Search results for: large amounts of data

Authors: Dewi Juliah Ratnaningsih, Imas Sukaesih Sitanggang

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Classification is one of data mining techniques that aims to discover a model from training data that distinguishes records into the appropriate category or class. Data mining classification methods can be applied in education, for example, to determine the classification of non-active students in Indonesia Open University. This paper presents a comparison of three methods of classification: Naïve Bayes, Bagging, and C.45. The criteria used to evaluate the performance of three methods of classification are stratified cross-validation, confusion matrix, the value of the area under the ROC Curve (AUC), Recall, Precision, and F-measure. The data used for this paper are from the non-active Indonesia Open University students in registration period of 2004.1 to 2012.2. Target analysis requires that non-active students were divided into 3 groups: C1, C2, and C3. Data analyzed are as many as 4173 students. Results of the study show: (1) Bagging method gave a high degree of classification accuracy than Naïve Bayes and C.45, (2) the Bagging classification accuracy rate is 82.99 %, while the Naïve Bayes and C.45 are 80.04 % and 82.74 % respectively, (3) the result of Bagging classification tree method has a large number of nodes, so it is quite difficult in decision making, (4) classification of non-active Indonesia Open University student characteristics uses algorithms C.45, (5) based on the algorithm C.45, there are 5 interesting rules which can describe the characteristics of non-active Indonesia Open University students.

Keywords: comparative analysis, data mining, clasiffication, Bagging, Naïve Bayes, C.45, non-active students, Indonesia Open University

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Authors: Asma Ben Yaghlane, Mohamed Naceur Azaiez, Mehdi Mrad

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We investigate the large scale of networks in the context of network survivability under attack. We use appropriate techniques to evaluate and the attacker-based- and the defender-based-network survivability. The attacker is unaware of the operated links by the defender. Each attacked link has some pre-specified probability to be disconnected. The defender choice is so that to maximize the chance of successfully sending the flow to the destination node. The attacker however will select the cut-set with the highest chance to be disabled in order to partition the network. Moreover, we extend the problem to the case of selecting the best p paths to operate by the defender and the best k cut-sets to target by the attacker, for arbitrary integers p,k > 1. We investigate some variations of the problem and suggest polynomial-time solutions.

Keywords: defense/attack strategies, large scale, networks, partitioning a network

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Authors: K. Parandhama Gowd

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The aim of this research paper is to conceptualize, discuss, analyze and propose alternate design methodologies for futuristic Black Box for flight safety. The proposal also includes global networking concepts for real time surveillance and monitoring of flight performance parameters including GPS parameters. It is expected that this proposal will serve as a failsafe real time diagnostic tool for accident investigation and location of debris in real time. In this paper, an attempt is made to improve the existing methods of flight data recording techniques and improve upon design considerations for futuristic FDR to overcome the trauma of not able to locate the block box. Since modern day communications and information technologies with large bandwidth are available coupled with faster computer processing techniques, the attempt made in this paper to develop a failsafe recording technique is feasible. Further data fusion/data warehousing technologies are available for exploitation.

Keywords: flight data recorder (FDR), black box, diagnostic tool, global networking, cockpit voice and data recorder (CVDR), air traffic control (ATC), air traffic, telemetry, tracking and control centers ATTTCC)

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Authors: Reza Rezaeipour Honarmandzad

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In this paper we propose an ANN for detection and localization of fatigue damage in aircraft structures. We used network of piezoelectric transducers for Lamb-wave measurements in order to calculate damage indices. Data gathered by the sensors was given to neural network classifier. A set of neural network electors of different architecture cooperates to achieve consensus concerning the state of each monitored path. Sensed signal variations in the ROI, detected by the networks at each path, were used to assess the state of the structure as well as to localize detected damage and to filter out ambient changes. The classifier has been extensively tested on large data sets acquired in the tests of specimens with artificially introduced notches as well as the results of numerous fatigue experiments. Effect of the classifier structure and test data used for training on the results was evaluated.

Keywords: ANN, fatigue damage, aircraft structures, piezoelectric transducers, lamb-wave measurements

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Authors: Jean Marie Tshimula, Atsushi Togashi

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We develop a data-science approach for providing an interactive visualization and predictive models to find insights into the projects' historical data in order for stakeholders understand some unseen opportunities in the African market that might escape them behind the online project portfolio of the African Development Bank. This machine learning-based web application identifies the market trend of the fastest growing economies across the continent as well skyrocketing sectors which have a significant impact on the future of business in Africa. Owing to this, the approach is tailored to predict where the investment needs are the most required. Moreover, we create a corpus that includes the descriptions of over more than 1,200 projects that approximately cover 14 sectors designed for some of 53 African countries. Then, we sift out this large amount of semi-structured data for extracting tiny details susceptible to contain some directions to follow. In the light of the foregoing, we have applied the combination of Latent Dirichlet Allocation and Random Forests at the level of the analysis module of our methodology to highlight the most relevant topics that investors may focus on for investing in Africa.

Keywords: machine learning, topic modeling, natural language processing, big data

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Authors: Faraj M. Elkhatri, Hana Ali Allafi

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The spatial and temporal distribution of diagenetic alterations related impact on the reservoir quality of the Sarir Formation. (present day burial depth of about 9000 feet) Depositional facies and diagenetic alterations are the main controls on reservoir quality of Sarir Formation Sirt Ba-sin Libya; these based on lithology and grain size as well as authigenic clay mineral types and their distributions. However, petrology investigation obtained on study area with five sandstone wells concentrated on main rock components and the parameters that may have impacts on reservoirs. the main authigenic clay minerals are kaolinite and dickite, these investigations have confirmed by X.R.D analysis and clay fraction. mainly Kaolinite and Dickite were extensively presented on all of wells with high amounts. As well as trace of detrital smectite and less amounts of illitized mud-matrix are possibly find by SEM image. Thin layers of clay presented as clay-grain coatings in local depth interpreted as remains of dissolved clay matrix is partly transformed into kaolinite adjacent and towards pore throat. This also may have impacts on most of the pore throats of this sandstone which are open and relatively clean with some of fine martial have been formed on occluded pores. This material is identified by EDS analysis to be collections of not only kaolinite booklets, but also small, disaggregated kaolinite platelets derived from the dis-aggregation of larger kaolinite booklets. These patches of kaolinite not only fill this pore, but also coat some of the sur-rounding framework grains. Quartz grains often enlarged by authigenic quartz overgrowths partially occlude and re-duce porosity. Scanning Electron Microscopy with Energy Dispersive Spectroscopy (SEM) was conducted on the post-test samples to examine any mud filtrate particles that may be in the pore throats. Semi-qualitative elemental data on select-ed minerals observed during the SEM study were obtained using an Energy Dispersive Spectroscopy (EDS) unit. The samples showed mostly clean open pore throats, with limited occlusion by kaolinite.

Keywords: por throat, formation damage, porosity lose, solids plugging

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Authors: Thierno Diop, Michel Fortin, Jean Deteix

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Since the precise formulation of the elastic part is irrelevant for the description of the algorithm, we shall consider a generic case. In practice, however, we will have to deal with a non linear material (for instance a Mooney-Rivlin model). We are interested in solving a finite element approximation of the problem, leading to large-scale non linear discrete problems and, after linearization, to large linear systems and ultimately to calculations needing iterative methods. This also implies that penalty method, and therefore augmented Lagrangian method, are to be banned because of their negative effect on the condition number of the underlying discrete systems and thus on the convergence of iterative methods. This is in rupture to the mainstream of methods for contact in which augmented Lagrangian is the principal tool. We shall first present the problem and its discretization; this will lead us to describe a general solution algorithm relying on a preconditioner for saddle-point problems which we shall describe in some detail as it is not entirely standard. We will propose an iterative approach for solving three-dimensional frictional contact problems between elastic bodies, including contact with a rigid body, contact between two or more bodies and also self-contact.

Keywords: frictional contact, three-dimensional, large-scale, iterative method

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Authors: Lilian Kishimbo

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This study aims to examine Corporate Social Responsibility (CSR) practices of local large firms of East Africa region. In this study CSR is defined as all actions that go beyond obeying minimum legal requirements as espoused by other authors. Despite the increase of CSR literature empirical evidence clearly demonstrate an imbalance of CSR studies in the developing countries . Moreover, it is evident that most of the research on CSR in developing economies emerges from large fast-growing economies or BRICS members (i.e. Brazil, India, China and South Africa), and Indonesia and Malaysia and a further call for more research in Africa is particularly advocated. Taking Africa as an example, there are scanty researches on CSR practices, and the few available studies are mainly from Nigeria and South Africa leaving other parts of Africa for example East Africa underrepresented. Furthermore, in the face of globalization, experience shows that literature has focused mostly on multinational companies (MNCs) operating in either North-North or North-South and less on South-South indigenous local firms. Thus the existing literature in Africa shows more studies of MNCs and little is known about CSR of local indigenous firms operating in the South particularly in the East Africa region. Accordingly, this paper explores CSR practices of indigenous local large firms of East Africa region particularly Kenya and Tanzania with the aim of testing the hypothesis that do local firms of East Africa region engage in similar CSR practices as firms in other parts of the world?. To answer this question only listed local large firms were considered based on the assumption that they are large enough to engage. Newspapers were the main source of data and information collected was supplemented by business Annual Reports for the period 2010-2012. The research finding revealed that local firms of East Africa engage in CSR practices. However, there are some differences in the set of activities these firms prefers to engage in compared to findings from previous studies. As such some CSR that were given priority by firms in East Africa were less prioritized in the other part of the world including Indonesia. This paper will add knowledge to the body of CSR and experience of CSR practices of South-South indigenous firms where is evidenced to have a relative dearth of literature on CSR. Finally, the paper concludes that local firms of East Africa region engage in similar activities like other firms globally. But firms give more priority to some activities such education and health related activities. Finally, the study intends to assist policy makers at firm’s levels to plan for long lasting projects related to CSR for their stakeholders.

Keywords: Africa, corporate social responsibility, developing countries, indigenous firms, Kenya, Tanzania

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Authors: Evren Şar İşbilen

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As it is known, the movies and tv series are occupying a large part in the daily lives of adults and children in our era. In this connection, in the present study, the most popular historical TV series of recent years in Turkey, “Muhteşem Yüzyıl” (The Magnificent Century), was selected as the sample for the data collection in order to explore the perception of history of university students’. The data collected was analyzed bothqualitatively and quantitatively. The findings discussed in relation to the possible educative effects of historical non-educational TV series and movies on students' perceptions related to history. Additionally, suggestions were made regarding to the utilization of non-educational TV series or movies in education in a positive way.

Keywords: education, history, movies, teacher candidates

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Authors: Rutcher M. Lacaza, Stephen Jun V. Villejo

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This paper investigated the patterns of private transfers in the Philippines using the Family Income Expenditure Survey (FIES) 2009, conducted by the Philippine government’s National Statistics Office (NSO) every three years. The paper performed bivariate analysis on net transfers, using the identified determinants for a household to be either a net receiver or a net giver. The household characteristics considered are the following: age, sex, marital status, employment status and educational attainment of the household head, and also size, location, pre-transfer income and the number of employed members of the household. The variables net receiver and net giver are determined by computing the net transfer, subtracting total gifts from total receipts. The receipts are defined as the sum of cash received from abroad, cash received from domestic sources, total gifts received and inheritance. While gifts are defined as the sum of contributions and donations to church and other religious institutions, contributions and donations to other institutions, gifts and contributions to others, and gifts and assistance to private individuals outside the family. Both in kind and in cash transfers are considered in the analysis. It also performed a multiple regression analysis on transfers received and income including other household characteristics to examine the motives for giving transfers – whether altruism or exchanged. It also used the binary logistic regression to estimate the probability of being a net receiver or net giver given the household characteristics. The study revealed that receiving tends to be universal – both the non-poor and the poor benefit although the poor receive substantially less than the non-poor. Regardless of whether households are net receivers or net givers, households in the upper deciles generally give and receive more than those in the lower deciles. It also appears that private transfers may just flow within economic groups. Big amounts of transfers are, therefore, directed to the non-poor and the small amounts go to the poor. This was also supported by the increasing function of gross transfers received and the income of households – the poor receiving less and the non-poor receiving more. This is contrary to the theory that private transfers can help equalize the distribution of income. This suggested that private transfers in the Philippines are not altruistically motivated but exchanged. However, bilateral data on transfers received or given is needed to test this theory directly. The results showed that transfers are much needed by the poor and it is important to understand the nature of private transfers, to ensure that government transfer programs are properly designed and targeted so as to prevent the duplication of private safety nets already present among the non-poor.

Keywords: private transfers, net receiver, net giver, altruism, exchanged.

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Authors: G. Rajeshwari, V. D. M. Jabez Daniel

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Radio Frequency Identification systems are used for automated identification in various applications such as automobiles, health care and security. It is also called as the automated data collection technology. RFID readers are placed in any area to scan large number of tags to cover a wide distance. The placement of the RFID elements may result in several types of collisions. A major challenge in RFID system is collision avoidance. In the previous works the collision was avoided by using algorithms such as ALOHA and tree algorithm. This work proposes collision reduction and increased throughput through reading enhancement method with tree algorithm. The reading enhancement is done by improving interrogation procedure and increasing the data handling capacity of RFID reader with parallel processing. The work is simulated using Xilinx ISE 14.5 verilog language. By implementing this in the RFID system, we can able to achieve high throughput and avoid collision in the reader at a same instant of time. The overall system efficiency will be increased by implementing this.

Keywords: antenna, anti-collision protocols, data management system, reader, reading enhancement, tag

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Authors: Elisa Coraggio, Dawei Han, Weiru Liu, Theo Tryfonas

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Water is one of the most important resources for human society. The world is currently undergoing a wave of urban growth, and pollution problems are of a great impact. Monitoring water quality is a key task for the future of the environment and human species. In recent times, researchers, using Smart Cities technologies are trying to mitigate the problems generated by the population growth in urban areas. The availability of huge amounts of data collected by a pervasive urban IoT can increase the transparency of decision making. Several services have already been implemented in Smart Cities, but more and more services will be involved in the future. Water quality monitoring can successfully be implemented in the urban IoT. The combination of water quality sensors, cloud computing, smart city infrastructure, and IoT technology can lead to a bright future for environmental monitoring. In the past decades, lots of effort has been put on monitoring and predicting water quality using traditional approaches based on manual collection and laboratory-based analysis, which are slow and laborious. The present study proposes a methodology for implementing a water quality prediction model using artificial intelligence techniques and comparing the results obtained with different algorithms. Furthermore, a 3D numerical model will be created using the software D-Water Quality, and simulation results will be used as a training dataset for the artificial intelligence algorithm. This study derives the methodology and demonstrates its implementation based on information and data collected at the floating harbour in the city of Bristol (UK). The city of Bristol is blessed with the Bristol-Is-Open infrastructure that includes Wi-Fi network and virtual machines. It was also named the UK ’s smartest city in 2017.In recent times, researchers, using Smart Cities technologies are trying to mitigate the problems generated by the population growth in urban areas. The availability of huge amounts of data collected by a pervasive urban IoT can increase the transparency of decision making. Several services have already been implemented in Smart Cities, but more and more services will be involved in the future. Water quality monitoring can successfully be implemented in the urban IoT. The combination of water quality sensors, cloud computing, smart city infrastructure, and IoT technology can lead to a bright future for the environment monitoring. In the past decades, lots of effort has been put on monitoring and predicting water quality using traditional approaches based on manual collection and laboratory-based analysis, which are slow and laborious. The present study proposes a new methodology for implementing a water quality prediction model using artificial intelligence techniques and comparing the results obtained with different algorithms. Furthermore, a 3D numerical model will be created using the software D-Water Quality, and simulation results will be used as a training dataset for the Artificial Intelligence algorithm. This study derives the methodology and demonstrate its implementation based on information and data collected at the floating harbour in the city of Bristol (UK). The city of Bristol is blessed with the Bristol-Is-Open infrastructure that includes Wi-Fi network and virtual machines. It was also named the UK ’s smartest city in 2017.

Keywords: artificial intelligence, hydroinformatics, numerical modelling, smart cities, water quality

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Authors: Szymon Kuczynski, Krystian Liszka, Mariusz Laciak, Andrii Oliinyk, Adam Szurlej

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Currently, in automotive transport to power vehicles, almost exclusively hydrocarbon based fuels are used. Due to increase of hydrocarbon fuels consumption, quality parameters are tightend for clean environment. At the same time efforts are undertaken for development of alternative fuels. The reasons why looking for alternative fuels for petroleum and diesel are: to increase vehicle efficiency and to reduce the environmental impact, reduction of greenhouse gases emissions and savings in consumption of limited oil resources. Significant progress was performed on development of alternative fuels such as methanol, ethanol, natural gas (CNG / LNG), LPG, dimethyl ether (DME) and biodiesel. In addition, biggest vehicle manufacturers work on fuel cell vehicles and its introduction to the market. Alcohols such as methanol and ethanol create the perfect fuel for spark-ignition engines. Their advantages are high-value antiknock which determines their application as additive (10%) to unleaded petrol and relative purity of produced exhaust gasses. Ethanol is produced in distillation process of plant products, which value as a food can be irrational. Ethanol production can be costly also for the entire economy of the country, because it requires a large complex distillation plants, large amounts of biomass and finally a significant amount of fuel to sustain the process. At the same time, the fermentation process of plants releases into the atmosphere large quantities of carbon dioxide. Natural gas cannot be directly converted into liquid fuels, although such arrangements have been proposed in the literature. Going through stage of intermediates is inevitable yet. Most popular one is conversion to methanol, which can be processed further to dimethyl ether (DME) or olefin (ethylene and propylene) for the petrochemical sector. Methanol uses natural gas as a raw material, however, requires expensive and advanced production processes. In relation to pollution emissions, the optimal vehicle fuel is LPG which is used in many countries as an engine fuel. Production of LPG is inextricably linked with production and processing of oil and gas, and which represents a small percentage. Its potential as an alternative for traditional fuels is therefore proportionately reduced. Excellent engine fuel may be biogas, however, follows to the same limitations as ethanol - the same production process is used and raw materials. Most essential fuel in the campaign of environment protection against pollution is natural gas. Natural gas as fuel may be either compressed (CNG) or liquefied (LNG). Natural gas can also be used for hydrogen production in steam reforming. Hydrogen can be used as a basic starting material for the chemical industry, an important raw material in the refinery processes, as well as a fuel vehicle transportation. Natural gas can be used as CNG which represents an excellent compromise between the availability of the technology that is proven and relatively cheap to use in many areas of the automotive industry. Natural gas can also be seen as an important bridge to other alternative sources of energy derived from fuel and harmless to the environment. For these reasons CNG as a fuel stimulates considerable interest in the worldwide.

Keywords: alternative fuels, CNG (Compressed Natural Gas), LNG (Liquefied Natural Gas), NGVs (Natural Gas Vehicles)

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Authors: Armineh Nourbakhsh, Sameena Shah, Carolyn Rose

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Layout-aware language models have been used to create multimodal representations for documents that are in image form, achieving relatively high accuracy in document understanding tasks. However, the large number of parameters in the resulting models makes building and using them prohibitive without access to high-performing processing units with large memory capacity. We propose an alternative approach that can create efficient representations without the need for a neural visual backbone. This leads to an 80% reduction in the number of parameters compared to the smallest SOTA model, widely expanding applicability. In addition, our layout embeddings are pre-trained on spatial and visual cues alone and only fused with text embeddings in downstream tasks, which can facilitate applicability to low-resource of multi-lingual domains. Despite using 2.5% of training data, we show competitive performance on two form understanding tasks: semantic labeling and link prediction.

Keywords: layout understanding, form understanding, multimodal document understanding, bias-augmented attention

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Authors: Jihyun Song, Kyeongjoo Kim, Minsoo Lee

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Due to the development of information technology and wireless Internet technology, various data are being generated in various fields. These data are advantageous in that they provide real-time information to the users themselves. However, when the data are accumulated and analyzed, more various information can be extracted. In addition, development and dissemination of boards such as Arduino and Raspberry Pie have made it possible to easily test various sensors, and it is possible to collect sensor data directly by using database application tools such as MySQL. These directly collected data can be used for various research and can be useful as data for data mining. However, there are many difficulties in using the board to collect data, and there are many difficulties in using it when the user is not a computer programmer, or when using it for the first time. Even if data are collected, lack of expert knowledge or experience may cause difficulties in data analysis and visualization. In this paper, we aim to construct a library for sensor data collection and analysis to overcome these problems.

Keywords: clustering, data mining, DBSCAN, k-means, k-medoids, sensor data

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Authors: Yiea Funk Te, Daniel Mueller, Irena Pletikosa Cvijikj

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Small and medium enterprises (SMEs) play an important role in the economy of many countries. When the overall world economy is considered, SMEs represent 95% of all businesses in the world, accounting for 66% of the total employment. Existing studies show that the current business environment is characterized as highly turbulent and strongly influenced by modern information and communication technologies, thus forcing SMEs to experience more severe challenges in maintaining their existence and expanding their business. To support SMEs at improving their competitiveness, researchers recently turned their focus on applying data mining techniques to build risk and growth prediction models. However, data used to assess risk and growth indicators is primarily obtained via questionnaires, which is very laborious and time-consuming, or is provided by financial institutes, thus highly sensitive to privacy issues. Recently, web mining (WM) has emerged as a new approach towards obtaining valuable insights in the business world. WM enables automatic and large scale collection and analysis of potentially valuable data from various online platforms, including companies’ websites. While WM methods have been frequently studied to anticipate growth of sales volume for e-commerce platforms, their application for assessment of SME risk and growth indicators is still scarce. Considering that a vast proportion of SMEs own a website, WM bears a great potential in revealing valuable information hidden in SME websites, which can further be used to understand SME risk and growth indicators, as well as to enhance current SME risk and growth prediction models. This study aims at developing an automated system to collect business-relevant data from the Web and predict future growth trends of SMEs by means of WM and data mining techniques. The envisioned system should serve as an 'early recognition system' for future growth opportunities. In an initial step, we examine how structured and semi-structured Web data in governmental or SME websites can be used to explain the success of SMEs. WM methods are applied to extract Web data in a form of additional input features for the growth prediction model. The data on SMEs provided by a large Swiss insurance company is used as ground truth data (i.e. growth-labeled data) to train the growth prediction model. Different machine learning classification algorithms such as the Support Vector Machine, Random Forest and Artificial Neural Network are applied and compared, with the goal to optimize the prediction performance. The results are compared to those from previous studies, in order to assess the contribution of growth indicators retrieved from the Web for increasing the predictive power of the model.

Keywords: data mining, SME growth, success factors, web mining

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Authors: Syed Iftikhar Hussain Shah, Vasilis Peristeras, Ioannis Magnisalis

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Organizations, including governments, generate (big) data that are high in volume, velocity, veracity, and come from a variety of sources. Public Administrations are using (big) data, implementing base registries, and enforcing data sharing within the entire government to deliver (big) data related integrated services, provision of insights to users, and for good governance. Government (Big) data ecosystem actors represent distinct entities that provide data, consume data, manipulate data to offer paid services, and extend data services like data storage, hosting services to other actors. In this research work, we perform a systematic literature review. The key objectives of this paper are to propose a robust definition of government (big) data ecosystem and a classification of government (big) data ecosystem actors and their roles. We showcase a graphical view of actors, roles, and their relationship in the government (big) data ecosystem. We also discuss our research findings. We did not find too much published research articles about the government (big) data ecosystem, including its definition and classification of actors and their roles. Therefore, we lent ideas for the government (big) data ecosystem from numerous areas that include scientific research data, humanitarian data, open government data, industry data, in the literature.

Keywords: big data, big data ecosystem, classification of big data actors, big data actors roles, definition of government (big) data ecosystem, data-driven government, eGovernment, gaps in data ecosystems, government (big) data, public administration, systematic literature review

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Authors: Melik Kara, Gulsah Tulger Kara

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The soil is a crucial component of the ecosystem, and in industrial and urban areas it receives large amounts of trace elements from several sources. Therefore, accumulated pollutants in surface soils can be transported to different environmental components, such as deep soil, water, plants, and dust particles. While elemental contamination of soils is caused mainly by atmospheric deposition, soil also affects the air quality since enriched trace elemental contents in atmospheric particulate matter originate from resuspension of polluted soils. The objectives of this study were to determine the total and leachate concentrations of trace elements in soils of city area in Izmir and characterize their spatial distribution and to identify the possible sources of trace elements in surface soils. The surface soil samples were collected from 20 sites. They were analyzed for total element concentrations and leachate concentrations. Analyses of trace elements (Ag, Al, As, B, Ba, Be, Bi, Ca, Cd, Ce, Co, Cr, Cs, Cu, Dy, Er, Eu, Fe, Ga, Gd, Hf, Ho, K, La, Li, Lu, Mg, Mn, Mo, Na, Nd, Ni, P, Pb, Pr, Rb, Sb, Sc, Se, Si, Sm, Sn, Sr, Tb, Th, Ti, Tl, Tm, U, V, W, Y, Yb, Zn and Zr) were carried out using ICP-MS (Inductively Coupled Plasma-Mass Spectrometer). The elemental concentrations were calculated along with overall median, kurtosis, and skewness statistics. Elemental composition indicated that the soil samples were dominated by crustal elements such as Si, Al, Fe, Ca, K, Mg and the sea salt element, Na which is typical for Aegean region. These elements were followed by Ti, P, Mn, Ba and Sr. On the other hand, Zn, Cr, V, Pb, Cu, and Ni (which are anthropogenic based elements) were measured as 61.6, 39.4, 37.9, 26.9, 22.4, and 19.4 mg/kg dw, respectively. The leachate element concentrations were showed similar sorting although their concentrations were much lower than total concentrations. In the study area, the spatial distribution patterns of elemental concentrations varied among sampling sites. The highest concentrations were measured in the vicinity of industrial areas and main roads. To determine the relationships among elements and to identify the possible sources, PCA (Principal Component Analysis) was applied to the data. The analysis resulted in six factors. The first factor exhibited high loadings of Co, K, Mn, Rb, V, Al, Fe, Ni, Ga, Se, and Cr. This factor could be interpreted as residential heating because of Co, K, Rb, and Se. The second factor associated positively with V, Al, Fe, Na, Ba, Ga, Sr, Ti, Se, and Si. Therefore, this factor presents mixed city dust. The third factor showed high loadings with Fe, Ni, Sb, As, Cr. This factor could be associated with industrial facilities. The fourth factor associated with Cu, Mo, Zn, Sn which are the marker elements of traffic. The fifth factor presents crustal dust, due to its high correlation with Si, Ca, and Mg. The last factor is loaded with Pb and Cd emitted from industrial activities.

Keywords: trace elements, surface soil, source apportionment, Izmir

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Authors: Trupti Diwan

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Predicting student failure at school has changed into a difficult challenge due to both the large number of factors that can affect the reduced performance of students and the imbalanced nature of these kinds of data sets. This paper surveys the two elements needed to make prediction on Students’ Academic Performances which are parameters and methods. This paper also proposes a framework for predicting the performance of engineering students. Genetic programming can be used to predict student failure/success. Ranking algorithm is used to rank students according to their credit points. The framework can be used as a basis for the system implementation & prediction of students’ Academic Performance in Higher Learning Institute.

Keywords: classification, educational data mining, student failure, grammar-based genetic programming

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Authors: Parul Goel, Jyeshtharaj B. Joshi, Arun K. Nayak

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Nucleate boiling is characterized by the nucleation, growth and departure of the tiny individual vapor bubbles that originate in the cavities or imperfections present in the heating surface. It finds a wide range of applications, e.g. in heat exchangers or steam generators, core cooling in power reactors or rockets, cooling of electronic circuits, owing to its highly efficient transfer of large amount of heat flux over small temperature differences. Hence, it is important to be able to predict the rate of heat transfer and the safety limit heat flux (critical heat flux, heat flux higher than this can lead to damage of the heating surface) applicable for any given system. A large number of experimental and analytical works exist in the literature, and are based on the idea that the knowledge of the bubble dynamics on the microscopic scale can lead to the understanding of the full picture of the boiling heat transfer. However, the existing data in the literature are scattered over various sets of conditions and often in disagreement with each other. The correlations obtained from such data are also limited to the range of conditions they were established for and no single correlation is applicable over a wide range of parameters. More recently, a number of researchers have been trying to remove empiricism in the heat transfer models to arrive at more phenomenological models using extensive numerical simulations; these models require state-of-the-art experimental data for a wide range of conditions, first for input and later, for their validation. With this idea in mind, experiments with sub-cooled and saturated demineralized water have been carried out under atmospheric pressure to study the bubble dynamics- growth rate, departure size and frequencies for nucleate pool boiling. A number of heating elements have been used to study the dependence of vapor bubble dynamics on the heater surface finish and heater geometry along with the experimental conditions like the degree of sub-cooling, super heat and the heat flux. An attempt has been made to compare the data obtained with the existing data and the correlations in the literature to generate an exhaustive database for the pool boiling conditions.

Keywords: experiment, boiling, bubbles, bubble dynamics, pool boiling

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Authors: Guowei Hou, Lixin Yu, Wei Zhuang, Hui Qin, Xue Yang

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Formal verification is proposed to ensure the correctness of the design and make functional verification more efficient. As cache plays a vital role in the design of System on Chip (SoC), and cache with Memory Management Unit (MMU) and cache memory unit makes the state space too large for simulation to verify, then a formal verification is presented for such system design. In the paper, a formal model checking verification flow is suggested and a new cache memory model which is called “exhaustive search model” is proposed. Instead of using large size ram to denote the whole cache memory, exhaustive search model employs just two cache blocks. For cache system contains data cache (Dcache) and instruction cache (Icache), Dcache memory model and Icache memory model are established separately using the same mechanism. At last, the novel model is employed to the verification of a cache which is module of a custom-built SoC system that has been applied in practical, and the result shows that the cache system is verified correctly using the exhaustive search model, and it makes the verification much more manageable and flexible.

Keywords: cache system, formal verification, novel model, system on chip (SoC)

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Authors: Ayşin Sev, Görkem Aslan

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Sustainable tall buildings that provide comfortable, healthy and efficient indoor environments are clearly desirable as the densification of living and working space for the world’s increasing population proceeds. For environmental concerns, these buildings must also be energy efficient. One component of these tasks is the provision of indoor air quality and thermal comfort, which can be enhanced with natural ventilation by the supply of fresh air. Working spaces can only be naturally ventilated with connections to the outdoors utilizing operable windows, double facades, ventilation stacks, balconies, patios, terraces and skygardens. Large amounts of fresh air can be provided to the indoor spaces without mechanical air-conditioning systems, which are widely employed in contemporary tall buildings. This paper tends to present the concept of natural ventilation for sustainable tall office buildings in order to achieve healthy and comfortable working spaces, as well as energy efficient environments. Initially the historical evolution of ventilation strategies for tall buildings is presented, beginning with natural ventilation and continuing with the introduction of mechanical air-conditioning systems. Then the emergence of natural ventilation due to the health and environmental concerns in tall buildings is handled, and the strategies for implementing this strategy are revealed. In the next section, a number of case studies that utilize this strategy are investigated. Finally, how tall office buildings can benefit from this strategy is discussed.

Keywords: tall office building, energy efficiency, double-skin façade, stack ventilation, air conditioning

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Authors: Xi Gu, Guan Heng Yeoh, Victoria Timchenko

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In the current work, a three-dimensional geometry of a 75% stenosed blood vessel is analysed. Large eddy simulation (LES) with the help of a dynamic subgrid scale Smagorinsky model is applied to model the turbulent pulsatile flow. The geometry, the transmural pressure and the properties of the blood and the elastic boundary were based on clinical measurement data. For the flexible wall model, a thin solid region is constructed around the 75% stenosed blood vessel. The deformation of this solid region was modelled as a deforming boundary to reduce the computational cost of the solid model. Fluid-structure interaction is realised via a two-way coupling between the blood flow modelled via LES and the deforming vessel. The information of the flow pressure and the wall motion was exchanged continually during the cycle by an arbitrary lagrangian-eulerian method. The boundary condition of current time step depended on previous solutions. The fluctuation of the velocity in the post-stenotic region was analysed in the study. The axial velocity at normalised position Z=0.5 shows a negative value near the vessel wall. The displacement of the elastic boundary was concerned in this study. In particular, the wall displacement at the systole and the diastole were compared. The negative displacement at the stenosis indicates a collapse at the maximum velocity and the deceleration phase.

Keywords: Large Eddy Simulation, Fluid Structural Interaction, constricted artery, Computational Fluid Dynamics

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Authors: Rivindu Nethmin Bandara Menik Hitihamy Mudiyanselage, Matthias Hank Haeusler, Ben Doherty

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Investors and clients in the Architectural, Engineering and Construction industry find it difficult to understand complex datasets and reports with little to no graphic representation. The stakeholders examined in this paper include designers, design clients and end-users. Communicating embodied carbon information graphically and concisely can aid with decision support early in a building's life cycle. It is essential to create a common visualisation approach as the level of knowledge about embodied carbon varies between stakeholders. The tool, designed in conjunction with Bates Smart, condenses Tally Life Cycle Assessment data to a carbon hot-spotting visualisation, highlighting the sections with the highest amounts of embodied carbon. This allows stakeholders at every stage of a given project to have a better understanding of the carbon implications with minimal effort. It further allows stakeholders to differentiate building elements by their carbon values, which enables the evaluation of the cost-effectiveness of the selected materials at an early stage. To examine and build a decision-support tool, an action-design research methodology of cycles of iterations was used along with precedents of embodied carbon visualising tools. Accordingly, the importance of visualisation and Building Information Modelling are also explored to understand the best format for relaying these results.

Keywords: embodied carbon, visualisation, summarisation, data filtering, early-stage decision-making, materiality

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Authors: Rei-Heng Cheng, Wen-Pinn Fang

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A wireless sensor network (WSN) is composed by a large number of sensors and one or a few base stations, where the sensor is responsible for detecting specific event information, which is sent back to the base station(s). However, how to save electricity consumption to extend the network lifetime is a problem that cannot be ignored in the wireless sensor networks. Since the sensor network is used to monitor a region or specific events, how the information can be reliably sent back to the base station is surly important. Network coding technique is often used to enhance the reliability of the network transmission. When a node needs to send out M data packets, it encodes these data with redundant data and sends out totally M + R packets. If the receiver can get any M packets out from these M + R packets, it can decode and get the original M data packets. To transmit redundant packets will certainly result in the excess energy consumption. This paper will explore relationship between the quality of wireless transmission and the number of redundant packets. Hopefully, each sensor can overhear the nearby transmissions, learn the wireless transmission quality around it, and dynamically determine the number of redundant packets used in network coding.

Keywords: energy consumption, network coding, transmission reliability, wireless sensor networks

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Authors: Juan A. Ferriz-Papi, Simon Thomas

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The construction industry generates large amounts of waste, usually mixed, which can be composed of different origin materials, most of them catalogued as non-hazardous. The European Union targets for this waste for 2020 have been already achieved by the UK, but it is mainly developed in downcycling processes (backfilling) whereas upcycling (such as recycle in new concrete batches) still keeps at a low percentage. The aim of this paper is to explore further in the use of recycled aggregates from construction and demolition waste (CDW) in concrete mixes so as to improve upcycling. A review of most recent research and legislation applied in the UK is developed regarding the production of concrete blocks. As a case study, initial tests were developed with a CDW recycled aggregate sample from a CDW plant in Swansea. Composition by visual inspection and sieving tests of two samples were developed and compared to original aggregates. More than 70% was formed by soil waste from excavation, and the rest was a mix of waste from mortar, concrete, and ceramics with small traces of plaster, glass and organic matter. Two concrete mixes were made with 80% replacement of recycled aggregates and different water/cement ratio. Tests were carried out for slump, absorption, density and compression strength. The results were compared to a reference sample and showed a substantial reduction of quality in both mixes. Despite that, the discussion brings to identify different aspects to solve, such as heterogeneity or composition, and analyze them for the successful use of these recycled aggregates in the production of concrete blocks. The conclusions obtained can help increase upcycling processes ratio with mixed CDW as recycled aggregates in concrete mixes.

Keywords: aggregates, concrete, concrete block, construction and demolition waste, recycling

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Authors: Alma Orucevic-Alagic, Martin Höst

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Open source communities have demonstrated that complex and enterprise grade software can be produced, supported, and maintained by self-organizing groups of developers using primarily electronic form of communication. Due to the inherent nature of open source development, a specific set of open source software development practices has evolved. While there is an ongoing research on the topic of applicability of open source development practices within a company setting, still little is known about their benefits and challenges. The objective of this research is to understand if and to what degree open source development practices observed within a mature open source community are aligned with development practices within a large software and hardware company setting. For the purpose of this case study a set of open source development practices that are present in a mature open source community has been identified. Then, development practices of a large, international, hardware and software company based in Sweden were assessed and compared to the identified open source community practices. It is shown that there are many similarities between a mature open source community and a large company setting in regard to software development practices. We also identify practices that exist in open source communities and that are not standard within a company setting, but whose implementation can result in an improved software development efficiency within the company setting.

Keywords: development practices, open source software, innersource, closed open source

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Authors: Tingting Zhou

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The partial privatization of state-owned enterprises (SOEs) is a dynamic process. The main features of this process lie in not only gradual and sequential privatizations, but also privatized shares transfer. For partially privatized SOEs, the introduction of private sector ownership is not the end of the story because the previously introduced private owners may choose to leave the SOEs by transferring the privatized shares after privatization, a process that is called “privatized shares transfer”. This paper investigates the determinants of privatized shares transfer from the perspective of large shareholders’ control rights. The results captures the fact that the higher control rights of large shareholders lead to more privatized shares transfer. After exploring the impacts of excessive control rights, the results provide evidence supporting the idea that firms with excessive numbers of directors, senior managers or supervisors who also have positions in the largest controlling shareholder’s entity are more likely to transfer privatized shares owned by private owners. In addition, the largest shareholders’ ownership also plays a role in privatized shares transfer. This evidence suggests that the large shareholders’ control rights should be limited to an appropriate range during the process of privatization, thereby giving private shareholders more opportunity to participate in the operation of firms, strengthen the state and enhance the competitiveness of state capital.

Keywords: control rights of large shareholders, partial privatization, privatized shares transfer, state-owned listed companies

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Authors: A. E. Dumitriu

Abstract:

The LHCb experiment is situated at one of the four points around CERN’s Large Hadron Collider, being a single-arm forward spectrometer covering 10 mrad to 300 (250) mrad in the bending (non-bending) plane, designed primarily to study particles containing b and c quarks. Each one of LHCb’s sub-detectors specializes in measuring a different characteristic of the particles produced by colliding protons, its significant detection characteristics including a high precision tracking system and 2 ring-imaging Cherenkov detectors for particle identification. The major two topics that I am currently concerned in are: the RIVET project (Robust Independent Validation of Experiment and Theory) which is an efficient and portable tool kit of C++ class library useful for validation and tuning of Monte Carlo (MC) event generator models by providing a large collection of standard experimental analyses useful for High Energy Physics MC generator development, validation, tuning and regression testing and V0 analysis for 2013 LHCb NoBias type data (trigger on bunch + bunch crossing) at √s=2.76 TeV.

Keywords: LHCb physics, RIVET plug-in, RIVET, CERN

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Authors: Won Il Jung, Gene Lee, Luis Rabelo

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Since many weapon systems are getting more complex and diverse, various problems occur in terms of the acquisition cost, time, and performance limitation. As a matter of fact, the experiment execution in real world is costly, dangerous, and time-consuming to obtain Required Operational Characteristics (ROC) for a new weapon acquisition although enhancing the fidelity of experiment results. Also, until presently most of the research contained a large amount of assumptions so therefore a bias is present in the experiment results. At this moment, the new methodology is proposed to solve these problems without a variety of assumptions. ROC of the new weapon system is developed through the new methodology, which is a way to analyze big data generated by simulating various scenarios based on virtual and constructive models which are involving 6 Degrees of Freedom (6DoF). The new methodology enables us to identify unbiased ROC on new weapons by reducing assumptions and provide support in terms of the optimal weapon systems acquisition.

Keywords: big data, required operational characteristics (ROC), virtual and constructive models, weapon acquisition

Procedia PDF Downloads 274