Search results for: parallel data mining

Authors: Saadoun Abd Errazak, Hafssaoui Abdallah, Fredj Mohamed

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Mining operations open induce risks of instability that can cause landslides and collapse at the bleachers slope. These risks may occur both during and after the operation phase. The magnitude of these risks depends on the mechanical and physical characteristics of the rock mass, the geometrical dimensions of ore bodies, their spatial arrangement, and the state of the operated area. If security and technology measures are not taken into account for this purpose, the environment will be affected. The main objective of this work is to assess these risks by analytical and numerical methods. The study is based on the geological, hydrogeological and geotechnical rock mass of the open pit quarry of Chouf Amar M'sila. The results obtained have allowed us to obtain an acceptable factor of safety and stability study of the open pit.

Keywords: stability, land sliding, numerical modeling, safety factor, open-pit quarry

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Authors: Ebrahim Asadi-Gangraj

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Hybrid flow shop scheduling problem (HFS) contains sequencing in a flow shop where, at any stage, there exist one or more related or unrelated parallel machines. This production system is a common manufacturing environment in many real industries, such as the steel manufacturing, ceramic tile manufacturing, and car assembly industries. In this research, a mixed integer linear programming (MILP) model is presented for the hybrid flow shop scheduling problem, in which, the objective consists of minimizing the maximum completion time (makespan). For this purpose, a Benders Decomposition (BD) method is developed to solve the research problem. The proposed approach is tested on some test problems, small to moderate scale. The experimental results show that the Benders decomposition approach can solve the hybrid flow shop scheduling problem in a reasonable time, especially for small and moderate-size test problems.

Keywords: hybrid flow shop, mixed integer linear programming, Benders decomposition, makespan

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Authors: Amara Rafik, Bougherara Maamar, Belhadj Aissa Mostefa

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Radar data is one of the many data sources used by ATM Air Traffic Management systems. These data come from air navigation radar antennas. These radars intercept signals emitted by the various aircraft crossing the controlled airspace and calculate the position of these aircraft and retransmit their positions to the Air Traffic Management System. For greater reliability, these radars are positioned in such a way as to allow their coverage areas to overlap. An aircraft will therefore be detected by at least one of these radars. However, the position coordinates of the same aircraft and sent by these different radars are not necessarily identical. Therefore, the ATM system must calculate a single position (radar track) which will ultimately be sent to the control position and displayed on the air traffic controller's monitor. There are several techniques for calculating the radar track. Furthermore, the geographical nature of the problem requires the use of a Geographic Information System (GIS), i.e. a geographical database on the one hand and geographical processing. The objective of this work is to propose a GIS for traffic simulation which reconstructs the evolution over time of aircraft positions from a multi-source radar data set and by applying these different techniques.

Keywords: ATM, GIS, radar data, air traffic simulation

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Authors: Amir Hossein Ghaffari Nejad, Forouhar Ferdowsi, Reza Mashhadi

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In the interest-free banking system of Iran, the savings of society are in the form of bank deposits, and banks using the Islamic contracts, allocate the resources to applicants for obtaining facilities and credit. In the meantime, the central bank, with the aim of introducing monetary policy, determines the maximum interest rate on bank deposits in terms of macroeconomic requirements. But in recent years, the country's economic constraints with the stagflation and the consequence of the institutional weaknesses of the financial market of Iran have resulted in massive disturbances in the balance sheet of the banking system, resulting in a period of mismatch maturity in the banks' assets and liabilities and the implementation of a Ponzi game. This issue caused determination of the interest rate in long-term bank deposit contracts to be associated with non-observance of the maximum rate set by the central bank. The result of this condition was in the allocation of new sources of equipment to meet past commitments towards the old depositors and, as a result, a significant part of the supply of equipment was leaked out of the facilitating cycle and credit crunch emerged. The purpose of this study is to identify the most important factors affecting the occurrence of non-confirmatory financial banking behavior using data from 19 public and private banks of Iran. For this purpose, the causes of this non-confirmatory behavior of banks have been investigated using the panel vector autoregression method (PVAR) for the period of 2007-2015. Granger's causality test results suggest that the return of parallel markets for bank deposits, non-performing loans and the high share of the ratio of facilities to banks' deposits are all a cause of the formation of non-confirmatory behavior. Also, according to the results of impulse response functions and variance decomposition, NPL and the ratio of facilities to deposits have the highest long-term effect and also have a high contribution to explaining the changes in banks' non-confirmatory behavior in determining the interest rate on deposits.

Keywords: non-conformity behavior, Ponzi Game, panel vector autoregression, nonperforming loans

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Authors: Radhia Toujani, Jalel Akaichi

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Social Networks generally present a hierarchy of communities. To determine these communities and the relationship between them, detection algorithms should be applied. Most of the existing algorithms, proposed for hierarchical communities identification, are based on either agglomerative clustering or divisive clustering. In this paper, we present a hybrid hierarchical clustering approach for community detection based on both bottom-up and bottom-down clustering. Obviously, our approach provides more relevant community structure than hierarchical method which considers only divisive or agglomerative clustering to identify communities. Moreover, we performed some comparative experiments to enhance the quality of the clustering results and to show the effectiveness of our algorithm.

Keywords: agglomerative hierarchical clustering, community structure, divisive hierarchical clustering, hybrid hierarchical clustering, opinion mining, social network, social network analysis

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Authors: Sukla Saha, Alok Sinha

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Acid mine drainage (AMD) refers to the production of acidified water from abandoned mines and active mines as well. The reason behind the generation of this kind of acidified water is the oxidation of pyrites present in the rocks in and around mining areas. Thiobacillus ferrooxidans, which is a sulfur oxidizing bacteria, helps in the oxidation process. AMD is extremely acidic in nature, (pH 2-3) with high concentration of several trace and heavy metals such as Fe, Al, Zn, Mn, Cu and Co and anions such as chloride and sulfate. AMD has several detrimental effect on aquatic organism and environment. It can directly or indirectly contaminate the ground water and surface water as well. The present study considered the treatment of AMD with metallurgical slag, which is a waste material. Slag helped to enhance the pH of AMD to 8.62 from 1.5 with 99% removal of trace metals such as Fe, Al, Mn, Cu and Co. Metallurgical slag was proven as efficient neutralizing material for the treatment of AMD.

Keywords: acid mine drainage, Heavy metals, metallurgical slag, Neutralization

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Authors: Christian Kapuku, Seung-Young Kho

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An accurate representation of the transportation system serving the region is one of the important aspects of transportation modeling. Such representation often requires developing an abstract model of the system elements, which also requires important amount of data, surveys and time. However, in some cases such as in developing countries, data deficiencies, time and budget constraints do not always allow such accurate representation, leaving opportunities to assumptions that may negatively affect the quality of the analysis. With the emergence of Internet open source data especially in the mapping technologies as well as the advances in Geography Information System, opportunities to tackle these issues have raised. Therefore, the objective of this paper is to demonstrate such application through a practical case of the development of the transportation network for the city of Kinshasa. The GIS geo-referencing was used to construct the digitized map of Transportation Analysis Zones using available scanned images. Centroids were then dynamically placed at the center of activities using an activities density map. Next, the road network with its characteristics was built using OpenStreet data and other official road inventory data by intersecting their layers and cleaning up unnecessary links such as residential streets. The accuracy of the final network was then checked, comparing it with satellite images from Google and Bing. For the validation, the final network was exported into Emme3 to check for potential network coding issues. Results show a high accuracy between the built network and satellite images, which can mostly be attributed to the use of open source data.

Keywords: geographic information system (GIS), network construction, transportation database, open source data

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Authors: G. Farkas, K. Mathis, J. Pilch, P. Minarik

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Deformation mechanisms in an Mg-Al-Ca alloy reinforced with short alumina fibres were studied by acoustic emission and in-situ neutron diffraction method. The fibres plane orientation with respect to the loading axis was found to be a key parameter, which influences the acting deformation processes, such as twinning or dislocation slip. In-situ neutron diffraction tests were measured at different temperatures from room temperature (RT) to 200°C. The measurement shows the lattice strain changes in the matrix and also in the reinforcement phase depending on macroscopic compressive deformation and stress. In case of parallel fibre plane orientation, the increment of compressive lattice strain is lower in the matrix and higher in the fibres in comparison to perpendicular fibre orientation. Furthermore, acoustic emission results indicate a larger twinning activity and more frequent fibre cracking in sample with perpendicular fibre plane orientation. Both types of mechanisms are more dominant at elevated temperatures.

Keywords: neutron diffraction, acoustic emission, magnesium based composite, deformation mechanisms

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Authors: Avishkar Gawade, Omkar Bansode, Ketan Bhambure, Bhargav Deore

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In recent year wide range of business intelligence technology have been applied to different area in order to support decision making process BI enables extraction of knowledge from data store. BI tools usually used in public health field for financial and administrative purposes.BI uses a dashboard in presentation stage to deliver information to information to end users.In this paper,we intend to analyze some open source BI tools on the market and their applicability in the clinical sphere taking into consideration the general characteristics of the clinical environment.A pervasive BI platform was developed using a real case in order to prove the tool viability.Analysis of various BI Tools in done with the help of several parameters such as data security,data integration,data quality reporting and anlaytics,performance,scalability and cost effectivesness.

Keywords: CDSS, EHR, business intelliegence, tools

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Authors: Ahmad K. Samaila, Basant K. Jha

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This study is devoted to investigate the effect of transpiration on transient as well as steady-state natural convection flow of a reactive viscous fluid in a vertical channel formed by two infinite vertical parallel porous plates. The Boussinesq assumption is applied and the nonlinear governing equations of energy and momentum are developed. The problem is solved numerically using implicit finite difference method and analytically for steady-state case using perturbation method. Solutions are presented in graphical form for fluid temperature, velocity, and skin-friction and wall heat transfer rate for various parametric values. It is found that velocity, temperature, rate of heat transfer as well as skin-friction are strongly affected by mass leakage through the porous plates.

Keywords: transpiration, reactive viscous fluid, porous plates, natural convection, suction/injection

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Authors: Sen Tanmoy, Jain Sarika, Panda Jagabandhu

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The studies regarding the impact of urbanization using the WRF-ARW model rely heavily on the static geographical information selected, including domain configuration and land use land cover (LULC) data. Accurate representation of LULC data provides essential information for understanding urban growth and simulating meteorological parameters such as temperature, precipitation etc. Researchers are using different LULC data as per availability and their requirements. As far as India is concerned, we have very limited resources and data availability. So, it is important to understand how we can optimize our results using limited LULC data. In this review article, we explored how a LULC map is generated from different sources in the Indian context and what its significance is in WRF-ARW modeling to study urbanization/Climate change or any other meteorological parameters. Bibliometric analyses were also performed in this review article based on countries of study and indexed keywords. Finally, some key points are marked out for selecting the most suitable LULC map for any urbanization-related study.

Keywords: LULC, LULC mapping, LANDSAT, WRF-ARW, ISRO, bibliometric Analysis.

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Authors: Lenka Matulova

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Geopolymers are alumosilicate materials that have long been studied. Despite this fact, little is known about the long-term stability of geopolymer mechanical and structural properties, so crucial for their successful industrial application. To improve understanding, we investigated the effect of four different types of environments on the mechanical and structural properties of a metakaolin-based geopolymer (MK GP). The MK GP samples were stored in laboratory conditions (control samples), in water at 20 °C, in water at 80 °C, and outside exposed to the weather. Compressive and tensile strengths were measured after 28, 56, 90, and 360 days. In parallel, structural properties were analyzed using XRD, SEM, and mercury intrusion porosimetry. Whereas the mechanical properties of the samples in laboratory conditions and in 20 °C water were stable, the mechanical properties of the outdoor samples and the samples 80 °C water decreased noticeably after 360 days. Structural analyses were focused on changes in sample microstructure (developing microcrack network, porosity) and identifying zeolites, the presence of which would indicate detrimental processes in the structure that can change it from amorphous to crystalline. No zeolites were found during the 360-day period in MK GP samples, but the reduction in mechanical properties coincided with a developing network of microcracks and changes in pore size distribution.

Keywords: geopolymer, long-term properties, mechanical properties, metakaolin, structural properties

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Authors: Mikel Niño, Roberto V. Zicari, Todor Ivanov, Kim Hee, Naveed Mushtaq, Marten Rosselli, Concha Sánchez-Ocaña, Karsten Tolle, José Miguel Blanco, Arantza Illarramendi, Jörg Besier, Harry Underwood

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One of the application fields for data analysis techniques and technologies gaining momentum is the area of social good or “common good”, covering cases related to humanitarian crises, global health care, or ecology and environmental issues, among others. The promotion of data-driven projects in this field aims at increasing the efficacy and efficiency of social initiatives, improving the way these actions help humanity in general and people in need in particular. This application field, however, poses its own barriers and challenges when developing data-driven projects, lagging behind in comparison with other scenarios. These challenges derive from aspects such as the scope and scale of the social issue to solve, cultural and political barriers, the skills of main stakeholders and the technological resources available, the motivation to be engaged in such projects, or the ethical and legal issues related to sensitive data. This paper analyzes the application of data projects in the field of social good, reviewing its current state and noteworthy initiatives, and presenting a framework covering the key aspects to analyze in such projects. The goal is to provide guidelines to understand the main challenges and opportunities for this type of data project, as well as identifying the main differential issues compared to “classical” data projects in general. A case study is presented on the initial steps and stakeholder analysis of a data project for the inclusion of refugees in the city of Frankfurt, Germany, in order to empirically confront the framework with a real example.

Keywords: data-driven projects, humanitarian operations, personal and sensitive data, social good, stakeholders analysis

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Authors: Suren Chilingaryan

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We study two models describing a single two-level system coupled to two boson field modes in either a parallel or orthogonal setup. Both models may be feasible for experimental realization through Raman adiabatic driving in cavity QED. We study their ground state configurations; that is, we find the quantum precursors of the corresponding semi-classical phase transitions. We found that the ground state configurations of both models present the same critical coupling as the quantum Rabi model. Around this critical coupling, the ground state goes from the so-called normal configuration with no excitation, the qubit in the ground state and the fields in the quantum vacuum state, to a ground state with excitations, the qubit in a superposition of ground and excited state, while the fields are not in the vacuum anymore, for the first model. The second model shows a more complex ground state configuration landscape where we find the normal configuration mentioned above, two single-mode configurations, where just one of the fields and the qubit are excited, and a dual-mode configuration, where both fields and the qubit are excited.

Keywords: quantum optics, quantum phase transition, cavity QED, circuit QED

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Authors: Wanqing You, Kai Qian, Ying Qian

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The concepts of Cloud Computing provide users with infrastructure, platform and software as service, which make those services more accessible for people via Internet. To better analysis the performance of Cloud Computing provisioning policies as well as resources allocation strategies, a toolkit named CloudSim proposed. With CloudSim, the Cloud Computing environment can be easily constructed by modelling and simulating cloud computing components, such as datacenter, host, and virtual machine. A good scheduling strategy is the key to achieve the load balancing among different machines as well as to improve the utilization of basic resources. Recently, the existing scheduling algorithms may work well in some presumptive cases in a single machine; however they are unable to make the best decision for the unforeseen future. In real world scenario, there would be numbers of tasks as well as several virtual machines working in parallel. Based on the concepts of multi-queue, this paper presents a new scheduling algorithm to schedule tasks with CloudSim by taking into account several parameters, the machines’ capacity, the priority of tasks and the history log.

Keywords: hierarchical queue, load balancing, CloudSim, information technology

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Authors: Salah Alrabeei, Mohammad Yousuf

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The goal of option pricing theory is to help the investors to manage their money, enhance returns and control their financial future by theoretically valuing their options. However, most of the option pricing models have no analytical solution. Furthermore, not all the numerical methods are efficient to solve these models because they have nonsmoothing payoffs or discontinuous derivatives at the exercise price. In this paper, we solve the American option under jump diffusion models by using efficient time-dependent numerical methods. several techniques are integrated to reduced the overcome the computational complexity. Fast Fourier Transform (FFT) algorithm is used as a matrix-vector multiplication solver, which reduces the complexity from O(M2) into O(M logM). Partial fraction decomposition technique is applied to rational approximation schemes to overcome the complexity of inverting polynomial of matrices. The proposed method is easy to implement on serial or parallel versions. Numerical results are presented to prove the accuracy and efficiency of the proposed method.

Keywords: integral differential equations, jump–diffusion model, American options, rational approximation

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Authors: B. Y. Danjuma, A. Archibong-Eso, Aliyu M. Aliyu, H. Yeung

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In this experimental investigation, a new data for slugging frequency for high viscosity oil-gas flow are reported. Scale experiments were carried out using a mixture of air and mineral oil as the liquid phase in a 17 m long horizontal pipe with 0.0762 ID. The data set was acquired using two high-speed Gamma Densitometers at a data acquisition frequency of 250 Hz over a time interval of 30 seconds. For the range of flow conditions investigated, increase in liquid oil viscosity was observed to strongly influence the slug frequency. A comparison of the present data with prediction models available in the literature revealed huge discrepancies. A new correlation incorporating the effect of viscosity on slug frequency has been proposed for the horizontal flow, which represents the main contribution of this work.

Keywords: gamma densitometer, flow pattern, pressure gradient, slug frequency

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Authors: Tolga Hayit, Ucman Ergun, Ugur Fidan

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Being healthy is undoubtedly an indispensable necessity for human life. With technological improvements, in the literature, various health monitoring and imaging systems have been developed to satisfy your health needs. In this context, the work of monitoring and recording the data of individual health monitoring data via wireless technology is also being part of these studies. Nowadays, mobile devices which are located in almost every house and which become indispensable of our life and have wireless technology infrastructure have an important place of making follow-up health everywhere and every time because these devices were using in the health monitoring systems. In this study, Arduino an open-source microcontroller card was used in which a sample sugar measuring device was connected in series. In this way, the glucose data (glucose ratio, time) obtained with the glucometer is transferred to the mobile device based on the Android operating system with the Bluetooth technology channel. A mobile application was developed using the Apache Cordova framework for listing data, presenting graphically and reading data over Arduino. Apache Cordova, HTML, Javascript and CSS are used in coding section. The data received from the glucometer is stored in the local database of the mobile device. It is intended that people can transfer their measurements to their mobile device by using wireless technology and access the graphical representations of their data. In this context, the aim of the study is to be able to perform health monitoring by using different wireless technologies in mobile devices that can respond to different wireless technologies at present. Thus, that will contribute the other works done in this area.

Keywords: Arduino, Bluetooth, glucose measurement, mobile health monitoring

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Authors: Masood Roohi, Amir Taghavipour

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This paper describes a strategy to develop an energy management system (EMS) for a charge-sustaining power-split hybrid electric vehicle. This kind of hybrid electric vehicles (HEVs) benefit from the advantages of both parallel and series architecture. However, it gets relatively more complicated to manage power flow between the battery and the engine optimally. The applied strategy in this paper is based on nonlinear model predictive control approach. First of all, an appropriate control-oriented model which was accurate enough and simple was derived. Towards utilization of this controller in real-time, the problem was solved off-line for a vast area of reference signals and initial conditions and stored the computed manipulated variables inside look-up tables. Look-up tables take a little amount of memory. Also, the computational load dramatically decreased, because to find required manipulated variables the controller just needed a simple interpolation between tables.

Keywords: hybrid electric vehicles, energy management system, nonlinear model predictive control, real-time

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Authors: Natalia Kalinowska

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The adoption of the General Data Protection Regulation, (GDPR) finished the four-year work of the European Commission in this area in the European Union. Considering far-reaching changes, which will be applied by GDPR, the European legislator envisaged two-year transitional period. Member states and companies have to prepare for a new regulation until 25 of May 2018. The idea, which becomes a new look at an attitude to data protection in the European Union is risk-based approach. So far, as a result of implementation of Directive 95/46/WE, in many European countries (including Poland) there have been adopted very particular regulations, specifying technical and organisational security measures e.g. Polish implementing rules indicate even how long password should be. According to the new approach from May 2018, controllers and processors will be obliged to apply security measures adequate to level of risk associated with specific data processing. The risk in GDPR should be interpreted as the likelihood of a breach of the rights and freedoms of the data subject. According to Recital 76, the likelihood and severity of the risk to the rights and freedoms of the data subject should be determined by reference to the nature, scope, context and purposes of the processing. GDPR does not indicate security measures which should be applied – in recitals there are only examples such as anonymization or encryption. It depends on a controller’s decision what type of security measures controller considered as sufficient and he will be responsible if these measures are not sufficient or if his identification of risk level is incorrect. Data protection regulation indicates few levels of risk. Recital 76 indicates risk and high risk, but some lawyers think, that there is one more category – low risk/now risk. Low risk/now risk data processing is a situation when it is unlikely to result in a risk to the rights and freedoms of natural persons. GDPR mentions types of data processing when a controller does not have to evaluate level of risk because it has been classified as „high risk” processing e.g. processing on a large scale of special categories of data, processing with using new technologies. The methodology will include analysis of legal regulations e.g. GDPR, the Polish Act on the Protection of personal data. Moreover: ICO Guidelines and articles concerning risk based approach in GDPR. The main conclusion is that an appropriate risk assessment is a key to keeping data safe and avoiding financial penalties. On the one hand, this approach seems to be more equitable, not only for controllers or processors but also for data subjects, but on the other hand, it increases controllers’ uncertainties in the assessment which could have a direct impact on incorrect data protection and potential responsibility for infringement of regulation.

Keywords: general data protection regulation, personal data protection, privacy protection, risk based approach

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Authors: Kamel Barka, Lyamine Guezouli, Assem Rezki

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In this article, we propose a protocol called DataGA-DRF (a protocol for Data collection using a Genetic Algorithm through Dynamic Reference Points) that collects data from Heterogeneous wireless sensor networks. This protocol is based on DGA (Destination selection according to Genetic Algorithm) to control the movement of the UAV (Unmanned aerial vehicle) between dynamic reference points that virtually represent the sensor node deployment. The dynamics of these points ensure an even distribution of energy consumption among the sensors and also improve network performance. To determine the best points, DataGA-DRF uses a classification algorithm such as K-Means.

Keywords: heterogeneous wireless networks, unmanned aerial vehicles, reference point, collect data, genetic algorithm

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Authors: Zafer Ceylan, Gülgün F.Unal Şengör, Onur Gönülal

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In this study, sous vide technology were treated with different herbs into different fish species which were caught from northern Aegean and Marmara Sea. Before samples were packaged under vacuum, herbs had been cut and added at the same ratio into the package. Samples were sliced, the weight of each sample was about 150 g, and packaged under vacuum. During the storage period at 4ºC, taste, odor, texture properties of fish samples treated with sous vide were evaluated by trained panelists. Meanwhile, the effect of different herbs on pH values of the samples was investigated. These results were correlated with sensorial results. Furthermore, the effects of different herbs on L, a, b values of fish samples treated with sous vide were evaluated by color measurement. All sensorial results indicated that the values of samples treated with herbs were higher than that of the control group. Color measurement results and pH values were found parallel with sensorial results.

Keywords: Sous vide, fish, herbs, consumer preferences, pH, color measurement

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Authors: Yasser Elhenaw, A. Farag, Mohamed El-Ghandour, M. Shatat, G. H. Moustafa

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This study investigates the performance of two spiral-wound Air Gap Membrane Distillation (AGMD) units. These units are connected in two different configurations in order to be tested and compared experimentally. In AGMD, the coolant water is used to condensate water vapor leaving membrane via condensing plate. The rejected cooling water has a relativity high temperature which can be used, depending on operation parameters, to increase the thermal efficiency and water productivity. In the first configuration, the seawater feed flows parallel and equally through both units then rejected. The coolant water is divided into the two units, and the heat source is divided into the two heat exchangers. In the second one, only the feed of the first unit is heated while the cooling rejected from the unit is used in heating the feed to the second. The performance of the system, estimated by the water productivity as well as the Gain Output Ratio (GOR), is measured for the two configurations at different feed flow rates, temperatures and salinities. The results show that at steady state condition, the heat recovery configurations lead to an increase in water productivity by 25%.

Keywords: membrane distillation, heat transfer, heat recovery, desalination

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Authors: Shubham Bhonde, Nekzad Doctor, Shashwat Gawande

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For the use and the import of Keys and ID Transmitter as well as Body Control Modules with radio transmission in a lot of countries, homologation is required. Final deliverables in homologation of the product are certificates. In considering the world of homologation, there are approximately 200 certificates per product, with most of the certificates in local languages. It is challenging to manually investigate each certificate and extract relevant data from the certificate, such as expiry date, approval date, etc. It is most important to get accurate data from the certificate as inaccuracy may lead to missing re-homologation of certificates that will result in an incompliance situation. There is a scope of automation in reading the certificate data in the field of homologation. We are using deep learning as a tool for automation. We have first trained a model using machine learning by providing all country's basic data. We have trained this model only once. We trained the model by feeding pdf and jpg files using the ETL process. Eventually, that trained model will give more accurate results later. As an outcome, we will get the expiry date and approval date of the certificate with a single click. This will eventually help to implement automation features on a broader level in the database where certificates are stored. This automation will help to minimize human error to almost negligible.

Keywords: homologation, re-homologation, data science, deep learning, machine learning, ETL (extract transform loading)

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Authors: Sithandazile Masuku

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Introduction: Public health approaches to offender mental health are driven by international policies and frameworks in response to the disproportionately large representation of people with mental health problems within the offender pathway compared to the general population. Public health service innovations include mental health courts in the US, restorative models in Singapore and, liaison and diversion services in Australia, the UK, and some other European countries. Mental health nurses are at the forefront of offender health service innovations. In the U.K. context, police custody has been identified as an early point within the offender pathway where nurses can improve outcomes by offering assessments and share information with criminal justice partners. This scope of nursing practice has introduced challenges related to skills and support required for nurses working at the interface of health and the criminal justice system. Parallel literature exploring experiences of nurses working in forensic settings suggests the presence of compassion fatigue, burnout and vicarious trauma that may impede risk harm to the nurses in these settings. Published research explores mainly service-level outcomes including monitoring of figures indicative of a reduction in offending behavior. There is minimal research exploring the experiences of liaison and diversion nurses who are situated away from a supportive clinical environment and engaged in complex autonomous decision-making. Aim: This paper will share qualitative findings (in progress) from a PhD study that aims to explore the experiences of liaison and diversion nurses in one service in the U.K. Methodology: This is a qualitative interview study conducted using an Interpretative Phenomenological Analysis to gain an in-depth analysis of lived experiences. Methods: A purposive sampling technique was used to recruit n=8 mental health nurses registered with the UK professional body, Nursing and Midwifery Council, from one UK Liaison and Diversion service. All participants were interviewed online via video call using semi-structured interview topic guide. Data were recorded and transcribed verbatim. Data were analysed using the seven steps of the Interpretative Phenomenological Analysis data analysis method. Emerging Findings Analysis to date has identified pertinent themes: • Difficulties of meaning-making for nurses because of the complexity of their boundary spanning role. • Emotional burden experienced in a highly emotive and fast-changing environment. • Stress and difficulties with role identity impacting on individual nurses’ ability to be resilient. • Challenges to wellbeing related to a sense of isolation when making complex decisions. Conclusion Emerging findings have highlighted the lived experiences of nurses working in liaison and diversion as challenging. The nature of the custody environment has an impact on role identity and decision making. Nurses left feeling isolated and unsupported are less resilient and may go on to experience compassion fatigue. The findings from this study thus far point to a need to connect nurses working in these boundary spanning roles with a supportive infrastructure where the complexity of their role is acknowledged, and they can be connected with a health agenda. In doing this, the nurses would be protected from harm and the likelihood of sustained positive outcomes for service users is optimised.

Keywords: liaison and diversion, nurse experiences, offender health, staff wellbeing

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Authors: Kanchan Mondal, Dasharath Koulage, Dattatray Manerikar, Asmita Ghate

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This paper presents an additive reliability model using warranty data and Finite Element Analysis (FEA) data. Warranty data for any product gives insight to its underlying issues. This is often used by Reliability Engineers to build prediction model to forecast failure rate of parts. But there is one major limitation in using warranty data for prediction. Warranty periods constitute only a small fraction of total lifetime of a product, most of the time it covers only the infant mortality and useful life zone of a bathtub curve. Predicting with warranty data alone in these cases is not generally provide results with desired accuracy. Failure rate of a mechanical part is driven by random issues initially and wear-out or usage related issues at later stages of the lifetime. For better predictability of failure rate, one need to explore the failure rate behavior at wear out zone of a bathtub curve. Due to cost and time constraints, it is not always possible to test samples till failure, but FEA-Fatigue analysis can provide the failure rate behavior of a part much beyond warranty period in a quicker time and at lesser cost. In this work, the authors proposed an Additive Weibull Model, which make use of both warranty and FEA fatigue analysis data for predicting failure rates. It involves modeling of two data sets of a part, one with existing warranty claims and other with fatigue life data. Hazard rate base Weibull estimation has been used for the modeling the warranty data whereas S-N curved based Weibull parameter estimation is used for FEA data. Two separate Weibull models’ parameters are estimated and combined to form the proposed Additive Weibull Model for prediction.

Keywords: bathtub curve, fatigue, FEA, reliability, warranty, Weibull

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Authors: Sukrit Ghorai

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Proof of controlling crack width is a basic condition for securing suitable performance in serviceability limit state. The cracking in concrete can occur at any time from the casting of time to the years after the concrete has been set in place. Most codes struggle with offering procedure for crack width calculation. There is lack in availability of design charts for designers to compute crack width with ease. The focus of the study is to utilize design charts and parametric equations in calculating crack width with minimum error. The paper contains a simplified procedure to calculate crack width for reinforced concrete (RC) sections subjected to bending with axial tensile force following the guidelines of Euro code [DS EN-1992-1-1 & DS EN-1992-1-2]. Numerical examples demonstrate the application of the suggested procedure. Comparison with parallel analytical tools support the validity of result and show the percentage deviation of crack width in both the procedures. The technique is simple, user-friendly and ready to evolve for a greater spectrum of section sizes and materials.

Keywords: concrete structures, crack width calculation, serviceability limit state, structural design, bridge engineering

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Authors: Rajesh Bhatt, Dilip Kumar Maiti

Abstract:

The incompressible shear flow past a square cylinder placed parallel to a plane wall of side length A in presence of upstream rectangular cylinder of height 0.5A and width 0.25A in an inline tandem arrangement are numerically investigated using finite volume method. The discretized equations are solved by an implicit, time-marching, pressure correction based SIMPLE algorithm. This study provides the qualitative insight in to the dependency of basic structure (i.e. vortex shedding or suppression) of flow over the downstream square cylinder and the upstream rectangular cylinder (and hence the aerodynamic characteristics) on inter-cylinder spacing (S) and Reynolds number (Re). The spacing between the cylinders is varied systematically from S = 0.5A to S = 7.0A so the sensitivity of the flow structure between the cylinders can be inspected. A sudden jump in strouhal number is observed, which shows the transition of flow pattern in the wake of the cylinders. The results are presented at Re = 100 and 200 in term of Strouhal number, RMS and mean of lift and drag coefficients and contour plots for different spacing.

Keywords: square cylinder, vortex shedding, isolated, tandem arrangement, spacing distance

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Authors: Graciela Soares Marcelli, Elison Eduardo Jardim Bierhals, Luciane Teresa Salvi, Claudineia Brazil, Rafael Haag

Abstract:

The sun is a source of renewable energy, and its use as both a source of heat and light is one of the most promising energy alternatives for the future. To measure the thermal or photovoltaic systems a solar irradiation database is necessary. Brazil still has a reduced number of meteorological stations that provide frequency tests, as an alternative to the radio data platform, with reanalysis systems, quite significant. ERA-Interim is a global fire reanalysis by the European Center for Medium-Range Weather Forecasts (ECMWF). The data assimilation system used for the production of ERA-Interim is based on a 2006 version of the IFS (Cy31r2). The system includes a 4-dimensional variable analysis (4D-Var) with a 12-hour analysis window. The spatial resolution of the dataset is approximately 80 km at 60 vertical levels from the surface to 0.1 hPa. This work aims to make a comparative analysis between the ERA-Interim data and the data observed in the Solarimmetric Atlas of the State of Rio Grande do Sul, to verify its applicability in the absence of an observed data network. The analysis of the results obtained for a study region as an alternative to the energy potential of a given region.

Keywords: energy potential, reanalyses, renewable energy, solar radiation

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Authors: Vasantha Gouri Prathapagiri

Abstract:

Innovations in ICT sector facilitate qualitative life style for citizens across the globe. Countries that facilitate usage of new techniques in ICT, i.e., big data analytics find it easier to fulfil the needs of their citizens. Big data is characterised by its volume, variety, and speed. Analytics involves its processing in a cost effective way in order to draw conclusion for their useful application. Big data also involves into the field of machine learning, artificial intelligence all leading to accuracy in data presentation useful for public policy making. Hence using data analytics in public policy making is a proper way to march towards all round development of any country. The data driven insights can help the government to take important strategic decisions with regard to socio-economic development of her country. Developed nations like UK and USA are already far ahead on the path of digitization with the support of Big Data analytics. India is a huge country and is currently on the path of massive digitization being realised through Digital India Mission. Internet connection per household is on the rise every year. This transforms into a massive data set that has the potential to improvise the public services delivery system into an effective service mechanism for Indian citizens. In fact, when compared to developed nations, this capacity is being underutilized in India. This is particularly true for administrative system in rural areas. The present paper focuses on the need for big data analytics adaptation in Indian rural administration and its contribution towards development of the country on a faster pace. Results of the research focussed on the need for increasing awareness and serious capacity building of the government personnel working for rural development with regard to big data analytics and its utility for development of the country. Multiple public policies are framed and implemented for rural development yet the results are not as effective as they should be. Big data has a major role to play in this context as can assist in improving both policy making and implementation aiming at all round development of the country.

Keywords: Digital India Mission, public service delivery system, public policy, Indian administration

Procedia PDF Downloads 141