Search results for: scientific data mining

Authors: P. Halder, A. Zaman

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It is estimated that heart disease accounts for one in ten deaths worldwide. United States deaths due to heart disease are among the leading causes of death according to the World Health Organization. Cardiovascular diseases (CVDs) account for one in four U.S. deaths, according to the Centers for Disease Control and Prevention (CDC). According to statistics, women are more likely than men to die from heart disease as a result of strokes. A 50% increase in men's mortality was reported by the World Health Organization in 2009. The consequences of cardiovascular disease are severe. The causes of heart disease include diabetes, high blood pressure, high cholesterol, abnormal pulse rates, etc. Machine learning (ML) can be used to make predictions and decisions in the healthcare industry. Thus, scientists have turned to modern technologies like Machine Learning and Data Mining to predict diseases. The disease prediction is based on four algorithms. Compared to other boosts, the Ada boost is much more accurate.

Keywords: heart disease, cardiovascular disease, coronary artery disease, feature selection, random forest, AdaBoost, SVM, decision tree

Procedia PDF Downloads 136

Authors: Gatot Dwi Hendro, Hayyan ul Haq

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This work aims to explore the strategy in embodying the ecological validity in creating the sustainability of public policy, particularly in strengthening the green economy in Indonesia. This green economy plays an important role in supporting the national development in Indonesia, as it is a part of the national policy that posits the primary priority in Indonesian governance. The green economy refers to the national development covering strategic natural resources, such as mining, gold, oil, coal, forest, water, marine, and the other supporting infrastructure for products and distribution, such as fabrics, roads, bridges, and so forth. Thus, all activities in those national development should consider the sustainability. This sustainability requires the strong commitment of the national and regional government, as well as the local governments to put the ecology as the main requirement for issuing any policy, such as licence in mining production, and developing and building new production and supporting infrastructures for optimising the national resources. For that reason this work will focus on the strategy how to embody the ecological values and norms in the public policy. In detail, this work will offer the method, i.e. legal techniques, in visualising and embodying the norms and public policy that valid ecologically. This ecological validity is required in order to maintain and sustain our collective life.

Keywords: ecological validity, sustainable development, coherence, Indonesian Pancasila values, environment, marine

Procedia PDF Downloads 462

Authors: Ashraf M. Khalifa, Hwat Bing So, Greg Maddocks

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Changes to the mining environmental approvals process in Queensland have been rolled out under the MERFP Act (2018). This includes requirements for a Progressive Rehabilitation and Closure Plan (PRC Plan). Key considerations of the landform design report within the PRC Plan must include: (i) identification of materials available for landform rehabilitation, including their ability to achieve the required landform design outcomes, (ii) erosion assessments to determine landform heights, gradients, profiles, and material placement, (iii) slope profile design considering the interactions between soil erodibility, rainfall erosivity, landform height, gradient, and vegetation cover to identify acceptable erosion rates over a long-term average, (iv) an analysis of future stability based on the factors described above e.g., erosion and /or landform evolution modelling. ACARP funded an extensive and thorough erosion assessment program using rainfall simulators from 1998 to 2010. The ACARP program included laboratory assessment of 35 soil and spoil samples from 16 coal mines and samples from a gold mine in Queensland using 3 x 0.8 m laboratory rainfall simulator. The reliability of the laboratory rainfall simulator was verified through field measurements using larger flumes 20 x 5 meters and catchment scale measurements at three sites (3 different catchments, average area of 2.5 ha each). Soil cover systems are a primary component of a constructed mine landform. The primary functions of a soil cover system are to sustain vegetation and limit the infiltration of water and oxygen into underlying reactive mine waste. If the external surface of the landform erodes, the functions of the cover system cannot be maintained, and the cover system will most likely fail. Assessing a constructed landform’s potential ‘long-term’ erosion stability requires defensible erosion rate thresholds below which rehabilitation landform designs are considered acceptably erosion-resistant or ‘stable’. The process used to quantify erosion rates using rainfall simulators (flumes) to measure rill and inter-rill erosion on bulk samples under laboratory conditions or on in-situ material under field conditions will be explained.

Keywords: open-cut, mining, erosion, rainfall simulator

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Authors: Levente Varga, Dávid Deritei, Mária Ercsey-Ravasz, Răzvan Florian, Zsolt I. Lázár, István Papp, Ferenc Járai-Szabó

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One of the major shortcomings of widely used scientometric indicators is that different disciplines cannot be compared with each other. The issue of cross-disciplinary normalization has been long discussed, but even the classification of publications into scientific domains poses problems. Structural properties of citation networks offer new possibilities, however, the large size and constant growth of these networks asks for precaution. Here we present a new tool that in order to perform cross-field normalization of scientometric indicators of individual publications relays on the structural properties of citation networks. Due to the large size of the networks, a systematic procedure for identifying scientific domains based on a local community detection algorithm is proposed. The algorithm is tested with different benchmark and real-world networks. Then, by the use of this algorithm, the mechanism of the scientometric indicator normalization process is shown for a few indicators like the citation number, P-index and a local version of the PageRank indicator. The fat-tail trend of the article indicator distribution enables us to successfully perform the indicator normalization process.

Keywords: citation networks, cross-field normalization, local cluster detection, scientometric indicators

Procedia PDF Downloads 182

Authors: Michael Gidey Gebru

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Most of Data Envelopment Analysis models operate in a static environment with input and output parameters that are chosen by deterministic data. However, due to ambiguity brought on shifting market conditions, input and output data are not always precisely gathered in real-world scenarios. Fuzzy numbers can be used to address this kind of ambiguity in input and output data. Therefore, this work aims to expand crisp Data Envelopment Analysis into Data Envelopment Analysis with fuzzy environment. In this study, the input and output data are regarded as fuzzy triangular numbers. Then, the Data Envelopment Analysis model with fuzzy environment is solved using a multi-objective method to gauge the Decision Making Units' efficiency. Finally, the developed Data Envelopment Analysis model is illustrated with an application on real data 50 educational institutions.

Keywords: efficiency, Data Envelopment Analysis, fuzzy, higher education, input, output

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Authors: Partha Saha, Uttam Kumar Banerjee

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Maternal and Child Healthcare (MCH) has always been regarded as one of the important issues globally. Reduction of maternal and child mortality rates and increase of healthcare service coverage were declared as one of the targets in Millennium Development Goals till 2015 and thereafter as an important component of the Sustainable Development Goals. Over the last decade, worldwide MCH indicators have improved but could not match the expected levels. Progress of both maternal and child mortality rates have been monitored by several researchers. Each of the studies has stated that only less than 26% of low-income and middle income countries (LMICs) were on track to achieve targets as prescribed by MDG4. Average worldwide annual rate of reduction of under-five mortality rate and maternal mortality rate were 2.2% and 1.9% as on 2011 respectively whereas rates should be minimum 4.4% and 5.5% annually to achieve targets. In spite of having proven healthcare interventions for both mothers and children, those could not be scaled up to the required volume due to fragmented health systems, especially in the developing and under-developed countries. In this research, a knowledge discovery based interactive Decision Support System (DSS) has been developed on web platform which would assist healthcare policy makers to develop evidence-based policies. To achieve desirable results in MCH, efficient resource planning is very much required. In maximum LMICs, resources are big constraint. Knowledge, generated through this system, would help healthcare managers to develop strategic resource planning for combatting with issues like huge inequity and less coverage in MCH. This system would help healthcare managers to accomplish following four tasks. Those are a) comprehending region wise conditions of variables related with MCH, b) identifying relationships within variables, c) segmenting regions based on variables status, and d) finding out segment wise key influential variables which have major impact on healthcare indicators. Whole system development process has been divided into three phases. Those were i) identifying contemporary issues related with MCH services and policy making; ii) development of the system; and iii) verification and validation of the system. More than 90 variables under three categories, such as a) educational, social, and economic parameters; b) MCH interventions; and c) health system building blocks have been included into this web-based DSS and five separate modules have been developed under the system. First module has been designed for analysing current healthcare scenario. Second module would help healthcare managers to understand correlations among variables. Third module would reveal frequently-occurring incidents along with different MCH interventions. Fourth module would segment regions based on previously mentioned three categories and in fifth module, segment-wise key influential interventions will be identified. India has been considered as case study area in this research. Data of 601 districts of India has been used for inspecting effectiveness of those developed modules. This system has been developed by importing different statistical and data mining techniques on Web platform. Policy makers would be able to generate different scenarios from the system before drawing any inference, aided by its interactive capability.

Keywords: maternal and child heathcare, decision support systems, data mining techniques, low and middle income countries

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Authors: Mark McGuire, Eric Shannon, John Parmigiani

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Timber harvesting increasingly involves mechanized equipment. This has increased the efficiency of harvesting, but has also introduced worker-safety concerns. One such concern arises from the use of harvesters. During operation, harvesters subject saw chain to large dynamic mechanical stresses. These stresses can, under certain conditions, cause the saw chain to fracture. The high speed of harvester saw chain can cause the resulting open chain loop to fracture a second time due to the dynamic loads placed upon it as it travels through space. If a second fracture occurs, it can result in a projectile consisting of one-to-several chain links. This projectile is referred to as a chain shot. It has speeds similar to a bullet but typically has greater mass and is a significant safety concern. Numerous examples exist of chain shots penetrating bullet-proof barriers and causing severe injury and death. Improved harvester-cab barriers can help prevent injury however a comprehensive scientific understanding of chain shot is required to consistently reduce or prevent it. Obtaining this understanding requires a test machine with the capability to cause chain shot to occur under carefully controlled conditions and accurately measure the response. Worldwide few such test machine exist. Those that do focus on validating the ability of barriers to withstand a chain shot impact rather than obtaining a scientific understanding of the chain shot event itself. The purpose of this paper is to describe the design, fabrication, and use of a test machine capable of a comprehensive scientific investigation of chain shot. The capabilities of this machine are to test all commercially-available saw chains and bars at chain tensions and speeds meeting and exceeding those typically encountered in harvester use and accurately measure the corresponding key technical parameters. The test machine was constructed inside of a standard shipping container. This provides space for both an operator station and a test chamber. In order to contain the chain shot under any possible test conditions, the test chamber was lined with a base layer of AR500 steel followed by an overlay of HDPE. To accommodate varying bar orientations and fracture-initiation sites, the entire saw chain drive unit and bar mounting system is modular and capable of being located anywhere in the test chamber. The drive unit consists of a high-speed electric motor with a flywheel. Standard Ponsse harvester head components are used to bar mounting and chain tensioning. Chain lubrication is provided by a separate peristaltic pump. Chain fracture is initiated through ISO standard 11837. Measure parameters include shaft speed, motor vibration, bearing temperatures, motor temperature, motor current draw, hydraulic fluid pressure, chain force at fracture, and high-speed camera images. Results show that the machine is capable of consistently causing chain shot. Measurement output shows fracture location and the force associated with fracture as a function of saw chain speed and tension. Use of this machine will result in a scientific understanding of chain shot and consequently improved products and greater harvester operator safety.

Keywords: chain shot, safety, testing, timber harvesters

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Authors: Waode Nurmayani, Nikmatul Riswanda

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Broilers are chickens which are kept with the most efficient time and hoped get a good body weight. All things are done, for example with the improvement of feed and use antibiotics. Feed cost is the most cost to be spent. Nearly 80% of the cost is spent just for buy feed. Earthworm (Lumbricus rubellus) is a good choice to reduce the cost of feed protein source. The Earthworm has a high crude protein content of about 48.5%-61.9%, rich with proline amino acid about 15% of the 62 amino acids. Not only about protein, this earthworm also has a role in disease prevention. Prevention of disease in livestock usual with use feed supplement. Earthworm (Lumbricus rubellus) is one of the natural materials used as feed. In addition, several types of earthworms that have been known to contain active substances about antibacterial pathogens namely Lumbricus rubellus. The earthworm could be used as an antibiotic because it contain the antibody of Lumbricine active substance. So that, this animal feed from Lumbricus rubellus could improve the performance of broilers. Bioactive of anti-bacterial is called Lumbricine able to inhibit the growth of pathogenic bacteria in the intestinal wall so that the population of pathogenic bacteria is reduced. The method of write in this scientific writing is divided into 3 techniques, namely data completion, data analysis, and thinking pan from various literature about earthworm (Lumbricus rubellus) as broiler feed. It is expected that innovation of feed material of earthworm (Lumbricus rubellus) could reduce the cost of protein feed and the use of chemical antibiotics.

Keywords: earthworm, broiler, protein, antibiotic

Procedia PDF Downloads 139

Authors: A. Sathya, C. Manojkumar, D. Visithra

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The South Indian peninsula has rich diversity of both heritage and conventional rice varieties. With the prime focus set on high yield and increased productivity, a number of traditional/heritage rice varieties have dwindled into the forgotten past. At present, in the face of climate change, the hybrids and conventional varieties struggle for sustainable yield. The need of copious irrigation and high nutrient inputs for the hybrids and conventional varieties have cornered the farming and research community to resort to heritage rice varieties for their sturdy survival capability. An ethno-scientific effort has been taken in the Cauvery delta tracts of South India to restore these traditional/heritage rice varieties. A closer field level performance evaluation under organic condition has been undertaken for 10 heritage rice varieties. The morpho-agronomic characterization across vegetative and reproductive stages have revealed a pattern of variation in duration, plant height, number of tillers, productive tillers, etc. The shortest duration was recorded for a variety with the vernacular name of ‘Arubadaam kuruvai’. A traditional rice variety called ‘Maapillai samba’ is claimed to impart instant energy. The supernatant water of the overnight soaked cooked rice of Maapillai samba is a source of instant energy. The physico-chemical analysis of this variety is being explored for its instant nutritional boosting ability. Wide spectrum of nutritional characters including palatability and marketability preferences has also been analyzed for all these 10 heritage rice varieties. A ‘Farmer’s harvest day festival’ was organized, providing opportunity for the ‘Cauvery delta farmers’ to identify the special features and exchange their views on these standing golden ripe paddy varieties directly. The airing of their ethnic knowledge pooled with interesting scientific investigations of these 10 rich heritage rice varieties of South India undertaken will be elaborately discussed enlightening the perspectives on the pathway of resurrection and restoration of this heritage of the past.

Keywords: biodiversity, conservation, heritage, rice, traditional, varieties

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Authors: M. J. Alcedo, K. Ito, K. Maeda

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Measuring animal welfare is a newly emerging area of research and it needs multi-disciplinary way to do it. Due to the diversity of what constitutes the definition of animal welfare, different methods and models were developed and mostly conducted in semi and commercial farms in developed countries. Few studies have been conducted in developing countries and in backyard livestock operation. Recognizing that majority of livestock operations are categorized as backyard in developing countries, it is crucial to come up with parameters that can assess the welfare of the animal in the backyard level. This research had made use of stockmanship competence as the proxy indicator to assess animal welfare. Stockmanship competence in this study refers to the capacity of the animal owner to ensure the welfare of their animal by providing their needs for growth and reproduction. The Philippine recommend on goat production, tips on goat raising and goat scientific literatures were used as references to come up with indicators that are known to be important in meeting the needs of the animal and ensuring its welfare. Scores from -1 to +2 were assigned depending on how close it is of satisfying the animal’s need. It is hoped that this assessment method could contribute to the growing body of knowledge on animal welfare and can be utilized as logical and scientific framework in assessing welfare in backyard goat operation. It is suggested that further study needs to be conducted to refine and standardize indicators and identify other indicators for goat welfare assessment.

Keywords: backyard goat production, stockmanship competence, animal welfare, Philippines

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Authors: Lina Dagilienė

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The article explores the impact of normative institutional factors on the development of sustainability reporting. The vast majority of research in the scientific literature focuses on mandatory institutional factors, i.e. how public institutions and market regulators affect sustainability reporting. Meanwhile, there is lack of empirical data for the impact of normative institutional factors. The effect of normative factors in this paper is based on the role of non-governmental organizations (NGO) and institutional theory. The case of Global Compact Local Network in the developing country was examined. The research results revealed that in the absence of regulated factors, companies were not active with regard to social disclosures; they presented non-systemized social information of a descriptive nature. Only 10% of sustainability reports were prepared using the GRI methodology. None of the reports were assured by third parties.

Keywords: institutional theory, normative, sustainability reporting, Global Compact Local Network

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Authors: Abhishek Khupsare, Ajay Parmar, Ajay Agarwal, Swapnil Wanjari

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The extreme demand for aggregate leads to the exploitation of river-bed for fine aggregates, affecting the environment adversely. Therefore, a suitable alternative to natural river sand is essentially required. This study focuses on preventing environmental impact by developing polymer sand to replace natural river sand (NRS). Development of polymer sand by mixing high volume fly ash, bottom ash, cement, natural river sand, and locally purchased high solid content polycarboxylate ether-based superplasticizer (HS-PCE). All the physical and chemical properties of polymer sand (P-Sand) were observed and satisfied the requirement of the Indian Standard code. P-Sand yields good specific gravity of 2.31 and is classified as zone-I sand with a satisfactory friction angle (37˚) compared to natural river sand (NRS) and Geopolymer fly ash sand (GFS). Though the water absorption (6.83%) and pH (12.18) are slightly more than those of GFS and NRS, the alkali silica reaction and soundness are well within the permissible limit as per Indian Standards. The chemical analysis by X-Ray fluorescence showed the presence of high amounts of SiO2 and Al2O3 with magnitudes of 58.879% 325 and 26.77%, respectively. Finally, the compressive strength of M-25 grade concrete using P-sand and Geopolymer sand (GFS) was observed to be 87.51% and 83.82% with respect to natural river sand (NRS) after 28 days, respectively. The results of this study indicate that P-sand can be a good alternative to NRS for construction work as it not only reduces the environmental effect due to sand mining but also focuses on utilising fly ash and bottom ash.

Keywords: polymer sand, fly ash, bottom ash, HSPCE plasticizer, river sand mining

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Authors: Kenny Raharjo, Ramon Lawrence

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Game designers have the challenging task of building games that engage players to spend their time and money on the game. There are an infinite number of game variations and design choices, and it is hard to systematically determine game design choices that will have positive experiences for players. In this work, we demonstrate how multi-arm bandits can be used to automatically explore game design variations to achieve improved player metrics. The advantage of multi-arm bandits is that they allow for continuous experimentation and variation, intrinsically converge to the best solution, and require no special infrastructure to use beyond allowing minor game variations to be deployed to users for evaluation. A user study confirms that applying multi-arm bandits was successful in determining the preferred game variation with highest play time metrics and can be a useful technique in a game designer's toolkit.

Keywords: game design, multi-arm bandit, design exploration and data mining, player metric optimization and analytics

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Authors: Bingchun Liu, Pei-Chann Chang, Natasha Huang, Dun Li

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Machine Learning and Data Mining are the two important tools for extracting useful information and knowledge from large datasets. In machine learning, classification is a wildly used technique to predict qualitative variables and is generally preferred over regression from an operational point of view. Due to the enormous increase in air pollution in various countries especially China, Air Quality Classification has become one of the most important topics in air quality research and modelling. This study aims at introducing a hybrid classification model based on information theory and Support Vector Machine (SVM) using the air quality data of four cities in China namely Beijing, Guangzhou, Shanghai and Tianjin from Jan 1, 2014 to April 30, 2016. China's Ministry of Environmental Protection has classified the daily air quality into 6 levels namely Serious Pollution, Severe Pollution, Moderate Pollution, Light Pollution, Good and Excellent based on their respective Air Quality Index (AQI) values. Using the information theory, information gain (IG) is calculated and feature selection is done for both categorical features and continuous numeric features. Then SVM Machine Learning algorithm is implemented on the selected features with cross-validation. The final evaluation reveals that the IG and SVM hybrid model performs better than SVM (alone), Artificial Neural Network (ANN) and K-Nearest Neighbours (KNN) models in terms of accuracy as well as complexity.

Keywords: machine learning, air quality classification, air quality index, information gain, support vector machine, cross-validation

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Authors: Surajo Ladan

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There is no doubt nowadays, the media plays a crucial role in the development of languages. Media practitioners influence and set our linguistic norms to a greater extent. Their strategic position makes them influential than school teachers as linguistic pacesetters and models. This is so because of the direct access to the general public that media enjoys being public, oriented and at the same time being patronized by the public, the media is regarded as an authority as far as language use is concerned. In the modern world, listening to the news has become part and parcel of our daily lives. Easy communication has made the world a global village. Contact between countries and people are increasing daily. In Nigeria and indeed the whole of West Africa, radio is the most widely spread out of the three types of media (radio, television, and print). This is because of its (radio) cheapness and less cumbersome and flexibility. Therefore, the positive or negative effect of radio on the lives of a typical Nigerian or African cannot be over emphasized. Hausa language, on the other hand, is one of the most widely spoken languages in West Africa and, of course, the lingua franca in the Northern part of Nigeria and Southern Niger. The language has been in use to a large extent by almost all the popular foreign media houses of BBC, VOA, Deutsche Welle Radio, Radio France International, Radio China, etc. The many people in Nigeria and West Africa depend so much on the news in this language. In fact even government programmes, mobilization, education and sensitization of the populace are done in this language through the broadcast media. It is against this background, for effective and efficient work of this nature it requires the services of a trained translator for the purpose of translating scientific and technological terms. The main thrust of this paper was necessitated for the fact that no nation develops using foreign or borrowed language. This is in lined with UNESCO declaration of 1953 where it says 'the best Language of Instruction (LOI) is the vernacular or the Mother Tongue (MT) of the learner'. This idea is in the right direction especially nowadays that the developing nations have come to terms with realities that their destiny is really in their own hands, not in the hands of the so-called developed nations.

Keywords: translation, scientific, technological, language, radio, media

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Authors: Mariam Tsitsagi, Ana Berdzenishvili

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Rainfall intensity change is one of the main indicators of climate change. It has a great influence on agriculture as one of the main factors causing soil erosion. Splash and sheet erosion are one of the most prevalence and harmful for agriculture. It is invisible for an eye at first stage, but the process will gradually move to stream cutting erosion. Our study provides the assessment of rainfall erosivity potential with the use of modern research methods in Kakheti region. The region is the major provider of wheat and wine in the country. Kakheti is located in the eastern part of Georgia and characterized quite a variety of natural conditions. The climate is dry subtropical. For assessment of the exact rate of rainfall erosion potential several year data of rainfall with short intervals are needed. Unfortunately, from 250 active metro stations running during the Soviet period only 55 of them are active now and 5 stations in Kakheti region respectively. Since 1936 we had data on rainfall intensity in this region, and rainfall erosive potential is assessed, in some old papers, but since 1990 we have no data about this factor, which in turn is a necessary parameter for determining the rainfall erosivity potential. On the other hand, researchers and local communities suppose that rainfall intensity has been changing and the number of haily days has also been increasing. However, finding a method that will allow us to determine rainfall erosivity potential as accurate as possible in Kakheti region is very important. The study period was divided into three sections: 1936-1963; 1963-1990 and 1990-2015. Rainfall erosivity potential was determined by the scientific literature and old meteorological stations’ data for the first two periods. And it is known that in eastern Georgia, at the boundary between steppe and forest zones, rainfall erosivity in 1963-1990 was 20-75% higher than that in 1936-1963. As for the third period (1990-2015), for which we do not have data of rainfall intensity. There are a variety of studies, where alternative ways of calculating the rainfall erosivity potential based on lack of data are discussed e.g.based on daily rainfall data, average annual rainfall data and the elevation of the area, etc. It should be noted that these methods give us a totally different results in case of different climatic conditions and sometimes huge errors in some cases. Three of the most common methods were selected for our research. Each of them was tested for the first two sections of the study period. According to the outcomes more suitable method for regional climatic conditions was selected, and after that, we determined rainfall erosivity potential for the third section of our study period with use of the most successful method. Outcome data like attribute tables and graphs was specially linked to the database of Kakheti, and appropriate thematic maps were created. The results allowed us to analyze the rainfall erosivity potential changes from 1936 to the present and make the future prospect. We have successfully implemented a method which can also be use for some another region of Georgia.

Keywords: erosivity potential, Georgia, GIS, Kakheti, rainfall

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Authors: Alicja Kot-Niewiadomska

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Securing sustainable access to raw materials is vital for the growth of the European economy and for the goals laid down in Strategy Europe 2020. One of the most important sources of mineral raw materials are primary deposits. The efficient management of them, including extraction, will ensure competitiveness of the European economy. A critical element of this approach is mineral deposits safeguarding and the most important tool - spatial planning. The safeguarding of deposits should be understood as safeguarding of land access, and safeguarding of area against development, which may (potential) prevent the use of the deposit and the necessary mining activities. Many European Union countries successfully integrated their mineral policy and spatial policy, which has ensured the proper place of mineral deposits in their spatial planning systems. These, in turn, are widely recognized as the most important mineral deposit safeguarding tool, the essence of which is to ensure long-term access to its resources. The examples of Austria, Portugal, Slovakia, Czech Republic, Sweden, and the United Kingdom, discussed in the paper, are often mentioned as examples of good practices in this area. Although none of these countries managed to avoid cases of social and environmental conflicts related to mining activities, the solutions they implement certainly deserve special attention. And for many countries, including Poland, they can be a potential source of solutions aimed at improving the protection of mineral deposits.

Keywords: mineral deposits, land use planning, mineral deposit safeguarding, European practices

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Authors: Qiuyu Dai, Haochong Zhang, Xiangrong Liu

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Diagonal sparse matrix-vector multiplication is a well-studied topic in the fields of scientific computing and big data processing. However, when diagonal sparse matrices are stored in DIA format, there can be a significant number of padded zero elements and scattered points, which can lead to a degradation in the performance of the current DIA kernel. This can also lead to excessive consumption of computational and memory resources. In order to address these issues, the authors propose the DIA-Adaptive scheme and its kernel, which leverages the parallel instruction sets on MLU. The researchers analyze the effect of allocating a varying number of threads, clusters, and hardware architectures on the performance of SpMV using different formats. The experimental results indicate that the proposed DIA-Adaptive scheme performs well and offers excellent parallelism.

Keywords: adaptive method, DIA, diagonal sparse matrices, MLU, sparse matrix-vector multiplication

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Authors: Ouafae Baida, Najma Hamzaoui, Maha Akbib, Abdelfettah Sedqui, Abdelouahid Lyhyaoui

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Numerous scientific works present various methods to analyze the data for several domains, specially the comparison of classifications. In our recent work, we presented a new approach to help the user choose the best classification method from the results obtained by every method, by basing itself on the distances between the trees of classification. The result of our approach was in the form of a dendrogram contains methods as a succession of connections. This approach is much needed in phylogeny analysis. This discipline is intended to analyze the sequences of biological macro molecules for information on the evolutionary history of living beings, including their relationship. The product of phylogeny analysis is a phylogenetic tree. In this paper, we recommend the use of a new method of construction the phylogenetic tree based on comparison of different classifications obtained by different molecular genes.

Keywords: hierarchical classification, classification methods, structure of tree, genes, phylogenetic analysis

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Authors: Emre Bayamlıoğlu

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This paper aims to provide an account of the legal and the regulative aspects of the algorithmic reputation systems with a special emphasis on the sharing economy (i.e., Uber, Airbnb, Lyft) business model. The first section starts with an analysis of the legal and commercial nature of the tripartite relationship among the parties, namely, the host platform, individual sharers/service providers and the consumers/users. The section further examines to what extent an algorithmic system of reputational information could serve as an alternative to legal regulation. Shortcomings are explained and analyzed with specific examples from Airbnb Platform which is a pioneering success in the sharing economy. The following section focuses on the issue of governance and control of the reputational information. The section first analyzes the legal consequences of algorithmic filtering systems to detect undesired comments and how a delicate balance could be struck between the competing interests such as freedom of speech, privacy and the integrity of the commercial reputation. The third section deals with the problem of manipulation by users. Indeed many sharing economy businesses employ certain techniques of data mining and natural language processing to verify consistency of the feedback. Software agents referred as "bots" are employed by the users to "produce" fake reputation values. Such automated techniques are deceptive with significant negative effects for undermining the trust upon which the reputational system is built. The third section is devoted to explore the concerns with regard to data mobility, data ownership, and the privacy. Reputational information provided by the consumers in the form of textual comment may be regarded as a writing which is eligible to copyright protection. Algorithmic reputational systems also contain personal data pertaining both the individual entrepreneurs and the consumers. The final section starts with an overview of the notion of reputation as a communitarian and collective form of referential trust and further provides an evaluation of the above legal arguments from the perspective of public interest in the integrity of reputational information. The paper concludes with certain guidelines and design principles for algorithmic reputation systems, to address the above raised legal implications.

Keywords: sharing economy, design principles of algorithmic regulation, reputational systems, personal data protection, privacy

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Authors: Mostafa Firoozabadi, Alireza Foroughi Nematollahi

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Wet mills are one of the most important equipment in the mining industries and any defect occurrence in them can stop the production line and it can make some irrecoverable damages to the system. Electromotors are the significant parts of a mill and their monitoring is a necessary process to prevent unwanted defects. The purpose of this study is to investigate the Electromotor bearing defects, theoretically and practically, using the vibration analysis method. When a defect happens in a bearing, it can be transferred to the other parts of the equipment like inner ring, outer ring, balls, and the bearing cage. The electromotor defects source can be electrical or mechanical. Sometimes, the electrical and mechanical defect frequencies are modulated and the bearing defect detection becomes difficult. In this paper, to detect the electromotor bearing defects, the electrical and mechanical defect frequencies are extracted firstly. Then, by calculating the bearing defect frequencies, and the spectrum and time signal analysis, the bearing defects are detected. In addition, the obtained frequency determines that the bearing level in which the defect has happened and by comparing this level to the standards it determines the bearing remaining lifetime. Finally, the defect length is calculated by theoretical equations to demonstrate that there is no need to replace the bearing. The results of the proposed method, which has been implemented on the wet mills in the Golgohar mining and industrial company in Iran, show that this method is capable of detecting the electromotor bearing defects accurately and on time.

Keywords: bearing defect length, defect frequency, electromotor defects, vibration analysis

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Authors: S. Chandrasekaran, S. Nandita, M. Shivathmika, Srikrishnan Shivakumar

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The objective of the research work is to analyze the computational chemical-composition of carbohydrates in the context of healthcare informatics. The computation involves the representation of complex chemical molecular structure of carbohydrate using graph theory and in a deployable Chemical Markup Language (CML). The parallel molecular structure of the chemical molecules with or without other adulterants for the sake of business profit can be analyzed in terms of robustness and derivatization measures. The rural healthcare program should create awareness in malnutrition to reduce ill-effect of decomposition and help the consumers to know the level of such energy storage mixtures in a quantitative way. The earlier works were based on the empirical and wet data which can vary from time to time but cannot be made to reuse the results of mining. The work is carried out on the quantitative computational chemistry on carbohydrates to provide a safe and secure right to food act and its regulations.

Keywords: carbohydrates, chemical-composition, chemical markup, robustness, food safety

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Authors: Wayne Tarrant, Ethan Petersen

Abstract:

The concept of a flat tax goes back to at least the Biblical tithe. A progressive income tax was first vociferously espoused in a small, but famous, pamphlet in 1848 (although England had an emergency progressive tax for war costs prior to this). Within a few years many countries had adopted the progressive structure. The flat tax was only reinstated in some small countries and British protectorates until Mart Laar was elected Prime Minister of Estonia in 1992. Since Estonia’s adoption of the flat tax in 1993, many other formerly Communist countries have likewise abandoned progressive income taxes. Economists had expectations of what would happen when a flat tax was enacted, but very little work has been done on actually measuring the effect. With a testbed of 21 countries in this region that currently have a flat tax, much comparison is possible. Several countries have retained progressive taxes, giving an opportunity for contrast. There are also the cases of Czech Republic and Slovakia, which have adopted and later abandoned the flat tax. Further, with over 20 years’ worth of economic history in some flat tax countries, we can begin to do some serious longitudinal study. In this paper we consider many economic variables to determine if there are statistically significant differences from before to after the adoption of a flat tax. We consider unemployment rates, tax receipts, GDP growth, Gini coefficients, and market data where the data are available. Comparisons are made through the use of event studies and time series methods. The results are mixed, but we draw statistically significant conclusions about some effects. We also look at the different implementations of the flat tax. In some countries there are equal income and corporate tax rates. In others the income tax has a lower rate, while in others the reverse is true. Each of these sends a clear message to individuals and corporations. The policy makers surely have a desired effect in mind. We group countries with similar policies, try to determine if the intended effect actually occurred, and then report the results. This is a work in progress, and we welcome the suggestion of variables to consider. Further, some of the data from before the fall of the Iron Curtain are suspect. Since there are new ruling regimes in these countries, the methods of computing different statistical measures has changed. Although we first look at the raw data as reported, we also attempt to account for these changes. We show which data seem to be fictional and suggest ways to infer the needed statistics from other data. These results are reported beside those on the reported data. Since there is debate about taxation structure, this paper can help inform policymakers of change the flat tax has caused in other countries. The work shows some strengths and weaknesses of a flat tax structure. Moreover, it provides beginnings of a scientific analysis of the flat tax in practice rather than having discussion based solely upon theory and conjecture.

Keywords: flat tax, financial markets, GDP, unemployment rate, Gini coefficient

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Authors: Tatiana Ponomarenko, Oksana Marinina, Marina Nevskaya

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Modern corporate social responsibility (CSR) is a sphere of multilevel responsibility of a company toward society represented by various stakeholders. The relevance of CSR management grows due to the active development of socially responsible investing (principles for responsible investment) taking into account factors of environmental, social and corporate governance (ESG), growing attention of the investment community in general to the long-term stability of companies and the quality of control of nonfinancial risks. The modern approach to CSR strategic management is aimed at the creation of trustful relationships with stakeholders, on the basis of which a contribution to the sustainable development of companies, regions, and national economics is insured. However, the practical concepts of social responsibility in mining companies are different, which leads to various degrees of application of CSR. A number of companies implement CSR using a traditional (limited) understanding of responsibility toward employees and counteragents, the others understand CSR much wider and try to use leverages of efficient cooperation. As in large mining companies the scope of CSR measures is diverse and characterized by different indices, the study was aimed at evaluating CSR efficiency on the basis of a proprietary methodology and determining the level of development of CSR management in terms of anti-crisis, reactive and proactive development. The methodology of the research includes analysis of integrated global reporting initiative (GRI) reports of large mining companies; choice of most representative sectoral agents by a criterion of the regularity of issuance and publication of reports; calculation of indices of evaluation of CSR level of the selected companies in dynamics. The methodology of evaluation of CSR level is based on a rating score of changes in standard indices of GRI reports by economic, environmental, and social directions. Result. By the results of the analysis, companies of fuel and energy and metallurgic complexes, in overwhelming majority, reflecting three indices out of a wide range of possible indicators of SDGs (Sustainable Development Goals), were selected for the study. The evaluation of the scopes of CSR of the companies Gazprom, LUKOIL, Metalloinvest, Nornikel, Rosneft, Severstal, SIBUR, SUEK corresponds to the reactive type of development according to a scale of CSR strategic management, which is the average value out of the possible values. The chief drawback is that companies, in the process of analyzing global goals, often choose the goals which relate to their own activities, paying insufficient attention to the interests of the stakeholders inside the country. This fact evidences the necessity of searching for more effective mechanisms of CSR control. Acknowledgment: This article is prepared within grant support of the RFBR, project 19-510-44013 'Development of the concept of mineral resources value formation in the context of sustainable development in resource-oriented economies'.

Keywords: sustainable development, corporate social responsibility, development strategies, efficiency assessment

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Authors: Kacper Tomasz Kröber-Mulawa

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This paper will address the topic of data ownership from an economic perspective, and examples of economic limitations of data property rights will be provided, which have been identified using methods and approaches of economic analysis of law. To properly build a background for the economic focus, in the beginning a short perspective of data and data ownership in the EU’s legal system will be provided. It will include a short introduction to its political and social importance and highlight relevant viewpoints. This will stress the importance of a Single Market for data but also far-reaching regulations of data governance and privacy (including the distinction of personal and non-personal data, data held by public bodies and private businesses). The main discussion of this paper will build upon the briefly referred to legal basis as well as methods and approaches of economic analysis of law.

Keywords: antitrust, data, data ownership, digital economy, property rights

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Authors: Sérgio J. Teixeira, João J. Ferreira

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Tourism frequently gets identified as one of the sectors with the greatest potential for expansion on a global scale and hence conveying the importance of attempting to better understand the regional factors of competitiveness prevailing in this sector. This study’s objective essentially strives to provide a mapping of the scientific publications and the intellectual knowledge therein contained while conveying past research trends and identifying potential future lines of research in the fields of regional competitiveness and tourism innovation. This correspondingly deploys a systematic review of the literature in keeping with the bibliometric approach based upon VOSviewer software, with a particular focus on drafting maps for visualising the underlying intellectual structure. This type of analysis encapsulates the number of articles published and their annual number of citations for the period between 1900 and 2016 as registered by the Web of Science database. The results demonstrate how the intellectual structure on regional competitiveness divides essentially into three major categories: regional competitiveness, tourism innovation, and tourism clusters. Thus, the main contribution of this study arises out of identifying the main research trends in this field and the respective shortcomings and specific needs for future scientific research in the field of regional competitiveness and innovation in tourism.

Keywords: regional competitiveness, tourism cluster, bibliometric studies, tourism innovation, systematic review

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Authors: Abdullah Alsaeed

Abstract:

Virtualized computing and cloud computing infrastructures are no longer fuzz or marketing term. They are a core reality in today’s corporate Information Technology (IT) organizations. Hence, developing an effective and efficient methodologies for data backup and data recovery is required more than any time. The purpose of data backup and recovery techniques are to assist the organizations to strategize the business continuity and disaster recovery approaches. In order to accomplish this strategic objective, a variety of mechanism were proposed in the recent years. This research paper will explore and examine the latest techniques and solutions to provide data backup and restoration for the cloud computing platforms.

Keywords: data backup, data recovery, cloud computing, business continuity, disaster recovery, cost-effective, data encryption.

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Authors: JaeHwan Yang, Da-Woon Jeong, Seung-Young Kho, Dong-Kyu Kim

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In terms of ITS, information on link characteristic is an essential factor for plan or operation. But in practical cases, not every link has installed sensors on it. The link that does not have data on it is called “Missing Link”. The purpose of this study is to impute data of these missing links. To get these data, this study applies the machine learning method. With the machine learning process, especially for the deep learning process, missing link data can be estimated from present link data. For deep learning process, this study uses “Recurrent Neural Network” to take time-series data of road. As input data, Dedicated Short-range Communications (DSRC) data of Dalgubul-daero of Daegu Metropolitan Area had been fed into the learning process. Neural Network structure has 17 links with present data as input, 2 hidden layers, for 1 missing link data. As a result, forecasted data of target link show about 94% of accuracy compared with actual data.

Keywords: data estimation, link data, machine learning, road network

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Authors: Pil Kyoo Jo, Jee Young Kim, Yu Jin Oh, Sohyun Park, Young Ha Joo, Hye Suk Kim, Semi Kang

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When convenience drives daily food choices, the increased consumption of processed foods may be associated with the increased intakes of sodium and fat and further with the onset of chronic diseases. The purpose of this study was to investigate the levels of sodium, saturated fat, and calories intakes through processed foods and the dietary patterns among adult populations in South Korea. We used the nationally representative data from the 5th Korea National Health and Nutrition Examination Survey (KNHANES, 2010-2012) and a cross-sectional survey on the eating behaviors among university students(N=893, 380 men, 513 women) aged from 20 to 24 years. Results showed that South Koreans consumed 43.5% of their total food consumption from processed foods. The 24-hour recalls data showed that 77% of sodium, 60% of fats, 59% of saturated fat, and 44% of calories were consumed from processed food. The intake of processed foods increased by 1.7% in average since 2008 annually. Only 33% of processed food that respondents consumed had nutrition labeling. The data from university students showed that students selected processed foods in convenience store when eating alone compared to eating with someone else. Given the convenience and lack of time, more people will consume processed foods and it may impact their overall dietary intake and further their health. In order to help people to make healthier food choices, regulations and policies to reduce the potentially unhealthy nutrients of processed foods should be strengthened. This research was supported by the National Research Foundation of Korea for 2011 Korea-Japan Basic Scientific Cooperation Program. This work was supported by the Ministry of Education of the Republic of Korea and the National Research Foundation of Korea (NRF-2015S1A5B6037369).

Keywords: sodium, fat, processed foods, diet trends

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Authors: Isaac Owusu Asante, Yushi Jiang, Hailin Tao

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Live streaming marketing, the new electronic commerce element, became an optional marketing channel following the COVID-19 pandemic. Many sellers have leveraged the features presented by live streaming to increase sales. Studies on live streaming have focused on gaming and consumers’ loyalty to brands through live streaming, using interview questionnaires. This study, however, was conducted to measure real-time observable interactions between consumers and sellers. Based on the affordance theory, this study conceptualized constructs representing the interactive features and examined how they drive consumers’ purchase willingness during live streaming sessions using 1238 datasets from Amazon Live, following the manual observation of transaction records. Using structural equation modeling, the ordinary least square regression suggests that live viewers, new followers, live chats, and likes positively affect purchase willingness. The Sobel and Monte Carlo tests show that new followers, live chats, and likes significantly mediate the relationship between live viewers and purchase willingness. The study introduces a new way of measuring interactions in live streaming commerce and proposes a way to manually gather data on consumer behaviors in live streaming platforms when the application programming interface (API) of such platforms does not support data mining algorithms.

Keywords: livestreaming marketing, live chats, live viewers, likes, new followers, purchase willingness

Procedia PDF Downloads 57