Search results for: Alibaba data centers

Authors: C. Hamamura, V. Gialluca

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Much of the Eclectricity Distributors has about 70% of its electricity interruptions arising from cause "trees", alone or associated with wind and rain and with or without falling branch and / or trees. This contributes inexorably and significantly to outages, resulting in high costs as compensation in addition to the operation and maintenance costs. On the other hand, there is little data structure and solutions to better organize the trees pruning plan effectively, minimizing costs and environmentally friendly. This work describes the development of an algorithm to provide data of trees associated to power grid. The method is accomplished on several steps using satellite imagery and geographically vectorized grid. A sliding window like approach is performed to seek the area around the grid. The proposed method counted 764 trees on a patch of the grid, which was very close to the 738 trees counted manually. The trees data was used as a part of a larger project that implements a system to optimize tree pruning plan.

Keywords: image pattern recognition, trees pruning, trees recognition, neural network

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Authors: Toufic Sarieddine

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As the belt and road Initiative (henceforth, BRI) enters its 9th year, Iran and China are forging stronger ties on economic and military fronts, a development which has not only caused alarm in Washington but also risks staining China’s relationships with the oil-rich Gulf monarchies. World-systems theory has been used to examine the impact of the BRI on the current world order, with scholarship split on the capacity of China to emerge as a hegemon contending with the US or even usurping it. This paper argues the emergence of a new China-centered world-system comprised of states/areas and processes participating in the BRI and overlapping with the global world-system under (shaky) US hegemony. This world-system centers around China as core and hegemon via economic domination, capable new institutions (Shanghai Cooperation Council), legal modi operandi, the common goal of infrastructure development to rally support among developing states, and other indicators of hegemony outlined in world-systems theory. In this regard, while states like Pakistan could become peripheries to China in the BRI-bound world-system via large-scale projects such as the China-Pakistan Economic Corridor, Iran has greater capacities and influence in the Middle East, making it superior to a periphery. This paper thus argues that the increasing proximity between Iran and China sees the former becoming a semi-periphery with respect to China within the BRI-bound world-system, having economic dependence on its new core and hegemon while simultaneously wielding political and military influence on weaker states such as Iraq, Lebanon, Yemen, and Syria. The indicators for peripheralization as well as the characteristics of a semi-periphery outlined in world-systems theory are used to examine the current economic, political, and militaristic dimensions of Iran and China’s growing relationship, as well as the trajectory of these dimensions as part of the BRI-bound world-system.

Keywords: belt and road initiative, China, China-Middle East relations, Iran, world-systems analysis

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Authors: C. Romero, R. Ortega, P. Sánchez-Camacho, P. Aguilar, V. Segur, J. Ruiz, G. Gutiérrez

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Introduction: Breast cancer is a leading cause of death in CLM. (2.8% of all deaths in women and 13,8% of deaths from tumors in womens). It is the most tumor incidence in CLM region with 26.1% from all tumours, except nonmelanoma skin (Cancer Incidence in Five Continents, Volume X, IARC). Cancer registries are a good information source to estimate cancer incidence, however the data are usually available with a lag which makes difficult their use for health managers. By contrast, mortality and survival statistics have less delay. In order to serve for resource planning and responding to this problem, a method is presented to estimate the incidence of mortality and survival data. Objectives: To estimate the incidence of breast cancer by age group in CLM in the period 1991-2013. Comparing the data obtained from the model with current incidence data. Sources: Annual number of women by single ages (National Statistics Institute). Annual number of deaths by all causes and breast cancer. (Mortality Registry CLM). The Breast cancer relative survival probability. (EUROCARE, Spanish registries data). Methods: A Weibull Parametric survival model from EUROCARE data is obtained. From the model of survival, the population and population data, Mortality and Incidence Analysis MODel (MIAMOD) regression model is obtained to estimate the incidence of cancer by age (1991-2013). Results: The resulting model is: Ix,t = Logit [const + age1*x + age2*x2 + coh1*(t – x) + coh2*(t-x)2] Where: Ix,t is the incidence at age x in the period (year) t; the value of the parameter estimates is: const (constant term in the model) = -7.03; age1 = 3.31; age2 = -1.10; coh1 = 0.61 and coh2 = -0.12. It is estimated that in 1991 were diagnosed in CLM 662 cases of breast cancer (81.51 per 100,000 women). An estimated 1,152 cases (112.41 per 100,000 women) were diagnosed in 2013, representing an increase of 40.7% in gross incidence rate (1.9% per year). The annual average increases in incidence by age were: 2.07% in women aged 25-44 years, 1.01% (45-54 years), 1.11% (55-64 years) and 1.24% (65-74 years). Cancer registries in Spain that send data to IARC declared 2003-2007 the average annual incidence rate of 98.6 cases per 100,000 women. Our model can obtain an incidence of 100.7 cases per 100,000 women. Conclusions: A sharp and steady increase in the incidence of breast cancer in the period 1991-2013 is observed. The increase was seen in all age groups considered, although it seems more pronounced in young women (25-44 years). With this method you can get a good estimation of the incidence.

Keywords: breast cancer, incidence, cancer registries, castilla-la mancha

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Authors: Islam Elsayed Hussein

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The aim of this paper is to discover the impact of students’ attitude towards social media and the skills required to adopt social media as a university e-learning (2.0) platform. In addition, it measures the effect of social media adoption on interactive learning effectiveness. The population of this study was students at Faculty of tourism and Hotels, Fayoum University. A questionnaire was used as a research instrument to collect data from respondents, which had been selected randomly. Data had been analyzed using quantitative data analysis method. Findings showed that the students have a positive attitude towards adopting social networking in the learning process and they have also good skills for effective use of social networking tools. In addition, adopting social media is effectively affecting the interactive learning environment.

Keywords: attitude, skills, e-learning 2.0, interactive learning, Egypt

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Authors: Mário Ernesto Sitoe, Orlando Zacarias

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University education is influenced by several factors that range from the adoption of strategies to strengthen the whole process to the academic performance improvement of the students themselves. This work uses data mining techniques to develop a predictive model to identify students with a tendency to evasion and retention. To this end, a database of real students’ data from the Department of University Admission (DAU) and the Department of Mathematics and Informatics (DMI) was used. The data comprised 388 undergraduate students admitted in the years 2009 to 2014. The Weka tool was used for model building, using three different techniques, namely: K-nearest neighbor, random forest, and logistic regression. To allow for training on multiple train-test splits, a cross-validation approach was employed with a varying number of folds. To reduce bias variance and improve the performance of the models, ensemble methods of Bagging and Stacking were used. After comparing the results obtained by the three classifiers, Logistic Regression using Bagging with seven folds obtained the best performance, showing results above 90% in all evaluated metrics: accuracy, rate of true positives, and precision. Retention is the most common tendency.

Keywords: evasion and retention, cross-validation, bagging, stacking

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Authors: Alexander Wachtel, Michael T. Franzen, Walter F. Tichy

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Programming requires years of training. With natural language and end user development methods, programming could become available to everyone. It enables end users to program their own devices and extend the functionality of the existing system without any knowledge of programming languages. In this paper, we describe an Interactive Spreadsheet Processing Module (ISPM), a natural language interface to spreadsheets that allows users to address ranges within the spreadsheet based on inferred table schema. Using the ISPM, end users are able to search for values in the schema of the table and to address the data in spreadsheets implicitly. Furthermore, it enables them to select and sort the spreadsheet data by using natural language. ISPM uses a machine learning technique to automatically infer areas within a spreadsheet, including different kinds of headers and data ranges. Since ranges can be identified from natural language queries, the end users can query the data using natural language. During the evaluation 12 undergraduate students were asked to perform operations (sum, sort, group and select) using the system and also Excel without ISPM interface, and the time taken for task completion was compared across the two systems. Only for the selection task did users take less time in Excel (since they directly selected the cells using the mouse) than in ISPM, by using natural language for end user software engineering, to overcome the present bottleneck of professional developers.

Keywords: natural language processing, natural language interfaces, human computer interaction, end user development, dialog systems, data recognition, spreadsheet

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Authors: Anne N. Heirman, Lisette van der Molen, Richard Dirven, Gyorgi B. Halmos, Michiel W.M. van den Brekel

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Background: Due to the rising incidence of oropharyngeal squamous cell cancer (OPSCC), many patients are challenged with choosing between transoral(robotic) surgery and radiotherapy, with equal survival and oncological outcomes. Also, functional outcomes are of little difference over the years. With this study, the wants and needs of patients and caregivers are identified to develop a comprehensible patient decision aid (PDA). Methods: The development of this PDA is based on the International Patient Decision Aid Standards criteria. In phase 1, relevant literature was reviewed and compared to current counseling papers. We interviewed ten post-treatment patients and ten doctors from four head and neck centers in the Netherlands, which were transcribed verbatim and analyzed. With these results, the first draft of the PDA was developed. Phase 2 beholds testing the first draft for comprehensibility and usability. Phase 3 beholds testing for feasibility. After this phase, the final version of the PDA was developed. Results: All doctors and patients agreed a PDA was needed. Phase 1 showed that 50% of patients felt well-informed after standard care and 35% missed information about treatment possibilities. Side effects and functional outcomes were rated as the most important for decision-making. With this information, the first version was developed. Doctors and patients stated (phase 2) that they were satisfied with the comprehensibility and usability, but there was too much text. The PDA underwent text reduction revisions and got more graphics. After revisions, all doctors found the PDA feasible and would contribute to regular counseling. Patients were satisfied with the results and wished they would have seen it before their treatment. Conclusion: Decision-making for OPSCC should focus on differences in side-effects and functional outcomes. Patients and doctors found the PDA to be of great value. Future research will explore the benefits of the PDA in clinical practice.

Keywords: head-and-neck oncology, oropharyngeal cancer, patient decision aid, development, shared decision making

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Authors: Manoj Gujar

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The present paper is an attempt to interpret two Marathi translations of Khushwant Singh’s (1915-2014) novel Train to Pakistan (1956). The 20th century was branded as an era of Liberalization, Privatization and Globalization. Different countries and cultures have enunciated interaction with one another in an unprecedented manner. The world is becoming multilingual and multicultural. The democratic countries such as the U.S.A., the U.K., and India have become pivotal centers of interlingual and cross-cultural exchange. People belonging to different nationalities showed keen interest in knowing the characteristic features of different languages and of their cultures. Here, ‘Translation’ plays an important role in such multilingual and multicultural contexts. Translation is not only translation of a language but a translation of a culture. However, in the act of translation a translator makes use of such procedures as borrowing, definition, literal translation, substitution, lexical creation, omission, addition as well as their various combinations. To him, a text produced in one linguistic and cultural context can reach other linguistic and cultural contexts through these processes of translation. A worthy work of art appeals many readers. India, being a multilingual country we find that there goes multiple translations of the same text in different Indian languages. But sometimes, if can be found that a same text appeals to different ages and the same text gets translated into the same language by the two or more authors. In this reference, the present paper is an attempt to study how different translations of the same text differ in terms of procedures and strategies during the process of the translation of culture. The source text is Khushwant Singh’s historical novel Train to Pakistan (1956). The novel was widely appreciated and so translated into different regional languages in India. The novel has two Marathi translations: Agniratha (1972) by Hidayatkhan and Train to Pakistan (1980) by Anil Kinikar. This paper is an attempt to evaluate the strategies and procedures in translation to analyze these two Marathi translations. Hidayat Khan made a lot of omissions of the significant details and distorted the original text to a large extent, whereas, Anil Kinikar has done justice to the Source Text by rendering it in Marathi as faithfully as possible.

Keywords: culture, multilingual, procedures and strategies, translation

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Authors: Sathapath Kilaso

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Nowadays, Today, wireless sensor networks are an important technology that works with Internet of Things. It is receiving various data from many sensor. Then sent to processing or storing. By wireless network or through the Internet. The devices around us are intelligent, can receiving/transmitting and processing data and communicating through the system. There are many applications of wireless sensor networks, such as smart city, smart farm, environmental management, weather. This article will explore the use of wireless sensor networks in Thailand and collect data from Thai Thesis database in 2012-2017. How to Implementing Wireless Sensor Network Technology. Advantage from this study To know the usage wireless technology in many fields. This will be beneficial for future research. In this study was found the most widely used wireless sensor network in agriculture field. Especially for smart farms. And the second is the adoption of the environment. Such as weather stations and water inspection.

Keywords: wireless sensor network, smart city, survey, Adhoc Network

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Authors: Jaturong Som-ard

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The heavy rainfall from 3rd to 22th January 2017 had swamped much area of Ranot district in southern Thailand. Due to heavy rainfall, the district was flooded which had a lot of effects on economy and social loss. The major objective of this study is to detect flooding extent using Sentinel-1A data and identify a number of damaged buildings over there. The data were collected in two stages as pre-flooding and during flood event. Calibration, speckle filtering, geometric correction, and histogram thresholding were performed with the data, based on intensity spectral values to classify thematic maps. The maps were used to identify flooding extent using change detection, along with the buildings digitized and collected on JOSM desktop. The numbers of damaged buildings were counted within the flooding extent with respect to building data. The total flooded areas were observed as 181.45 sq.km. These areas were mostly occurred at Ban khao, Ranot, Takhria, and Phang Yang sub-districts, respectively. The Ban khao sub-district had more occurrence than the others because this area is located at lower altitude and close to Thale Noi and Thale Luang lakes than others. The numbers of damaged buildings were high in Khlong Daen (726 features), Tha Bon (645 features), and Ranot sub-district (604 features), respectively. The final flood extent map might be very useful for the plan, prevention and management of flood occurrence area. The map of building damage can be used for the quick response, recovery and mitigation to the affected areas for different concern organization.

Keywords: flooding extent, Sentinel-1A data, JOSM desktop, damaged buildings

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Authors: S. Nandagopalan, N. Pradeep

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The aim of this paper is to propose a general framework for storing, analyzing, and extracting knowledge from two-dimensional echocardiographic images, color Doppler images, non-medical images, and general data sets. A number of high performance data mining algorithms have been used to carry out this task. Our framework encompasses four layers namely physical storage, object identification, knowledge discovery, user level. Techniques such as active contour model to identify the cardiac chambers, pixel classification to segment the color Doppler echo image, universal model for image retrieval, Bayesian method for classification, parallel algorithms for image segmentation, etc., were employed. Using the feature vector database that have been efficiently constructed, one can perform various data mining tasks like clustering, classification, etc. with efficient algorithms along with image mining given a query image. All these facilities are included in the framework that is supported by state-of-the-art user interface (UI). The algorithms were tested with actual patient data and Coral image database and the results show that their performance is better than the results reported already.

Keywords: active contour, bayesian, echocardiographic image, feature vector

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Authors: A. Bayaga

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This research provides a technical account of estimating Transition Probability using Time-homogeneous Markov Jump Process applying by South African HIV/AIDS data from the Statistics South Africa. It employs Maximum Likelihood Estimator (MLE) model to explore the possible influence of Transition Probability of mortality cases in which case the data was based on actual Statistics South Africa. This was conducted via an integrated demographic and epidemiological model of South African HIV/AIDS epidemic. The model was fitted to age-specific HIV prevalence data and recorded death data using MLE model. Though the previous model results suggest HIV in South Africa has declined and AIDS mortality rates have declined since 2002 – 2013, in contrast, our results differ evidently with the generally accepted HIV models (Spectrum/EPP and ASSA2008) in South Africa. However, there is the need for supplementary research to be conducted to enhance the demographic parameters in the model and as well apply it to each of the nine (9) provinces of South Africa.

Keywords: AIDS mortality rates, epidemiological model, time-homogeneous markov jump process, transition probability, statistics South Africa

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Authors: Akbar Khodavirdizadeh, Ali Nemati Babaylou, Hassan Moomivand

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The history of human access to water technique has been one of the factors in the formation of human civilizations in the ancient world. The technique that makes surface water and groundwater accessible to humans on the ground has been a clever technique in human life to reach the water. In this study, while examining the water technique of ancient Iran using the Qanats technique, the water supply system of different regions of the ancient world were also studied and compared. Six groups of the ancient region of ancient Greece (Archaic 480-750 BC and Classical 223-480 BC), Urartu in Tuspa (600-850 BC), Petra (106-168 BC), Ancient Rome (265 BC), and the ancient United States (1450 BC) and ancient Iranian water technologies were studied under water supply systems. Past water technologies in these areas: water transmission systems in primary urban centers, use of water structures in water control, use of bridges in water transfer, construction of waterways for water transfer, storage of rainfall, construction of various types of pottery- ceramic, lead, wood and stone pipes have been used in water transfer, flood control, water reservoirs, dams, channel, wells, and Qanat. The central plateau of Iran is one of the arid and desert regions. Archaeological, geomorphological, and paleontological studies of the central region of the Iranian plateau showed that without the use of Qanats, the possibility of urban civilization in this region was difficult and even impossible. Zarch aqueduct is the most important aqueduct in Yazd region. Qanat of Zarch is a plain Qanat with a gallery length of 80 km; its mother well is 85 m deep and has 2115 well shafts. The main purpose of building the Qanat of Zārch was to access the groundwater source and transfer it to the surface of the ground. Regarding the structure of the aqueduct and the technique of transferring water from the groundwater source to the surface, it has a great impact on being different from other water techniques in the ancient world. The results show that the use of water technologies in ancient is very important to understand the history of humanity in the use of hydraulic techniques.

Keywords: ancient water technologies, groundwaters, qanat, human history, Ancient Iran

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Authors: Xiaofang Wei

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Harmful Algal Blooms are a recurrent disturbing occurrence in Lake Erie that has caused significant negative impacts on water quality and aquatic ecosystem around Great Lakes areas in the United States. Targeting the recent HAB events in western Lake Erie, this paper utilizes satellite imagery and hydrological modeling to monitor HAB cyanobacteria blooms and analyze the impacts of agricultural activities from Maumee watershed, the biggest watershed of Lake Erie and agriculture dominant.SWAT (Soil & Water Assessment Tool) Model for Maumee watershed was established with DEM, land use data, crop data layer, soil data, and weather data, and calibrated with Maumee River gauge stations data for streamflow and nutrients. Fast Line-of-sight Atmospheric Analysis of Hypercubes (FLAASH) was applied to remove atmospheric attenuation and cyanobacteria Indices were calculated from Landsat OLI imagery to study the intensity of HAB events in the years 2015, 2017, and 2019. The agricultural practice and nutrients management within the Maumee watershed was studied and correlated with HAB cyanobacteria indices to study the relationship between HAB intensity and nutrient loadings. This study demonstrates that hydrological models and satellite imagery are effective tools in HAB monitoring and modeling in rivers and lakes.

Keywords: harmful algal bloom, landsat OLI imagery, SWAT, HAB cyanobacteria

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Authors: Chante J. De Klerk

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The potential of music to facilitate superior performance during high to elite level gymnastics conditioning instigated this research. A team of seven gymnasts completed a fixed conditioning programme eight times, alternating the two variable conditions. Four sessions of each condition were conducted: without music (session 1), with music (session 2), without music (3), with music (4), without music (5), and so forth. Quantitative data were collected in both conditions through physiological monitoring of the gymnasts, and administration of the Situational Motivation Scale (SIMS). Statistical analysis of the physiological data made it possible to quantify the presence as well as the magnitude of the musical intervention’s impact on various aspects of the gymnasts' physiological functioning during conditioning. The SIMS questionnaire results were used to evaluate if their motivation towards conditioning was altered by the intervention. Thematic analysis of qualitative data collected through semi-structured interviews revealed themes reflecting the gymnasts’ sentiments towards the data collection process. Gymnast-specific descriptions and experiences of the team as a whole were integrated with the quantitative data to facilitate greater dimension in establishing the impact of the intervention. The results showed positive physiological, motivational, and emotional effects. In the presence of music, superior sympathetic nervous activation, and energy efficiency, with more economic breathing, dominated the physiological data. Fatigue and arousal levels (emotional and physiological) were also conducive to improved conditioning outcomes compared to conventional conditioning (without music). Greater levels of positive affect and motivation emerged in analysis of both the SIMS and interview data sets. Overall, the intervention was found to promote psychophysiological coherence during the physical activity. In conclusion, a strategically constructed musical intervention, designed to accompany a gymnastics conditioning session for high to elite level gymnasts, has ergogenic potential.

Keywords: arousal, fatigue, gymnastics conditioning, motivation, musical intervention, psychophysiological coherence

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Authors: Zhila Hemati, Seyed Sajjad Hosseni, Sohrab Zamzami

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In nature, forests serve a multitude of functions. They stabilize and nourish soil, store carbon, clean the air and water, and support biodiverse ecosystems. A natural disaster that can affect forests and ecosystems locally or globally is wildfires. Iran experiences annual forest fires that affect roughly 6000 hectares, with the Arasbaran forest being the most affected. These fires may be generated unnaturally by human activity in the forests, or they could occur naturally as a result of climate change. These days, wildfires pose a major natural risk. Wildfires significantly reduce the amount of property and human life in ecosystems globally. Concerns regarding the immediate and longterm effects have been raised by the rise in fire activity in various Iranian regions in recent decades. Natural ecosystem abundance, quality, and health will all be impacted by pasture and forest fires. Monitoring is the first line of defense against and control for forest fires. To determine the spatial-temporal variations of these occurrences in the vegetation regions of Arasbaran, this study was carried out to estimate the areas affected by fires. The findings indicated that July through September, which spans over 130000 hectares, is when fires in Arasbaran's vegetation areas occur to their greatest extent. A significant portion of the nation's forests caught fire in 2024, particularly in the northwest of the Arasbaran vegetation area. On the other hand, January through March sees the least number of fire locations in the Arasbaran vegetation areas. The Arasbaran forest experiences its greatest number of forest fires during the hot, dry months of the year. As a result, the linear association between the burned and active fire regions in the Arasbaran forest indicates a substantial relationship between species abundance and plant species. This link demonstrates that some of the active forest fire centers are the burned regions in Arasbaran's vegetation areas.

Keywords: wildfire, vegetation, plant species, forest

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Authors: Mansoureh Karimollahi, Mehriar Adrmohammadi, Mohsen Mohammadi

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Introduction: Patient satisfaction with nursing care is considered as an important indicator of the quality and effectiveness of the health care system, and improving the quality of care is not possible without paying attention to the opinions and expectations of patients. Considering that the scales for assessing satisfaction with nursing care in our country are not comprehensive and measure very few areas, therefore, in this study, psychometrically, the Persian version of the Newcastle Nursing Care Satisfaction Scale was used in patients hospitalized in the wards. Internal medicine and general surgery were discussed. Methods: This cross-sectional study was conducted on 200 patients admitted to the surgery and internal departments of hospitals affiliated to Ardabil University of Medical Sciences. The Newcastle nursing care satisfaction scale was used for the first time in Iran in comparison with the good nursing care scale from the patients' point of view to evaluate the criterion validity. The Newcastle nursing care satisfaction scale was used after translation, validity, and reliability. Results: The level of satisfaction of patients and the experience of patients with nursing care was at a favorable level, respectively, with an average of 111.8 ± 14.2 and 69.07 ± 14.8. Total CVI was estimated at 0.96 for the experience section, 0.95 for the satisfaction section, and 0.96 for the whole scale. The index (CVR) was also 0.95 for the experience section, 0.95 for the satisfaction section, and 0.95 for the whole scale. Criterion validity was also estimated using 0.725 correlation. The validity of the construct was also confirmed using the goodness of fit index (X2=1932/05, p=0.013, KMO=0.913). Convergent validity was estimated at 0.99 in the experience subscale and 0.98 in the satisfaction subscale. . The overall reliability in the experience subscale and satisfaction subscale was 94%, 92%, and 98%, respectively, which indicated the acceptable reliability of the questionnaire. Conclusion: The Persian version of the Newcastle nursing care satisfaction scale as a comprehensive tool that can be easily completed by patients and is easy to interpret, has good validity and reliability and can be used in patient care centers, in departments Surgery, and internal medicine are recommended.

Keywords: psychometrics, Newcastle nursing care satisfaction scale, nursing care satisfaction, general surgery department

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Authors: Nazi Pharsadanishvili, Anastasia Kitiashvili

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The importance of studying the social-psychological features of people living in poverty is often emphasized in international research. Building a multidimensional economic framework for reducing poverty grounded in people’s experiences and values is the main goal of famous Poverty Research Centers (such as Oxford Poverty and Human Development Initiative, Abdul Latif Jameel Poverty Action Lab). The aims of the proposed research are to investigate the following characteristics of socially vulnerable people living in Georgia: 1) The features of the perceived stigma of poverty; 2) economic system justification and social justice beliefs; 3) Perceived social mobility and actual attempts at upward social mobility. Qualitative research was conducted to address the indicated research goals and descriptive research questions. Conducting in-depth interviews was considered to be the most appropriate method to capture the vivid feelings and experiences of people living in poverty. 17 respondents (registered in the unified database of socially vulnerable families) participated in in-depth interviews. According to the research results, socially vulnerable people living in Georgia perceive stigma targeted toward them. Two sub-dimensions were identified in perceived stigma: experienced stigma and internalized stigma. Experienced stigma reflects the instances of being discriminated and perceptions of negative treatment from other members of society. Internalized stigma covers negative personal emotions, the feelings of shame, the fear of future stigmatization, and self-isolation. The attitudes and justifications of the existing economic system affect people’s attempts to cope with poverty. Complex analysis of those results is important during the planning and implementing of social welfare reforms. Particularly, it is important to implement poverty stigma reduction mechanisms and help socially vulnerable people to see real perspectives on upward social mobility.

Keywords: coping with poverty, economic system justification, perceived stigma of poverty, upward social mobility

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Authors: Mohammad Javad Behzadnia, Amir Bahador Boroumand

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Introduction: Limited facility situations require allocating the most available resources for most casualties. Accordingly, Traumatic Brain Injury (TBI) is the one that may need to transport the patient as soon as possible. In a mass casualty event, deciding when the facilities are restricted is hard. The Extended Glasgow Outcome Score (GOSE) has been introduced to assess the global outcome after brain injuries. Therefore, we aimed to evaluate the prognostic factors associated with GOSE. Materials and Methods: In a multicenter cross-sectional study conducted on 144 patients with TBI admitted to trauma emergency centers. All the patients with isolated TBI who were mentally and physically healthy before the trauma entered the study. The patient’s information was evaluated, including demographic characteristics, duration of hospital stays, mechanical ventilation on admission laboratory measurements, and on-admission vital signs. We recorded the patients’ TBI-related symptoms and brain computed tomography (CT) scan findings. Results: GOSE assessments showed an increasing trend by the comparison of on-discharge (7.47 ± 1.30), within a month (7.51 ± 1.30), and within three months (7.58 ± 1.21) evaluations (P < 0.001). On discharge, GOSE was positively correlated with Glasgow Coma Scale (GCS) (r = 0.729, P < 0.001) and motor GCS (r = 0.812, P < 0.001), and inversely with age (r = −0.261, P = 0.002), hospitalization period (r = −0.678, P < 0.001), pulse rate (r = −0.256, P = 0.002) and white blood cell (WBC). Among imaging signs and trauma-related symptoms in univariate analysis, intracranial hemorrhage (ICH), interventricular hemorrhage (IVH) (P = 0.006), subarachnoid hemorrhage (SAH) (P = 0.06; marginally at P < 0.1), subdural hemorrhage (SDH) (P = 0.032), and epidural hemorrhage (EDH) (P = 0.037) were significantly associated with GOSE at discharge in multivariable analysis. Conclusion: Our study showed some predictive factors that could help to decide which casualty should transport earlier to a trauma center. According to the current study findings, GCS, pulse rate, WBC, and among imaging signs and trauma-related symptoms, ICH, IVH, SAH, SDH, and EDH are significant independent predictors of GOSE at discharge in TBI patients.

Keywords: field, Glasgow outcome score, prediction, traumatic brain injury.

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Authors: Shinji Kawakura, Ryosuke Shibasaki

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We have been grouping and developing various kinds of practical, promising sensing applied systems concerning agricultural advancement and technical tradition (guidance). These include advanced devices to secure real-time data related to worker motion, and we analyze by methods of various advanced statistics and human dynamics (e.g. primary component analysis, Ward system based cluster analysis, and mapping). What is more, we have been considering worker daily health and safety issues. Targeted fields are mainly common farms, meadows, and gardens. After then, we observed and discussed time-line style, changing data. And, we made some suggestions. The entire plan makes it possible to improve both the aforementioned applied systems and farms.

Keywords: advanced statistical analysis, wearable sensing system, tradition of skill, supporting for workers, detecting crisis

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Authors: Hasan G. Elmazoghi, Aisha I. Alzayani, Lubna S. Bentaher

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Rainfall is a highly non-linear phenomena, which requires application of powerful supervised data mining techniques for its accurate prediction. In this study the Artificial Neural Network (ANN) technique is used to predict the mean monthly historical rainfall data collected from BENINA station in Benghazi for 31 years, the period of “1977-2006” and the results are compared against the observed values. The specific objective to achieve this goal was to determine the best combination of weather variables to be used as inputs for the ANN model. Several statistical parameters were calculated and an uncertainty analysis for the results is also presented. The best ANN model is then applied to the data of one year (2007) as a case study in order to evaluate the performance of the model. Simulation results reveal that application of ANN technique is promising and can provide reliable estimates of rainfall.

Keywords: neural networks, rainfall, prediction, climatic variables

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Authors: E. A. Krasikov

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Dependence of the materials properties on neutron irradiation intensity (flux) is a key problem while usage data of the accelerated materials irradiation in test reactors for forecasting of their capacity for work in realistic (practical) circumstances of operation. Investigations of the reactor pressure vessel steel radiation degradation dependence on fast neutron fluence (embrittlement kinetics) at low flux reveal the instability in the form of the scatter of the experimental data and wave-like sections of embrittlement kinetics appearance. Disclosure of the steel degradation oscillating is a sign of the steel structure cyclic self-recovery transformation as it take place in self-organization processes. This assumption has received support through the discovery of the similar ‘anomalous’ data in scientific publications and by means of own additional experiments. Data obtained stimulate looking-for ways to management of the structural steel radiation stability (for example, by means of nano - structure modification for radiation defects annihilation intensification) for creation of the intelligent self-recovering material. Expected results: - radiation degradation theory and mechanisms development, - more adequate models of the radiation embrittlement elaboration, - surveillance specimen programs improvement, - methods and facility development for usage data of the accelerated materials irradiation for forecasting of their capacity for work in realistic (practical) circumstances of operation, - search of the ways for creating of the radiation stable self-recovery intelligent materials.

Keywords: degradation, radiation, steel, wave-like kinetics

Procedia PDF Downloads 301

Authors: Deokho Kim, Wonwoo Lee, Jaewoong Lee, Teresa Ng, Gun-Ill Lee, Jiwon Jeong

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This paper presents a method for improving object search accuracy using a deep learning model. A major limitation to provide accurate similarity with deep learning is the requirement of huge amount of data for training pairwise similarity scores (metrics), which is impractical to collect. Thus, similarity scores are usually trained with a relatively small dataset, which comes from a different domain, causing limited accuracy on measuring similarity. For this reason, this paper proposes a deep learning model that can be trained with a significantly small amount of data, a clustered data which of each cluster contains a set of visually similar images. In order to measure similarity distance with the proposed method, visual features of two images are extracted from intermediate layers of a convolutional neural network with various pooling methods, and the network is trained with pairwise similarity scores which is defined zero for images in identical cluster. The proposed method outperforms the state-of-the-art object similarity scoring techniques on evaluation for finding exact items. The proposed method achieves 86.5% of accuracy compared to the accuracy of the state-of-the-art technique, which is 59.9%. That is, an exact item can be found among four retrieved images with an accuracy of 86.5%, and the rest can possibly be similar products more than the accuracy. Therefore, the proposed method can greatly reduce the amount of training data with an order of magnitude as well as providing a reliable similarity metric.

Keywords: visual search, deep learning, convolutional neural network, machine learning

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Authors: Waraporn Boonchieng, Ekkarat Boonchieng, Wilawan Senaratana, Jaras Singkaew

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Geographical information system (GIS) is a designated system widely used for collecting and analyzing geographical data. Since the introduction of ultra-mobile, 'smart' devices, investigators, clinicians, and even the general public have had powerful new tools for collecting, uploading and accessing information in the field. Epidemiology paired with GIS will increase the efficacy of preventive health care services. The objective of this study is to apply GPS location services that are available on the common mobile device with district health systems, storing data on our private cloud system. The mobile application has been developed for use on iOS, Android, and web-based platforms. The system consists of two parts of district health information, including recorded resident data forms and individual health recorded data forms, which were developed and approved by opinion sharing and public hearing. The application's graphical user interface was developed using HTML5 and PHP with MySQL as a database management system (DBMS). The reporting module of the developed software displays data in a variety of views, from traditional tables to various types of high-resolution, layered graphics, incorporating map location information with street views from Google Maps. Multi-extension exporting is also supported, utilizing standard platforms such as PDF, PNG, JPG, and XLS. The data were collected in the database beginning in March 2013, by district health volunteers and district youth volunteers who had completed the application training program. District health information consisted of patients’ household coordinates, individual health data, social and economic information. This was combined with Google Street View data, collected in March 2014. Studied groups consisted of 16,085 (67.87%) and 47,811 (59.87%) of the total 23,701 households and 79,855 people were collected by the system respectively, in Saraphi district, Chiang Mai Province. The report generated from the system has had a major benefit directly to the Saraphi District Hospital. Healthcare providers are able to use the basic health data to provide a specific home health care service and also to create health promotion activities according to medical needs of the people in the community.

Keywords: health, public health, GIS, geographic information system

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Authors: Mostafa Aminzadeh, Min Deng

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Modeling loss data is an important part of actuarial science. Actuaries use models to predict future losses and manage financial risk, which can be beneficial for marketing purposes. In the insurance industry, small claims happen frequently while large claims are rare. Traditional distributions such as Normal, Exponential, and inverse-Gaussian are not suitable for describing insurance data, which often show skewness and fat tails. Several authors have studied classical and Bayesian inference for parameters of composite distributions, such as Exponential-Pareto, Weibull-Pareto, and Inverse Gamma-Pareto. These models separate small to moderate losses from large losses using a threshold parameter. This research introduces a computational approach using a nonlinear regression model for loss data that relies on multiple predictors. Simulation studies were conducted to assess the accuracy of the proposed estimation method. The simulations confirmed that the proposed method provides precise estimates for regression parameters. It's important to note that this approach can be applied to datasets if goodness-of-fit tests confirm that the composite distribution under study fits the data well. To demonstrate the computations, a real data set from the insurance industry is analyzed. A Mathematica code uses the Fisher information algorithm as an iteration method to obtain the maximum likelihood estimation (MLE) of regression parameters.

Keywords: maximum likelihood estimation, fisher scoring method, non-linear regression models, composite distributions

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Authors: Mattias Bergstrom

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Significance of the Study: This research will provide new insights into the risks with digital embedded infrastructure. Through this research, we will analyze each risk and its potential negation strategies, especially for AI and autonomous automation. Moreover, the analysis that is presented in this paper will convey valuable information for future research that can create more stable, secure, and efficient autonomous systems. To learn and understand the risks, a large IoT system was envisioned, and risks with hardware, tampering, and cyberattacks were collected, researched, and evaluated to create a comprehensive understanding of the potential risks. Potential solutions have then been evaluated on an open source IoT hardware setup. This list shows the identified passive and active risks evaluated in the research. Passive Risks: (1) Hardware failures- Critical Systems relying on high rate data and data quality are growing; SCADA systems for infrastructure are good examples of such systems. (2) Hardware delivers erroneous data- Sensors break, and when they do so, they don’t always go silent; they can keep going, just that the data they deliver is garbage, and if that data is not filtered out, it becomes disruptive noise in the system. (3) Bad Hardware injection- Erroneous generated sensor data can be pumped into a system by malicious actors with the intent to create disruptive noise in critical systems. (4) Data gravity- The weight of the data collected will affect Data-Mobility. (5) Cost inhibitors- Running services that need huge centralized computing is cost inhibiting. Large complex AI can be extremely expensive to run. Active Risks: Denial of Service- It is one of the most simple attacks, where an attacker just overloads the system with bogus requests so that valid requests disappear in the noise. Malware- Malware can be anything from simple viruses to complex botnets created with specific goals, where the creator is stealing computer power and bandwidth from you to attack someone else. Ransomware- It is a kind of malware, but it is so different in its implementation that it is worth its own mention. The goal with these pieces of software is to encrypt your system so that it can only be unlocked with a key that is held for ransom. DNS spoofing- By spoofing DNS calls, valid requests and data dumps can be sent to bad destinations, where the data can be extracted for extortion or to corrupt and re-inject into a running system creating a data echo noise loop. After testing multiple potential solutions. We found that the most prominent solution to these risks was to use a Peer 2 Peer consensus algorithm over a blockchain to validate the data and behavior of the devices (sensors, storage, and computing) in the system. By the devices autonomously policing themselves for deviant behavior, all risks listed above can be negated. In conclusion, an Internet middleware that provides these features would be an easy and secure solution to any future autonomous IoT deployments. As it provides separation from the open Internet, at the same time, it is accessible over the blockchain keys.

Keywords: IoT, security, infrastructure, SCADA, blockchain, AI

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Authors: Oscar E. Cariceo, Claudia V. Casal

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Machine learning offers a set of techniques to promote social work interventions and can lead to support decisions of practitioners in order to predict new behaviors based on data produced by the organizations, services agencies, users, clients or individuals. Machine learning techniques include a set of generalizable algorithms that are data-driven, which means that rules and solutions are derived by examining data, based on the patterns that are present within any data set. In other words, the goal of machine learning is teaching computers through 'examples', by training data to test specifics hypothesis and predict what would be a certain outcome, based on a current scenario and improve that experience. Machine learning can be classified into two general categories depending on the nature of the problem that this technique needs to tackle. First, supervised learning involves a dataset that is already known in terms of their output. Supervising learning problems are categorized, into regression problems, which involve a prediction from quantitative variables, using a continuous function; and classification problems, which seek predict results from discrete qualitative variables. For social work research, machine learning generates predictions as a key element to improving social interventions on complex social issues by providing better inference from data and establishing more precise estimated effects, for example in services that seek to improve their outcomes. This paper exposes the results of a classification algorithm to predict cyberbullying among adolescents. Data were retrieved from the National Polyvictimization Survey conducted by the government of Chile in 2017. A logistic regression model was created to predict if an adolescent would experience cyberbullying based on the interaction and behavior of gender, age, grade, type of school, and self-esteem sentiments. The model can predict with an accuracy of 59.8% if an adolescent will suffer cyberbullying. These results can help to promote programs to avoid cyberbullying at schools and improve evidence based practice.

Keywords: cyberbullying, evidence based practice, machine learning, social work research

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Authors: Awdhesh Narayan Sharma

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The use of herbal medicines for the cure of various ailments among the tribal population is as old as human origin itself. Most of the tribal populations of Madhya Pradesh inhabit in remote and inaccessible ecological setup. From long back, tribals and forests are interrelated to each other. They use an enormous range of wild plants for their basic needs and medicines. The tribal developed a unique understanding with wild plants, herbs, etc., and earned specialized knowledge of disease pattern and curative therapy-through hard experiences, common sense, trial, and error methods. They have passed this knowledge through traditions, taboos, totems, folklore by words of mouth from generation to generation. Here, an attempt has been made to study the possible aspects of herbal medicine for the cure of Jaundice among the tribal populations of Madhya Pradesh, India, through primary data as well as available secondary data. The data have been collected from the 305 Bharias of Patalkot, Madhya Pradesh, India, and included available secondary source of data by various investigators. It may be concluded that a sizable herbal medicinal plants' wealth exists in Madhya Pradesh, India, which still awaits for scientific exploration. The existing herbal medicines used for the cure of jaundice need an extensive investigation from the pharmaceutical point of view.

Keywords: Bharias, herbal medicine, tribal, Madhya Pradesh

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Authors: Yamba Dabone, Tounwendyam Frédéric Ouedraogo, Pengwendé Justin Kouraogo, Oumarou Sie

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Reliable data transport over the Internet is one of the goals of researchers in the field of computer science. Data such as videos and audio files are becoming increasingly large. As a result, transporting them over the Internet is becoming difficult. Therefore, it has been important to establish a method to locally interconnect autonomous systems (AS) with each other to facilitate traffic exchange. It is in this context that Internet Exchange Points (IXPs) are set up to facilitate local and even regional traffic. They are now the lifeblood of the Internet. Therefore, it is important to think about the factors that can characterize IXPs. However, other more quantifiable characteristics can help determine the quality of an IXP. In addition, these characteristics may allow ISPs to have a clearer view of the exchange node and may also convince other networks to connect to an IXP. To that end, we define five new IXP characteristics: the attraction rate (τₐₜₜᵣ); and the peering rate (τₚₑₑᵣ); the target rate of an IXP (Objₐₜₜ); the number of IXP links (Nₗᵢₙₖ); the resistance rate τₑ𝒻𝒻 and the attraction failure rate (τ𝒻).

Keywords: characteristic, autonomous system, internet service provider, internet exchange point, rate

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Authors: R. Udayabhaskar, R. V. Mangalaraja, V. T. Perarasu, Saeed Farhang Sahlevani, B. Karthikeyan, David Contreras

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Bandgap engineering of CeO₂ nanocrystals is of high interest for many research groups to meet the requirement of desired applications. The band gap of CeO₂ nanostructures can be modified by varying the particle size, morphology and dopants. Anchoring the metal oxide nanostructures on graphene sheets will result in composites with improved properties than the parent materials. The presence of graphene sheets will acts a support for the growth, influences the morphology and provides external paths for electronic transitions. Thus, the controllable synthesis of ceria:graphene composites with various morphologies and the understanding of the optical properties is highly important for the usage of these materials in various applications. The development of ceria and ceria:graphene composites with low cost, rapid synthesis with tunable optical properties is still desirable. By this work, we discuss the synthesis of pure ceria (nanospheres) and ceria:graphene composites (nano-rice like morphology) by using commercial microwave oven as a cost effective and environmentally friendly approach. The influence of the graphene on the crystallinity, morphology, band gap and luminescence of the synthesized samples were analyzed. The average crystallite size obtained by using Scherrer formula of the CeO₂ nanostructures showed a decreasing trend with increasing the graphene loading. The higher graphene loaded ceria composite clearly depicted morphology of nano-rice like in shape with the diameter below 10 nm and the length over 50 nm. The presence of graphene and ceria related vibrational modes (100-4000 cm⁻¹) confirmed the successful formation of composites. We observed an increase in band gap (blue shift) with increasing loading amount of graphene. Further, the luminescence related to various F-centers was quenched in the composites. The authors gratefully acknowledge the FONDECYT Project No.: 3160142 and BECA Conicyt National Doctorado2017 No. 21170851 Government of Chile, Santiago, for the financial assistance.

Keywords: ceria, graphene, luminescence, blue shift, band gap widening

Procedia PDF Downloads 186