Search results for: healthcare data security

Authors: Alireza Karimi

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Artificial Intelligence (AI) is reshaping various industries, and accounting is no exception. With the ability to process vast amounts of data quickly and accurately, AI is revolutionizing how financial professionals manage, analyze, and report financial information. In this article, we will explore the diverse applications of AI in accounting and its profound impact on the field. Automation of Repetitive Tasks: One of the most significant contributions of AI in accounting is automating repetitive tasks. AI-powered software can handle data entry, invoice processing, and reconciliation with minimal human intervention. This not only saves time but also reduces the risk of errors, leading to more accurate financial records. Pattern Recognition and Anomaly Detection: AI algorithms excel at pattern recognition. In accounting, this capability is leveraged to identify unusual patterns in financial data that might indicate fraud or errors. AI can swiftly detect discrepancies, enabling auditors and accountants to focus on resolving issues rather than hunting for them. Real-Time Financial Insights: AI-driven tools, using natural language processing and computer vision, can process documents faster than ever. This enables organizations to have real-time insights into their financial status, empowering decision-makers with up-to-date information for strategic planning. Fraud Detection and Prevention: AI is a powerful tool in the fight against financial fraud. It can analyze vast transaction datasets, flagging suspicious activities and reducing the likelihood of financial misconduct going unnoticed. This proactive approach safeguards a company's financial integrity. Enhanced Data Analysis and Forecasting: Machine learning, a subset of AI, is used for data analysis and forecasting. By examining historical financial data, AI models can provide forecasts and insights, aiding businesses in making informed financial decisions and optimizing their financial strategies. Artificial Intelligence is fundamentally transforming the accounting profession. From automating mundane tasks to enhancing data analysis and fraud detection, AI is making financial processes more efficient, accurate, and insightful. As AI continues to evolve, its role in accounting will only become more significant, offering accountants and finance professionals powerful tools to navigate the complexities of modern finance. Embracing AI in accounting is not just a trend; it's a necessity for staying competitive in the evolving financial landscape.

Keywords: artificial intelligence, accounting automation, financial analysis, fraud detection, machine learning in finance

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Authors: Bushra Alghamdi, Alla Alsharif, Hamzah Aljohani, Saba Kassim

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Introduction: Collaborative work has always been acknowledged as a fundamental concept in delivering oral health care. Aim: This study aimed to assess the perception and attitude of pharmacists in oral health promotion and to determine the confident levels of pharmacists in delivering advice on oral health problems. Methods: An observational cross-sectional survey, using self-administered anonymous questionnaires, was conducted between March and April 2017. The study recruited a convenience sample of registered community pharmacists who were working in local private pharmaceutical stores in the urban area of Madinah, Kingdom of Saudi Arabia (KSA). A preliminary descriptive analysis was performed. Results: Thirty-five pharmacists have completed the surveys. All participants were males, with a mean age of 35.5 ( ± 6.92) years. Eighty-six percent of the participants reported that pharmacists should have a role in oral health promotion. Eighty percent have reported adequate level of confident when giving advice on most of the common oral health problems that include; oral health related risk behaviors such as tobacco cessation (46%), bleeding gums (63%) and sensitive teeth (60%). However, higher percentages of pharmacists have reported low confident levels when giving advice in relation to specific domain of dentistry, such as lost dental fillings (57%), loose crowns (60%), trauma to teeth (40%), denture-related problems (51%) and oral cancer (6.9%). Conclusion: Community pharmacists recognized their potential role in promoting oral health in KSA. Community pharmacists had varying levels of ability and confidence to offer support for oral health. The study highlighted that inner professional collaboration between pharmacists and dental care healthcare should be enhanced.

Keywords: community, oral health, promotion, pharmacist

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Authors: Prateep Wajeetongratana

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The purpose of this research was to study the influence of accountants’ potential performance on their working process, a case study of Government Savings Banks in the northeast of Thailand. The independent variables included accounting knowledge, accounting skill, accounting value, accounting ethics, and accounting attitude, while the dependent variable included the success of the working process. A total of 155 accountants working for Government Savings Banks were selected by random sampling. A questionnaire was used as a tool for collecting data. Descriptive statistics in this research included percentage, mean, and multiple regression analyses. The findings revealed that the majority of accountants were female with an age between 35-40 years old. Most of the respondents had an undergraduate degree with ten years of experience. Moreover, the factors of accounting knowledge, accounting skill, accounting a value and accounting ethics and accounting attitude were rated at a high level. The findings from regression analysis of observation data revealed a causal relationship in that the observation data could explain at least 51 percent of the success in the accountants’ working process.

Keywords: influence, potential performance, success, working process

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Authors: Roghayeh Karami, Ahmad Gharaei

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Backgrounds and objectives: This study was undertaken at four different sites (north polluted, south polluted, south healthy and north healthy) in Tehran, in order to examine whether there was a relationship between publicly available air quality data and the public’s perception of air quality and to suggest some guidelines for reducing air pollution. Materials and Methods: A total of 200 people were accidentally filled out the research questionnaires at mentioned sites and air quality data were obtained simultaneously from the Air Quality Control Department. Data was analyzed in Excel and SPSS software. Results: Clean air and secure job were of great importance to people comparing to other pleasant aspect of life. Also air pollution and fear of dangerous diseases were the most important of people concerns. The Indies bored /news paper services on air quality were little used by the public as a means of obtaining information on air pollution. Using public transportation and avoid unessential journeys are the most important ways for reducing air pollution. Conclusion: The results reveal that the public’s perception of air quality is not a reliable indicator of the actual levels of air pollution. Current earths to down actions are not effective and enough in reducing air pollution, therefore it seems participatory management and public participation is suitable guideline.

Keywords: air pollution, quality of life, opinion poll, public participation

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Authors: Ikawati Wulandari

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Acquisition of geomagnetic field has been done at Geothermal manifestation Candi Umbul, Grabag, Magelang, Central Java Province on 10-12 May 2013. The purpose of this research to study sub-surface structure condition and the structure which control the hot springs manifestation. The research area have size of 1,5 km x 2 km and measurement spacing of 150 m. Total magnetic field data, the position, and the north pole direction have acquired by Proton Precession Magnetometer (PPM), Global Positioning System (GPS), and of geology compass, respectively. The raw data has been processed and performed using IGRF (International Geomagnetics Reference Field) correction to obtain total field magnetic anomaly. Upward continuation was performed at 100 meters height using software Magpick. Analysis conclude horizontal position of the body causing anomaly which is located at hot springs manifestation, and it stretch along Northeast - Southwest, which later interpreted as normal fault. This hotsprings manifestation was controlled by the downward fault which becomes a weak zone where hot water from underground the geothermal reservoir leakage

Keywords: PPM, Geothermal, Fault, Grabag

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Authors: Agah Tugrul Korucu

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Information and communication technologies have become an important part of our daily lives with significant investments in technology in the 21st century. Individuals are more willing to design and implement computer-related activities, and they are the main component of computer self-efficacy and self-efficacy related to the fact that the increase in information technology, with operations in parallel with these activities more successful. The Self-efficacy level is a significant factor which determines how individuals act in events, situations and difficult processes. It is observed that individuals with higher self-efficacy perception of computers who encounter problems related to computer use overcome them more easily. Therefore, this study aimed to examine self-efficacy perceptions of pre-service art and music teachers towards the use of information and communication technologies in terms of different variables. Research group consists of 60 pre-service teachers who are studying at Necmettin Erbakan University Ahmet Keleşoğlu Faculty of Education Art and Music department. As data collection tool of the study; “personal information form” developed by the researcher and used to collect demographic data and "the perception scale related to self-efficacy of informational technology" are used. The scale is 5-point Likert-type scale. It consists of 27 items. The Kaiser-Meyer-Olkin (KMO) sample compliance value is found 0.959. The Cronbach alpha reliability coefficient of the scale is found to be 0.97. computer-based statistical software package (SPSS 21.0) is used in order to analyze the data collected by data collection tools; descriptive statistics, t-test, analysis of variance are used as statistical techniques.

Keywords: self-efficacy perceptions, teacher candidate, information and communication technologies, art teacher

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Authors: Citra Pertiwi, Muhammad Fikruzzaman Rahawarin

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Government of Indonesia had committed to increasing its national defense the budget up to 1,5 percent of GDP. However, the budget increase does not necessarily allocate efficiently and effectively. Using Data Envelopment Analysis (DEA), the operational units of Indonesian Armed Forces are considered as a proxy to measure those two aspects. The bootstrap technique is being used as well to reduce uncertainty in the estimation. Additionally, technological change is being measured as a nonstationary component. Nearly half of the units are being estimated as fully efficient, with less than a third is considered as effective. Longer and larger sets of data might increase the robustness of the estimation in the future.

Keywords: bootstrap, effectiveness, efficiency, DEA, military, Malmquist, technological change

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Authors: Ali Muhammad

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The purpose of this study is to develop and test a theoretical framework which demonstrates the effect of procedural justice on four work outcomes: effective organizational commitmentو organizational trust, organizational citizenship behaviour, and adherence to rules. The new model attempts to explain how procedural justice effects work outcomes. Data were collected from 267 employees working in nine Kuwaiti business organizations. Structural equation modelling was used to analysis the data. A discussion of issues related to procedural justice is presented, as well as recommendations for future research.

Keywords: procedural justice, affective organizational commitment, organizational citizenship behaviour, organizational trust, adherence to rules

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Authors: Nusret Mesut Sahin

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Hrant Dink, a prominent Turkish-Armenian journalist, and editor-in-chief of the bilingual Turkish-Armenian newspaper Agos, was assassinated in Istanbul on January 19th, 2007 by a nationalist extremist, Ogun Samast. Dink had been voicing the atrocities against the Armenians between 1915 and 1922 during the Ottoman rule, and his comments on the issue appeared in the Turkish media many times before his assassination. Despite intensive media coverage of his assassination, there is not enough research analyzing how national and international media presented Dink’s assassination. In this research, a content analysis of national and international news articles (N= 139) is conducted to identify whether there is a significant difference in national and international media’s coverage of the assassination. The content of the newspaper articles is categorized and coded according to the topics covered. The findings of this research suggested that Dink’s assassination wounded Turkey’s image as a democratic country. It has also been found that the Turkish media focused on security forces and their responsibility in Dink’s assassination, whereas international media focused more on the Article 301 of the Turkish penal code, freedom of expression, and atrocities against the Armenians during the Ottoman rule.

Keywords: Hrant Dink, Armenian, journalist, assassination

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Authors: Peterson Thokozani Ngema, Paramespri Naidoo, Amir H. Mohammadi, Deresh Ramjugernath

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Phase equilibrium data (dissociation data) for clathrate hydrate (gas hydrate) were undertaken for systems involving fluorinated refrigerants with a single and mixed electrolytes (NaCl, CaCl₂, MgCl₂, and Na₂SO₄) aqueous solution at various salt concentrations in the absence and presence of cyclopentane (CP). The ternary systems for (R410a or R507) with the water system in the presence of CP were performed in the temperature and pressures ranges of (279.8 to 294.4) K and (0.158 to 1.385) MPa, respectively. Measurements for R410a with single electrolyte {NaCl or CaCl₂} solution in the presence of CP were undertaken at salt concentrations of (0.10, 0.15 and 0.20) mass fractions in the temperature and pressure ranges of (278.4 to 293.7) K and (0.214 to1.179) MPa, respectively. The temperature and pressure conditions for R410a with Na₂SO₄ aqueous solution system were investigated at a salt concentration of 0.10 mass fraction in the range of (283.3 to 291.6) K and (0.483 to 1.373) MPa respectively. Measurements for {R410a or R507} with mixed electrolytes {NaCl, CaCl₂, MgCl₂} aqueous solution was undertaken at various salt concentrations of (0.002 to 0.15) mass fractions in the temperature and pressure ranges of (274.5 to 292.9) K and (0.149 to1.119) MPa in the absence and presence of CP, in which there is no published data related to mixed salt and a promoter. The phase equilibrium measurements were performed using a non-visual isochoric equilibrium cell that co-operates the pressure-search technique. This study is focused on obtaining equilibrium data that can be utilized to design and optimize industrial wastewater, desalination process and the development of Hydrate Electrolyte–Cubic Plus Association (HE–CPA) Equation of State. The results show an impressive improvement in the presence of promoter (CP) on hydrate formation because it increases the dissociation temperatures near ambient conditions. The results obtained were modeled using a developed HE–CPA equation of state. The model results strongly agree with the measured hydrate dissociation data.

Keywords: association, desalination, electrolytes, promoter

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Authors: Ilda Muçmataj, Anjeza Liçenji, Borana Kalemi

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Copyright and related rights have been pivotal in driving the economic growth of nations worldwide and fostering culture and new forms of entertainment. The introduction of the internet and technological advancement has significantly expanded the opportunities for creators and rights holders to promote their works and boost their revenues. However, this digital era has also brought about complex challenges, leading to a more extensive range of copyright infringement, primarily due to the substantial surge in piracy and counterfeiting. Despite being reported internationally, the mechanisms to tackle and the responsibility for enforcing copyright infringements often remain rooted in national jurisdictions, resulting in a gap between the scale of the problem and the efficacy of enforcement measures. Thus, it is essential to ensure adequate legal protection, a vital safeguard for authors' economic and moral interests, information security, innovative development promotion, and intellectual creativity preservation. This paper describes Albanian criminal law-based copyright enforcement legislation, focusing on doctrinal guidance and practical judicial considerations. Lastly, the paper offers recommendations for enhancing copyright protection and related rights.

Keywords: author, copyright infringement, copyright, criminal liability, intellectual property, piracy

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Authors: Ailing Yang, Penghan Song, Aihua Cai

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The nonlinear maneuvering target tracking problem is mainly a state estimation problem when the target motion model is uncertain. Traditional solutions include Kalman filtering based on Bayesian filtering framework and extended Kalman filtering. However, these methods need prior knowledge such as kinematics model and state system distribution, and their performance is poor in state estimation of nonprior complex dynamic systems. Therefore, in view of the problems existing in traditional algorithms, a convolution LSTM target state estimation (SAConvLSTM-SE) algorithm based on Self-Attention memory (SAM) is proposed to learn the historical motion state of the target and the error distribution information measured at the current time. The measured track point data of airborne radar are processed into data sets. After supervised training, the data-driven deep neural network based on SAConvLSTM can directly obtain the target state at the next moment. Through experiments on two different maneuvering targets, we find that the network has stronger robustness and better tracking accuracy than the existing tracking methods.

Keywords: maneuvering target, state estimation, Kalman filter, LSTM, self-attention

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Authors: Santosh B. Phad, Priyanka V. Janbandhu, Dhananjay W. Bansod

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Population Ageing is a growing concern for the social scientists. There is a higher level of aged male participation compared to elderly females. Now, the critical question is whether participation in work improves the quality of life among the elderly and the impact of working status on the mental well-being of the elderly. While examining these research questions, the present paper focuses on the workforce participation of the elderly and the reasons behind it, additionally, determines the association between employment status and the mental well-being of the elderly. The present study has a base of two data sources. First one is Census of India data, 2001 and 2011, and another one is – the Study on Global Ageing and Adult Health (SAGE), a survey conducted in 2007. To capture the trend of workforce participation elderly Census data is significant and to obtain other information associated with this issue the SAGE data is studied. The research piece consists of univariate and bivariate analysis along with some statistical methods like principal component analysis (PCA) and regression modeling – to investigate the association between workforce participation of elderly and subjective well-being (SWB). The results show that the percentage of elderly participating in the labor market is gradually reducing, but the share of working elderly has increased within the group of overall workers. i.e., the ratio of aged workers to non-aged workers is rising. The findings from survey data specify that there is a considerable share of the elderly in the labor market; three-fourths of the employed elderly enrolled the workforce unwillingly. They are in need of some earnings mainly to afford the medical expenses on their health or the health of their spouse, also to support their family members who are economically inactive. Apart from need, duration of working is another vital aspect for the elderly, whereas more than 80 percent of the elderly are working for six hours or more, and most of them engaged in self-employment. However, more than one-third of the working elderly falls into a negative cluster of the subjective well-being (SWB) index, and it is consistent with the result of the discriminant analysis. Here, the SWB index calculated from the 12 items and the reliability score of these items is 0.89.

Keywords: ageing, workforce, census of India, SAGE

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Authors: Sohail Ahmad, Inayat Kaleem

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Federally Administered Tribal Area(FATA) of Pakistan is one of the most neglected regions in the world as far as development is concerned. It has been the hub of all sorts of illegal activities including militancy and export of terrorism. Therefore, it became inevitable for the government of Pakistan to take action against militants through military operations. Small and large scale military operations are being taken against the non-state actors in FATA with continuity. Over the years, hundreds of thousands have been displaced from the tribal areas of the country. Moreover, military operation Zarb-e-Azb has been launched in North Waziristan Agency in June 2014 to counter militancy across the Af-Pak border region. Though successful in curbing militancy, the operation has displaced around 0.5 million people from the area. Most of them opt to take shelter in the government installed shelter camps, some of them take refuge outside tent villages in the country while some of them prefer to cross into Afghanistan rather their own country Pakistan. This paper will evaluate how the influx of these internally displaced persons in the country is influencing the socio-economic situation of not only the displaced but of the hosting areas as well. Secondly, attention would be given to gauge the impact of such a huge number of displaced population on the law and order and security situation in the host areas.

Keywords: Af-Pak, federally administered tribal area, IDPs, internal displacement, Pakistan

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Authors: Linyao Qiu, Zhiqiang Du

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As the rapid development of urbanization, economic developments, and steady population growth in China, the widespread devastation, economic damages, and loss of human lives caused by numerous forms of natural disasters are becoming increasingly serious every year. Disaster management requires available and effective cooperation of different roles and organizations in whole process including mitigation, preparedness, response and recovery. Due to the imbalance of regional development in China, the disaster management capabilities of national and provincial disaster reduction centers are uneven. When an undeveloped area suffers from disaster, neither local reduction department could get first-hand information like high-resolution remote sensing images from satellites and aircrafts independently, nor sharing mechanism is provided for the department to access to data resources deployed in other place directly. Most existing disaster management systems operate in a typical passive data-centric mode and work for single department, where resources cannot be fully shared. The impediment blocks local department and group from quick emergency response and decision-making. In this paper, we introduce a collaborative platform for distributed disaster reduction. To address the issues of imbalance of sharing data sources and technology in the process of disaster reduction, we propose a multi-role oriented collaboration business mechanism, which is capable of scheduling and allocating for optimum utilization of multiple resources, to link various roles for collaborative reduction business in different place. The platform fully considers the difference of equipment conditions in different provinces and provide several service modes to satisfy technology need in disaster reduction. An integrated collaboration system based on focusing services mechanism is designed and implemented for resource scheduling, functional integration, data processing, task management, collaborative mapping, and visualization. Actual applications illustrate that the platform can well support data sharing and business collaboration between national and provincial department. It could significantly improve the capability of disaster reduction in China.

Keywords: business collaboration, data sharing, distributed disaster reduction, focusing service

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Authors: Prabin Raj Gautam

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Entrepreneurship in tourism sectors, particularly hotel entrepreneurship has contributed to Nepalese Gross Domestic Production (GDP). The tourist standard and star hotels in developing countries have not only been generating revenues but also providing international hospitality to the guest in the local areas. For doing so, these hotel enterprises must need to implement different business strategies to enhance and maintain their international business benchmark. The Entrepreneurial Orientation (EO) is core for making business strategies. Meanwhile, the corruption is labeled as negative factor for economic development. This paper presents the relationship between EO of Nepalese star hotels and organizational corruption. The study employed questionnaire survey as data collection tool under the quantitative methodology. Five hypotheses are developed and tested. After gathering the data form 216 questionnaire distributed to CEOs/Managers of the sample hotels, the findings show that out of five dimensions of EO, only autonomy, pro-activeness, and innovativeness are not significant to organizational corruption; however, risk-taking and competitive aggressiveness are found significant contributor. The descriptive statistics and structural equation modeling are employed to describe the data and fit the model.

Keywords: entrepreneurship, entrepreneurial orientation, organizational corruption, dimensions

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Authors: Mara Getachew Zenebe, Luuk Fleskens, Abdu Obieda Ahmed

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This paper seeks to advance our scientific understanding of optimizing flood utilization in regions impacted by climate change, with a focus on enhancing agricultural productivity through effective irrigation management. The study was conducted as part of a three-year (2021 to 2023) USAID-supported initiative aimed at promoting Economic Growth and Peace in the Gash Agricultural Scheme (GAS), situated in Sudan's water-stressed Eastern region. GAS is the country's largest flood-irrigated scheme, covering 100,800 hectares of cultivable land, with a potential to provide the food security needs of over a quarter of a million agro-pastoral community members. GAS relies on the Gash River, which sources its water from high-intensity rainfall events in the highlands of Ethiopia and Eritrea. However, climate change and variations in these highlands have led to increased variability in the Gash River's flow. The study conducted water balance analyses based on a ten-year dataset of the annual Gash River flow, irrigated area; as well as the evapotranspiration demand of the major sorghum crop. Data collection methods included field measurements, surveys, remote sensing, and CropWat modelling. The water balance assessment revealed that the existing three-year rotation-based irrigation system management, capping cultivated land at 33,000 hectares annually, is excessively risk-averse. While this system reduced conflicts among the agro-pastoral communities by consistently delivering on the land promised to be annually cultivated, it also increased GAS's vulnerability to flood damage due to several reasons. The irrigation efficiency over the past decade was approximately 30%, leaving significant unharnessed floodwater that caused damage to infrastructure and agricultural land. The three-year rotation resulted in inadequate infrastructural maintenance, given the destructive nature of floods. Additionally, it led to infrequent land tillage, allowing the encroachment of mesquite trees hindering major sorghum crop growth. Remote sensing data confirmed that mesquite trees have overtaken 70,000 hectares in the past two decades, rendering them unavailable for agriculture. The water balance analyses suggest shifting to a two-year rotation, covering approximately 50,000 hectares annually while maintaining risk aversion. This shift could boost GAS's annual sorghum production by two-thirds, exceeding 850,000 tons. The scheme's efficiency can be further enhanced through low-cost on-farm interventions. Currently, large irrigation plots that range from 420 to 756 hectares are irrigated with limited water distribution guidance, leading to uneven irrigation. As demonstrated through field trials, implementing internal longitudinal bunds and horizontal deflector bunds can increase adequately irrigated parts of the irrigation plots from 50% to 80% and thus nearly double the sorghum yield to 2 tons per hectare while reducing the irrigation duration from 30 days to a maximum of 17 days. Flow measurements in 2021 and 2022 confirmed that these changes sufficiently meet the sorghum crop's water requirements, even with a conservative 60% field application efficiency assumption. These insights and lessons from the GAS on enhancing agricultural resilience and sustainability in the face of climate change are relevant to flood-based livelihood systems globally.

Keywords: climate change, irrigation management and productivity, variable flood flows, water balance analysis

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Authors: Daiva Skuciene

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The Baltic States turned to free market and capitalism after independency. The new socioeconomic system, democracy and priorities about the welfare of citizens formed. The researches show that Baltic states choose the neoliberal development. Related to this neoliberal path, a few questions arouse: how do people evaluate the results of such policy and socioeconomic development? What are their priorities? And what are the values of the Baltic societies that support neoliberal policy? The purpose of this research – to analyze the socioeconomic context and the priorities and the values of the Baltics societies related to neoliberal regime. The main objectives are: firstly, to analyze the neoliberal socioeconomic features and results; secondly, to analyze people opinions and priorities about the results of neoliberal development; thirdly, to analyze the values of the Baltic societies related to the neoliberal policy. For the implementation of the purpose and objectives, the comparative analyses among European countries are used. The neoliberal regime was defined through two indicators: the taxes on capital income and expenditures on social protection. The socioeconomic outcomes of neoliberal welfare regime are defined through the Gini inequality and at risk of the poverty rate. For this analysis, the data of 2002-2013 of Eurostat were used. For the analyses of opinion about inequality and preferences on society, people want to live in, the preferences for distribution between capital and wages in enterprise data of Eurobarometer in 2010-2014 and the data of representative survey in the Baltic States in 2016 were used. The justice variable was selected as a variable reflecting the evaluation of socioeconomic context and analyzed using data of Eurobarometer 2006-2015. For the analyses of values were selected: solidarity, equality, and individual responsibility. The solidarity, equality was analyzed using data of Eurobarometer 2006-2015. The value “individual responsibility” was examined by opinions about reasons of inequality and poverty. The survey of population in the Baltic States in 2016 and data of Eurobarometer were used for this aim. The data are ranged in descending order for understanding the position of opinion of people in the Baltic States among European countries. The dynamics of indicators is also provided to examine stability of values. The main findings of the research are that people in the Baltics are dissatisfied with the results of the neoliberal socioeconomic development, they have priorities for equality and justice, but they have internalized the main neoliberal narrative- individual responsibility. The impact of socioeconomic context on values is huge, resulting in a change in quite stable opinions and values during the period of the financial crisis.

Keywords: neoliberal, inequality and poverty, solidarity, individual responsibility

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Authors: Zhou Shangcheng, Yi Sicen

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Objective: To understand the mortality patterns of Zhangwan District in 2010 and provide the basis for the development of scientific and rational health policy. Methods: Data are collected from the Sixth Census of Zhangwan District and disease surveillance system. The statistical analysis include death difference between age, gender, region and time and the related factors. Methods developed for the Global Burden of Disease (GBD) Study by the World Bank and World Health Organization (WHO) were adapted and applied to Zhangwan District population health data. DALY rate per 1,000 was calculated for varied causes of death. SPSS 16 is used by statistic analysis. Results: From the data of death population of Zhangwan District we know the crude mortality rate was 6.03 ‰. There are significant differences of mortality rate in male and female population which was respectively 7.37 ‰ and 4.68 ‰. 0 age group population life expectancy in Zhangwan District in 2010 was 78.40 years old(Male 75.93, Female 81.03). The five leading causes of YLL in descending order were: cardiovascular diseases(42.63DALY/1000), malignant neoplasm (23.73DALY/1000), unintentional injuries (5.84DALY/1000), Respiratory diseases(5.43 DALY/1000), Respiratory infections (2.44DALY/1000). In addition, there are strong relation between the marital status , educational level and mortality in some to a certain extend. Conclusion Zhangwan District, as city level, is at lower mortality levels. The mortality of the total population of Zhangwan District has a downward trend and life expectancy is rising.

Keywords: sixth census, Zhangwan district, death level differences, influencing factors, cause of death

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Authors: Amir B. Khoshnevis, Morteza Mirhosseini

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The paper deals with a sub-part of an extensive research program on the wake survey method in various Reynolds numbers and angles of attack. This research experimentally investigates the wake flow characteristics behind S823 and S822 airfoils in which designed for small wind turbines. Velocity measurements determined by using hot-wire anemometer. Data acquired in the wake of the airfoil at locations(c is the chord length): 0.01c - 3c. Reynolds number increased due to increase of free stream velocity. Results showed that mean velocity profiles depend on the angle of attack and location of data collections. Data acquired at the low Reynolds numbers (smaller than 10^5). Effects of Reynolds numbers on the mean velocity profiles are more significant in near locations the trailing edge and these effects decrease by taking distance from trailing edge toward downstream. Mean velocity profiles region increased by increasing the angle of attack, except for 7°, and also the maximum velocity deficit (velocity defect) increased. The difference of mean velocity in and out of the wake decreased by taking distance from trailing edge, and mean velocity profile become wider and more uniform.

Keywords: angle of attack, Reynolds number, velocity deficit, separation

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Authors: S. Chuenchooklin, S. Taweepong, U. Pangnakorn

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This research was conducted in the Mae Sot Watershed whereas located in the Moei River Basin at the Upper Salween River Basin in Tak Province, Thailand. The Mae Sot Municipality is the largest urbanized in Tak Province and situated in the midstream of the Mae Sot Watershed. It usually faces flash flood problem after heavy rain due to poor flood management has been reported since economic rapidly bloom up in recently years. Its catchment can be classified as ungauged basin with lack of rainfall data and no any stream gaging station was reported. It was attached by most severely flood event in 2013 as the worst studied case for those all communities in this municipality. Moreover, other problems are also faced in this watershed such shortage water supply for domestic consumption and agriculture utilizations including deterioration of water quality and landslide as well. The research aimed to increase capability building and strengthening the participation of those local community leaders and related agencies to conduct better water management in urban area was started by mean of the data collection and illustration of appropriated application of some short period rainfall forecasting model as the aim for better flood relief plan and management through the hydrologic model system and river analysis system programs. The authors intended to apply the global rainfall data via the integrated data viewer (IDV) program from the Unidata with the aim for rainfall forecasting in short period of 7 - 10 days in advance during rainy season instead of real time record. The IDV product can be present in advance period of rainfall with time step of 3 - 6 hours was introduced to the communities. The result can be used to input to either the hydrologic modeling system model (HEC-HMS) or the soil water assessment tool model (SWAT) for synthesizing flood hydrographs and use for flood forecasting as well. The authors applied the river analysis system model (HEC-RAS) to present flood flow behaviors in the reach of the Mae Sot stream via the downtown of the Mae Sot City as flood extents as water surface level at every cross-sectional profiles of the stream. Both models of HMS and RAS were tested in 2013 with observed rainfall and inflow-outflow data from the Mae Sot Dam. The result of HMS showed fit to the observed data at dam and applied at upstream boundary discharge to RAS in order to simulate flood extents and tested in the field, and the result found satisfied. The result of IDV’s rainfall forecast data was compared to observed data and found fair. However, it is an appropriate tool to use in the ungauged catchment to use with flood hydrograph and river analysis models for future efficient flood relief plan and management.

Keywords: global rainfall, flood forecast, hydrologic modeling system, river analysis system

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Authors: Rodrigo Buaiz Boabaid

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Tokenization of Blue Bonds is an emerging Green Finance tool that has the potential to scale Blue Carbon Projects to fight climate change. This innovative solution has a huge potential to democratize the green finance market and catalyze innovations in the climate change finance sector. Switzerland has emerged as a leader in the Green Finance space and is well-positioned to drive the adoption of Tokenization of Blue & Green Bonds. This unique approach has the potential to unlock new sources of capital and enable global investors to participate in the financing of sustainable blue carbon projects. By leveraging the power of blockchain technology, Tokenization of Blue Bonds can provide greater transparency, efficiency, and security in the investment process while also reducing transaction costs. Investments are in line with the highest regulations and designed according to the stringent legal framework and compliance standards set by Switzerland. The potential benefits of Tokenization of Blue Bonds are significant and could transform the way that sustainable projects are financed. By unlocking new sources of capital, this approach has the potential to accelerate the deployment of Blue Carbon projects and create new opportunities for investors to participate in the fight against climate change.

Keywords: blue bonds, blue carbon, tokenization, green finance

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Authors: Satyanarayana Engu, Ahmed Mohd, V. Murugan

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We study the large time asymptotics of solutions to the Cauchy problem for a forced Burgers equation (FBE) with the initial data, which is continuous and summable on R. For which, we first derive explicit solutions of FBE assuming a different class of initial data in terms of Hermite polynomials. Later, by violating this assumption we prove the existence of a solution to the considered Cauchy problem. Finally, we give an asymptotic approximate solution and establish that the error will be of order O(t^(-1/2)) with respect to L^p -norm, where 1≤p≤∞, for large time.

Keywords: Burgers equation, Cole-Hopf transformation, Hermite polynomials, large time asymptotics

Procedia PDF Downloads 336

Authors: Alfredo Fortunato, Carmelofrancesco Origlia, Sara Laurita, Rossella Nicoletti

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In the post-pandemic recovery phase of tourism, the role of a Destination Management Organization (DMO) as a coordinated management system of all the elements that make up a destination (attractions, access, marketing, human resources, brand, pricing, etc.) is also becoming relevant for local territories. The objective of a DMO is to maximize the visitor's perception of value and quality while ensuring the competitiveness and sustainability of the destination, as well as the long-term preservation of its natural and cultural assets, and to catalyze benefits for the local economy and residents. In carrying out the multiple functions to which it is called, the DMO can leverage a collective intelligence that comes from the ability to pool information, explicit and tacit knowledge, and relationships of the various stakeholders: policymakers, public managers and officials, entrepreneurs in the tourism supply chain, researchers, data journalists, schools, associations and committees, citizens, etc. The DMO potentially has at its disposal large volumes of data and many of them at low cost, that need to be properly processed to produce value. Based on these assumptions, the paper presents a conceptual framework for building an information system to support the DMO in the intelligent management of a tourist destination tested in an area of southern Italy. The approach adopted is data-informed and consists of four phases: (1) formulation of the knowledge problem (analysis of policy documents and industry reports; focus groups and co-design with stakeholders; definition of information needs and key questions); (2) research and metadatation of relevant sources (reconnaissance of official sources, administrative archives and internal DMO sources); (3) gap analysis and identification of unconventional information sources (evaluation of traditional sources with respect to the level of consistency with information needs, the freshness of information and granularity of data; enrichment of the information base by identifying and studying web sources such as Wikipedia, Google Trends, Booking.com, Tripadvisor, websites of accommodation facilities and online newspapers); (4) definition of the set of indicators and construction of the information base (specific definition of indicators and procedures for data acquisition, transformation, and analysis). The framework derived consists of 6 thematic areas (accommodation supply, cultural heritage, flows, value, sustainability, and enabling factors), each of which is divided into three domains that gather a specific information need to be represented by a scheme of questions to be answered through the analysis of available indicators. The framework is characterized by a high degree of flexibility in the European context, given that it can be customized for each destination by adapting the part related to internal sources. Application to the case study led to the creation of a decision support system that allows: •integration of data from heterogeneous sources, including through the execution of automated web crawling procedures for data ingestion of social and web information; •reading and interpretation of data and metadata through guided navigation paths in the key of digital story-telling; •implementation of complex analysis capabilities through the use of data mining algorithms such as for the prediction of tourist flows.

Keywords: collective intelligence, data framework, destination management, smart tourism

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Authors: Hossein Aghababaei, Sergio Vitale, Giampaolo Ferraioli

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In the context of Synthetic Aperture Radar (SAR) data, polarization is an important source of information for Earth's surface monitoring. SAR Systems are often considered to transmit only one polarization. This constraint leads to either single or dual polarimetric SAR imaging modalities. Single polarimetric systems operate with a fixed single polarization of both transmitted and received electromagnetic (EM) waves, resulting in a single acquisition channel. Dual polarimetric systems, on the other hand, transmit in one fixed polarization and receive in two orthogonal polarizations, resulting in two acquisition channels. Dual polarimetric systems are obviously more informative than single polarimetric systems and are increasingly being used for a variety of remote sensing applications. In dual polarimetric systems, the choice of polarizations for the transmitter and the receiver is open. The choice of circular transmit polarization and coherent dual linear receive polarizations forms a special dual polarimetric system called hybrid polarimetry, which brings the properties of rotational invariance to geometrical orientations of features in the scene and optimizes the design of the radar in terms of reliability, mass, and power constraints. The complete characterization of target scattering, however, requires fully polarimetric data, which can be acquired with systems that transmit two orthogonal polarizations. This adds further complexity to data acquisition and shortens the coverage area or swath of fully polarimetric images compared to the swath of dual or hybrid polarimetric images. The search for solutions to augment dual polarimetric data to full polarimetric data will therefore take advantage of full characterization and exploitation of the backscattered field over a wider coverage with less system complexity. Several methods for reconstructing fully polarimetric images using hybrid polarimetric data can be found in the literature. Although the improvements achieved by the newly investigated and experimented reconstruction techniques are undeniable, the existing methods are, however, mostly based upon model assumptions (especially the assumption of reflectance symmetry), which may limit their reliability and applicability to vegetation and forest scenarios. To overcome the problems of these techniques, this paper proposes a new framework for reconstructing fully polarimetric information from hybrid polarimetric data. The framework uses Deep Learning solutions to augment hybrid polarimetric data without relying on model assumptions. A convolutional neural network (CNN) with a specific architecture and loss function is defined for this augmentation problem by focusing on different scattering properties of the polarimetric data. In particular, the method controls the CNN training process with respect to several characteristic features of polarimetric images defined by the combination of different terms in the cost or loss function. The proposed method is experimentally validated with real data sets and compared with a well-known and standard approach from the literature. From the experiments, the reconstruction performance of the proposed framework is superior to conventional reconstruction methods. The pseudo fully polarimetric data reconstructed by the proposed method also agree well with the actual fully polarimetric images acquired by radar systems, confirming the reliability and efficiency of the proposed method.

Keywords: SAR image, polarimetric SAR image, convolutional neural network, deep learnig, deep neural network

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Authors: Alaa A. Almarzuki, Nora A. Farraj, Aisha M. Alshiky, Omar A. Batarfi

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The number of internet users is dramatically increased every year. Most of these users are exposed to the dangers of attackers in one way or another. The reason for this lies in the presence of many weaknesses that are not known for native users. In addition, the lack of user awareness is considered as the main reason for falling into the attackers’ snares. Cross Site Request Forgery (CSRF) has placed in the list of the most dangerous threats to security in OWASP Top Ten for 2013. CSRF is an attack that forces the user’s browser to send or perform unwanted request or action without user awareness by exploiting a valid session between the browser and the server. When CSRF attack successes, it leads to many bad consequences. An attacker may reach private and personal information and modify it. This paper aims to detect and prevent a specific type of CSRF, called reflected CSRF. In a reflected CSRF, a malicious code could be injected by the attackers. This paper explores how CSRF Detection Extension prevents the reflected CSRF by checking browser specific information. Our evaluation shows that the proposed solution succeeds in preventing this type of attack.

Keywords: CSRF, CSRF detection extension, attackers, attacks

Procedia PDF Downloads 416

Authors: Mary Jane B. Suarez

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Public speaking anxiety (PSA), also known as speech anxiety, is innumerably persistent in any traditional communication classes, especially for students who learn English as a second language. The speech anxiety intensifies when communication skills assessments have taken their toll in an online or a remote mode of learning due to the perils of the COVID-19 virus. Both teachers and students have experienced vast ambiguity on how to realize a still effective way to teach and learn speaking skills amidst the pandemic. Communication skills assessments like public speaking, oral presentations, and student reporting have defined their new meaning using Google Meet, Zoom, and other online platforms. Though using such technologies has paved for more creative ways for students to acquire and develop communication skills, the effectiveness of using such assessment tools stands in question. This mixed method study aimed to determine the factors that affected the public speaking skills of students in a communication class, to probe on the assessment gaps in assessing speaking skills of students attending online classes vis-à-vis the implementation of remote and blended modalities of learning, and to recommend ways on how to address the public speaking anxieties of students in performing a speaking task online and to bridge the assessment gaps based on the outcome of the study in order to achieve a smooth segue from online to on-ground instructions maneuvering towards a much better post-pandemic academic milieu. Using a convergent parallel design, both quantitative and qualitative data were reconciled by probing on the public speaking anxiety of students and the potential assessment gaps encountered in an online English communication class under remote and blended learning. There were four phases in applying the convergent parallel design. The first phase was the data collection, where both quantitative and qualitative data were collected using document reviews and focus group discussions. The second phase was data analysis, where quantitative data was treated using statistical testing, particularly frequency, percentage, and mean by using Microsoft Excel application and IBM Statistical Package for Social Sciences (SPSS) version 19, and qualitative data was examined using thematic analysis. The third phase was the merging of data analysis results to amalgamate varying comparisons between desired learning competencies versus the actual learning competencies of students. Finally, the fourth phase was the interpretation of merged data that led to the findings that there was a significantly high percentage of students' public speaking anxiety whenever students would deliver speaking tasks online. There were also assessment gaps identified by comparing the desired learning competencies of the formative and alternative assessments implemented and the actual speaking performances of students that showed evidence that public speaking anxiety of students was not properly identified and processed.

Keywords: blended learning, communication skills assessment, public speaking anxiety, speech anxiety

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Authors: Al Omari Moahmmed Ahmed

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In the Bayesian, we developed an approach by using non-informative prior with covariate and obtained by using Gauss quadrature method to estimate the parameters of the covariate and reliability function of the Weibull regression distribution with Type-I censored data. The maximum likelihood seen that the estimators obtained are not available in closed forms, although they can be solved it by using Newton-Raphson methods. The comparison criteria are the MSE and the performance of these estimates are assessed using simulation considering various sample size, several specific values of shape parameter. The results show that Bayesian with non-informative prior is better than Maximum Likelihood Estimator.

Keywords: non-informative prior, Bayesian method, type-I censoring, Gauss quardature

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Authors: Andres F. Ramirez, Carlos F. Valencia

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The increasing interest in renewable energies strategies application and the path for diminishing the use of carbon related energy sources have encouraged the development of novel strategies for integration of solar energy into the electricity network. A correct inclusion of the fluctuating energy output of a photovoltaic (PV) energy system into an electric grid requires improvements in the forecasting and simulation methodologies for solar energy potential, and the understanding not only of the mean value of the series but the associated underlying stochastic process. We present a methodology for synthetic generation of solar irradiance (shortwave flux) and air temperature bivariate time series based on copula functions to represent the cross-dependence and temporal structure of the data. We explore the advantages of using this nonlinear time series method over traditional approaches that use a transformation of the data to normal distributions as an intermediate step. The use of copulas gives flexibility to represent the serial variability of the real data on the simulation and allows having more control on the desired properties of the data. We use discrete zero mass density distributions to assess the nature of solar irradiance, alongside vector generalized linear models for the bivariate time series time dependent distributions. We found that the copula autoregressive methodology used, including the zero mass characteristics of the solar irradiance time series, generates a significant improvement over state of the art strategies. These results will help to better understand the fluctuating nature of solar energy forecasting, the underlying stochastic process, and quantify the potential of a photovoltaic (PV) energy generating system integration into a country electricity network. Experimental analysis and real data application substantiate the usage and convenience of the proposed methodology to forecast solar irradiance time series and solar energy across northern hemisphere, southern hemisphere, and equatorial zones.

Keywords: copula autoregressive, solar irradiance forecasting, solar energy forecasting, time series generation

Procedia PDF Downloads 327

Authors: Dangut Maren David, Skaf Zakwan

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Adequate monitoring of vehicle component in other to obtain high uptime is the goal of predictive maintenance, the major challenge faced by businesses in industries is the significant cost associated with a delay in service delivery due to system downtime. Most of those businesses are interested in predicting those problems and proactively prevent them in advance before it occurs, which is the core advantage of Prognostic Health Management (PHM) application. The recent emergence of industry 4.0 or industrial internet of things (IIoT) has led to the need for monitoring systems activities and enhancing system-to-system or component-to- component interactions, this has resulted to a large generation of data known as big data. Analysis of big data represents an increasingly important, however, due to complexity inherently in the dataset such as imbalance classification problems, it becomes extremely difficult to build a model with accurate high precision. Data-driven predictive modeling for condition-based maintenance (CBM) has recently drowned research interest with growing attention to both academics and industries. The large data generated from industrial process inherently comes with a different degree of complexity which posed a challenge for analytics. Thus, imbalance classification problem exists perversely in industrial datasets which can affect the performance of learning algorithms yielding to poor classifier accuracy in model development. Misclassification of faults can result in unplanned breakdown leading economic loss. In this paper, an advanced approach for handling imbalance classification problem is proposed and then a prognostic model for predicting aircraft component replacement is developed to predict component replacement in advanced by exploring aircraft historical data, the approached is based on hybrid ensemble-based method which improves the prediction of the minority class during learning, we also investigate the impact of our approach on multiclass imbalance problem. We validate the feasibility and effectiveness in terms of the performance of our approach using real-world aircraft operation and maintenance datasets, which spans over 7 years. Our approach shows better performance compared to other similar approaches. We also validate our approach strength for handling multiclass imbalanced dataset, our results also show good performance compared to other based classifiers.

Keywords: prognostics, data-driven, imbalance classification, deep learning

Procedia PDF Downloads 177