Search results for: regional data

Authors: Bouhouf Atef, Beloulou Mohamed Lamine

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Introduction: Outpatient surgery is continually developing compared to conventional inpatient surgery; its rate is constantly increasing every year due to global socio-economic pressure. Most hospitals continue to perform proctologic surgery in conventional hospitalization. Purpose: As part of a monocentric prospective descriptive study, we examined the feasibility of proctologic surgery under saddle block on an outpatient basis with the same safety conditions as in traditional hospitalization. Material and methods: This is a monocentric prospective descriptive study spread over a period of 24 months, from December 2018 to December 2020 including 150 patients meeting the medico-surgical and socio-environmental criteria of eligibility for outpatient surgery, operated for proctological pathologies under saddle block in outpatient mode, in the surgery department of the regional military hospital of Constantine Algeria. The data were collected and analyzed by the biomedical statistics software Epi-info and Microsoft Excel, then compared with other related studies. Results: This study involved over a period of two years, 150 male patients with an average age of 32 years (20-64). Most patients (95,33%) were ASA I class, and 4,67% ASA II class. All patients received saddle blocks. The average length of stay of patients was six hours. The quality indicators in outpatient surgery in our study were: zero (0)% of deprogrammings, three (3)% of conversions to full hospitalization, 0,7% of readmissions, an average waiting time before access to the operating room of 83 minutes without delay of discharge, a satisfaction rate of 90,8% and a reduction in the cost compared to conventional inpatient surgery in proportions ranging from – 32,6% and – 48,75%. Conclusions: The outpatient management of proctological surgery under saddle block is very beneficial in terms of safety, efficiency, simplicity, and economy. Our results are in line with those of the literature and our work deserves to be continued to include many patients.

Keywords: outpatient surgery, proctological surgery, saddle block, satisfaction, cost

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Authors: Bhat Geetalaxmi Jairam, D. V. Ashoka

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Wireless Sensor Networks are used in many applications to collect sensed data from different sources. Sensed data has to be delivered through sensors wireless interface using multi-hop communication towards the sink. The data collection in wireless sensor networks consumes energy. Energy consumption is the major constraints in WSN .Reducing the energy consumption while increasing the amount of generated data is a great challenge. In this paper, we have implemented two data gathering protocols with multiple mobile sinks/elements to collect data from sensor nodes. First, is Energy-Efficient Data Gathering with Tour Length-Constrained Mobile Elements in Wireless Sensor Networks (EEDG), in which mobile sinks uses vehicle routing protocol to collect data. Second is An Intelligent Agent-based Routing Structure for Mobile Sinks in WSNs (IAR), in which mobile sinks uses prim’s algorithm to collect data. Authors have implemented concepts which are common to both protocols like deployment of mobile sinks, generating visiting schedule, collecting data from the cluster member. Authors have compared the performance of both protocols by taking statistics based on performance parameters like Delay, Packet Drop, Packet Delivery Ratio, Energy Available, Control Overhead. Authors have concluded this paper by proving EEDG is more efficient than IAR protocol but with few limitations which include unaddressed issues likes Redundancy removal, Idle listening, Mobile Sink’s pause/wait state at the node. In future work, we plan to concentrate more on these limitations to avail a new energy efficient protocol which will help in improving the life time of the WSN.

Keywords: aggregation, consumption, data gathering, efficiency

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Authors: Ryan Maclellan

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EXO-200 has provided one of the most sensitive searches for neutrinoless double-beta decay utilizing 175 kg of enriched liquid xenon in an ultra-low background time projection chamber. This detector has demonstrated excellent energy resolution and background rejection capabilities. Using the first two years of data, EXO-200 has set a limit of 1.1x10^25 years at 90% C.L. on the neutrinoless double-beta decay half-life of Xe-136. The experiment has experienced a brief hiatus in data taking during a temporary shutdown of its host facility: the Waste Isolation Pilot Plant. EXO-200 expects to resume data taking in earnest this fall with upgraded detector electronics. Results from the analysis of EXO-200 data and an update on the current status of EXO-200 will be presented.

Keywords: double-beta, Majorana, neutrino, neutrinoless

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Authors: Amit R. Bhende, G. K. Awari

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Remaining useful life (RUL) prediction is one of key technologies to realize prognostics and health management that is being widely applied in many industrial systems to ensure high system availability over their life cycles. The present work proposes a data-driven method of RUL prediction based on multiple health state assessment for rolling element bearings. Bearing degradation data at three different conditions from run to failure is used. A RUL prediction model is separately built in each condition. Feed forward back propagation neural network models are developed for prediction modeling.

Keywords: bearing degradation data, remaining useful life (RUL), back propagation, prognosis

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Authors: Tolga Aydin, M. Fatih Alaeddinoğlu

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People, throughout the history, have made estimates and inferences about the future by using their past experiences. Developing information technologies and the improvements in the database management systems make it possible to extract useful information from knowledge in hand for the strategic decisions. Therefore, different methods have been developed. Data mining by association rules learning is one of such methods. Apriori algorithm, one of the well-known association rules learning algorithms, is not commonly used in spatio-temporal data sets. However, it is possible to embed time and space features into the data sets and make Apriori algorithm a suitable data mining technique for learning spatio-temporal association rules. Lake Van, the largest lake of Turkey, is a closed basin. This feature causes the volume of the lake to increase or decrease as a result of change in water amount it holds. In this study, evaporation, humidity, lake altitude, amount of rainfall and temperature parameters recorded in Lake Van region throughout the years are used by the Apriori algorithm and a spatio-temporal data mining application is developed to identify overflows and newly-formed soil regions (underflows) occurring in the coastal parts of Lake Van. Identifying possible reasons of overflows and underflows may be used to alert the experts to take precautions and make the necessary investments.

Keywords: apriori algorithm, association rules, data mining, spatio-temporal data

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Authors: Busayo Fashoto, Abdulhakeem Shaibu, Justice Agbadu, Samuel Aiyeoribe

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Data has gone from just rows and columns to being an infrastructure itself. The traditional medium of data infrastructure has been managed by individuals in different industries and saved on personal work tools; one of such is the laptop. This hinders data sharing and Sustainable Development Goal (SDG) 9 for infrastructure sustainability across all countries and regions. However, there has been a constant demand for data across different agencies and ministries by investors and decision-makers. The rapid development and adoption of open-source technologies that promote the collection and processing of data in new ways and in ever-increasing volumes are creating new data infrastructure in sectors such as lands and health, among others. This paper examines the process of developing data infrastructure and, by extension, a data portal to provide baseline data for sustainable development and decision making in Nigeria. This paper employs the FAIR principle (Findable, Accessible, Interoperable, and Reusable) of data management using open-source technology tools to develop data portals for public use. eHealth Africa, an organization that uses technology to drive public health interventions in Nigeria, developed a data portal which is a typical data infrastructure that serves as a repository for various datasets on administrative boundaries, points of interest, settlements, social infrastructure, amenities, and others. This portal makes it possible for users to have access to datasets of interest at any point in time at no cost. A skeletal infrastructure of this data portal encompasses the use of open-source technology such as Postgres database, GeoServer, GeoNetwork, and CKan. These tools made the infrastructure sustainable, thus promoting the achievement of SDG 9 (Industries, Innovation, and Infrastructure). As of 6th August 2021, a wider cross-section of 8192 users had been created, 2262 datasets had been downloaded, and 817 maps had been created from the platform. This paper shows the use of rapid development and adoption of technologies that facilitates data collection, processing, and publishing in new ways and in ever-increasing volumes. In addition, the paper is explicit on new data infrastructure in sectors such as health, social amenities, and agriculture. Furthermore, this paper reveals the importance of cross-sectional data infrastructures for planning and decision making, which in turn can form a central data repository for sustainable development across developing countries.

Keywords: data portal, data infrastructure, open source, sustainability

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Authors: Budi Purnomo, Karen M. Fernandez

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The creation of an ASEAN Community in 2015 is definitely one thing to look forward to. Integration may have birth pains in the beginning but at the end of the day, there are many opportunities that each member-state can take advantage that will benefit the people of ASEAN. Once fully integrated in 2015, ASEAN-certified tourism professionals who pass the common competency standards may find employment in various divisions of labor that are common across various sectors of tourism in member countries. At present, there are six labor divisions where tourism professionals may find employment in ASEAN member countries: namely Front Office; Housekeeping; Food Production; Food and Beverage Services (for Hotel Services); Travel Agency; and Tour Operations (for Travel Services Division). The study attempts to assess the readiness of Indonesian and Filipino students prospective skilled and educated tourism labors to work in ASEAN member countries by 2015. The data sources are obtained from a researcher-designed questionnaire and in-depth interview to reveal the interest of Indonesian and Filipino students to work in other ASEAN member states. The questionnaires were distributed to 240 third and fourth year students who are currently enrolled at the leading tourism institutes/universities in Indonesia and Philippines. The findings of the study will reveal the fulfillment of the requirements to work in ASEAN member-states, the comparison of existing tourism management curricula of Indonesia and Philippines to the Common ASEAN Curriculum (CATC) and Regional Qualifications Framework and Skills Recognition System (RQFSRS) which supports the policies of the Ministry of Tourism and Creative Economy of the Republic of Indonesia and the Department of Tourism and Department of Labor and Employment of the Republic of the Philippines.

Keywords: ASEAN economic community, prospective skilled and educated tourism labors, tourism labor movement, ASEAN certified-tourism professionals

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Authors: Hyun-Woo Cho

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Unexpected operational events or abnormalities of industrial processes have a serious impact on the quality of final product of interest. In terms of statistical process control, fault detection and diagnosis of processes is one of the essential tasks needed to run the process safely. In this work, nonlinear representation of process measurement data is presented and evaluated using a simulation process. The effect of using different representation methods on the diagnosis performance is tested in terms of computational efficiency and data handling. The results have shown that the nonlinear representation technique produced more reliable diagnosis results and outperforms linear methods. The use of data filtering step improved computational speed and diagnosis performance for test data sets. The presented scheme is different from existing ones in that it attempts to extract the fault pattern in the reduced space, not in the original process variable space. Thus this scheme helps to reduce the sensitivity of empirical models to noise.

Keywords: fault diagnosis, nonlinear technique, process data, reduced spaces

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Authors: Dzhavidan Zeinalov, Bugra Sen, Firangiz Aslanova

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Most text-to-speech models cannot operate well in low-resource languages and require a great amount of high-quality training data to be considered good enough. Yet, with the improvements made in ASR systems, it is now much easier than ever to collect data for the design of custom text-to-speech models. In this work, our work on using the ASR model to collect data to build a viable text-to-speech system for one of the leading financial institutions of Azerbaijan will be outlined. NVIDIA’s implementation of the Tacotron 2 model was utilized along with the HiFiGAN vocoder. As for the training, the model was first trained with high-quality audio data collected from the Internet, then fine-tuned on the bank’s single speaker call center data. The results were then evaluated by 50 different listeners and got a mean opinion score of 4.17, displaying that our method is indeed viable. With this, we have successfully designed the first text-to-speech model in Azerbaijani and publicly shared 12 hours of audiobook data for everyone to use.

Keywords: Azerbaijani language, HiFiGAN, Tacotron 2, text-to-speech, transfer learning, whisper

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Authors: Ruchika Malhotra, Megha Khanna

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The development of change prediction models can help the software practitioners in planning testing and inspection resources at early phases of software development. However, a major challenge faced during the training process of any classification model is the imbalanced nature of the software quality data. A data with very few minority outcome categories leads to inefficient learning process and a classification model developed from the imbalanced data generally does not predict these minority categories correctly. Thus, for a given dataset, a minority of classes may be change prone whereas a majority of classes may be non-change prone. This study explores various alternatives for adeptly handling the imbalanced software quality data using different sampling methods and effective MetaCost learners. The study also analyzes and justifies the use of different performance metrics while dealing with the imbalanced data. In order to empirically validate different alternatives, the study uses change data from three application packages of open-source Android data set and evaluates the performance of six different machine learning techniques. The results of the study indicate extensive improvement in the performance of the classification models when using resampling method and robust performance measures.

Keywords: change proneness, empirical validation, imbalanced learning, machine learning techniques, object-oriented metrics

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Authors: Olakanmi Oladayo Olufemi, Bamifewe Olusegun James, Badmus Yaya Opeyemi, Adegoke Kayode

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The wireless sensor network (WSN) has made a significant contribution to the emergence of various intelligent services or cloud-based applications. Most of the time, these data are stored on a cloud platform for efficient management and sharing among different services or users. However, the sensitivity of the data makes them prone to various confidentiality and performance-related attacks during and after harvesting. Various security schemes have been developed to ensure the integrity and confidentiality of the WSNs' data. However, their specificity towards particular attacks and the resource constraint and heterogeneity of WSNs make most of these schemes imperfect. In this paper, we propose a secure variance-aware routing and authentication scheme with two-tier verification to collect, share, and manage WSN data. The scheme is capable of classifying WSN into different subnets, detecting any attempt of wormhole and black hole attack during harvesting, and enforcing access control on the harvested data stored in the cloud. The results of the analysis showed that the proposed scheme has more security functionalities than other related schemes, solves most of the WSNs and cloud security issues, prevents wormhole and black hole attacks, identifies the attackers during data harvesting, and enforces access control on the harvested data stored in the cloud at low computational, storage, and communication overheads.

Keywords: data block, heterogeneous IoT network, data harvesting, wormhole attack, blackhole attack access control

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Authors: A. Sathiya Susuman, Hamisi F. Hamisi

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Background: Many socio-economic and demographic data are age-sex attributed. However, a variety of irregularities and misstatement are noted with respect to age-related data and less to sex data because of its biological differences between the genders. Noting the misstatement/misreporting of age data regardless of its significance importance in demographics and epidemiological studies, this study aims at assessing the quality of 2012 Tanzania Population and Housing Census Results. Methods: Data for the analysis are downloaded from Tanzania National Bureau of Statistics. Age heaping and digit preference were measured using summary indices viz., Whipple’s index, Myers’ blended index, and Age-Sex Accuracy index. Results: The recorded Whipple’s index for both sexes was 154.43; male has the lowest index of about 152.65 while female has the highest index of about 156.07. For Myers’ blended index, the preferences were at digits ‘0’ and ‘5’ while avoidance were at digits ‘1’ and ‘3’ for both sexes. Finally, Age-sex index stood at 59.8 where sex ratio score was 5.82 and age ratio scores were 20.89 and 21.4 for males and female respectively. Conclusion: The evaluation of the 2012 PHC data using the demographic techniques has qualified the data inaccurate as the results of systematic heaping and digit preferences/avoidances. Thus, innovative methods in data collection along with measuring and minimizing errors using statistical techniques should be used to ensure accuracy of age data.

Keywords: age heaping, digit preference/avoidance, summary indices, Whipple’s index, Myer’s index, age-sex accuracy index

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Authors: Mohanad Elemary, Imose Itua, Rajeswari B. Matam

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Virologists and public health experts have been predicting potential pandemics from coronaviruses for decades. The viruses which caused the SARS and MERS pandemics and the Nipah virus led to many lost lives, but still, the COVID-19 pandemic caused by the SARS-CoV2 virus surprised many scientific communities, experts, and governments with its ease of transmission and its pathogenicity. Governments of various countries reacted by locking down entire populations to their homes to combat the devastation caused by the virus, which led to a loss of livelihood and economic hardship to many individuals and organizations. To revive national economies and support their citizens in resuming their lives, governments focused on the development and use of contact tracing apps as a digital way to track and trace exposure. Google and Apple introduced the Exposure Notification Systems (ENS) framework. Independent organizations and countries also developed different frameworks for contact tracing apps. The efficiency, popularity, and adoption rate of these various apps have been different across countries. In this paper, we present a critical analysis of the different contact tracing apps with respect to their efficiency, adoption rate and general perception, and the governmental strategies and policies, which led to the development of the applications. When it comes to the European countries, each of them followed an individualistic approach to the same problem resulting in different realizations of a similarly functioning application with differing results of use and acceptance. The study conducted an extensive review of existing literature, policies, and reports across multiple disciplines, from which a framework was developed and then validated through interviews with six key stakeholders in the field, including founders and executives in digital health startups and corporates as well as experts from international organizations like The World Health Organization. A framework of best practices and tactics is the result of this research. The framework looks at three main questions regarding the contact tracing apps; how to develop them, how to deploy them, and how to regulate them. The findings are based on the best practices applied by governments across multiple countries, the mistakes they made, and the best practices applied in similar situations in the business world. The findings include multiple strategies when it comes to the development milestone regarding establishing frameworks for cooperation with the private sector and how to design the features and user experience of the app for a transparent, effective, and rapidly adaptable app. For the deployment section, several tactics were discussed regarding communication messages, marketing campaigns, persuasive psychology, and the initial deployment scale strategies. The paper also discusses the data privacy dilemma and how to build for a more sustainable system of health-related data processing and utilization. This is done through principles-based regulations specific for health data to allow for its avail for the public good. This framework offers insights into strategies and tactics that could be implemented as protocols for future public health crises and emergencies whether global or regional.

Keywords: contact tracing apps, COVID-19, digital health applications, exposure notification system

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Authors: Muhammed Shahriar Haque

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As an offshoot of journalistic discourse, the documentary should be objective in nature without harbouring any preconceived notion to foster ulterior motifs. When it comes to a social issue like rape in South Asian countries, as media in recent times is inundated with this violent act in India, Pakistan, Myanmar, Bangladesh, how does one document it in terms of objectivity and subjectivity? The objective of this study is twofold: to document the history of documentaries, and to critically analyze South Asian rape/flesh trade-documentaries. The overall goal is to trace the (re/de)construction of objectivity-subjectivity in documentaries. This paper adopts a qualitative approach to documentarist discourse through the lens of critical discourse analysis (CDA). Data was gathered for 10 documentaries on the theme of rape and/or flesh trade from eight South Asian countries, predominantly the South Asian Association of Regional Cooperation (SAARC) region. The documentaries were primarily categorised by using three frameworks based on six modes, six subgenres, and four basic approaches of documentary. Subsequently, the findings were critiqued from CDA perspective. The outcome suggests that there a two schools of thoughts regarding documentaries. According to journalistic ethics, news and/or documentaries should be objective in orientation and focus on informing the audience and/common people. The empirical findings tend to challenge ethical parameters of objectivity. At times, it seems that journalistic discourse is discursively (re)constructed to give an augmented simulation of objectivity. Based on the findings it may be recommended that if documentaries steer away from empirical facts and indulge in poetic naivety, their credibility could be questioned. A research of this nature is significant as it raises questions with regard to ethical and moral conscience of documentary filmmakers. Furthermore, it looks at whether they uphold journalistic integrity or succumb to their bias, and thereby depict subjective views, which could be tainted with political and/or propagandist ulterior motifs.

Keywords: discursive (re/de)construction, documentaries, journalistic integrity, rape/flesh trade

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Authors: Debasis Sarkar, Jatan Talati

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This paper is an attempt to develop an Integrated Mass Rapid Transit System (MRTS) for a smart city project in Western India. Integrated transportation is one of the enablers of smart transportation for providing a seamless intercity as well as regional level transportation experience. The success of a smart city project at the city level for transportation is providing proper integration to different mass rapid transit modes by way of integrating information, physical, network of routes fares, etc. The methodology adopted for this study was primary data research through questionnaire survey. The respondents of the questionnaire survey have responded on the issues about their perceptions on the ways and means to improve public transport services in urban cities. The respondents were also required to identify the factors and attributes which might motivate more people to shift towards the public mode. Also, the respondents were questioned about the factors which they feel might restrain the integration of various modes of MRTS. Furthermore, this study also focuses on developing a utility equation for respondents with the help of multiple linear regression analysis and its probability to shift to public transport for certain factors listed in the questionnaire. It has been observed that for shifting to public transport, the most important factors that need to be considered were travel time saving and comfort rating. Also, an Integrated MRTS can be obtained by combining metro rail with BRTS, metro rail with monorail, monorail with BRTS and metro rail with Indian railways. Providing a common smart card to transport users for accessing all the different available modes would be a pragmatic solution towards integration of the available modes of MRTS.

Keywords: mass rapid transit systems, smart city, metro rail, bus rapid transit system, multiple linear regression, smart card, automated fare collection system

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Authors: Junjie Fu

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This paper explores the cultural evolution of the "city-mountain" landscape in ancient Chinese cities, tracing its origins in the regional mountain and town division within the national system. It delves into the cultural archetype of "city-mountain" landscape divine imagery and its spatial characteristics, drawing from the spatial conception of mountain worship and divine order in the model of Kunlun and Penglai. Furthermore, it examines the shift from religious to daily life influences, leading to a poetic aesthetic turn in the "city-mountain" landscape. The paper also discusses the organizational structure of the "city-mountain" poetic landscape and its role as a space for enjoyment. By studying the cultural connotations, evolving relationships, and power mechanisms of the "city-mountain" landscape, this research provides theoretical insights for the construction and development of "city-mountain" landscapes and mountain cities.

Keywords: city-mountain landscape, cultural image, divinity, landscape image, poetry

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Authors: Kiran Bala

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Health, education and employment opportunities available for a common citizen reflect the development status of a country. Health of an individual affects the growth of a country in every aspect. According to a study by WHO, India is estimated to lose more than $237 billion of its GDP over the period 2006-15 on account of premature death and morbidity from Non-communicable diseases alone. Each year 37 million people fall below poverty line due to high expenditure on health services they have to incur. Falling sick puts a double burden on them in terms of loss of income and expenditure on health care which pushes them further into debt and poverty. Adding to the gravity of situation, public spending on health in India has itself declined after liberalization from 1.3% of GDP in 1990 to 0.9% in 1999. The Approach Paper of the Government of India to the Twelfth Five Year Plan indicated that health expenditure alone as a per cent of GDP was about 1.4 per cent (B.E.) in 2011-12. It also mentioned that if one included expenditure on rural water supply and sanitation, the figure would be about 1.8 per cent. Given the abysmally low level of priority accorded to health in Indian economic policy, it becomes rather important to study the representation of health in the Indian public sphere. To this end, this study examines the prioritization of health in the public policy agenda of the national/regional political parties as evidenced in their election manifestos at a time when the nation is poised to go for the General Elections. The paper also focuses attention on the prioritization of health in the public perception as evidenced in their reasons for their preferences for a particular party or individual contestant. To arrive at the reasons for the priority level accorded by the political actors and the citizens, the study uses Focus groups of health policy makers, media persons, medical practitioners and voters. Collected data will be analysed in the theoretical framework of spiral of silence and agenda setting theory.

Keywords: health, election manifestos, public perception, policies

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Authors: Naveen Kumar Perumalla, Devadas Kuna, Mohammed Akhter Ali

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Satellite Navigation System such as the United States Global Positioning System (GPS) plays a significant role in determining the user position. Similar to that of GPS, Indian Regional Navigation Satellite System (IRNSS) is a Satellite Navigation System indigenously developed by Indian Space Research Organization (ISRO), India, to meet the country’s navigation applications. This system is also known as Navigation with Indian Constellation (NavIC). The NavIC system’s main objective, is to offer Positioning, Navigation and Timing (PNT) services to users in its two service areas i.e., covering the Indian landmass and the Indian Ocean. Six NavIC satellites are already deployed in the space and their receivers are in the performance evaluation stage. Four NavIC dual frequency receivers are installed in the ‘Advanced GNSS Research Laboratory’ (AGRL) in the Department of Electronics and Communication Engineering, University College of Engineering, Osmania University, India. The NavIC receivers can be operated in two positioning modes: Stand-alone IRNSS and Hybrid (IRNSS+GPS) modes. In this paper, analysis of various parameters such as Dilution of Precision (DoP), three Dimension (3D) Root Mean Square (RMS) Position Error and Horizontal Position Error with respect to Visibility of Satellites is being carried out using the real-time IRNSS data, obtained by operating the receiver in both positioning modes. Two typical days (6th July 2017 and 7th July 2017) are considered for Hyderabad (Latitude-17°24'28.07’N, Longitude-78°31'4.26’E) station are analyzed. It is found that with respect to the considered parameters, the Hybrid mode operation of NavIC receiver is giving better results than that of the standalone positioning mode. This work finds application in development of NavIC receivers for civilian navigation applications.

Keywords: DoP, GPS, IRNSS, GNSS, position error, satellite visibility

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Authors: Komol Phaisarn, Anuphan Suttimarn, Vitchanan Keawtong, Kittisak Thongyoun, Chaiyos Jamsawang

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This article is intended to analyze insurance information which contains information on the customer decision when purchasing life insurance pay package. The data were analyzed in order to present new customers with Life Insurance Perfect Pay package to meet new customers’ needs as much as possible. The basic data of insurance pay package were collect to get data mining; thus, reducing the scattering of information. The data were then classified in order to get decision model or decision tree using Algorithm C4.5 (J-48). In the classification, WEKA tools are used to form the model and testing datasets are used to test the decision tree for the accurate decision. The validation of this model in classifying showed that the accurate prediction was 68.43% while 31.25% were errors. The same set of data were then tested with other models, i.e. Naive Bayes and Zero R. The results showed that J-48 method could predict more accurately. So, the researcher applied the decision tree in writing the program used to introduce the product to new customers to persuade customers’ decision making in purchasing the insurance package that meets the new customers’ needs as much as possible.

Keywords: decision tree, data mining, customers, life insurance pay package

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Authors: Nithra Kitreerawutiwong, Sunsanee Mekrungrongwong, Artitaya Wongwonsin, Chakkraphan Phetphoom, Buaploy Phromjang

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Background: Thailand has implemented a district health system based on the concept of primary health care. Since 2014, Family Care Team (FCT) was launched to improve the quality of care through a multidisciplinary team include not only the health sector but also social sector work together. FCT classified into 3 levels: district, sub-district, and community. This system now consists of 66,353 teams, including 3,890 teams at district level, 12,237 teams at the sub-district level, and 50,326 teams at the community level. There is a report regarding assessment the situation and perception on FCT, however, relatively few examined the operationality of this policy. This study aimed to explore the perception of district manager on the process of the implementation of FCT policy and the factors associating to implement FCT in the district health system. Methods/Results: Forty in-depth interviews were performed: 5 of primary care manager at the provincial medical health office, 5 of community hospital director, 5 of district administrative health office, 10 of sub-district health promoting hospital, and 10 of local organization. Semi-structure interview guidelines were used in the discussions. The data was analyzed by thematic analysis. This policy was formulated based on the demographic change and epidemiology transition to serve a long term care for elderly. Facilitator factors are social capital in district health systems such as family health leader and multidisciplinary team. Barrier factors are communication to the frontline provider and local organization. The output of this policy in relation to the structure of FCT is well-defined. Unanticipated effects include training of FCT in community level. Conclusion: Early feedback from healthcare manager is valuable information for the improvement of FCT to function optimally. Moreover, in the long term, health outcome need to be evaluated.

Keywords: family care team, district health system, primary care, qualitative study

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Authors: Arun Das

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Indian agriculture is acclaimed from the dates of Indus civilization (2500 BC). Since this time until the day, there were tremendous expansion in terms of space and technology has taken place. Abrupt growth in technology took place past one and half century. Consequent to this development, the land which was brought under agriculture in the initial stages of introducing agriculture for the first time, that land is not possessing the same physical condition. Either it has lost the productive capacity or modified into semi agriculture land. On the grounds of its capacity and interwoven characteristics seven phases of agriculture scenario has been identified. Most of the land is on the march of desertification. Identifying the stages and the phase of the agriculture scenario is most relevant from the point of view of food security at regional, national and at global level. Secondly decisive measure can put back the degenerating environmental condition into arrest. GIS and Remote sensing applications have been used to identify the phases of agriculture.

Keywords: agriculture phases, desertification, deforestation, foods security, transmigration

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Authors: Faisal Muhibuddin, Ani Dijah Rahajoe

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This in-depth exploration, through a systematic literature review, scrutinizes the nuanced role of data mining in the classification of criminal activities. The research focuses on investigating various methodological aspects and recent developments in leveraging data mining techniques to enhance the effectiveness and precision of crime categorization. Commencing with an exposition of the foundational concepts of crime classification and its evolutionary dynamics, this study details the paradigm shift from conventional methods towards approaches supported by data mining, addressing the challenges and complexities inherent in the modern crime landscape. Specifically, the research delves into various data mining techniques, including K-means clustering, Naïve Bayes, K-nearest neighbour, and clustering methods. A comprehensive review of the strengths and limitations of each technique provides insights into their respective contributions to improving crime classification models. The integration of diverse data sources takes centre stage in this research. A detailed analysis explores how the amalgamation of structured data (such as criminal records) and unstructured data (such as social media) can offer a holistic understanding of crime, enriching classification models with more profound insights. Furthermore, the study explores the temporal implications in crime classification, emphasizing the significance of considering temporal factors to comprehend long-term trends and seasonality. The availability of real-time data is also elucidated as a crucial element in enhancing responsiveness and accuracy in crime classification.

Keywords: data mining, classification algorithm, naïve bayes, k-means clustering, k-nearest neigbhor, crime, data analysis, sistematic literature review

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Authors: Abd El-Aziz Khairy Abd El-Aal, Yuji Yagi, Heba Kamal

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In this study, an integrated multi-channel analysis of Surface Waves (MASW) technique is applied to explore the geotechnical parameters of subsurface layers at the Zafarana wind farm. Moreover, a seismic hazard procedure based on the extended deterministic technique is used to estimate the seismic hazard load for the investigated area. The study area includes many active fault systems along the Gulf of Suez that cause many moderate and large earthquakes. Overall, the seismic activity of the area has recently become better understood following the use of new waveform inversion methods and software to develop accurate focal mechanism solutions for recent recorded earthquakes around the studied area. These earthquakes resulted in major stress-drops in the Eastern desert and the Gulf of Suez area. These findings have helped to reshape the understanding of the seismotectonic environment of the Gulf of Suez area, which is a perplexing tectonic domain. Based on the collected new information and data, this study uses an extended deterministic approach to re-examine the seismic hazard for the Gulf of Suez region, particularly the wind turbine towers at Zafarana Wind Farm and its vicinity. Alternate seismic source and magnitude-frequency relationships were combined with various indigenous attenuation relationships, adapted within a logic tree formulation, to quantify and project the regional exposure on a set of hazard maps. We select two desired exceedance probabilities (10 and 20%) that any of the applied scenarios may exceed the largest median ground acceleration. The ground motion was calculated at 50th, 84th percentile levels.

Keywords: MASW, seismic hazard, wind turbine towers, Zafarana wind farm

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Authors: Emin Gundogar, Burak Erkayman, Nusret Sazak

Abstract:

Providing effective management performance through the whole supply chain is critical issue and hard to applicate. The proper evaluation of integrated data may conclude with accurate information. Analysing the supply chain data through OLAP (On-Line Analytical Processing) technologies may provide multi-angle view of the work and consolidation. In this study, association rules and classification techniques are applied to measure the supply chain performance metrics of an automotive manufacturer in Turkey. Main criteria and important rules are determined. The comparison of the results of the algorithms is presented.

Keywords: supply chain performance, performance measurement, data mining, automotive

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Authors: Joseph Marzouk Gerais Abdelmalak

Abstract:

The interface between development and human rights has long been the subject of academic debate. Therefore, to understand the dynamics between the two concepts, a number of principles have been adopted, ranging from the right to development to a human rights-based approach to development. Despite these attempts, the exact connection between development and human rights is not yet fully understood. However, the inherent interdependence between these two concepts and the idea that development efforts should be undertaken with respect for human rights guarantees have gained momentum in recent years. It will then be examined whether the right to sustainable development is recognized.The article therefore concludes that the principles of sustainable development are recognized, directly or indirectly, in various human rights instruments, which represents a positive answer to the question posed above. Therefore, this work discusses international and regional human rights instruments as well as case law and interpretative guidelines from human rights bodies to demonstrate this hypothesis.

Keywords: sustainable development, human rights, the right to development, the human rights-based approach to development, environmental rights, economic development, social sustainability human rights protection, human rights violations, workers’ rights, justice, security

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Authors: Liang Zhou, Qinke Sun

Abstract:

Taking the Yangtze River Economic Belt as an example, using long-term nighttime lighting data from DMSP/OLS from 1992 to 2012, support vector machine classification (SVM) was used to quantitatively extract urban built-up areas of economic belts, and spatial analysis of expansion intensity index, standard deviation ellipse, etc. was introduced. The model conducts detailed and in-depth discussions on the strength, direction, and type of the expansion of the middle and lower reaches of the economic belt and the key node cities. The results show that: (1) From 1992 to 2012, the built-up areas of the major cities in the Yangtze River Valley showed a rapid expansion trend. The built-up area expanded by 60,392 km², and the average annual expansion rate was 31%, that is, from 9615 km² in 1992 to 70007 km² in 2012. The spatial gradient analysis of the watershed shows that the expansion of urban built-up areas in the middle and lower reaches of the river basin takes Shanghai as the leading force, and the 'bottom-up' model shows an expanding pattern of 'upstream-downstream-middle-range' declines. The average annual rate of expansion is 36% and 35%, respectively. 17% of which the midstream expansion rate is about 50% of the upstream and downstream. (2) The analysis of expansion intensity shows that the urban expansion intensity in the Yangtze River Basin has generally shown an upward trend, the downstream region has continued to rise, and the upper and middle reaches have experienced different amplitude fluctuations. To further analyze the strength of urban expansion at key nodes, Chengdu, Chongqing, and Wuhan in the upper and middle reaches maintain a high degree of consistency with the intensity of regional expansion. Node cities with Shanghai as the core downstream continue to maintain a high level of expansion. (3) The standard deviation ellipse analysis shows that the overall center of gravity of the Yangtze River basin city is located in Anqing City, Anhui Province, and it showed a phenomenon of reciprocating movement from 1992 to 2012. The nighttime standard deviation ellipse distribution range increased from 61.96 km² to 76.52 km². The growth of the major axis of the ellipse was significantly larger than that of the minor axis. It had obvious east-west axiality, in which the nighttime lights in the downstream area occupied in the entire luminosity scale urban system leading position.

Keywords: urban space, support vector machine, spatial characteristics, night lights, Yangtze River Economic Belt

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Authors: Hadeer M. Sayed, Hesham E. El Deeb, Shereen A. Taie

Abstract:

In the big data era, we are facing a diversity of datasets from different sources in different domains that describe a single life event. These datasets consist of multiple modalities, each of which has a different representation, distribution, scale, and density. Multimodal fusion is the concept of integrating information from multiple modalities in a joint representation with the goal of predicting an outcome through a classification task or regression task. In this paper, multimodal fusion techniques are classified into two main classes: model-agnostic techniques and model-based approaches. It provides a comprehensive study of recent research in each class and outlines the benefits and limitations of each of them. Furthermore, the audiovisual speech recognition task is expressed as a case study of multimodal data fusion approaches, and the open issues through the limitations of the current studies are presented. This paper can be considered a powerful guide for interested researchers in the field of multimodal data fusion and audiovisual speech recognition particularly.

Keywords: multimodal data, data fusion, audio-visual speech recognition, neural networks

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Authors: Simont Toussi

Abstract:

Cameroon and the Central African Republic arebound by the provisions of many regional and international charters, which condemn the manipulation of information, obstacles to access reliable information, or the limitation of freedoms of expression and opinion. These two countries also have constitutional guarantees for free speech and access to true and liable information. However, they are yet to define specific policies and regulations for access to information, disinformation, or misinformation. Yet, certain countries’ laws and regulations related to information and communication technologies, to criminal procedures, to terrorism, or intelligence services contain provisions that rather hider human rights by condemning false information. Like many other African countries, Cameroon and the Central African Republic face a profound democratic regression, and governments use multiple methods to stifle online discourse and digital rights. Despite the increased uptake of digital tools for political participation, there is a lack of interactivity and adoption of these tools. This enables a scarcity of information and creates room for the spreading of disinformation in the public space, hamperingdemocracy and the respect for human rights. This research aims to analyse the adequacy of stakeholders’ responses to disinformation in Cameroon and the Central African Republic in periods of political contestation, such as elections and anti-government protests, to highlight the nature, perpetrators, strategies, and channels of disinformation, as well as its effects on democratic actors, including civil society, bloggers, government critics, activists, and other human rights defenders. The study follows a qualitative method with literature review, content analysis, andkey informant’sinterviews with stakeholders’ representatives, emphasized crowdsourcing as a data and information collecting method in the two countries.

Keywords: disinformation, democracy, political manipulation, social media, media, fake news, central Africa, cameroon, misinformation, free speech

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Authors: Pejman Hosseinioun, Hasan Shakeri, Ghasem Ghorbanirostam

Abstract:

In recent years, we have seen an increasing importance of research and study on knowledge source, decision support systems, data mining and procedure of knowledge discovery in data bases and it is considered that each of these aspects affects the others. In this article, we have merged information source and knowledge source to suggest a knowledge based system within limits of management based on storing and restoring of knowledge to manage information and improve decision making and resources. In this article, we have used method of data mining and Apriori algorithm in procedure of knowledge discovery one of the problems of Apriori algorithm is that, a user should specify the minimum threshold for supporting the regularity. Imagine that a user wants to apply Apriori algorithm for a database with millions of transactions. Definitely, the user does not have necessary knowledge of all existing transactions in that database, and therefore cannot specify a suitable threshold. Our purpose in this article is to improve Apriori algorithm. To achieve our goal, we tried using fuzzy logic to put data in different clusters before applying the Apriori algorithm for existing data in the database and we also try to suggest the most suitable threshold to the user automatically.

Keywords: decision support system, data mining, knowledge discovery, data discovery, fuzzy logic

Procedia PDF Downloads 334

Authors: Mohamad Saeed Ahrari-Khafi, Abutorab Tabatabai-Naini, Niloofar Ajvadi

Abstract:

Scapular fracture is not common in horses, due to the proper protection of scapular muscles. However, if it happens, it can cause lameness in horses. Because of the overlapping of the scapula on the contralateral scapula and the thorax, usually radiography cannot be helpful in evaluation, except in small amount of its ventral part. Although ultrasonography is mainly used for diagnosis of soft tissue injuries, it also can be used for evaluation of bone surface abnormalities. This study was intended to document the normal ultrasonographic appearance of the equine scapula. Right forelimb of six horses was used. To facilitate the image assessment, a zoning system was developed. Ultrasonography was performed by using a 5-11 MHz linear array transducer. Ultrasonographic anatomy of scapula in different parts and planes was imaged and documented, hoping to help practitioners to diagnose fractures and injuries. Results showed that ultrasonography is capable to depict different parts of the scapula and regional muscles, and can be used for detecting fractures and other abnormalities.

Keywords: horse, scapula, scapular fracture, ultrasonography

Procedia PDF Downloads 304