entire process of the impact assessment should enable those affected and interested to access information and better understand the technology, product, or service and resulting impacts, but also to learn about their rights and the respective obligations and responsibilities of developers and deployers to protect and/or respect these rights. This paper will provide an overview of the study and practice of the participatory design process for AI, including inclusive impact assessment, its main elements, propose a framework, and discuss the lessons learned from the existing theory. In addition, it will explore pathways for enhancing and promoting individual and group rights through such engagement by discussing when, how, and whom to include, at which stage of the process, and what are the pre-requisites for meaningful and engaging. The overall aim is to ensure using the technology that works for the benefit of society, individuals, and particular (historically marginalised) groups.

Keywords: rights-based design, AI impact assessment, inclusion, harm mitigation

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Authors: Abdulkarim Nasir, Alhassan T. Yahaya, Hauwa T. Abdulkarim, Abdussalam El-Suleiman, Yakubu K. Abubakar

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The need for sustainable and reliable electricity supply in rural communities of Nigeria remains a pressing issue, given the country's vast energy deficit and the significant number of inhabitants lacking access to electricity. This research focuses on the development of a portable hybrid renewable energy system designed to provide a sustainable and efficient electricity supply to these underserved regions. The proposed system integrates multiple renewable energy sources, specifically solar and wind, to harness the abundant natural resources available in Nigeria. The design and development process involves the selection and optimization of components such as photovoltaic panels, wind turbines, energy storage units (batteries), and power management systems. These components are chosen based on their suitability for rural environments, cost-effectiveness, and ease of maintenance. The hybrid system is designed to be portable, allowing for easy transportation and deployment in remote locations with limited infrastructure. Key to the system's effectiveness is its hybrid nature, which ensures continuous power supply by compensating for the intermittent nature of individual renewable sources. Solar energy is harnessed during the day, while wind energy is captured whenever wind conditions are favourable, thus ensuring a more stable and reliable energy output. Energy storage units are critical in this setup, storing excess energy generated during peak production times and supplying power during periods of low renewable generation. These studies include assessing the solar irradiance, wind speed patterns, and energy consumption needs of rural communities. The simulation results inform the optimization of the system's design to maximize energy efficiency and reliability. This paper presents the development and evaluation of a 4 kW standalone hybrid system combining wind and solar power. The portable device measures approximately 8 feet 5 inches in width, 8 inches 4 inches in depth, and around 38 feet in height. It includes four solar panels with a capacity of 120 watts each, a 1.5 kW wind turbine, a solar charge controller, remote power storage, batteries, and battery control mechanisms. Designed to operate independently of the grid, this hybrid device offers versatility for use in highways and various other applications. It also presents a summary and characterization of the device, along with photovoltaic data collected in Nigeria during the month of April. The construction plan for the hybrid energy tower is outlined, which involves combining a vertical-axis wind turbine with solar panels to harness both wind and solar energy. Positioned between the roadway divider and automobiles, the tower takes advantage of the air velocity generated by passing vehicles. The solar panels are strategically mounted to deflect air toward the turbine while generating energy. Generators and gear systems attached to the turbine shaft enable power generation, offering a portable solution to energy challenges in Nigerian communities. The study also addresses the economic feasibility of the system, considering the initial investment costs, maintenance, and potential savings from reduced fossil fuel use. A comparative analysis with traditional energy supply methods highlights the long-term benefits and sustainability of the hybrid system.

Keywords: renewable energy, solar panel, wind turbine, hybrid system, generator

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Authors: Se-Han Lee, Kwang-Woo Go, Gwang-Hyun Ahn, Hee-Sung Park, Cheol-Kyu Han, Jun-Bo Shim, Geun-Chul Kang, Hyun-Jung Lee

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In recent years, with the advent of smart cars and the expansion of the market, the announcement of 'Adventures in Automotive Networks and Control Units' at the DEFCON21 conference in 2013 revealed that cars are not safe from hacking. As a result, the HEAVENS model considering not only the functional safety of the vehicle but also the security has been suggested. However, the HEAVENS model only presents a simple process, and there are no detailed procedures and activities for each process, making it difficult to apply it to the actual vehicle security vulnerability check. In this paper, we propose an automated attack database that systematically summarizes attack vectors, attack types, and vulnerable vehicle models to prepare for various car hacking attacks, and data flow diagrams that can detect various vulnerabilities and suggest a way to materialize the HEAVENS model.

Keywords: automotive security, HEAVENS, car hacking, security model, information security

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Authors: Sirus Sharifi, Arunima Haldar, S. V. D. Nageswara Rao

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The study attempts to analyze the impact of credit risk management practices of Indian scheduled commercial banks on their non-performing assets (NPAs). The data on credit risk practices was collected by administering a questionnaire to risk managers/executives at different banks. The data on NPAs (from 2012 to 2016) is sourced from Prowess, a database compiled by the Centre for Monitoring Indian Economy (CMIE). The model was estimated using cross-sectional regression method. As expected, the findings suggest that there is a negative relationship between credit risk management and NPA growth in Indian banks. The study has implications for Indian banks given the high level of losses, and the implementation of Basel III norms by the central bank, i.e. Reserve Bank of India (RBI). Evidence on credit risk management in Indian banks, and their relationship with non-performing assets held by them.

Keywords: credit risk, identification, Indian Banks, NPAs, ownership

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Authors: Chayanoot Sangwichien, Taweesak Reungpeerakul, Kyaw Thu

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Oil palm mills in Southern Thailand produced a large amount of biomass solid wastes. Lignocellulose biomass is the main source for production of biofuel which can be combined or used as an alternative to fossil fuels. Biomass composed of three main constituents of cellulose, hemicellulose, and lignin. Thermochemical conversion process applied to produce biofuel from biomass. Pyrolysis of biomass is the best way to thermochemical conversion of biomass into pyrolytic products (bio-oil, gas, and char). Operating parameters play an important role to optimize the product yields from fast pyrolysis of biomass. This present work concerns with the modeling of reaction kinetics parameters for fast pyrolysis of empty fruit bunch in the fluidized bed reactor. A global kinetic model used to predict the product yields from fast pyrolysis of empty fruit bunch. The reaction temperature and vapor residence time parameters are mainly affected by product yields of EFB pyrolysis. The reaction temperature and vapor residence time parameters effects on empty fruit bunch pyrolysis are considered at the reaction temperature in the range of 450-500˚C and at a vapor residence time of 2 s, respectively. The optimum simulated bio-oil yield of 53 wt.% obtained at the reaction temperature and vapor residence time of 450˚C and 2 s, 500˚C and 1 s, respectively. The simulated data are in good agreement with the reported experimental data. These simulated data can be applied to the performance of experiment work for the fast pyrolysis of biomass.

Keywords: kinetics, empty fruit bunch, fast pyrolysis, modeling

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Authors: Azadeh Mottaghi, Reyhaneh Yousefi, Saeed Safari

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Background: Bariatric surgery is widely proposed as the most effective approach to mitigate the growing pace of morbid obesity. As bariatric surgery candidates suffer from pre-existing nutritional deficiencies, it is of great importance to assess nutritional status of candidates before surgery in order to establish appropriate nutritional interventions. Objectives: The present study assessed and represented baseline data according to the nutritional status among candidates for bariatric surgery. Methods: A cross-sectional analysis of pre-surgery data was collected on 170 morbidly obese patients undergoing bariatric surgery between October 2017 and February 2018. Dietary intake data (evaluated through 147-item food frequency questionnaire), anthropometric measures and biochemical parameters were assessed. Results: Participants included 145 females (25 males) with average age of 37.3 ± 10.2 years, BMI of 45.7 ± 6.4 kg/m² and reported to have a total of 72.3 ± 22.2 kg excess body weight. The most common nutritional deficiencies referred to iron, ferritin, transferrin, albumin, vitamin B12, and vitamin D, the prevalence of which in the study population were as followed; 6.5, 6.5, 3, 2, 17.6 and 66%, respectively. Mean energy, protein, fat, and carbohydrate intake were 3887.3 ± 1748.32 kcal/day, 121.6 ± 57.1, 144.1 ± 83.05, and 552.4 ± 240.5 gr/day, respectively. The study population consumed lower levels of iron, calcium, folic acid, and vitamin B12 compared to the Dietary Reference Intake (DRI) recommendations (2, 26, 2.5, and 13%, respectively). Conclusion: According to the poor dietary quality of bariatric surgery candidates, leading to nutritional deficiencies pre-operatively, close monitoring and tailored supplementation pre- and post-bariatric surgery are required.

Keywords: bariatric surgery, food frequency questionnaire, obesity, nutritional status

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Authors: Maria Albuquerque, Miguel Matias, Ângelo Sá, Juliana Sousa, Maria Manuel Mouzinho

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Obesity is a frequent disease in Portugal. The surgical treatment is very effective and has an indication when there is a failure of the medical treatment. Although massive weight loss is associated with considerable health gains, these patients are characterized by a variable degree of dermolipodistrophy. In some cases, there is even the development of physical symptoms such as intertriginous, and some degree of psychological distress is present. In almost all cases, a desire for a better body contour, which inhibits some aspects of social life, is a fact. A prospective study was made to access the impact of body contouring surgery in the quality of life of patients who underwent a massive weight lost correction surgical procedure at Centro Hospitalar de Lisboa Central between January 2020 and December 2021. The patients were submitted to the Body Q subjective questionnaire adapted for the Portuguese language and accessed for the following categories: Anguish with Appearance, Contempt with Body Image, Satisfaction with the Abdomen, and Overall Satisfaction with the Body. The questionnaire was repeated at the 6 months mark. A total of 80 patients were sampled. The sex distribution was 79 female and 1 male. The median BMI index before surgery was inferior to 28%. The pre operatory questionnaire showed high scores for Anguish with Appearance and low scores for the body image self-evaluation. Overall, there was an improvement of at least 50% in all the evaluated scores. Additionally, a correlation was found between abdominoplasty and the contempt with body image and satisfaction with the abdomen (p-value <0.05). Massive weight loss is associated with important body deformities that have a significant impact on the patient’s personal and social life. Body contouring surgery is then vital for these patients as it implicates major aesthetic and functional benefits.

Keywords: abdominoplasty, cruroplasty, obesity, massive weight loss

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Authors: Maria Pavlova

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In our days, it is possible to put the camera on different vehicles like quadcopter, train, airplane and etc. The camera also can be the input sensor in many different systems. That means the object recognition like non separate part of monitoring control can be key part of the most intelligent systems. The aim of this paper is to focus of the object recognition process during vehicles movement. During the vehicle’s movement the camera takes pictures from the environment without storage in Data Base. In case the camera detects a special object (for example human or animal), the system saves the picture and sends it to the work station in real time. This functionality will be very useful in emergency or security situations where is necessary to find a specific object. In another application, the camera can be mounted on crossroad where do not have many people and if one or more persons come on the road, the traffic lights became the green and they can cross the road. In this papers is presented the system has solved the aforementioned problems. It is presented architecture of the object recognition system includes the camera, Raspberry platform, GPS system, neural network, software and Data Base. The camera in the system takes the pictures. The object recognition is done in real time using the OpenCV library and Raspberry microcontroller. An additional feature of this library is the ability to display the GPS coordinates of the captured objects position. The results from this processes will be sent to remote station. So, in this case, we can know the location of the specific object. By neural network, we can learn the module to solve the problems using incoming data and to be part in bigger intelligent system. The present paper focuses on the design and integration of the image recognition like a part of smart systems.

Keywords: camera, object recognition, OpenCV, Raspberry

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Authors: Kyungsuk Cho, Seungun Chae, Jihun Choi

Abstract:

Elevators are examined as one of evacuation methods in super-tall buildings. However, data on the use of elevators for evacuation at a fire are extremely scarce. Therefore, a test to measure delay time in using an evacuation elevator was conducted. In the test, time taken to get on and get off an elevator was measured and the case in which people gave up boarding when the capacity of the elevator was exceeded was also taken into consideration. 170 men and women participated in the test, 130 of whom were young people (20 ~ 50 years old) and 40 were senior citizens (over 60 years old). The capacity of the elevator was 25 people and it travelled between the 2nd and 4th floors. A video recording device was used to analyze the test. An elevator at an ordinary building, not a super-tall building, was used in the test to measure delay time in getting on and getting off an elevator. In order to minimize interference from other elements, elevator platforms on the 2nd and 4th floors were partitioned off. The elevator travelled between the 2nd and 4th floors where people got on and off. If less than 20 people got on the elevator which was empty, the data were excluded. If the elevator carrying 10 passengers stopped and less than 10 new passengers got on the elevator, the data were excluded. Getting-on an empty elevator was observed 49 times. The average number of passengers was 23.7, it took 14.98 seconds for the passengers to get on the empty elevator and the load factor was 1.67 N/s. It took the passengers, whose average number was 23.7, 10.84 seconds to get off the elevator and the unload factor was 2.33 N/s. When an elevator’s capacity is exceeded, the excessive number of people should get off. Time taken for it and the probability of the case were measure in the test. 37% of the times of boarding experienced excessive number of people. As the number of people who gave up boarding increased, the load factor of the ride decreased. When 1 person gave up boarding, the load factor was 1.55 N/s. The case was observed 10 times, which was 12.7% of the total. When 2 people gave up boarding, the load factor was 1.15 N/s. The case was observed 7 times, which was 8.9% of the total. When 3 people gave up boarding, the load factor was 1.26 N/s. The case was observed 4 times, which was 5.1% of the total. When 4 people gave up boarding, the load factor was 1.03 N/s. The case was observed 5 times, which was 6.3% of the total. Getting-on and getting-off time data for people who can walk freely were obtained from the test. In addition, quantitative results were obtained from the relation between the number of people giving up boarding and time taken for getting on. This work was supported by the National Research Council of Science & Technology (NST) grant by the Korea government (MSIP) (No. CRC-16-02-KICT).

Keywords: evacuation elevator, super tall buildings, evacuees, delay time

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Authors: Rohollah Asadian Kohestani, Nazanin Sedghi

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As the number of banks and financial institutions working in Iran has been significantly increased, the attracting and retaining customers and encouraging them to continually use the modern banking services have been important and vital issues. Therefore, there would be a serious competition without a deep perception of consumers and fitness of banking services with their needs in the current economic conditions of Iran. It should be noted that concepts such as 'brand equity' is defined based on the view of consumers; however, it is also focused by shareholders, competitors and other beneficiaries of a firm in addition to bank and its consumers. This study examines the impact of brand equity on the competitive advantage in the banking industry as intensive competition between brands of different banks leads to pay more attention to the brands. This research is based on the Aaker’s model examining the impact of four dimensions of brand equity on the competitive advantage of private banks in Behshahr city. Moreover, conducting an applied research and data analysis has been carried out by a descriptive method. Data collection was done using literature review and questionnaire. A 'simple random' methodology was selected for sampling staff of banks while sampling methodology to select consumers of banks was the distribution of questionnaire between staff and consumers of five private banks including Tejarat, Mellat, Refah K., Ghavamin and, Tose’e Ta’avon banks. Results show that there is a significant relationship between brand equity and their competitive advantage. In this research, software of SPSS 16 and LISREL 8.5, as well as different methods of descriptive inferential statistics for analyzing data and test hypotheses, were employed.

Keywords: brand awareness, brand loyalty, brand equity, competitive advantage

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Authors: Timothy Scheinert, Eliza Wright

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Background: Link Health is a Boston-based non-profit leveraging in-person and digital platforms to promote health equity. Its primary aim is to financially support low-income individuals through enrollment in federal benefit programs. This study examines the monetary impact of enrollment in several benefit programs. Methodologies: Approximately 17,000 individuals have been screened for eligibility via digital outreach, community events, and in-person clinics. Enrollment and financial distributions are evaluated across programs, including the Affordable Connectivity Program (ACP), Lifeline, LIHEAP, Transitional Aid to Families with Dependent Children (TAFDC), and the Supplemental Nutrition Assistance Program (SNAP). Major Findings: A total of 1,895 individuals have successfully applied, collectively distributing an estimated $1,288,152.00 in aid. The largest contributors to this sum include: ACP: 1,149 enrollments, $413,640 distributed annually. Child Care Financial Assistance (CCFA): 15 enrollments, $240,000 distributed annually. Lifeline: 602 enrollments, $66,822 distributed annually. LIHEAP: 25 enrollments, $48,750 distributed annually. SNAP: 41 enrollments, $123,000 distributed annually. TAFDC: 21 enrollments, $341,760 distributed annually. Conclusions: These results highlight the role of targeted outreach and effective enrollment processes in promoting access to federal benefit programs. High enrollment rates in ACP and Lifeline demonstrate a considerable need for affordable broadband and internet services. Programs like CCFA and TAFDC, despite lower enrollment numbers, provide sizable support per individual. This analysis advocates for continued funding of federal benefit programs. Future efforts can be made to develop screening tools that identify eligibility for multiple programs and reduce the complexity of enrollment.

Keywords: benefits, childcare, connectivity, equity, nutrition

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Authors: Ramin Karimi

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One of common highly mobile wireless ad hoc networks is Vehicular Ad Hoc Networks. Hence routing in vehicular ad hoc network (VANET) has attracted much attention during the last few years. VANET is characterized by its high mobility of nodes and specific topology patterns. Moreover these networks encounter a significant loss rate and a very short duration of communication. In vehicular ad hoc networks, one of challenging is routing of data due to high speed mobility and changing topology of vehicles. Geographic routing protocols are becoming popular due to advancement and availability of GPS devices. Delay Tolerant Networks (DTNs) are a class of networks that enable communication where connectivity issues like sparse connectivity, intermittent connectivity; high latency, long delay, high error rates, asymmetric data rate, and even no end-to-end connectivity exist. In this paper, we review the existing Geographic Routing Protocols for VANETs and also provide a qualitative comparison of them.

Keywords: vehicular ad hoc networks, mobility, geographic routing, delay tolerant networks

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Authors: Saad Bin Nasir

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This research will examine the impact of corporate governance on firm performance in family and non-family owned firms in Pakistan. For the purpose of this research, corporate governance mechanisms which included are board size, board composition, leadership structure, board meetings are taken as independent variable and firm performance taken as dependent variable and it will be measured with return on asset and return on equity. Firm size and firm’s age will be taken as control variables. Secondary data will collect from audited annul reports of companies and panel data regression model will applied, to check the impact of corporate governance on firm performance.

Keywords: board size, board composition, Leadership Structure, board meetings, firm performance, family and non-family owned firms

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Authors: Karim Hamidi Machekposhti, Hossein Sedghi, Abdolrasoul Telvari, Hossein Babazadeh

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Rainfall and runoff phenomenon is a chaotic and complex outcome of nature which requires sophisticated modelling and simulation methods for explanation and use. Time Series modelling allows runoff data analysis and can be used as forecasting tool. In the paper attempt is made to model river runoff data and predict the future behavioural pattern of river based on annual past observations of annual river runoff. The river runoff analysis and predict are done using ARIMA model. For evaluating the efficiency of prediction to hydrological events such as rainfall, runoff and etc., we use the statistical formulae applicable. The good agreement between predicted and observation river runoff coefficient of determination (R²) display that the ARIMA (4,1,1) is the suitable model for predicting Karkheh River runoff at Iran.

Keywords: time series modelling, ARIMA model, river runoff, Karkheh River, CLS method

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Authors: Claire Williams

Abstract:

Randomised controlled Trials (RCTs) of efficacy are still perceived as the gold standard for the generation of evidence, and whilst advances in data collection methods are well developed, this progress has not been matched for the reporting of adverse events (AEs). Assessment and reporting of AEs in clinical trials are fraught with human error and inefficiency and are extremely time and resource intensive. Recent research conducted into the quality of reporting of AEs during clinical trials concluded it is substandard and reporting is inconsistent. Investigators commonly send reports to sponsors who are incorrectly categorised and lacking in critical information, which can complicate the detection of valid safety signals. In our presentation, we will describe an electronic data capture system, which has been designed to support clinical trial processes by reducing the resource burden on investigators, improving overall trial efficiencies, and making trials safer for patients. This proprietary technology was developed using expertise proven in the delivery of the world’s first prospective, phase 3b real-world trial, ‘The Salford Lung Study, ’ which enabled robust safety monitoring and reporting processes to be accomplished by the remote monitoring of patients’ EHRs. This technology enables safety alerts that are pre-defined by the protocol to be detected from the data extracted directly from the patients EHR. Based on study-specific criteria, which are created from the standard definition of a serious adverse event (SAE) and the safety profile of the medicinal product, the system alerts the investigator or study team to the safety alert. Each safety alert will require a clinical review by the investigator or delegate; examples of the types of alerts include hospital admission, death, hepatotoxicity, neutropenia, and acute renal failure. This is achieved in near real-time; safety alerts can be reviewed along with any additional information available to determine whether they meet the protocol-defined criteria for reporting or withdrawal. This active surveillance technology helps reduce the resource burden of the more traditional methods of AE detection for the investigators and study teams and can help eliminate reporting bias. Integration of multiple healthcare data sources enables much more complete and accurate safety data to be collected as part of a trial and can also provide an opportunity to evaluate a drug’s safety profile long-term, in post-trial follow-up. By utilising this robust and proven method for safety monitoring and reporting, a much higher risk of patient cohorts can be enrolled into trials, thus promoting inclusivity and diversity. Broadening eligibility criteria and adopting more inclusive recruitment practices in the later stages of drug development will increase the ability to understand the medicinal products risk-benefit profile across the patient population that is likely to use the product in clinical practice. Furthermore, this ground-breaking approach to AE detection not only provides sponsors with better-quality safety data for their products, but it reduces the resource burden on the investigator and study teams. With the data taken directly from the source, trial costs are reduced, with minimal data validation required and near real-time reporting enables safety concerns and signals to be detected more quickly than in a traditional RCT.

Keywords: more comprehensive and accurate safety data, near real-time safety alerts, reduced resource burden, safer trials

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Authors: Julio Jesus Salazar, Julio Jesus De Lama

Abstract:

the fundamental objective of hydrological studies applied to the engineering field is to determine the statistically consistent volumes or water flows that, in each case, allow us to size or design a series of elements or structures to effectively manage and develop a river basin. To determine these values, there are several ways of working within the framework of traditional hydrology: (1) Study each of the factors that influence the hydrological cycle, (2) Study the historical behavior of the hydrology of the area, (3) Study the historical behavior of hydrologically similar zones, and (4) Other studies (rain simulators or experimental basins). Of course, this range of studies in a certain basin is very varied and complex and presents the difficulty of collecting the data in real time. In this complex space, the study of variables can only be overcome by collecting and transmitting data to decision centers through the Internet of things and artificial intelligence. Thus, this research work implemented the learning project of the sub-basin of the Shullcas river in the Andean basin of the Mantaro river in Peru. The sensor firmware to collect and communicate hydrological parameter data was programmed and tested in similar basins of the European Union. The Machine Learning applications was programmed to choose the algorithms that direct the best solution to the determination of the rainfall-runoff relationship captured in the different polygons of the sub-basin. Tests were carried out in the mountains of Europe, and in the sub-basins of the Shullcas river (Huancayo) and the Yauli river (Jauja) with heights close to 5000 m.a.s.l., giving the following conclusions: to guarantee a correct communication, the distance between devices should not pass the 15 km. It is advisable to minimize the energy consumption of the devices and avoid collisions between packages, the distances oscillate between 5 and 10 km, in this way the transmission power can be reduced and a higher bitrate can be used. In case the communication elements of the devices of the network (internet of things) installed in the basin do not have good visibility between them, the distance should be reduced to the range of 1-3 km. The energy efficiency of the Atmel microcontrollers present in Arduino is not adequate to meet the requirements of system autonomy. To increase the autonomy of the system, it is recommended to use low consumption systems, such as the Ashton Raggatt McDougall or ARM Cortex L (Ultra Low Power) microcontrollers or even the Cortex M; and high-performance direct current (DC) to direct current (DC) converters. The Machine Learning System has initiated the learning of the Shullcas system to generate the best hydrology of the sub-basin. This will improve as machine learning and the data entered in the big data coincide every second. This will provide services to each of the applications of the complex system to return the best data of determined flows.

Keywords: hydrology, internet of things, machine learning, river basin

Procedia PDF Downloads 165