Search results for: information adoption

Authors: Avinash Kumar Ranjan, Akash Anand

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The Land Surface Temperature (LST) is an essential factor accompanying to rise urban heat and climate warming within a city in micro level. It is also playing crucial role in global change study as well as radiation budgets measuring in heat balance studies. The information of LST is very substantial to recognize the urban climatology, ecological changes, anthropological and environmental interactions etc. The Chief motivation of present study focus on time series of ANN model that taken a sequence of LST values of 2000, 2008 and 2016, realize the pattern of variation within the data set and predict the LST values for 2024 and 2032. The novelty of this study centers on evaluation of LST using series of multi-temporal MODIS (MOD 11A2) satellite data by Maximum Value Composite (MVC) techniques. The results derived from this study endorse the proficiency of Geoinformatics Technology with integration of ANN to gain knowledge, understanding and building of precise forecast from the complex physical world database. This study will also focus on influence of Land Use/ Land Cover (LU/LC) variation on Land Surface Temperature.

Keywords: LST, geoinformatics technology, ANN, MODIS satellite imagery, MVC

Procedia PDF Downloads 238

Authors: Meng Sun, Bin Wei

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In the past decades, design-build has become a more popular project delivery system especially for the large scaled infrastructure project in North America. It provides a one-stop shopping system for the client therefore improves the efficiency of construction, and reduces the risks and overall cost for the clients. Compared to the project with traditional delivery method, design-build project requires contractor and designer to work together efficiently to deliver the best-value solutions through the construction process. How to facilitate a solid integration and efficient interaction between contractor and designer often affects the schedule, budget and quality of the construction therefore becomes a key factor to the success of a design-build project. This paper presents a concept of using modern mobile cloud technology to provide an integrated solution during the design-build construction. It uses mobile cloud architecture to provide a platform for real-time field progress, change request approval, job progress log, and project time entry with devices integration for field information and communications. The paper uses a real filed change notice as an example to demonstrate how mobile cloud technology applies in a design-build project and how it can improve the project efficiency.

Keywords: cloud, design-build, field change notice, mobile application

Procedia PDF Downloads 246

Authors: Kittipong Tissayakorn, Fumio Akagi, Yu Song

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Manufacturers have been exploring innovative strategies to achieve and sustain competitive advantages as they face a new era of intensive global competition. Such strategy is known as Supply Chain Management (SCM), which has gained a tremendous amount of attention from both researchers and practitioners over the last decade. Supply chain management (SCM) is considered as the most popular operating strategy for improving organizational competitiveness in the twenty-first century. It has attracted a lot of attention recently due to its role involving all of the activities in industrial organizations, ranging from raw material procurement to final product delivery to customers. Well-designed supply chain systems can substantially improve efficiency and product quality, and eventually enhance customer satisfaction and profitability. In this paper, a manufacturing engineering perspective on supply chain integration is presented. Research issues discussed include the product and process design for the supply chain, design evaluation of manufacturing in the supply chain, agent-based techniques for supply chain integration, intelligent information for sharing across the supply chain, and a development of standards for product, process, and production data exchange to facilitate electronic commerce. The objective is to provide guidelines and references for manufacturing engineers and researchers interested in supply chain integration.

Keywords: supply chain, supply chain management, supply chain integration, manufacturing industries

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Authors: Julie Wittmannová, Petr Šeda

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Quality of life measurements (QLF) help to evaluate interventions programs in different groups of persons with special needs. Our presentation deals with QLF of persons with addiction in relation to the physical activity (PA), type of addiction, age, gender and other variables. The aim of presentation is to summarize the basic findings and offer thoughts for questions arose. Methods: SQUALA (Subjective Quality of Life Analysis); SEIQoL (Schedule for the Evaluation of Individual Quality of Life); questionnaire of own construction. The results are evaluated by Mann­Whitney U test and Kruskall­Wallis ANOVA test (p ≤ 0,05). Sample of 64 participants – clients of aftercare center, aged 18 plus. Findings: Application of the methods SQUALA and SEIQoL in the chosen population seems appropriate, the obtaining information regarding the QLF correlate to intervention program topics, the need of an activelifestyle and health related topics in persons with addiction is visible. Conclusions or Implications: The subjective evaluation of quality of life of Aftercare clients is an important part of evaluation process, especially used to evaluate satisfaction with offered services and programs. Techniques SQUALA and SEIQoL gave us the desired outcomes.

Keywords: adapted physical activity, addiction, quality of life, physical activity, aftercare

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Authors: Cem Isik Dogru, Salih Tekin, Kursad Derinkuyu

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Electric vehicle (EV) carsharing is an alternative method to tackle urban transportation problems. This method can be applied by several options. One of the options is the one-way carsharing, which allow an EV to be taken at a designated location and leaving it on another specified location customer desires. Although it may increase users’ satisfaction, the issues, namely, demand dissatisfaction, relocation of EVs and charging schedules, must be dealt with. Also, excessive electricity has to be stored in batteries of EVs. To cope with aforementioned issues, two-step mixed integer programming (MIP) model is proposed. In first step, the integer programming model is used to determine amount of electricity to be sold to the grid in terms of time periods for extra profit. Determined amounts are provided from the batteries of EVs. Also, this step works in day-ahead electricity markets with forecast of periodical electricity prices. In second step, other MIP model optimizes daily operations of one-way carsharing: charging-discharging schedules, relocation of EVs to serve more demand and renting to maximize the profit of EV fleet owner. Due to complexity of the models, heuristic methods are introduced to attain a feasible solution and different price information scenarios are compared.

Keywords: electric vehicles, forecasting, mixed integer programming, one-way carsharing

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Authors: Md. Enamul Haque, Abdullah Al Kaisan, Mahmudur R. Saniat, Aminur Rahman

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In this paper, we have implemented both sequential and parallel version of fractal image compression algorithms using CUDA (Compute Unified Device Architecture) programming model for parallelizing the program in Graphics Processing Unit for medical images, as they are highly similar within the image itself. There is several improvements in the implementation of the algorithm as well. Fractal image compression is based on the self similarity of an image, meaning an image having similarity in majority of the regions. We take this opportunity to implement the compression algorithm and monitor the effect of it using both parallel and sequential implementation. Fractal compression has the property of high compression rate and the dimensionless scheme. Compression scheme for fractal image is of two kinds, one is encoding and another is decoding. Encoding is very much computational expensive. On the other hand decoding is less computational. The application of fractal compression to medical images would allow obtaining much higher compression ratios. While the fractal magnification an inseparable feature of the fractal compression would be very useful in presenting the reconstructed image in a highly readable form. However, like all irreversible methods, the fractal compression is connected with the problem of information loss, which is especially troublesome in the medical imaging. A very time consuming encoding process, which can last even several hours, is another bothersome drawback of the fractal compression.

Keywords: accelerated GPU, CUDA, parallel computing, fractal image compression

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Authors: Meng-Tzu Cheng, Louisa Rosenheck, Chen-Yen Lin, Eric Klopfer

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The purpose of the research is to explore some of the ways in which gameplay data can be analyzed to yield results that feedback into the learning ecosystem. Back-end data for all users as they played an MMOG, The Radix Endeavor, was collected, and this study reports the analyses on a specific genetics quest by using the data mining techniques, including the decision tree method. In the study, different reasons for quest failure between participants who eventually succeeded and who never succeeded were revealed. Regarding the in-game tools use, trait examiner was a key tool in the quest completion process. Subsequently, the results of decision tree showed that a lack of trait examiner usage can be made up with additional Punnett square uses, displaying multiple pathways to success in this quest. The methods of analysis used in this study and the resulting usage patterns indicate some useful ways that gameplay data can provide insights in two main areas. The first is for game designers to know how players are interacting with and learning from their game. The second is for players themselves as well as their teachers to get information on how they are progressing through the game, and to provide help they may need based on strategies and misconceptions identified in the data.

Keywords: MMOG, decision tree, genetics, gaming-learning interaction

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Authors: Julio Manuel De Luis Ruiz, Javier Sedano Cibrián, RubéN Pérez Álvarez, Raúl Pereda García, Felipe Piña García

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Nowadays it is common to resort to aerial photography to carry out the prospection and/or exploration of archaeological sites. In this sense, the classic 3D models are being applied to investigate the direction towards which the generally subterranean structures of an archaeological site may continue and therefore, to help in making the decisions that define the location of new excavations. In recent years, Unmanned Aerial Vehicles (UAVs) have been applied as the vehicles that carry the sensor. This implies certain advantages, such as the possibility of including low-cost sensors, given that these vehicles can carry the sensor at relatively low altitudes. Due to this, low-cost dual sensors have recently begun to be used. This new equipment can collaborate with classic Digital Elevation Models (DEMs) in the exploration of archaeological sites, but this entails the need for a methodological setting to optimise the acquisition, processing and exploitation of the information provided by low-cost dual sensors. This research focuses on the design of an appropriate workflow to obtain 3D models with low-cost sensors carried on UAVs, both in the RGB and thermal domains. All the foregoing has been applied to the archaeological site of Juliobriga, located in Cantabria (Spain).

Keywords: process optimization, RGB models, thermal models, , UAV, workflow

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Authors: Yiwen Jin, Jing Xiao, Pinfang Su

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The idea of adapting authentic materials in language teaching is from the communicative method in the 1970s. Different from the language in language textbooks, authentic materials is not deliberately written, it is from the native speaker’s real life and contains real information, which can meet social needs. It could improve learners ' interest, create authentic context and improve learners ' communicative competence. Authentic materials play an important role in CFL（Chinese as a foreign language） classroom. Different types of authentic materials can be used in different ways during learning and teaching. Because of the COVID-19 pandemic，a lot of Chinese learners are learning Chinese without the real language environment. Although there are some well-written textbooks, there is a certain distance between textbook language materials and daily life. Learners cannot automatically fill this gap. That is why it is necessary to apply authentic materials as a supplement to the language textbook to create the real context. Chinese teachers around the world are working together, trying to integrate the resources and apply authentic materials through different approach. They apply authentic materials in the form of new textbooks, manuals, apps and short videos they collect and create to help Chinese learning and teaching. A review of previous research on authentic materials and the Chinese teachers’ attempt to adapt it in the classroom are offered in this manuscript.

Keywords: authentic materials, Chinese as a second language, developmental use of digital resources, materials development for language teaching

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Authors: Esther Liyanage, Indrajith Liyanage, Masih Khan

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Neck pain has become a common epidemiological problem. One of the reasons for this is a sedentary way of life, connected with using a personal computer during all daily activities. Work place and work duration has not been properly adapted to the personal physical conditions of these employees. During 1990’s the importance of workstation design and work methods, or ergonomics on health was brought to the forefront of public attention. Ergonomics is the application of scientific information concerning humans to the design of objects. Ergonomic intervention results in improvement of working posture and a decrease in prevalence of musculoskeletal symptoms. Stretching and resistance exercises to the neck are easy to do, when performed 1-2 times daily reduce discomfort and ease neck stiffness. This study is aimed at finding if ergonomics with exercises to the neck prove beneficial to reduce neck pain in Computer Professionals. The outcomes measures used were: Oswestry neck disability index and VAS score for pain. 100 subjects satisfying the inclusion criteria were included in the study. Results: Ergonomic intervention along with isometric neck exercises and stretching proved to reduce neck pain and disability among computer professionals.

Keywords: ergonomics, neck pain, neck exercises, physiotherapy for neck pain

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Authors: Niya Chen, Jennifer Chan

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In the financial market, risk management helps to minimize potential loss and maximize profit. There are two ways to assess risks; the first way is to calculate the risk directly based on the volatility. The most common risk measurements are Value at Risk (VaR), sharp ratio, and beta. Alternatively, we could look at the quantile of the return to assess the risk. Popular return models such as GARCH and stochastic volatility (SV) focus on modeling the mean of the return distribution via capturing the volatility dynamics; however, the quantile/expectile method will give us an idea of the distribution with the extreme return value. It will allow us to forecast VaR using return which is direct information. The advantage of using these non-parametric methods is that it is not bounded by the distribution assumptions from the parametric method. But the difference between them is that expectile uses a second-order loss function while quantile regression uses a first-order loss function. We consider several quantile functions, different volatility measures, and estimates from some volatility models. To estimate the expectile of the model, we use Realized Conditional Autoregressive Expectile (CARE) model with the bayesian method to achieve this. We would like to see if our proposed models outperform existing models in cryptocurrency, and we will test it by using Bitcoin mainly as well as Ethereum.

Keywords: expectile, CARE Model, CARR Model, quantile, cryptocurrency, Value at Risk

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Authors: Sushil K. Sharma, Jeff Zhang, Saeed Tabar

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Worldwide, several governments are utilizing the Internet of Things (IoT) and other information and communication technologies (ICTs) to create smart city infrastructures to improve both the quality of government services and citizen welfare. Over 700 cities from around the world have already started implementing their smart city projects. Smart City utilizes the network of connected things, or the Internet of Things (IoT), that interconnects devices and various components across city infrastructure, making them work together seamlessly to enhance the quality, performance, and interactivity of urban services, optimize resources, and reduce costs. Without developing smart cities, the accelerating growth of cities, and their disproportionate consumption of physical and social resources are unsustainable. In 2016, the Indian Government released a list of 100 cities with the intention of kick-starting the process of developing them into 'smart cities’ as part of the Smart Cities Mission. This study reports the progress and challenges of Smart City projects in India. The data were collected through the city/state government websites, media reports, and focus group discussions/interviews. The preliminary results indicate that smart city projects are not only behind in their implementation and scope but also lacks the sincerity for its implementation.

Keywords: smart city, smart government, Internet of Things, digital government

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Authors: Sean Goltz, Michael Mayo

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The purpose of this research is to use Global-Regulation.com database of the world laws, focusing on tax treaties between countries, in order to create an AI-driven tax simulator that will run an AI agent through potential tax scenarios across countries. The AI agent goal is to identify the scenario that will result in minimum tax liability based on tax treaties between countries. The results will be visualized by a three dimensional matrix. This will be an online web application. Multinational corporations are running their business through multiple countries. These countries, in turn, have a tax treaty with many other countries to regulate the payment of taxes on income that is transferred between these countries. As a result, planning the best tax scenario across multiple countries and numerous tax treaties is almost impossible. This research propose to use Global-Regulation.com database of word laws in English (machine translated by Google and Microsoft API’s) in order to create a simulator that will include the information in the tax treaties. Once ready, an AI agent will be sent through the simulator to identify the scenario that will result in minimum tax liability. Identifying the best tax scenario across countries may save multinational corporations, like Google, billions of dollars annually. Given the nature of the raw data and the domain of taxes (i.e., numbers), this is a promising ground to employ artificial intelligence towards a practical and beneficial purpose.

Keywords: taxation, law, multinational, corporation

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Authors: Rachita Lal

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Solar energy is a clean energy source. Because it is readily available in India and has many potential decentralized uses, urban local authorities may use it in various ways to manage the energy needs in the territory under their control. Apart from these and other services for which people pay a substantial number of money, urban local councils play a crucial role in administering essential services like water supply, street lighting, and health care. ULBs may contribute considerably to the transition to solar energy, both for their benefit and simultaneously for several additional direct and indirect advantages at multiple levels. The research primarily focuses on using clean energy management to reduce urban areas' reliance on traditional (electricity) energy. A technique for estimating the rooftop solar power potential using GIS (Geographical Information System) is described. Given that the combustion of fossil fuels produces 75% of India's power, meeting the country's energy needs through renewable energy sources is a step toward sustainable development and combating climate change. The study will further help in categorization, phasing, and understanding the demand and supply and thus calculating the cumulative benefits. The main objectives are to study the consumption of conventional energy in the study area and to identify the potential areas where solar photovoltaic intervention can be installed.

Keywords: solar energy, GIS, clean energy management, sustainable development

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Authors: Adebayo J. Julius, Oluremi N. Iluyomade

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Livelihood in Nigeria is a paradox of poverty amidst plenty. The Country is endowed with a good climate for agriculture, naturally growing fruit trees and vegetables, and undomesticated water resources. In spite of all its endowment, Nigeria continues to live in poverty year in year out. Rural communities adopted for this study are Ido, Omi-Adio, Onigambari, Okija and Lambata, 500 questionnaires were administered to solicit information from the respondents. This study focused on comparative analysis of the utilization of community informatics for sustainable livelihoods through agriculture. The idea projected in this study is that small strategic changes in the modus operandi of social informatics can have a significant impact on the sustainability of livelihoods. This paper carefully explored the theories of community informatics and its efficacies in dealing with sustainability issues. This study identified, described and evaluates the roles of community informatics in some sectors of the economy, different analytical tools to benchmark the influence of social informatics in agriculture against what is obtainable in agricultural sectors of the economy were used. It further employed comparative analysis to build a case model for sustainable livelihood in agriculture through community informatics.

Keywords: informatics, model, rural community, livelihood, Nigeria

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Authors: Mahfoud Djebbar

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Stock dilution is a financial phenomenon resulting from the issue of additional shares by a company, or when holders convert their convertibles into new shares (capital increase). This issue and/or conversion enlarge the company’s share base that will result in marginal dilution (loss) for existing shareholders, and a benefit to new ones. Dilution issues have already been addressed in mainstream finance, particularly as far as information disclosure is concerned. However, in Islamic finance, stock dilution problems have not been deeply studied and the subject has not received sufficient attention from shariah-compatible firms, investors, and scholars. In this regard, this paper emphasises the forms, the effects of capital dilution on current shareholders as well as the ways and techniques of compensating them. And since the research in this field, in its Islamic perspective, is still in its infancy, the paper tries to analyse the phenomenon theoretically in detail using numerical examples, and expose some case studies of Shariah-compliant issuers of convertible Sukuk and how they compensate their existing shareholders. Finally, this study shows that the Sukuk issuers compensate old shareholders using the right of shuf’ah as a well known and practiced pre-emptive right in Islamic transactions centuries ago, as well as the ways conventional bond issuers use.

Keywords: compensating shareholders, convertible Sukuk, Islamic financial innovation, Shuf’ah

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Authors: Lasha Kamashidze

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COVID19 has already become one of the biggest challenges in the modern world. The virus has also had a significant impact on the world economy, which has faced a major crisis. Each crisis and challenge creates new opportunities. Changes in the world have allowed us to see business in a new light. The aim of the article is to explore new opportunities in the business that have arisen as a result of the Corona virus. Now, organizations with a service profile are working to meet the rapidly changing needs of their staff and customers. Due to the situation created by the pandemic, it became necessary to make some changes in people's daily lives. It became necessary to adapt to the new reality. The changes caused by Coronavirus require in-depth research and analysis in the world economy, as the current situation is not ruled out to be repeated in the future. Many companies have resorted to remote work methods, which require organizational changes. The form of remote work is not new to the Georgian reality. In Georgia, as well as in the rest of the world, the business sector has undergone changes. It will be beneficial for many Georgian companies to make organizational changes that will allow them to work remotely. The current situation has shown the managers of both Georgian and other companies to have "weak points" in organizing modern business. A survey was conducted (online survey), as a result of which it received important information about the problems of remote work in Georgia.

Keywords: organizational change, coronomics, remote work, management

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Authors: Asma Khalid

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Children’s drawings are unique as children are. Children manifest their happiness, sadness, future dreams, likes, dislikes through drawings. Research with children aged 8-12 was conducted in 2017 in which it was asked to them ‘what they think about child-friendly cities?’ The focus was to get ideas from children about the cities in which they live and what they want in their cities. The research was conducted in different private schools. Children were accessed through teachers and principals of the schools (the gatekeepers). Consent forms were developed for children which contained information about the research project and their consent was taken on paper. It was ensured that children are not forced to take part in the research and they can leave the research whenever they want, without informing anyone. The qualitative participatory approach was taken where children were given papers and colors to draw their ideas. During the research, it was found that children are interested in showing their emotions and liking through drawing as this medium seems easy and comfortable to them as compared to have the individual face to face interviews or participate in surveys. However, the clarity of the ideas presented in the drawings was discussed at length with children in their school’s premises. Results of the research show that children like to live in clean, green places which are also safe for them. Furthermore, they want to live with their families and want to have recreational activities including parks in their nearby vicinity.

Keywords: qualitative participative research clean, children, drawing, clean, green and protected place, family

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Authors: Yin Zhang, Kai Qiao, Xiyang Zhi, Jinnan Gong, Jianming Hu

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In order to achieve effective detection of aerial targets over long distances from space-based platforms, the mechanism of interaction between the radiation characteristics of the aerial targets and the complex scene environment including the sunlight conditions, underlying surfaces and the atmosphere are analyzed. A large simulated database of space-based radiance images is constructed considering several typical aerial targets, target working modes (flight velocity and altitude), illumination and observation angles, background types (cloud, ocean, and urban areas) and sensor spectrums ranging from visible to thermal infrared. The target detectability is characterized by the signal-to-clutter ratio (SCR) extracted from the images. The influence laws of the target detectability are discussed under different detection bands and instantaneous fields of view (IFOV). Furthermore, the optimal center wavelengths and widths of the detection bands are suggested, and the minimum IFOV requirements are proposed. The research can provide theoretical support and scientific guidance for the design of space-based detection systems and on-board information processing algorithms.

Keywords: space-based detection, aerial targets, detectability analysis, scene environment

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Authors: Norah Alshayhan

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Dealing with public problems is one of the struggles that may face the leaders in the public sector. Collaborative leadership is one of the most important approaches in dealing with difficult situations that affect both public, private, and nonprofit organizations. Current literature does not show exactly the extent of utilizing collaborative leadership during the post-COVID-19 world in Saudi Arabia. This study is worth exploring in order to examine collaborative leadership in similar environments. This research will utilize both integrative public leadership and transformational leadership theories to guide the researcher in answering the research question. The researcher utilizes content analysis and reviews government documents, plans, and reports to gain more information about collaborative leadership in Saudi Arabia. The researcher analyzes the data in themes and sub-themes to categorize the data in answering the research question. Leader’s behavior and performance in the public sector will be the focus of this study. Findings from this research will benefit leaders in both public, private, and nonprofit sectors in their leadership during a post-disaster time. Findings from this study support collaborative leadership practices and performance in leading future post-crises/disasters.

Keywords: collaborative leadership, post-COVID-19, Saudi Arabia, performance, skills

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Authors: Sadia Basar, Naila Habib, Awais Adnan

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The paper presents the Technique for Image Segmentation Using K-Means Clustering Classification. The presented algorithms were specific, however, missed the neighboring information and required high-speed computerized machines to run the segmentation algorithms. Clustering is the process of partitioning a group of data points into a small number of clusters. The proposed method is content-aware and feature extraction method which is able to run on low-end computerized machines, simple algorithm, required low-quality streaming, efficient and used for security purpose. It has the capability to highlight the boundary and the object. At first, the user enters the data in the representation of the input. Then in the next step, the digital image is converted into groups clusters. Clusters are divided into many regions. The same categories with same features of clusters are assembled within a group and different clusters are placed in other groups. Finally, the clusters are combined with respect to similar features and then represented in the form of segments. The clustered image depicts the clear representation of the digital image in order to highlight the regions and boundaries of the image. At last, the final image is presented in the form of segments. All colors of the image are separated in clusters.

Keywords: clustering, image segmentation, K-means function, local and global minimum, region

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Authors: Chryssa Thermolia, Ekaterini S. Bei, Stelios Sotiriadis, Kostas Stravoskoufos, Euripides G. M. Petrakis

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Moving into a new era of healthcare, new tools and devices are developed to extend and improve health services, such as remote patient monitoring and risk prevention. In this concept, Internet of Things (IoT) and Cloud Computing present great advantages by providing remote and efficient services, as well as cooperation between patients, clinicians, researchers and other health professionals. This paper focuses on patients suffering from bipolar disorder, a brain disorder that belongs to a group of conditions called effective disorders, which is characterized by great mood swings.We exploit the advantages of Semantic Web and Cloud Technologies to develop a patient monitoring system to support clinicians. Based on intelligently filtering of evidence-knowledge and individual-specific information we aim to provide treatment notifications and recommended function tests at appropriate times or concluding into alerts for serious mood changes and patient’s non-response to treatment. We propose an architecture, as the back-end part of a cloud platform for IoT, intertwining intelligence devices with patients’ daily routine and clinicians’ support.

Keywords: bipolar disorder, intelligent systems patient monitoring, semantic web technologies, healthcare

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Authors: Vitor S. Mendonca, Maria Luisa S. Schmidt

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The Brazilian medical profession is viewed as being error-free, so healthcare professionals who commit an error are condemned there. Medical errors occur frequently in the Brazilian healthcare system, so identifying better options for handling this issue has become of interest primarily for physicians. The purpose of this study is to better understand the tensions involved in the fear of making an error due to the harm and risk this would represent for those involved. A qualitative study was performed by means of the narratives of the lived experiences of ten acting physicians in the State of Sao Paulo. The concept and characterization of errors were discussed, together with the fear of making an error, the near misses or error in itself, how to deal with errors and what to do to avoid them. The analysis indicates an excessive pressure in the medical profession for error-free practices, with a well-established physician-patient relationship to facilitate the management of medical errors. The error occurs, but a lack of information and discussion often leads to its concealment due to fear or possible judgment by society or peers. The establishment of programs that encourage appropriate medical conduct in the event of an error requires coherent answers for humanization in Brazilian medical science. It is necessary to improve the discussion about medical errors and disseminate models of communication and notification of errors in Brazil.

Keywords: medical error, narrative, physician-patient relationship, qualitative research

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Authors: Ashok D. Satpute

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Ayurveda, the ancient Indian Medical system is practiced all over India and abroad, is rich in natural source of medicines, including marine products. The marine drugs which prominently used are pravala (coral), mukta (pearl), kapardika (cowry).Shukti (oyster shell), shankha (conch), agnijara (amber) etc. Except agnijara (amber) all are rich in calcium. Interestingly they are not used as supplements in calcium deficiency as done in conventional medical practice. They are used as medicines in the disease like fever, tuberculosis, bleeding disorders, eye problems, digestive complaints etc. Many scientific studies have shown their potent medicinal value. Each has its own properties and used therapeutically after subjecting them to various purificatory processes which are called shodhana in which several medicinal plants are used which also help in enhancing therapeutical activity. Then these purified marine products are subjected to marana (incineration) process and obtained in the form of Bhasma (a finest form of medicine). Agnijara, a derivative of whale is useful as aphrodisiac and prescribed in neuromuscular disorders and tetanus. The ancient scriptures written in Sanskrit language thousands of years back have rich information about all these natural marine products and their medicinal usage.

Keywords: Ayurveda, bhasma, marana, shodhana

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Authors: A. I. Alajtal, H. G. M. Edwards, M. A. Elbagermi

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Raman spectroscopy is currently a part of the instrumentation suite of the ESA ExoMars mission for the remote detection of life signatures in the Martian surface and subsurface. Terrestrial analogues of Martian sites have been identified and the biogeological modifications incurred as a result of extremophilic activity have been studied. Analytical instrumentation protocols for the unequivocal detection of biomarkers in suitable geological matrices are critical for future unmanned explorations, including the forthcoming ESA ExoMars mission to search for life on Mars scheduled for 2018 and Raman spectroscopy is currently a part of the Pasteur instrumentation suite of this mission. Here, Raman spectroscopy using 785nm excitation was evaluated for determining various concentrations of beta-carotene in admixture with polyaromatic hydrocarbons and usnic acid have been investigated by Raman microspectrometry to determine the lowest levels detectable in simulation of their potential identification remotely in geobiological conditions in Martian scenarios. Information from this study will be important for the development of a miniaturized Raman instrument for targetting Martian sites where the biosignatures of relict or extant life could remain in the geological record.

Keywords: raman spectroscopy, mars-analog, beta-carotene, PAHs

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Authors: Elif Aksel, Çagrı Imamoglu

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This ongoing study aims to investigate the effects of neighborhood location on place attachment and residential satisfaction. Place attachment will be examined by comparing place of residence in different areas of the city. Furthermore, the relationship between neighborhood and residential satisfaction will be investigated in terms of physical and social aspects of the places influencing residential satisfaction. This study will be carried out in two different districts of Ankara which are Çankaya, located in the city center, and Sincan, a suburb. Two-hundred adult respondents will participate in this research; 100 men and 100 women aged between 18-65 years with different socio-economic status using snowball sampling. A place attachment scale and a questionnaire related with residential satisfaction, including open-ended questions and 7-point Likert type scale, will be used as instruments. Apart from these, demographic information of the participants such as gender, age, education, the length of residence will be collected. The findings of the study are expected to demonstrate that neighborhood is seen to be influential on place attachment by affecting the intensity of attachment. The level of place attachment is expected to be greater in areas far from the city compared to areas in the center of the city. Apart from this, the neighborhood is also effective in residential satisfaction. The residents living in these neighborhoods having strong physical and social opportunities will be expected to have higher residential satisfaction.

Keywords: neighborhood, neighborhood satisfaction, place attachment, residential satisfaction

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Authors: Hyohun Kim, Dongwha Shin, Yeonseok Kim, Ji-Su Ahn, Kensuke Nakamura, Dongeun Choi, Byung-Woo Hong

Abstract:

Artefacts are commonly encountered in the imaging process of clinical computed tomography (CT) where the artefact refers to any systematic discrepancy between the reconstructed observation and the true attenuation coefficient of the object. It is known that CT images are inherently more prone to artefacts due to its image formation process where a large number of independent detectors are involved, and they are assumed to yield consistent measurements. There are a number of different artefact types including noise, beam hardening, scatter, pseudo-enhancement, motion, helical, ring, and metal artefacts, which cause serious difficulties in reading images. Thus, it is desired to remove nuisance factors from the degraded image leaving the fundamental intrinsic information that can provide better interpretation of the anatomical and pathological characteristics. However, it is considered as a difficult task due to the high dimensionality and variability of data to be recovered, which naturally motivates the use of machine learning techniques. We propose an image restoration algorithm based on the deep neural network framework where the denoising auto-encoders are stacked building multiple layers. The denoising auto-encoder is a variant of a classical auto-encoder that takes an input data and maps it to a hidden representation through a deterministic mapping using a non-linear activation function. The latent representation is then mapped back into a reconstruction the size of which is the same as the size of the input data. The reconstruction error can be measured by the traditional squared error assuming the residual follows a normal distribution. In addition to the designed loss function, an effective regularization scheme using residual-driven dropout determined based on the gradient at each layer. The optimal weights are computed by the classical stochastic gradient descent algorithm combined with the back-propagation algorithm. In our algorithm, we initially decompose an input image into its intrinsic representation and the nuisance factors including artefacts based on the classical Total Variation problem that can be efficiently optimized by the convex optimization algorithm such as primal-dual method. The intrinsic forms of the input images are provided to the deep denosing auto-encoders with their original forms in the training phase. In the testing phase, a given image is first decomposed into the intrinsic form and then provided to the trained network to obtain its reconstruction. We apply our algorithm to the restoration of the corrupted CT images by the artefacts. It is shown that our algorithm improves the readability and enhances the anatomical and pathological properties of the object. The quantitative evaluation is performed in terms of the PSNR, and the qualitative evaluation provides significant improvement in reading images despite degrading artefacts. The experimental results indicate the potential of our algorithm as a prior solution to the image interpretation tasks in a variety of medical imaging applications. This work was supported by the MISP(Ministry of Science and ICT), Korea, under the National Program for Excellence in SW (20170001000011001) supervised by the IITP(Institute for Information and Communications Technology Promotion).

Keywords: auto-encoder neural network, CT image artefact, deep learning, intrinsic image representation, noise reduction, total variation

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Authors: Laras Tursilowati, Bambang Siswanto

Abstract:

Urban climate change has short- and long-term implications for decision-makers in urban development. The problem for this important metropolitan regional of population and economic value is that there is very little usable information on climate change. Research about urban climate change has been carried out in Bali Indonesia by using Conformal Cubic Atmospheric Model (CCAM) that runs with Representative Concentration Pathway (RCP)4.5. The history data means average data from 1975 to 2005, climate projections with RCP4.5 scenario means average data from 2006 to 2099, and anomaly (urban climate change) is RCP4.5 minus history. The results are the history of temperature between 22.5-27.5 OC, and RCP4.5 between 25.5-29.5 OC. The temperature anomalies can be seen in most of northern Bali that increased by about 1.6 to 2.9 OC. There is a reduced humidity tendency (drier) in most parts of Bali, especially the northern part of Bali, while a small portion in the south increase moisture (wetter). The comfort index of Bali region in history is still relatively comfortable (20-26 OC), but on the condition RCP4.5 there is no comfortable area with index more than 26 OC (hot and dry). This research is expected to be useful to help the government make good urban planning.

Keywords: CCAM, comfort index, IPCC AR5, temperature, urban climate change

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Authors: Leslie Beale

Abstract:

Being a patient with a chronic disease is both a physical and emotional experience. The ability to recognize a patient’s emotional health is an important part of a health care provider’s skills. For the purposes of this paper, emotional health is viewed as the way that we feel, and the way that our feelings affect us. Understanding the patient’s emotional health leads to improved provider-patient relationships and health outcomes. For example, when a patient first hears his or her diagnosis from a provider, they might find it difficult to cope with their emotions. Struggling to cope with emotions interferes with the patient’s ability to read, understand, and act on health information and services. As a result, the patient becomes more frustrated and confused, creating barriers to accessing healthcare services. These barriers are challenging for both the patient and their healthcare providers. There are five basic emotions that are part of who we are and are always with us: fear, anger, sadness, joy, and compassion. Living with a chronic disease however can cause a patient to experience and express these emotions in new and unique ways. Within the provider-patient relationship, there needs to be an understanding that each patient experiences these five emotions and, experiences them at different times. In response to this need, the paper highlights a health promotion framework for patients with chronic disease. This framework emphasizes the emotional health of patients.

Keywords: health promotion, emotional health, patients with chronic disease, patient-centered care

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Authors: Alisher Agzamov, Hanan Al Harbi

Abstract:

BACKGROUND: The timely assessment and treatment of ICU Surgical and Medical Oncology patients is important for Oncology surgeons and Medical Oncologists and Intensivists. We hypothesized that the use of Robot Physician’s (RP - 7) ICU management and care in ICU can improve ICU physician rapid response to unstable ICU Oncology patients. METHODS: This is a prospective study using a before-after, cohort-control design to test the effectiveness of RP. We have used RP to make multidisciplinary ICU rounds in the ICU and for Emergency cases. Data concerning several aspects of the RP interaction including the latency of the response, the problem being treated, the intervention that was ordered, and the type of information gathered using the RP were documented. The effect of RP on ICU length of stay and cost was assessed. RESULTS: The use of RP was associated with a reduction in latency of attending physician face-to-face response for routine and urgent pages compared to conventional care (RP: 10.2 +/- 3.3 minutes vs conventional: 220 +/- 80 minutes). The response latencies to Oncology Emergency (8.0 +/- 2.8 vs 150 +/- 55 minutes) and for Respiratory Failure (12 +/- 04 vs 110 +/- 45 minutes) were reduced (P < .001), as was the LOS for patients with AML (5 days) and ARDS (10 day). There was an increase in ICU occupancy by 20 % compared with the prerobot era, and there was an ICU cost savings of KD2.5 million attributable to the use of RP. CONCLUSION: The use of RP enabled rapid face-to-face ICU Intensivist - physician response to unstable ICU Oncology patients and resulted in decreased ICU cost and LOS.

Keywords: robot physician, oncology patients, rp - 7 in icu management, cost and icu occupancy

Procedia PDF Downloads 79