Search results for: data dissemination

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

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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: Hirreche Baghdad Mohamed

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Our research is linked to cultural policies because the initiation to taste and beauty is a matter for all cultural and educational institutions. It's done by a downstream process (programs, actions, lessons, etc.) that begins at a young age in order to inscribe aesthetic values in memories, imaginations, and practices. Preparing future art lovers probably takes a lot of time. Upstream, continuity is ensured by the "cultural industries" which make cultural products available to actors in the "art market" through professional training, production, dissemination, and sales processes. It turns out that the cultural industries borrow from the "classical" industries the same processes and logic: product, production, marketing, diffusion, profit and profits, supply and demand, the market, the creation of wealth, the entrepreneurship. Today, culture has become a product almost like the others. In the cultural industries system, we protect the rights of authors (owners) and the rights of intermediaries (entrepreneurs of culture), and we provide consumers with an accessible product that meets their needs and expectations. We aim to present an inventory and to reveal, through the speeches of the actors themselves, the processes and modes of operation and deployment of the plastic arts market by showing how it is perceived, imagined, and lived in the city of 'Oran from the 2000s to the present day. However, it is possible to clarify this field of research by looking at previous periods; and even to make comparisons with other regions in Algeria in order to give meaning to practices in various contexts.

Keywords: Oran, Algeria, fine art, art market

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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: Santosh Kumar Suman, Vinod Kumar Giri

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The goal of this paper is to outline a speed controller of a DC motor by choice of a PID parameters utilizing genetic algorithms (GAs), the DC motor is extensively utilized as a part of numerous applications such as steel plants, electric trains, cranes and a great deal more. DC motor could be represented by a nonlinear model when nonlinearities such as attractive dissemination are considered. To provide effective control, nonlinearities and uncertainties in the model must be taken into account in the control design. The DC motor is considered as third order system. Objective of this paper three type of tuning techniques for PID parameter. In this paper, an independently energized DC motor utilizing MATLAB displaying, has been outlined whose velocity might be examined utilizing the Proportional, Integral, Derivative (KP, KI , KD) addition of the PID controller. Since, established controllers PID are neglecting to control the drive when weight parameters be likewise changed. The principle point of this paper is to dissect the execution of optimization techniques viz. The Genetic Algorithm (GA) for improve PID controllers parameters for velocity control of DC motor and list their points of interest over the traditional tuning strategies. The outcomes got from GA calculations were contrasted and that got from traditional technique. It was found that the optimization techniques beat customary tuning practices of ordinary PID controllers.

Keywords: DC motor, PID controller, optimization techniques, genetic algorithm (GA), objective function, IAE

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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: Mohammed Aladalah

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The emergence of digital citizens is no longer mere speculation; therefore, governments’ use of Web 2.0 tools (hereafter Gov 2.0) should be a part of all current and future e-government plans. The potential of Gov 2.0 to facilitate greater communication, participation, and collaboration with citizens has been highlighted and discussed extensively in recent literature. However, the current levels of citizens’ participation in Gov 2.0 have not lived up to the hype. Therefore, governments need to rethink the way in which they implement Gov 2.0, and take advantage of the digitally-engaged population. We propose a two-dimensional framework to tackle this issue: first, on the supply side, governments tend to use Gov 2.0 mainly for the dissemination of information and for self-promotion without the desire to encourage any interaction with citizens; this is due to many reasons, including the lack of time and the possibility of loss of control. The second dimension of the framework is the demand side; citizens are unwilling to participate in Gov 2.0 activities because they do not perceive its value or trust the government. We attempt to consider the elements of both supply and demand in order to provide a comprehensive solution whereby the potential of Gov 2.0 can be fully utilized. Our framework is based on the theoretical foundation of service science and value co-creation theory. This paper makes two significant contributions: (a) it provides an initial framework intended to increase citizens’ participation in Gov 2.0; and (b) it enhances the understanding of the government’s Gov 2.0 applications, particularly in terms of factors that ensure their attractiveness for citizens. This work is the first step in a comprehensive research undertaking, the purpose of which is to study public’s engagement with the Gov 2.0 concept. It contributes to providing a better understanding of e-government and its future.

Keywords: e-government, Gov 2.0, citizens participation, digital citizen

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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

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Authors: E. T. Svahn

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This article documents how open science policy is perceived in the scientific literature globally throughout the history. It also presents what policy needs are persistent to enable safe and effective dissemination of scientific knowledge. This information may be of interest to open science and science policy makers globally, especially in the view of recent adoption of supranational open science policies such as Plan S. Evaluation of open science policy landscape is in pressing need of assessment regarding its impact on the research community and society at wide as no previous literature review has been conducted on the topic. This study is a rigorous literature review based on constructivist grounded theory method on the full body of scientific open science policy publications. Selection of these articles has been conducted in 2019 and 2020 in major global knowledge databases. Through the analysis of these articles, two key themes emerged that are seen to shape the relationship between science and society. 1st is that of the policy enabling open science in a safe and effective way, and 2nd is that of the outcome of the science policy may have on the research community and the wider society. These findings accentuate that open science policies can have a major impact on not only research process and availability of knowledge but also on society itself. As an outcome of this study, a theoretical framework is constructed, and the need for further study on open science policy itself on a higher level becomes apparent.

Keywords: constructivist grounded theory, open science policy, rigorous literature review, science policy

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Authors: Nasrin Hosseinzad

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Troxerutin, a trihydroxyethylated derived of rutin, is a flavonoid existing in tea, coffee, cereal grains, various fruits and vegetables have been conveyed to display radioprotective, antithrombotic, nephron-protective and hepato-protective possessions. Troxerutin, has been well-proved to utilize hepatoprotective assets. Troxerutin could upturn the resistance of hippocampal neurons alongside apoptosis by lessening the action of AChE and oxidative stress. Consequently, troxerutin may have advantageous properties in the administration of Alzheimer's disease and cancer. Troxerutin has been testified to have several welfares and medicinal stuffs. It could shelter the mouse kidney against d-gal-induced damage by refining renal utility, decreasing histopathologic changes, dropping ROS construction, reintroducing the activities of antioxidant enzymes and reducing DNA oxidative destruction. The DNA cleavage study clarifies that troxerutin showed DNA protection against hydroxyl radical persuaded DNA mutilation. Troxerutin uses anti-cancer effect in HuH-7 hepatocarcinoma cells conceivably through synchronized regulation of the molecular signalling pathways, Nrf2 and NF-κB. DNA binding at slight channel by troxerutin may have donated to feature breaks leading to improved radiation brought cell death. Furthermore, the mechanism principal the observed variance in the antioxidant activities of troxerutin and its esters was qualified to equally their free radical scavenging capabilities and dissemination on the cell membrane outward.

Keywords: troxerutin, DNA, oxidative stress, antioxidant, free radical

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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

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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: 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: Kyle De Freitas, Margaret Bernard

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Enabling data mining analysis among a wider audience of educators is an active area of research within the educational data mining (EDM) community. The paper proposes a framework for developing an environment that caters for educators who have little technical data mining skills as well as for more advanced users with some data mining expertise. This framework architecture was developed through the review of the strengths and weaknesses of existing models in the literature. The proposed framework provides a modular architecture for future researchers to focus on the development of specific areas within the EDM process. Finally, the paper also highlights a strategy of enabling analysis through either the use of predefined questions or a guided data mining process and highlights how the developed questions and analysis conducted can be reused and extended over time.

Keywords: educational data mining, learning management system, learning analytics, EDM framework

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Authors: Andrew Wee

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As a result of the Italian Independence Wars starting in 1848, Italy began to change through unification. People gradually moved away from some of their traditional practices and values, such as the long-held belief that women were inferior to men, as part of the Risorgimento. Italians began to take interest in opera as a form of emotional release. As opera became more popular and prominent in their culture, it aided in the dissemination of ideas, especially stimulating the spread of imperialism, in the late 19th century, as Italy began extending its presence to other countries. In order to collect the information needed to analyze Italy’s foreign presence, it was necessary to consult texts concerning the culture of the Risorgimento. These texts included primary sources from operatic composers and contemporary recorded accounts. Letters from Giuseppe Verdi, a leader in opera during the Risorgimento, have been scrutinized for indications of popular attitudes of the time. The cultural context of the Risorgimento is essential to understanding the Italian motives and attitudes towards the outside world. On the more political side, research has also entailed the study of historical data of general laws, policies, and their purposes concerning geopolitical boundaries and foreign affairs, such as Edward Said’s thesis on Orientalism. By establishing these two characteristics of Italy, the paper will thoroughly illustrate Italy’s presence in foreign affairs. Texts have been searched with the intent of using information that reveals Italian attitudes toward exotic countries to determine whether their demeanor was positive or condescending. Motives behind sources have been interpreted in context in order to form a complete picture of the Italian sentiment towards foreigners. Additionally, research pertaining to Italian nationalism and imperialism such as song and literature has been used. The primary form of research has been the division of sources that are culturally based and those that are political in nature. Opera had always been developing since its creation in the 17th century, and in the 19th century, the bel canto movement revolutionized opera and its role in Italian society. This paper uses evidence that popular sentiment was influenced by opera to support the belief that the evolution of opera was as a result of the nationalist sentiment, and in turn fueled the cultural movement known as the Risorgimento. In this way, opera proceeded to affect Italian culture by spreading the idea of imperialism.

Keywords: opera, Italian unification, music history, imperialism

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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: 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: Lucas Caldas, Pablo Paulse, Karla Hora

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Shipping containers are present in different Brazilian cities, firstly used for transportation purposes, but which become waste materials and an environmental burden in their end-of-life cycle. In the last decade, in Brazil, some buildings made partly or totally from shipping containers started to appear, most of them for commercial and office uses. Although the use of a reused container for buildings seems a sustainable solution, it is very important to measure the thermal and energy aspects when they are used as such. In this context, this study aims to evaluate the thermal and energy performance of an office building totally made from a 12-meter-long, High Cube 40’ shipping container in different Brazilian Bioclimatic Zones. Four different constructive solutions, mostly used in Brazil were chosen: (1) container without any covering; (2) with internally insulated drywall; (3) with external fiber cement boards; (4) with both drywall and fiber cement boards. For this, the DesignBuilder with EnergyPlus was used for the computational simulation in 8760 hours. The EnergyPlus Weather File (EPW) data of six Brazilian capital cities were considered: Curitiba, Sao Paulo, Brasilia, Campo Grande, Teresina and Rio de Janeiro. Air conditioning appliance (split) was adopted for the conditioned area and the cooling setpoint was fixed at 25°C. The coefficient of performance (CoP) of air conditioning equipment was set as 3.3. Three kinds of solar absorptances were verified: 0.3, 0.6 and 0.9 of exterior layer. The building in Teresina presented the highest level of energy consumption, while the one in Curitiba presented the lowest, with a wide range of differences in results. The constructive option of external fiber cement and drywall presented the best results, although the differences were not significant compared to the solution using just drywall. The choice of absorptance showed a great impact in energy consumption, mainly compared to the case of containers without any covering and for use in the hottest cities: Teresina, Rio de Janeiro, and Campo Grande. This study brings as the main contribution the discussion of constructive aspects for design guidelines for more energy-efficient container buildings, considering local climate differences, and helps the dissemination of this cleaner constructive practice in the Brazilian building sector.

Keywords: bioclimatic zones, Brazil, shipping containers, thermal and energy performance

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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: Maryam Maleki, Esther Mead, Mohammad Arani, Nitin Agarwal

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This study is conducted to examine how opposing viewpoints related to COVID-19 were diffused on Twitter. To accomplish this, six datasets using two epidemiological models, SIR (Susceptible, Infected, Recovered) and SEIZ (Susceptible, Exposed, Infected, Skeptics), were analyzed. The six datasets were chosen because they represent opposing viewpoints on the COVID-19 pandemic. Three of the datasets contain anti-subject hashtags, while the other three contain pro-subject hashtags. The time frame for all datasets is three years, starting from January 2020 to December 2022. The findings revealed that while both models were effective in evaluating the propagation trends of these polarizing viewpoints, the SEIZ model was more accurate with a relatively lower error rate (6.7%) compared to the SIR model (17.3%). Additionally, the relative error for both models was lower for anti-subject hashtags compared to pro-subject hashtags. By leveraging epidemiological models, insights into the propagation trends of polarizing viewpoints on Twitter were gained. This study paves the way for the development of methods to prevent the spread of ideas that lack scientific evidence while promoting the dissemination of scientifically backed ideas.

Keywords: mathematical modeling, epidemiological model, seiz model, sir model, covid-19, twitter, social network analysis, social contagion

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

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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

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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

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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

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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

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Authors: Paulina Clara Appiah, Kofi Issah, Timothy Letsa, Kennedy Nartey, Amanua Chinbuah, Adoma Dwomo-Fokuo, Jacqeline G. Asibey

Abstract:

Background: The Every Newborn Action Plan provides evidence–based interventions to end preventable deaths in high burden countries. Brong Ahafo Region is one of ten regions in Ghana with less than half of its district hospitals having sick newborn units. Facility-based neonatal care is not prioritized and under-funded, and there is also inadequate knowledge and competence to manage the sick. The aim of this intervention was to make available in–patient care for sick newborns in all 19 district hospitals through the strengthening of facility-based systems. Methods: With the development and dissemination of the National Newborn Strategy and Action Plan 2014-2018, the country was able to attract PATH which provided the region with basic resuscitation equipment, supported hospital providers’ capacity building in Helping Babies Breathe, Essential Care of Every Baby, Infection Prevention and Management and held a symposia on managing the sick newborn. Newborn advocacy was promoted through newborn champions at the facility and community levels. Hospital management was then able to mobilize resources from communities, corporate organizations and from internally generated funds; created or expanded sick newborn care units and provided essential medicines and equipment. Kangaroo Mother Care was initiated in 6 hospitals. Pediatric specialist outreach services initiated comprised telephone consultations, teaching ward rounds and participating in perinatal death audits meetings. Newborn data capture and management was improved through the provision and training on the use of standard registers provided from the national level. Results: From February 2015 to November 2017, hospitals with sick newborn units increased from 7 to 19 (37%-100%). 180 pieces each of newborn ventilation bags and masks size 0, 1 and penguin suction bulbs were distributed to the hospitals, in addition to 20 newborn mannequin sets and 90 small clinical reminder posters. 802 providers (96.9%) were trained in resuscitation, of which 96% were successfully followed up in 6 weeks, 91% in 6 months and 80% in 12 months post-training. 53 clinicians (65%) were trained and mentored to manage sick newborns. 56 specialist teaching ward rounds were conducted. Data completeness improved from 92.6% - 99.9%. Availability of essential medicines improved from 11% to 100%. Number of hospital cots increased from 116 to 248 (214%). Cot occupancy rate increased from 57.4% to 92.5%. Hospitals with phototherapy equipment increased from 0 to 12 (63%). Hospitals with incubators increased from 1 to 12 (5%-63%). Newborn deaths among admissions reduced from 6.3% to 5.4%. Conclusion: Access to in-patient care increased significantly. Newborn advocacy successfully mobilized resources required for strengthening facility –based systems.

Keywords: facility-based systems, Ghana, in-patient care, newborn advocacy

Procedia PDF Downloads 204

Authors: Anusha Konduru, Zhiyong Shan, Preethi Santhanam, Vinod Namboodiri, Rajiv Bagai

Abstract:

Mobile applications are increasing in a significant amount, each to address the requirements of many users. However, the quick developments and enhancements are resulting in many underlying defects. Android apps create and handle a large variety of 'instance' data that has to persist across runs, such as the current navigation route, workout results, antivirus settings, or game state. Due to the nature of Android, an app can be paused, sent into the background, or killed at any time. If the instance data is not saved and restored between runs, in addition to data loss, partially-saved or corrupted data can crash the app upon resume or restart. However, it is difficult for the programmer to manually test this issue for all the activities. This results in the issue of data loss that the data entered by the user are not saved when there is any interruption. This issue can degrade user experience because the user needs to reenter the information each time there is an interruption. Automated testing to detect such data loss is important to improve the user experience. This research proposes a tool, DroidDL, a data loss detector for Android, which detects the instance data loss from a given android application. We have tested 395 applications and found 12 applications with the issue of data loss. This approach is proved highly accurate and reliable to find the apps with this defect, which can be used by android developers to avoid such errors.

Keywords: Android, automated testing, activity, data loss

Procedia PDF Downloads 213

Authors: James Moir

Abstract:

The mainstay of Big Data is prediction in that it allows practitioners, researchers, and policy analysts to predict trends based upon the analysis of large and varied sources of data. These can range from changing social and political opinions, patterns in crimes, and consumer behaviour. Big Data has therefore shifted the criterion of success in science from causal explanations to predictive modelling and simulation. The 19th-century science sought to capture phenomena and seek to show the appearance of it through causal mechanisms while 20th-century science attempted to save the appearance and relinquish causal explanations. Now 21st-century science in the form of Big Data is concerned with the prediction of appearances and nothing more. However, this pulls social science back in the direction of a more rule- or law-governed reality model of science and away from a consideration of the internal nature of rules in relation to various practices. In effect Big Data offers us no more than a world of surface appearance and in doing so it makes disappear any context-specific conceptual sensitivity.

Keywords: big data, appearance, disappearance, surface, epistemology

Procedia PDF Downloads 388