Search results for: thick data analytics

Authors: Rashi Bhalla, Russel Pears, M. Asif Naeem

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In this 'Information Explosion Era' analyzing data 'a critical commodity' and mining knowledge from vertically distributed data stream incurs huge communication cost. However, an effort to decrease the communication in the distributed environment has an adverse influence on the classification accuracy; therefore, a research challenge lies in maintaining a balance between transmission cost and accuracy. This paper proposes a method based on Bayesian inference to reduce the communication volume in a heterogeneous distributed environment while retaining prediction accuracy. Our experimental evaluation reveals that a significant reduction in communication can be achieved across a diverse range of dataset types.

Keywords: big data, bayesian inference, distributed data stream mining, heterogeneous-distributed data

Procedia PDF Downloads 140

Authors: N. Berrouachedi, M. Bouslama, S. Rioual, B. Lescop, J. Langlois

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Using first-principles calculations within the LSDA (Local Spin Density Approximation) method based on density functional theory (DFT), the electronic structure and magnetic properties of zinc blende Fe/In0.5Ga0.5As/InPsuperlattice are investigated. This compound are found to be half -metallic ferromagnets with a total magnetic moment of 2.25μB per Fe. In addition to this, we reported the DRX measurements of the thick iron sample before and after annealing. One should note, after the annealing treatment at a higher temperature, the disappearance of the peak associated to the Fe(001) plane. In contrast to this report, we observed after the annealing at low temperature the additional peaks attributed to the presence of indium and Fe2As. This suggests a subsequent process consisting in a strong migration of atoms followed with crystallization at the higher temperature.To investigate the origin of magnetism and electronic structure in these zb compounds, we calculated the total and partial DOS of FeInP.One can see that µtotal=4.24µBand µFe=3.27µB in contrast µIn=0.021µB and µP=0.049µB.These results predicted that FeInP compound do belong to the class of zb half metallic HM ferromagnetswith a pseudo gap= 0.93 eVare more promising materials for spintronics devices.

Keywords: zincblend structure, half metallic ferromagnet, spin moments, total and partial DOS, DRX, Wien2k

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Authors: Benny Sand, Yotam Lurie, Shlomo Mark

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Medical Internet of Things (MIoT), AI, and data privacy are linked forever in a gordian knot. This paper explores the conflicts of interests between the stakeholders regarding data privacy in the MIoT arena. While patients are at home during healthcare hospitalization, MIoT can play a significant role in improving the health of large parts of the population by providing medical teams with tools for collecting data, monitoring patients’ health parameters, and even enabling remote treatment. While the amount of data handled by MIoT devices grows exponentially, different stakeholders have conflicting understandings and concerns regarding this data. The findings of the research indicate that medical teams are not concerned by the violation of data privacy rights of the patients' in-home healthcare, while patients are more troubled and, in many cases, are unaware that their data is being used without their consent. MIoT technology is in its early phases, and hence a mixed qualitative and quantitative research approach will be used, which will include case studies and questionnaires in order to explore this issue and provide alternative solutions.

Keywords: MIoT, data privacy, stakeholders, home healthcare, information privacy, AI

Procedia PDF Downloads 80

Authors: Farhad Asadi, Mohammad Javad Mollakazemi, Aref Ghafouri

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Recent research in neural networks science and neuroscience for modeling complex time series data and statistical learning has focused mostly on learning from high input space and signals. Local linear models are a strong choice for modeling local nonlinearity in data series. Locally weighted projection regression is a flexible and powerful algorithm for nonlinear approximation in high dimensional signal spaces. In this paper, different learning scenario of one and two dimensional data series with different distributions are investigated for simulation and further noise is inputted to data distribution for making different disordered distribution in time series data and for evaluation of algorithm in locality prediction of nonlinearity. Then, the performance of this algorithm is simulated and also when the distribution of data is high or when the number of data is less the sensitivity of this approach to data distribution and influence of important parameter of local validity in this algorithm with different data distribution is explained.

Keywords: local nonlinear estimation, LWPR algorithm, online training method, locally weighted projection regression method

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Authors: Apkar Salatian

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To relieve the burden of reasoning on a point to point basis, in many domains there is a need to reduce large and noisy data sets into trends for qualitative reasoning. In this paper we propose and describe a new architectural design pattern called REDUCER for reducing large and noisy data sets that can be tailored for particular situations. REDUCER consists of 2 consecutive processes: Filter which takes the original data and removes outliers, inconsistencies or noise; and Compression which takes the filtered data and derives trends in the data. In this seminal article, we also show how REDUCER has successfully been applied to 3 different case studies.

Keywords: design pattern, filtering, compression, architectural design

Procedia PDF Downloads 191

Authors: Mario M. Figueroa de la Cruz, Claudia I. Solorzano, Raul Acosta, Ignacio Funes

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This technological development project seeks to create a tool that allows companies, in need of implementing a Data Center, intelligently determining factors for allocating resources support cooling and power supply (UPS) in its conception. The results should show clearly the speed, robustness and reliability of a system designed for deployment in environments where they must manage and protect large volumes of data.

Keywords: telecommunications, data center, fuzzy logic, expert systems

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Authors: Amy Gooden, Meshandren Naidoo

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Genetic research is not confined to a particular jurisdiction. Using direct-to-consumer genetic testing (DTC-GT) as an example, this research assesses the status of data sharing into and out of South Africa (SA). While SA laws cover the sending of genetic data out of SA, prohibiting such transfer unless a legal ground exists, the position where genetic data comes into the country depends on the laws of the country from where it is sent – making the legal position less clear.

Keywords: cross-border, data, genetic testing, law, regulation, research, sharing, South Africa

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Authors: Oksana Koval, Stephen Nabareseh

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Talent attraction is identified as a top priority between 2015 – 2020 for Shared Service Centers (SSCs) based on an industry-wide studies. Due to market dynamics and the structure of labour force, shared service industries in Eastern and Central Europe strive for qualified graduates with appropriate and unique skills to occupy such job places. The inbuilt interest and course prescriptions undertaken by prospective job seekers determine whether SSCs will eventually admit such professionals. This paper assesses students’ overall perception of careers in the shared services industry and further diagnosis gender impact and influence on the job preferences among students. Questionnaires were distributed among students in the Czech Republic universities using an online mode. Respondents vary by study year, gender, age, course of study, and work preferences. A total of 1283 student responses has been analyzed using Stata data analytics software. It was discovered that over 70% of respondents who are aware of SSCs are quite ignorant of the job opportunities offered by the centers. While majority of respondents are interested in support positions (e.g. procurement specialist, planning specialist, human resource specialist, process improvement specialist and payroll specialist, etc.), around a third of respondents (32.8 percent) will decline a job offer from SSCs. The analysis also revealed that males are more likely than females to seek careers in international companies, hence, tend to be more favorable towards shared service jobs. Females, however, have stronger preferences towards marketing and PR jobs. The research results provide insights into the job aspirations of students interviewed. The findings provide a huge resource for recruitment agencies and shared service industries to renew and redirect their search for talents into SSCs. Based on the fact that great portion of respondents are planning to start their career within 6-12 months, the research provides important highlights for the talent attraction and recruitment strategies in the industry and provides a curriculum direction in academia.

Keywords: Czech Republic labour market, gender, talent attraction, shared service centers, students

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Authors: Vikas Chawla, Buta Singh Sidhu, Amita Rani, Amit Handa

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The main objective of the present work is microstructural and mechanical characterization of the conventional and nanostructured TiAlN and AlCrN coatings deposited on T-11 boiler steel. In case of conventional coatings, Al-Cr and Ti-Al metallic powders were deposited using plasma spray process followed by gas nitriding of the surface which was done in the lab with optimized parameters after conducting several trials on plasma-sprayed coated specimens. The physical vapor deposition process (PAPVD) was employed for depositing nanostructured TiAlN and AlCrN coatings. The field emission scanning electron microscopy (FE-SEM) with energy dispersive X-ray analysis (EDAX) attachment, X-ray diffraction (XRD) analysis, atomic force microscopy (AFM) analysis and the X-Ray mapping analysis techniques have been used to study surface and cross-sectional morphology of the coatings. The surface roughness and micro-hardness were also measured. A good adhesion of the conventional thick TiAlN and AlCrN coatings was found. The coatings under study are recommended for the applications to super-heater and re-heater tubes of the boilers based upon the outcomes of the research work.

Keywords: nanostructure, physical vapour deposition, oxides, thin films, electron microscopy

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Authors: Baris Can Yalcin

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Motion sensors have been commonly used as a valuable component in mechatronic systems, however, many mechatronic designs and applications that need motion sensors cost enormous amount of money, especially high-tech systems. Design of a software for communication protocol between data acquisition card and motion sensor is another issue that has to be solved. This study presents how to design a low cost motion data acquisition setup consisting of MPU 6050 motion sensor (gyro and accelerometer in 3 axes) and Arduino Mega2560 microcontroller. Design parameters are calibration of the sensor, identification and communication between sensor and data acquisition card, interpretation of data collected by the sensor.

Keywords: design, mechatronics, motion sensor, data acquisition

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Authors: Sudhir Kumar Sharma, Ramesh Jagannathan

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The interaction of organic and inorganic matrices of biological origin resulting in self-assembled structures with unique properties is well established. The development of such self-assembled nanostructures by synthetic and bio-inspired techniques is an established field of active research. Among bio-materials, nacre, a laminar stack of calcium carbonate nanosheets, which are interleaved with organic material, has long been focused research due to its unique mechanical properties. In this paper, we present the development of nacre-like lamellar structures made up of calcium carbonate via a wet chemical route. We used the binding affinity of carboxylate anions and calcium cations using poly (acrylic) acid (PAA) to lead CaCO₃ crystallization. In these experiments, we selected calcium acetate as the precursor molecule along with PAA (Mw ~ 8000 Da). We found that Ca⁺²/COO⁻ ratio provided a tunable control for the morphology and growth of CaCO₃ nanostructures. Drop casting one such formulation on a silicon substrate followed by calcination resulted in co-planner, molecular sheets of CaCO₃, separated by a spacer layer of carbon. The scope of our process could be expanded to produce unit cell thick molecular sheets of other important inorganic materials.

Keywords: self-assembled structures, bio-inspired materials, calcium carbonate, wet chemical route

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Authors: Ashish Dhamaniya, Satish Chandra

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Speed and traffic volume data are collected on different sections of four lane and six lane roads in three metropolitan cities in India. Speed data are analyzed to fit the statistical distribution to individual vehicle speed data and all vehicles speed data. It is noted that speed data of individual vehicle generally follows a normal distribution but speed data of all vehicle combined at a section of urban road may or may not follow the normal distribution depending upon the composition of traffic stream. A new term Speed Spread Ratio (SSR) is introduced in this paper which is the ratio of difference in 85^th and 50^th percentile speed to the difference in 50^th and 15^th percentile speed. If SSR is unity then speed data are truly normally distributed. It is noted that on six lane urban roads, speed data follow a normal distribution only when SSR is in the range of 0.86 – 1.11. The range of SSR is validated on four lane roads also.

Keywords: normal distribution, percentile speed, speed spread ratio, traffic volume

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Authors: Ming Wei

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Over the past two decades, Location Based Service (LBS) data have been increasingly applied to urban and transportation studies due to their comprehensiveness and consistency. However, compared to other LBS data including mobile phone data, GPS and social networking platforms, smart card data collected from public transport users have arguably yet to be fully exploited in urban systems analysis. By using five weekdays of passenger travel transaction data taken from go card – Southeast Queensland’s transit smart card – this paper analyses the spatiotemporal distribution of passenger movement with regard to the land use patterns in Brisbane. Work and residential places for public transport commuters were identified after extracting journeys-to-work patterns. Our results show that the locations of the workplaces identified from the go card data and residential suburbs are largely consistent with those that were marked in the land use map. However, the intensity for some residential locations in terms of population or commuter densities do not match well between the map and those derived from the go card data. This indicates that the misalignment between residential areas and workplaces to a certain extent, shedding light on how enhancements to service management and infrastructure expansion might be undertaken.

Keywords: big data, smart card data, travel pattern, land use

Procedia PDF Downloads 264

Authors: Seung Hwan Park, Cheng-Sool Park, Jun Seok Kim, Youngji Yoo, Daewoong An, Jun-Geol Baek

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Depending on the big data analysis becomes important, yield prediction using data from the semiconductor process is essential. In general, yield prediction and analysis of the causes of the failure are closely related. The purpose of this study is to analyze pattern affects the final test results using a die map based clustering. Many researches have been conducted using die data from the semiconductor test process. However, analysis has limitation as the test data is less directly related to the final test results. Therefore, this study proposes a framework for analysis through clustering using more detailed data than existing die data. This study consists of three phases. In the first phase, die map is created through fail bit data in each sub-area of die. In the second phase, clustering using map data is performed. And the third stage is to find patterns that affect final test result. Finally, the proposed three steps are applied to actual industrial data and experimental results showed the potential field application.

Keywords: die-map clustering, feature extraction, pattern recognition, semiconductor manufacturing process

Procedia PDF Downloads 379

Authors: Afiq Juazer Rizal, Siti Zaleha Misnan, M. Zairi M. Yusof

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Seismic data is the fundamental tool utilized by exploration companies to determine potential hydrocarbon. However, the importance of seismic trace data will be undermined unless the geo-spatial component of the data is understood. Deriving a proposed well to be drilled from data that has positional ambiguity will jeopardize business decision and millions of dollars’ investment that every oil and gas company would like to avoid. Spatial integrity QC workflow has been introduced in PETRONAS to ensure positional errors within the seismic data are recognized throughout the exploration’s lifecycle from acquisition, processing, and seismic interpretation. This includes, amongst other tests, quantifying that the data is referenced to the appropriate coordinate reference system, survey configuration validation, and geometry loading verification. The direct outcome of the workflow implementation helps improve reliability and integrity of sub-surface geological model produced by geoscientist and provide important input to potential hazard assessment where positional accuracy is crucial. This workflow’s development initiative is part of a bigger geospatial integrity management effort, whereby nearly eighty percent of the oil and gas data are location-dependent.

Keywords: oil and gas exploration, PETRONAS, seismic data, spatial integrity QC workflow

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Authors: Hamed Chavoshi Pour, Javad Sadeghinejad

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The spinal cord is a long structure that starts at the end of the medulla oblongata and is located within the vertebral canal. Physiologically, the spinal cord connects the brain with the peripheral nervous system for sensory and motor activities. The cervical spinal cord is an area of particular interest in medicine and veterinary medicine due to the high prevalence of diseases in this region. This study describes the morphometric features of the cervical spinal cord in rabbits using design-unbiased stereology. The cervical spinal cords of five male rabbits were dissected, and slabs were taken according to systematic uniform random sampling. Each slab was embedded in paraffin and cut into a 6-µm thick section, and stained with cresyl violet 0.1% for stereological estimations. The total spinal cord volume, volume fraction of grey and white matter, and also dorsal and ventral horns were estimated using point counting and Cavalieri's estimator. The total cervical spinal cord volume was 0.98 ± 0.07 cm³. The relative volume of white matter and grey matter was 70.6 ± 1.7% and 29.31 ± 1.67%, respectively. The dorsal horn and ventral horn volume were 13.86 ± 1.36% and 14.9 ± 0.62% of the whole cervical spinal cord. This knowledge of rabbit spinal cord findings may serve as a foundation for a translational model in spinal cord experimental research and provide basic findings for the diagnosis and treatment of spinal cord disorders.

Keywords: stereology, spinal cord, rabbit, cervical

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Authors: Zhenqiu Liu

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Visualizing the heterogeneity within cell-populations for single-cell RNA-seq data is crucial for studying the functional diversity of a cell. However, because of the high level of noises, outlier, and dropouts, it is very challenging to measure the cell-to-cell similarity (distance), visualize and cluster the data in a low-dimension. Minimum volume embedding (MVE) projects the data into a lower-dimensional space and is a promising tool for data visualization. However, it is computationally inefficient to solve a semi-definite programming (SDP) when the sample size is large. Therefore, it is not applicable to single-cell RNA-seq data with thousands of samples. In this paper, we develop an efficient algorithm with an accelerated proximal gradient method and visualize the single-cell RNA-seq data efficiently. We demonstrate that the proposed approach separates known subpopulations more accurately in single-cell data sets than other existing dimension reduction methods.

Keywords: single-cell RNA-seq, minimum volume embedding, visualization, accelerated proximal gradient method

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Authors: Sara Ibn El Ahrache, Tajje-eddine Rachidi, Hassan Badir, Abderrahmane Sbihi

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Recently, there has been increasing confidence for a favorable usage of big data drawn out from the huge amount of information deposited in a cloud computing system. Data kept on such systems can be retrieved through the network at the user’s convenience. However, the data that users send include private information, and therefore, information leakage from these data is now a major social problem. The usage of secret sharing schemes for cloud computing have lately been approved to be relevant in which users deal out their data to several servers. Notably, in a (k,n) threshold scheme, data security is assured if and only if all through the whole life of the secret the opponent cannot compromise more than k of the n servers. In fact, a number of secret sharing algorithms have been suggested to deal with these security issues. In this paper, we present a Mapreduce implementation of Shamir’s secret sharing scheme to increase its performance and to achieve optimal security for cloud data. Different tests were run and through it has been demonstrated the contributions of the proposed approach. These contributions are quite considerable in terms of both security and performance.

Keywords: cloud computing, data security, Mapreduce, Shamir's secret sharing

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Authors: Samah Senbel

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Database Design is a fundamental part of the Computer Science and Information technology curricula in any school, as well as in the study of management, business administration, and data analytics. In this study, we compare the performance of two groups of students studying the same database design and implementation course at Sacred Heart University in the fall of 2018. Both courses used the same textbook and were taught by the same professor, one for seven graduate students and one for 26 undergraduate students (juniors). The undergraduate students were aged around 20 years old with little work experience, while the graduate students averaged 35 years old and all were employed in computer-related or management-related jobs. The textbook used was 'Database Systems, Design, Implementation, and Management' by Coronel and Morris, and the course was designed to follow the textbook roughly a chapter per week. The first 6 weeks covered the design aspect of a database, followed by a paper exam. The next 6 weeks covered the implementation aspect of the database using SQL followed by a lab exam. Since the undergraduate students are on a 16 week semester, we spend the last three weeks of the course covering NoSQL. This part of the course was not included in this study. After the course was over, we analyze the results of the two groups of students. An interesting discrepancy was observed: In the database design part of the course, the average grade of the graduate students was 92%, while that of the undergraduate students was 77% for the same exam. In the implementation part of the course, we observe the opposite: the average grade of the graduate students was 65% while that of the undergraduate students was 73%. The overall grades were quite similar: the graduate average was 78% and that of the undergraduates was 75%. Based on these results, we concluded that having both classes follow the same time schedule was not beneficial, and an adjustment is needed. The graduates could spend less time on design and the undergraduates would benefit from more design time. In the fall of 2019, 30 students registered for the undergraduate course and 15 students registered for the graduate course. To test our conclusion, the undergraduates spend about 67% of time (eight classes) on the design part of the course and 33% (four classes) on the implementation part, using the exact exams as the previous year. This resulted in an improvement in their average grades on the design part from 77% to 83% and also their implementation average grade from 73% to 79%. In conclusion, we recommend using two separate schedules for teaching the database design course. For undergraduate students, it is important to spend more time on the design part rather than the implementation part of the course. While for the older graduate students, we recommend spending more time on the implementation part, as it seems that is the part they struggle with, even though they have a higher understanding of the design component of databases.

Keywords: computer science education, database design, graduate and undergraduate students, pedagogy

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Authors: Vikrum Malhotra, Manpreet Kaur, Ayesha Ghotto

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Background: Cardiac registries such as ACC Percutaneous Coronary Intervention Registry require high quality data to be abstracted, including data elements such as nuclear cardiology, diagnostic coronary angiography, and PCI. Introduction: The audit tool created is used by data abstractors to provide data audits and assess the accuracy and inter-rater reliability of abstraction performed by the abstractors for a health system. This audit tool solution has been developed across 13 registries, including ACC/NCDR registries, PCI, STS, Get with the Guidelines. Methodology: The data audit tool was used to audit internal registry abstraction for all data elements, including stress test performed, type of stress test, data of stress test, results of stress test, risk/extent of ischemia, diagnostic catheterization detail, and PCI data elements for ACC/NCDR PCI registries. This is being used across 20 hospital systems internally and providing abstraction and audit services for them. Results: The data audit tool had inter-rater reliability and accuracy greater than 95% data accuracy and IRR score for the PCI registry in 50 PCI registry cases in 2021. Conclusion: The tool is being used internally for surgical societies and across hospital systems. The audit tool enables the abstractor to be assessed by an external abstractor and includes all of the data dictionary fields for each registry.

Keywords: abstraction, cardiac registry, cardiovascular registry, registry, data

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Authors: Ward Brullot, Thierry Verbiest

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Nonreciprocal optical effects, such as Faraday rotation or magnetic circular dichroism, are very useful both for fundamental studies as for applications such as magnetic field sensors or optical isolators. In this study, we developed layer-by-layer deposited 20nm thick plasmonic nanoparticle aggregates consisting of gold, silver and magnetite nanoparticles that show broadband nonreciprocal asymmetric transmission. As such, the optical transmittance, or absorbance, depends on the direction of light propagation in the material, which means that looking from one direction or the other, more or less light passes through the sample. Theoretical analysis showed that strong electric quadrupole fields, which are electric field gradients, occur in the aggregates and that these quadrupole fields are responsible for the observed asymmetric transmission and the nonreciprocity of the effect. Apart from nonreciprocal asymmetric transmission, also other effects such as, but not limited to, optical rotation, circular dichroism or nonlinear optical responses were measured in the plasmonic nanoparticle aggregates and the influences of the intense electric quadrupole fields determined. In conclusion, the presence of strong electric quadrupole fields make the developed plasmonic nanoparticle aggregates ideal candidates for the study and application of various nonreciprocal optical effects.

Keywords: asymmetric transmission, electric quadrupoles, nanoparticle aggregates, nonreciprocity

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Authors: Seyed Esmail Seyedi Bariran, Laysheng Ewe, Amy Ling

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Since supplier selection appears as a vital decision, selecting supplier based on the best and most accurate ways has a lot of importance for enterprises. In this study, a new Artificial Intelligence approach is exerted to remove weaknesses of supplier selection. The paper has three parts. First part is choosing the appropriate criteria for assessing the suppliers’ performance. Next one is collecting the data set based on experts. Afterwards, the data set is divided into two parts, the training data set and the testing data set. By the training data set the best structure of GEP and ANN are selected and to evaluate the power of the mentioned methods the testing data set is used. The result obtained shows that the accuracy of GEP is more than ANN. Moreover, unlike ANN, a mathematical equation is presented by GEP for the supplier selection.

Keywords: supplier selection, automotive supply chains, ANN, GEP

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Authors: Yasuyuki Takahashi, Maya Yamashita, Kyoko Saito

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In general, dynamic SPECT data acquisition needs a few minutes for one rotation. Thus, the time-activity curve (TAC) derived from the dynamic SPECT is relatively coarse. In order to effectively shorten the interval, between data points, we adopted a 180-degree interpolation method. This method is already used for reconstruction of the X-ray CT data. In this study, we applied this 180-degree interpolation method to SPECT and investigated its effectiveness.To briefly describe the 180-degree interpolation method: the 180-degree data in the second half of one rotation are combined with the 180-degree data in the first half of the next rotation to generate a 360-degree data set appropriate for the time halfway between the first and second rotations. In both a phantom and a patient study, the data points from the interpolated images fell in good agreement with the data points tracking the accumulation of 99mTc activity over time for appropriate region of interest. We conclude that data derived from interpolated images improves the apparent time resolution of dynamic SPECT.

Keywords: dynamic SPECT, time resolution, 180-degree interpolation method, 99mTc-GSA.

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Authors: Win Nee Phong, Tau Chuan Ling, Pau Loke Show

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From an industrial perspective, the exploitation of microalgae for protein source is of great economical and commercial interest due to numerous attractive characteristics. Nonetheless, the release of protein from microalgae is limited by the multiple layers of the rigid thick cell wall that generally contain a large proportion of cellulose. Thus an efficient cell disruption process is required to rupture the cell wall. The conventional downstream processing methods which typically involve several unit operational steps such as disruption, isolation, extraction, concentration and purification are energy-intensive and costly. To reduce the overall cost and establish a feasible technology for the success of the large-scale production, microalgal industry today demands a more cost-effective and eco-friendly technique in downstream processing. One of the main challenges to extract the proteins from microalgae is the presence of rigid cell wall. This study aims to provide some guidance on the selection of the efficient solvent to facilitate the proteins released during the cell disruption process. The effects of solvent types such as methanol, ethanol, 1-propanol and water in rupturing the microalgae cell wall were studied. It is interesting to know that water is the most effective solvent to recover proteins from microalgae and the cost is cheapest among all other solvents.

Keywords: green, microalgae, protein, solvents

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Authors: Inigo de Miguel Beriain

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Genetic data of deceased persons are of great interest for both biomedical research and clinical use. This is due to several reasons. On the one hand, many of our diseases have a genetic component; on the other hand, we share genes with a good part of our biological family. Therefore, it would be possible to improve our response considerably to these pathologies if we could use these data. Unfortunately, at the present moment, the status of data on the deceased is far from being satisfactorily resolved by the EU data protection regulation. Indeed, the General Data Protection Regulation has explicitly excluded these data from the category of personal data. This decision has given rise to a fragmented legal framework on this issue. Consequently, each EU member state offers very different solutions. For instance, Denmark considers the data as personal data of the deceased person for a set period of time while some others, such as Spain, do not consider this data as such, but have introduced some specifically focused regulations on this type of data and their access by relatives. This is an extremely dysfunctional scenario from multiple angles, not least of which is scientific cooperation at the EU level. This contribution attempts to outline a solution to this dilemma through an alternative proposal. Its main hypothesis is that, in reality, health data are, in a sense, a rara avis within data in general because they do not refer to one person but to several. Hence, it is possible to think that all of them can be considered data subjects (although not all of them can exercise the corresponding rights in the same way). When the person from whom the data were obtained dies, the data remain as personal data of his or her biological relatives. Hence, the general regime provided for in the GDPR may apply to them. As these are personal data, we could go back to thinking in terms of a general prohibition of data processing, with the exceptions provided for in Article 9.2 and on the legal bases included in Article 6. This may be complicated in practice, given that, since we are dealing with data that refer to several data subjects, it may be complex to refer to some of these bases, such as consent. Furthermore, there are theoretical arguments that may oppose this hypothesis. In this contribution, it is shown, however, that none of these objections is of sufficient substance to delegitimize the argument exposed. Therefore, the conclusion of this contribution is that we can indeed build a general framework on the processing of personal data of deceased persons in the context of the GDPR. This would constitute a considerable improvement over the current regulatory framework, although it is true that some clarifications will be necessary for its practical application.

Keywords: collective data conceptual issues, data from deceased people, genetic data protection issues, GDPR and deceased people

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Authors: Sherif Keddis, Rafik Mitry, Norbert Schwesinger

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Intelligent networking of devices has rapidly been gaining importance over the past years and with recent advances in the fields of microcontrollers, integrated circuits and wireless communication, low power applications have emerged, enabling this trend even more. Connected devices provide a much larger database thus enabling highly intelligent and accurate systems. Ensuring safe drinking water is one of the fields that require constant monitoring and can benefit from an increased accuracy. Monitoring is mainly achieved either through complex measures, such as collecting samples from the points of use, or through metering systems typically distant to the points of use which deliver less accurate assessments of the quality of water. Constant metering near the points of use is complicated due to their inaccessibility; e.g. buried water pipes, locked spaces, which makes system maintenance extremely difficult and often unviable. The research presented here attempts to overcome this challenge by providing these systems with enough energy through a flow harvester inside the pipe thus eliminating the maintenance requirements in terms of battery replacements or containment of leakage resulting from wiring such systems. The proposed flow harvester exploits the piezoelectric properties of polyvinylidene difluoride (PVDF) films to convert turbulence induced oscillations into electrical energy. It is intended to be used in standard water pipes with diameters between 0.5 and 1 inch. The working principle of the harvester uses a ring shaped bluff body inside the pipe to induce pressure fluctuations. Additionally the bluff body houses electronic components such as storage, circuitry and RF-unit. Placing the piezoelectric films downstream of that bluff body causes their oscillation which generates electrical charge. The PVDF-film is placed as a multilayered wrap fixed to the pipe wall leaving the top part to oscillate freely inside the flow. The warp, which allows for a larger active, consists of two layers of 30µm thick and 12mm wide PVDF layered alternately with two centered 6µm thick and 8mm wide aluminum foil electrodes. The length of the layers depends on the number of windings and is part of the investigation. Sealing the harvester against liquid penetration is achieved by wrapping it in a ring-shaped LDPE-film and welding the open ends. The fabrication of the PVDF-wraps is done by hand. After validating the working principle using a wind tunnel, experiments have been conducted in water, placing the harvester inside a 1 inch pipe at water velocities of 0.74m/s. To find a suitable placement of the wrap inside the pipe, two forms of fixation were compared regarding their power output. Further investigations regarding the number of windings required for efficient transduction were made. Best results were achieved using a wrap with 3 windings of the active layers which delivers a constant power output of 0.53µW at a 2.3MΩ load and an effective voltage of 1.1V. Considering the extremely low power requirements of sensor applications, these initial results are promising. For further investigations and optimization, machine designs are currently being developed to automate the fabrication and decrease tolerance of the prototypes.

Keywords: maintenance-free sensors, measurements at point of use, piezoelectric flow harvesting, universal micro generator, wireless metering systems

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Authors: Abdullah I. Alkraiji, Thomas W. Jackson, Ian Murray

Abstract:

The proliferation of health data standards today is somewhat overlapping and conflicting, resulting in market confusion and leading to increasing proprietary interests. The government role and support in standardization for health data are thought to be crucial in order to establish credible standards for the next decade, to maximize interoperability across the health sector, and to decrease the risks associated with the implementation of non-standard systems. The normative literature missed out the exploration of the different steps required to be undertaken by the government towards the development of national health data standards. Based on the lessons learned from a qualitative study investigating the different issues to the adoption of health data standards in the major tertiary hospitals in Saudi Arabia and the opinions and feedback from different experts in the areas of data exchange and standards and medical informatics in Saudi Arabia and UK, a list of steps required towards the development of national health data standards was constructed. Main steps are the existence of: a national formal reference for health data standards, an agreed national strategic direction for medical data exchange, a national medical information management plan and a national accreditation body, and more important is the change management at the national and organizational level. The outcome of this study can be used by academics and practitioners to develop the planning of health data standards, and in particular those in developing countries.

Keywords: interoperabilty, medical data exchange, health data standards, case study, Saudi Arabia

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Authors: SangWon Han, MuWook Pyeon, Sujung Moon, DaeKyo Seo

Abstract:

Recently, technologies based on three-dimensional (3D) space information are being developed and quality of life is improving as a result. Research on real-time digital map (RDM) is being conducted now to provide 3D space information. RDM is a service that creates and supplies 3D space information in real time based on location/shape detection. Research subjects on RDM include the construction of 3D space information with matching image data, complementing the weaknesses of image acquisition using multi-source data, and data collection methods using big data. Using RDM will be effective for space analysis using 3D space information in a U-City and for other space information utilization technologies.

Keywords: RDM, multi-source data, big data, U-City

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Authors: Nieto Bernal Wilson, Carmona Suarez Edgar

Abstract:

The organizations have structured and unstructured information in different formats, sources, and systems. Part of these come from ERP under OLTP processing that support the information system, however these organizations in OLAP processing level, presented some deficiencies, part of this problematic lies in that does not exist interesting into extract knowledge from their data sources, as also the absence of operational capabilities to tackle with these kind of projects.  Data Warehouse and its applications are considered as non-proprietary tools, which are of great interest to business intelligence, since they are repositories basis for creating models or patterns (behavior of customers, suppliers, products, social networks and genomics) and facilitate corporate decision making and research. The following paper present a structured methodology, simple, inspired from the agile development models as Scrum, XP and AUP. Also the models object relational, spatial data models, and the base line of data modeling under UML and Big data, from this way sought to deliver an agile methodology for the developing of data warehouses, simple and of easy application. The methodology naturally take into account the application of process for the respectively information analysis, visualization and data mining, particularly for patterns generation and derived models from the objects facts structured.

Keywords: data warehouse, model data, big data, object fact, object relational fact, process developed data warehouse

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Authors: Go Bong Choi, Shin Je Lee, Sung Jin Yoo, Gibaek Lee, Jong Min Lee

Abstract:

In South Korea, it is difficult to obtain data for statistical pipe assessment. In this paper, to address these issues, we find that various statistical model presented before is how data mixed with noise and are whether apply in South Korea. Three major type of model is studied and if data is presented in the paper, we add noise to data, which affects how model response changes. Moreover, we generate data from model in paper and analyse effect of noise. From this we can find robustness and applicability in Korea of each model.

Keywords: proportional hazard model, survival model, water main deterioration, ecological sciences

Procedia PDF Downloads 720