Search results for: heterogeneous massive data

Authors: Mohammed Abdelsabour-Khalaf, F. Yusuf , B Brand-Saberi

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Purpose: Applications of nanotechnology nowadays extended to include a wide range of scientific areas such electron micrscopy and gene expression. The aim of the current study was to investigate the developmental expression pattern of genes involved in human glomerulo-nephropathies associated with massive proteinuria and podocyte differentiation using the chicken mesonephros as a model system. Method: We performed in situ hybridization using chicken specific mRNA probes for genes expressed in the early nephron and slit diaphragm genes. The probes used were cNeph1, cNeph2, cSim1, cLmx1b, and cAtoh8. Chicken embryos from Hamburger Hamilton developmental stage HH19 (E3) to HH 34 (E9) were used for the in situ hybridization (ISH). ISH was performed on whole mount embryos which were sectioned by vibratome. Results: Our result show that Neph1, Neph2, Sim1. Lmx1b and Atoh8 genes are dynamically expressed during nephron morphogenesis and Neph1 and Atoh8 are also specifically expressed in the podocytes during late stages of differentiation. Conclusion: We conclude from our results that the genes implicated in congenital and acquired glomerulo-nephropathies like Neph1 and Neph2 are dynamically expressed during mesonephros development pointing towards a role in the formation of the filtration barrier and the differentiation of the mesonephric podocytes. Thus the avian mesonephros could serve as a model to study human kidney diseases.

Keywords: mesonephros, chicken embryo, gene expression, immunohistochemistry

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Authors: Harleen Kaur, Richa

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Plants produce a large variety of secondary metabolites. Phenolics are the compounds that contain hydroxyl functional group on an aromatic ring. These are chemically heterogeneous compounds. Some are soluble only in organic solvents, some are water soluble and others are large insoluble polymers. Flavonoids are one of the largest classes of plant phenolics. The carbon skeleton of a flavonoid contains 15 carbons arranged in two aromatic rings connected by a three carbon ridge. Both phenolics and flavonoids are good natural antioxidants. Four Indian aromatic plants were selected for the study i.e, Achillea species, Jasminum primulinum, Leucas cephalotes and Leonotis nepetaefolia. All the plant species were collected from Chail region of Himachal Pradesh, India. The identifying features and anatomical studies were done of the part containing the essential oils. Phenolic cotent was estimated by Folin Ciocalteu’s method and flavonoids content by aluminium chloride method. Antioxidant property was checked by using DPPH method. Maximum antioxidant potential was found in Achillea species, followed by Leonotis nepetaefolia, Jaminum primulinum and Leucas cephalotes. Phenolics and flavonoids are important compounds that serve as defences against herbivores and pathogens. Others function in attracting pollinators and absorbing harmful radiations.

Keywords: antioxidants, DPPH, flavonoids, phenolics

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Authors: Rizwan Latif, Syed Adnan Qasim, Muzaffar Ali

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Fuel direct injection represents one of the key aspects in the development of the diesel engines, the idea of controlling the auto-ignition and the consequent combustion of a liquid spray injected in a reacting atmosphere during a time scale of few milliseconds has been a challenging task for the engine community and pushed forward to a massive research in this field. The quality of the air-fuel mixture defines the combustion efficiency, and therefore the engine efficiency. A droplet interaction in dense as well as thin portion of the spray receives equal importance as other parameters in spray structure. Usually, these are modeled along with breakup process and analyzed alike. In this paper, droplet interaction is modeled and simulated for high torque low speed scenario. Droplet interactions may further be subdivided into droplet collision and coalescence, spray wall impingement, droplets drag, etc. Droplet collisions may occur in almost all spray applications, but especially in diesel like conditions such as high pressure sprays as utilized in combustion engines. These collisions have a strong influence on the mean droplet size and its spatial distribution and can, therefore, affect sub-processes of spray combustion such as mass, momentum and energy transfer between gas and droplets. Similarly, for high-pressure injection systems spray wall impingement is an inherent sub-process of mixture formation. However, its influence on combustion is in-explicit.

Keywords: droplet collision, coalescence, low speed, diesel fuel

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Authors: Hyun-Woo Cho

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Automatic process monitoring schemes are designed to give early warnings for unusual process events or abnormalities as soon as possible. For this end, various techniques have been developed and utilized in various industrial processes. It includes multivariate statistical methods, representation skills in reduced spaces, kernel-based nonlinear techniques, etc. This work presents a nonlinear empirical monitoring scheme for batch type production processes with incomplete process measurement data. While normal operation data are easy to get, unusual fault data occurs infrequently and thus are difficult to collect. In this work, noise filtering steps are added in order to enhance monitoring performance by eliminating irrelevant information of the data. The performance of the monitoring scheme was demonstrated using batch process data. The results showed that the monitoring performance was improved significantly in terms of detection success rate of process fault.

Keywords: batch process, monitoring, measurement, kernel method

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Authors: Alexandra Aslanidou

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The General Data Protection Regulation (GDPR), concerning the protection of natural persons within the European Union with regard to the processing of personal data and on the free movement of such data, became applicable in the European Union (EU) on 25 May 2018 and transformed the way personal data were being treated under the Data Protection Directive (DPD) regime, generating sweeping organizational changes to both public sector and business. A social practice that is considerably influenced in the way of its day-to-day operations is Human Resource (HR) management, for which the importance of GDPR cannot be underestimated. That is because HR processes personal data coming in all shapes and sizes from many different systems and sources. The significance of the proper functioning of an HR department, specifically in human-centered, service-oriented environments such as the education field, is decisive due to the fact that HR operations in schools, conducted effectively, determine the quality of the provided services and consequently have a considerable impact on the success of the educational system. The purpose of this paper is to analyze the decisive role that GDPR plays in HR departments that operate in schools and in order to practically evaluate the aftermath of the Regulation during the first months of its applicability; a comparative use cases analysis in five highly dynamic schools, across three EU Member States, was attempted.

Keywords: general data protection regulation, human resource management, educational system

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Authors: Sana Hamdi, Emna Bouazizi, Sami Faiz

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In recent years, real-time spatial applications, like location-aware services and traffic monitoring, have become more and more important. Such applications result dynamic environments where data as well as queries are continuously moving. As a result, there is a tremendous amount of real-time spatial data generated every day. The growth of the data volume seems to outspeed the advance of our computing infrastructure. For instance, in real-time spatial Big Data, users expect to receive the results of each query within a short time period without holding in account the load of the system. But with a huge amount of real-time spatial data generated, the system performance degrades rapidly especially in overload situations. To solve this problem, we propose the use of data partitioning as an optimization technique. Traditional horizontal and vertical partitioning can increase the performance of the system and simplify data management. But they remain insufficient for real-time spatial Big data; they can’t deal with real-time and stream queries efficiently. Thus, in this paper, we propose a novel data partitioning approach for real-time spatial Big data named VPA-RTSBD (Vertical Partitioning Approach for Real-Time Spatial Big data). This contribution is an implementation of the Matching algorithm for traditional vertical partitioning. We find, firstly, the optimal attribute sequence by the use of Matching algorithm. Then, we propose a new cost model used for database partitioning, for keeping the data amount of each partition more balanced limit and for providing a parallel execution guarantees for the most frequent queries. VPA-RTSBD aims to obtain a real-time partitioning scheme and deals with stream data. It improves the performance of query execution by maximizing the degree of parallel execution. This affects QoS (Quality Of Service) improvement in real-time spatial Big Data especially with a huge volume of stream data. The performance of our contribution is evaluated via simulation experiments. The results show that the proposed algorithm is both efficient and scalable, and that it outperforms comparable algorithms.

Keywords: real-time spatial big data, quality of service, vertical partitioning, horizontal partitioning, matching algorithm, hamming distance, stream query

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Authors: Vanshika Chutani, Priya Bhatnagar

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The pandemic has brought us to a standpoint where stress as a physical, cognitive, and behavioral construct is inevitable. The current research provides an overview of the relationship between stress and dysfunctional eating behavior during the challenging time of the COVID-19 pandemic. The present paper also aims to highlight the gender-specific differences in perception of stress and its correlation with dysfunctional eating behavior in the COVID-19 pandemic. Perceived Stress Scale-10 (PSS) and Adult Eating Behavior questionnaire (AEBQ) were used on a heterogeneous sample between 20-40 years. The research was conducted on 50 participants, 25 male, and 25 female. Quantitative analysis was done with SPSS 22.0. The results of the investigation revealed a significant difference in stress level, t(48)=2.01, p<0.01, with women (M=22.24. SD=5.23) having a higher stress level than men (M=19.04, SD=4.89). There was no significant difference in dysfunctional eating behavior between males and females. There was a significant positive correlation between stress and dysfunctional eating behavior in females, whereas, in males, there was no significant positive correlation between stress and dysfunctional eating behavior. The research extrapolates that the pandemic led to elevated stress levels in both genders and gender differences existed, and males & females responded differently on dysfunctional eating behavior. The research has also outlined intervention to help individuals cope with stress and dysfunctional eating behavior. The findings of the research propose the execution of different intervention programs and psychological first aid to help individuals who are predisposed to develop eating disorders.

Keywords: stress, dysfunctional eating behavior, gender-specific differences, COVID-19

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Authors: P. Venu, Joeju M. Issac

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Quality Function Deployment (QFD) is a systematic technique that creates a platform where the customer responses can be positively converted to design attributes. The accuracy of a QFD process heavily depends on the data that it is handling which is captured from customers or QFD team members. Customized computer programs that perform Quality Function Deployment within a stipulated time have been used by various companies across the globe. These programs heavily rely on storage and retrieval of the data on a common database. This database must act as a perfect source with minimum missing values or error values in order perform actual prioritization. This paper introduces a missing/error data handler module which uses Genetic Algorithm and Fuzzy numbers. The prioritization of customer requirements of sesame oil is illustrated and a comparison is made between proposed data handler module-based deployment and manual deployment.

Keywords: hybrid data handler, QFD, prioritization, module-based deployment

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Authors: Miao Yang

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PPCPs (pharmaceutical and personal care products) in water, as an environmental pollutant, becomes an issue of increasing concern. Therefore, the techniques for degradation of PPCPs has been a hotspot in water pollution control field. Since there are several disadvantages for common degradation techniques of PPCPs, such as low degradation efficiency for certain PPCPs (ibuprofen and Carbamazepine) this proposal will adopt a combined technique by using CDs (carbon nanodots)/C₃N₄ composite and ultrasonic irradiation to mitigate or overcome these shortages. There is a significant scientific problem that the mechanism including PPCPs, major reactants, and interfacial active sites is not clear yet in the study of PPCPs degradation. This work aims to solve this problem by using both theoretical and experimental methodologies. Firstly, optimized parameters will be obtained by evaluating the kinetics and oxidation efficiency under different conditions. The competition between H₂O₂ and PPCPs with HO• will be elucidated, after which the degradation mechanism of PPCPs by the synergy of CDs/C₃N₄ composite and ultrasonic irradiation will be proposed. Finally, a sonolysis-adsorption-catalysis coupling mechanism will be established which is the theoretical basis and technical support for developing new efficient degradation techniques for PPCPs in the future.

Keywords: carbon nanodots/C₃N₄, pharmaceutical and personal care products, ultrasonic irradiation, hydroxyl radical, heterogeneous catalysis

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Authors: Faisal Aburub, Wael Hadi

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Data mining is the process of extracting useful or hidden information from a large database. Extracted information can be used to discover relationships among features, where data objects are grouped according to logical relationships; or to predict unseen objects to one of the predefined groups. In this paper, we aim to investigate four well-known data mining algorithms in order to predict groundwater areas in Jordan. These algorithms are Support Vector Machines (SVMs), Naïve Bayes (NB), K-Nearest Neighbor (kNN) and Classification Based on Association Rule (CBA). The experimental results indicate that the SVMs algorithm outperformed other algorithms in terms of classification accuracy, precision and F1 evaluation measures using the datasets of groundwater areas that were collected from Jordanian Ministry of Water and Irrigation.

Keywords: classification, data mining, evaluation measures, groundwater

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Authors: Pankhudi Khandelwal

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The revenue models of digital giants such as Facebook and Google, use targeted advertising for revenues. Such a model requires huge amounts of consumer data. While the data protection law deals with the protection of personal data, however, this data is acquired by the companies on the basis of consent, performance of a contract, or legitimate interests. This paper analyses the role that competition law can play in evading these loopholes for the protection of data and privacy of online consumers. Digital markets have certain distinctive features such as network effects and feedback loop, which gives incumbents of these markets a first-mover advantage. This creates a situation where the winner takes it all, thus creating entry barriers and concentration in the market. It has been also seen that this dominant position is then used by the undertakings for leveraging in other markets. This can be harmful to the consumers in form of less privacy, less choice, and stifling innovation, as seen in the cases of Facebook Cambridge Analytica, Google Shopping, and Google Android. Therefore, the article aims to provide a legal framework wherein the data protection law and competition law can come together to provide a balance in regulating digital markets. The issue has become more relevant in light of the Facebook decision by German competition authority, where it was held that Facebook had abused its dominant position by not complying with data protection rules, which constituted an exploitative practice. The paper looks into the jurisdictional boundaries that the data protection and competition authorities can work from and suggests ex ante regulation through data protection law and ex post regulation through competition law. It further suggests a change in the consumer welfare standard where harm to privacy should be considered as an indicator of low quality.

Keywords: data protection, dominance, ex ante regulation, ex post regulation

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Authors: Gloria G. Delan, Alfonso S. Piquero, Rachel Luz V. Rica, Christine M. Corrales

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The selected marine protected areas (MPAs) of southern Cebu, Philippines were assessed after these have been established between the years 2000 to 2007. These include Casay of Argao, Cawayan of Dalaguete, Guiwang-Daang Lungsod of Alcoy, North Granada of Boljoon and Sta. Cruz of Ronda. These MPAs were assessed to gather baseline information on its coral life-form structure. Point-intercept transect (PIT) method was used in the observation. Benthic life form and reef substrate at each 0.25 m point interval were identified and recorded along 50 meters transect line both inside and outside of these MPAs. It has been observed that massive, branching and digitate form of corals dominated among the five sanctuaries. Percentage of Live Hard Corals was much higher inside than outside in all sanctuaries. Common to all sanctuaries were noticeable presence of dead corals with algae and coral rubbles indicating an over-exploited habitat. Casay, Cawayan and Daan-Lungsod MPAs had some Crown of Thorn Starfish (COTS) which may pose threat to its coral community. It has been recommended that there should be strict law enforcement and a long term monitoring to continuously conserve and protect coral reef which is an important habitat for fishes for its sustainability as food for human.

Keywords: coral rubbles, coral reef, live hard coral, point-intercept transect

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Authors: Mai Ghazal, Ahmed Hammad

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Cost overruns in construction projects are considered as worldwide challenges since the cost performance is one of the main measures of success along with schedule performance. To overcome this problem, studies were conducted to investigate the cost overruns' factors, also projects' historical data were analyzed to extract new and useful knowledge from it. This research is studying and analyzing the effect of some factors causing cost overruns using the historical data from completed construction projects. Then, using these factors to estimate the probability of cost overrun occurrence and predict its percentage for future projects. First, an intensive literature review was done to study all the factors that cause cost overrun in construction projects, then another review was done for previous researcher papers about mining process in dealing with cost overruns. Second, a proposed data warehouse was structured which can be used by organizations to store their future data in a well-organized way so it can be easily analyzed later. Third twelve quantitative factors which their data are frequently available at construction projects were selected to be the analyzed factors and suggested predictors for the proposed model.

Keywords: construction management, construction projects, cost overrun, cost performance, data mining, data warehousing, knowledge discovery, knowledge management

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Authors: Temiloluwa J. Akinyemi, Denis W. Aheto, Wisdom Akpalu

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Capture fisheries in developing countries provide significant animal protein and directly supports the livelihoods of several communities. However, the misperception of biophysical dynamics owing to a lack of adequate scientific data has contributed to the suboptimal management in marine capture fisheries. This is because yield and catch potentials are sensitive to the quality of catch and effort data. Yet, studies on fisheries data collection practices in developing countries are hard to find. This study investigates the data collection methods utilized by fisheries technical officers within the four fishing regions of Ghana. We found that the officers employed data collection and sampling procedures which were not consistent with the technical guidelines curated by FAO. For example, 50 instead of 166 landing sites were sampled, while 290 instead of 372 canoes were sampled. We argue that such sampling errors could result in the over-capitalization of capture fish stocks and significant losses in resource rents.

Keywords: Fisheries data quality, fisheries management, Ghana, Sustainable Fisheries

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Authors: Min-Shiuan Liou, Yi Shan Yang, Yang-Zhan Huang, Chia-Wen Hsieh

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A high speed growing and butanol-tolerant Clostridium acetobutylicum HOL1 mutant was screened throughout continuous adaption culture with C. acetobutylicum ATCC 824. The HOL1 strain can grow well in 10 g/L butanol contained CGM medium and can produce about 12.8 g /L butanol during 24 hrs. The C. acetobutylicum HOL1 strain was able to produce 166 mM butanol with 21 mM acetone at pH 4.8, resulting in a butanol selectivity (a molar ratio of butanol to total solvents) of 0.79, which is much higher than that (0.6) of the wild-type strain C. acetobutylicum ATCC 824. The acetate and butyrate accumulation were not observed during fermentation of the HOL1 strain. A hyper-butanol producing C. acetobutylicum HOL1 (pBPHS-3), which was created to overexpress the Bacillus psychrosaccharolyticus originated specific heat-shock protein gene, hspX, from a clostridial phosphotransbutyrylase promoter, was studied for its potential to produce a high titer of butanol. Overexpression of hspX resulted in increased final butanol yield 47% and 30% higher than those of the the ATCC824 and the HOL1 strains, respectively. The remarkable high-speed growth and butanol tolerance of strain HOL1 (pBPHS-3) demonstrates that overexpression of heterogeneous stress protein-encoding gene, hspX, could help C. acetobutylicum to effectively produce a high concentration of butanol.

Keywords: Clostridium acetobutylicum, butanol, heat-shock protein, resistance

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Authors: Ibrahim H. Kilic, A. B. Tugrul

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Energy is a fundamental component in economic development and energy consumption is an index of prosperity and the standard of living. The consumption of energy per capita has increased significantly over the last decades, as the standard of living has improved. Turkey’s geographical location has several advantages for extensive use of wind power. Among the renewable sources, Turkey has very high wind energy potential. Information such as installation capacity of wind power plants in installation, under construction and license stages in the country are reported in detail. Some suggestions are presented in order to increase the wind power installation capacity of Turkey. Turkey’s economic and social development has led to a massive increase in demand for electricity over the last decades. Since the Turkey has no major oil or gas reserves, it is highly dependent on energy imports and is exposed to energy insecurity in the future. But Turkey does have huge potential for renewable energy utilization. There has been a huge growth in the construction of wind power plants and small hydropower plants in recent years. To meet the growing energy demand, the Turkish Government has adopted incentives for investments in renewable energy production. Wind energy investments evaluated the impact of feed-in tariffs (FIT) based on three scenarios that are optimistic, realistic and pessimistic with APLUS software that is developed for rational evaluation for energy market. Results of the three scenarios are evaluated in the view of electricity market for Turkey.

Keywords: APLUS, energy policy, renewable energy, wind power, Turkey

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Authors: Ohoud Abdullatif Alshaiji

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Child-rearing is considered as the most important family role and with the modern lifestyle and busy families social institutions has taken this role from the family to encourage the individuals active's role in the social life, this study aimed to acknowledge the contributions of the social institutions in child-rearing the Saudi children and to acknowledge The Role of the community's partnership in activating the social child-rearing for the Saudi children. The research main question was how much the community's partnership is actually participating in activating the process of the social development of the Saudi children. The importance of this study comes from the massive care that has been given from all over the world, children international organizations, and this research is focusing on the participating of five social organization in child-rearing the Saudi children. The study was limited on the mothers of the children who are enrolled in the government's kindergarten the tool that has been used was the Questionnaire, using the descriptive and analytical approach. The important role of the family in encouraging the social development for the Saudi child, and the results has shown the importance of the mosque in encouraging the good social behaviors. And the kindergarten role has shown after the mosque because of the changes that made most of the families relying on the educational institutions to help the child to adapt in a different cultures. To spread the community's partnership in all the social actions, to support and encourage the role of community's partnership in activating the process of the social development of the Saudi children, to minimize the difficulties and the provide the need to fully support the community's partnership.

Keywords: child-rearing, social development, acknowledge the contributions

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Authors: Khaled Ahmed Kadouh, Kamal Ali Albashiri

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This paper presents a designed algorithm involves improvement of transferring data over Simple Object Access Protocol (SOAP). The aim of this work is to establish whether using SOAP in exchanging XML messages has any added advantages or not. The results showed that XML messages without SOAP take longer time and consume more memory, especially with binary data.

Keywords: JAX-WS, SMTP, SOAP, web service, XML

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Authors: Joseph Udofia, Isaac Olufadewa

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Everyday, the size of Electronic Health Records data keeps increasing as new patients visit health practitioner and returning patients fulfil their appointments. As these data grow, so is their susceptibility to cyber-attacks from criminals waiting to exploit this data. In the US, the damages for cyberattacks were estimated at $8 billion (2018), $11.5 billion (2019) and $20 billion (2021). These attacks usually involve the exposure of PII. Health data is considered PII, and its exposure carry significant impact. To this end, an enhancement of Health Policy and Standards in relation to data security, especially among patients and their clinical providers, is critical to ensure ethical practices, confidentiality, and trust in the healthcare system. As Clinical accelerators and applications that contain user data are used, it is expedient to have a review and revamp of policies like the Payment Card Industry Data Security Standard (PCI DSS), the Health Insurance Portability and Accountability Act (HIPAA), the Fast Healthcare Interoperability Resources (FHIR), all aimed to ensure data protection and security in healthcare. FHIR caters for healthcare data interoperability, FHIR caters to healthcare data interoperability, as data is being shared across different systems from customers to health insurance and care providers. The astronomical cost of implementation has deterred players in the space from ensuring compliance, leading to susceptibility to data exfiltration and data loss on the security accuracy of protected health information (PHI). Though HIPAA hones in on the security accuracy of protected health information (PHI) and PCI DSS on the security of payment card data, they intersect with the shared goal of protecting sensitive information in line with industry standards. With advancements in tech and the emergence of new technology, it is necessary to revamp these policies to address the complexity and ambiguity, cost barrier, and ever-increasing threats in cyberspace. Healthcare data in the wrong hands is a recipe for disaster, and we must enhance its protection and security to protect the mental health of the current and future generations.

Keywords: cloud security, healthcare, cybersecurity, policy and standard

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Authors: Peristera Baziana

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In this paper, we present a network configuration for a WDM LANs of passive star topology that assume that the set of data WDM channels is split into two separate sets of channels, with different access rights over them. Especially, a synchronous transmission WDMA access algorithm is adopted in order to increase the probability of successful transmission over the data channels and consequently to reduce the probability of data packets transmission cancellation in order to avoid the data channels collisions. Thus, a control pre-transmission access scheme is followed over a separate control channel. An analytical Markovian model is studied and the average throughput is mathematically derived. The performance is studied for several numbers of data channels and various values of control phase duration.

Keywords: access algorithm, channels division, collisions avoidance, wavelength division multiplexing

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Authors: D. I. George Amalarethinam, A. Emima

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Educational Data Mining (EDM) is one of the newest topics to emerge in recent years, and it is concerned with developing methods for analyzing various types of data gathered from the educational circle. EDM methods and techniques with machine learning algorithms are used to extract meaningful and usable information from huge databases. For scientists and researchers, realistic applications of Machine Learning in the EDM sectors offer new frontiers and present new problems. One of the most important research areas in EDM is predicting student success. The prediction algorithms and techniques must be developed to forecast students' performance, which aids the tutor, institution to boost the level of student’s performance. This paper examines various classification techniques in prediction methods and data mining tools used in EDM.

Keywords: classification technique, data mining, EDM methods, prediction methods

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Authors: Kunwar Paritosh, Vivekanand Vivekanand, Nidhi Pareek

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Presently, India depends primarily on fossil fuels for its acute energy demand. The swift in development of India in last two decades is accentuating its natural resources and compelling expenditures to cope energy security for the habitats. A total inhabitant of 1.2 billion, observing growing industrialization; is generating 68.8 million tonnes of municipal solid waste per year, 53.7 million tonnes is collected, and only trifling amount of 10.3 million tonnes of waste is treated per year that integrates to a massive amount of unimaginable land hill. In India, waste is mostly landfilled and/or incinerated with low technology and is poorly managed. Underutilization of this waste not only gulps resources but also stresses environment, public health and bionetwork thus affecting the bioeconomy negatively. It also creates conditions that invoke inevitable expenditures and loss of its renewable energy potential. The non-scientific approach to manage waste may lead to an economy downfall, underutilization and degradation of natural resources. Waste treatment technologies must be scientifically tailored and engineered as per the type of waste where it may be utilized as a source of energy (here biogas) and nutrients employing anaerobic digestion to the sorted waste. This paper presents a brief review on current practices, key achievements and forthcoming aspects of harnessing energy from municipal solid waste in Indian scenario.

Keywords: municipal discards, organic waste, anaerobic digestion, incineration, energy

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Authors: Aofan Liu, Qianqian Tan, Burra Venkata Durga Kumar

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Data security is of the utmost importance in the healthcare area, as sensitive patient information is constantly sent around and analyzed by many different parties. The use of federated learning, which enables data to be evaluated locally on devices rather than being transferred to a central server, has emerged as a potential solution for protecting the privacy of user information. To protect against data breaches and unauthorized access, federated learning alone might not be adequate. In this context, the application of blockchain technology could provide the system extra protection. This study proposes a distributed federated learning system that is built on blockchain technology in order to enhance security in healthcare. This makes it possible for a wide variety of healthcare providers to work together on data analysis without raising concerns about the confidentiality of the data. The technical aspects of the system, including as the design and implementation of distributed learning algorithms, consensus mechanisms, and smart contracts, are also investigated as part of this process. The technique that was offered is a workable alternative that addresses concerns about the safety of healthcare while also fostering collaborative research and the interchange of data.

Keywords: data privacy, distributed system, federated learning, machine learning

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Authors: Hiesik Kim, YongBeum Kim

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Internet of Things (IoT) applications are widely serviced and spread worldwide. Local wireless data transmission technique must be developed to speed up with some technique. Bluetooth wireless data communication is wireless technique is technique made by Special Inter Group(SIG) using the frequency range 2.4 GHz, and it is exploiting Frequency Hopping to avoid collision with different device. To implement experiment, equipment for experiment transmitting measured data is made by using Arduino as Open source hardware, Gas sensor, and Bluetooth Module and algorithm controlling transmission speed is demonstrated. Experiment controlling transmission speed also is progressed by developing Android Application receiving measured data, and controlling this speed is available at the experiment result. it is important that in the future, improvement for communication algorithm be needed because few error occurs when data is transferred or received.

Keywords: Arduino, Bluetooth, gas sensor, internet of things, transmission Speed

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Authors: Sreejith Gopinath, Aspen Olmsted

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This paper is based on our previous work that proposed a risk-transference-based architecture for healthcare systems to store sensitive data outside the system boundary, rendering the system unattractive to would-be bad actors. This architecture also allows a compromised system to be abandoned and a new system instance spun up in place to ensure business continuity without paying a ransom or engaging with a bad actor. This paper delves into the details of various attacks we simulated against the prototype system. In the paper, we discuss at length the time and computational costs associated with storing and retrieving data in the prototype system, abandoning a compromised system, and setting up a new instance with existing data. Lastly, we simulate some analytical workloads over the data stored in our specialized data storage system and discuss the time and computational costs associated with running analytics over data in a specialized storage system outside the system boundary. In summary, this paper discusses the total costs of data storage, access, and analytics incurred with the proposed architecture.

Keywords: cybersecurity, healthcare, ransomware, resilience, risk transference

Procedia PDF Downloads 133

Authors: Ismayanti Magfirah, Sartohadi Junun, Samodra Guruh

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Landslides are one of the most frequent and devastating natural disasters in Indonesia. Many studies have been conducted regarding this phenomenon. However, there is a lack of attention in the landslide inventory mapping. The natural condition (dense forest area) and the limited human and economic resources are some of the major problems in building landslide inventory in Indonesia. Considering the importance of landslide inventory data in susceptibility, hazard, and risk analysis, it is essential to generate landslide inventory based on available resources. In order to achieve this, the first thing we have to do is identify the landslides' location. The presence of Sentinel-1A and Sentinel-2A data gives new insights into land monitoring investigation. The free access, high spatial resolution, and short revisit time, make the data become one of the most trending open sources data used in landslide mapping. Sentinel-1A and Sentinel-2A data have been used broadly for landslide detection and landuse/landcover mapping. This study aims to generate landslide map by integrating Sentinel-1A and Sentinel-2A data use change detection method. The result will be validated by field investigation to make preliminary landslide inventory in the study area.

Keywords: change detection method, landslide inventory mapping, Sentinel-1A, Sentinel-2A

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Authors: Michael Gidey Gebru

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

Keywords: efficiency, DEA, fuzzy, decision making units, higher education institutions

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Authors: Iulia Crisan

Abstract:

Objective: The present study investigates the cross-cultural validity of three North-American performance validity indicators (PVTs) by comparing base rates of failure (BRF) in Romanian and Canadian disability applicants. Methods: Three PVTs (Test of Memory Malingering Trial 1 [TOMM-1], Rey Fifteen Item Test free recall [Rey-15 FR], and Rey FR+Recognition [Rey COMB]) were administered to a heterogeneous Romanian clinical sample (N Ro =54) and a similar Canadian sample (N Can = 52). Patients were referred for assessment to determine the severity of their cognitive deficits. Results: We compared the BRF in both samples at various cutoffs. BRF on TOMM-1 at ≤ 43 was similar (Ro = 33.3% vs. Can = 40.4%); at ≤40, Ro = 22.2% vs. Can = 25.0%. Likewise, comparable BRF were observed on Rey-15 FR at ≤ 8 (Ro = 7.4% vs. Can = 11.5%) and ≤ 11 (Ro = 27.8% vs. Can = 23.1%). However, the Romanian sample produced significantly higher failure rates on the Rey COMB at variable cutoffs (p <.05), possibly because Romanian patients were significantly older than the Canadian sample. Conclusion: Our findings offer proof of concept for the cross-cultural validity of the TOMM and Rey-15 FR. At the same time, they serve as a reminder that the generalizability of PVT cutoffs to different populations should not be assumed but verified empirically. Employing the TOMM as a criterion measure for newly developed PVTs is discussed.

Keywords: performance validity indicators, cross-cultural validity, failure base rates, clinical samples, cognitive dysfunction, TOMM-1, Rey-15, Rey COMB

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Authors: Denise Hexom, Judith Menoher

Abstract:

Teachers and administrators across America are being asked to use data and hard evidence to inform practice as they begin the task of implementing Common Core State Standards. Yet, the courses they are taking in schools of education are not preparing teachers or principals to understand the data-driven decision making (DDDM) process nor to utilize data in a much more sophisticated fashion. DDDM has been around for quite some time, however, it has only recently become systematically and consistently applied in the field of education. This paper discusses the theoretical framework of DDDM; empirical evidence supporting the effectiveness of DDDM; a process a department in a school of education has utilized to implement DDDM; and recommendations to other schools of education who attempt to implement DDDM in their decision-making processes and in their students’ coursework.

Keywords: data-driven decision making, institute of higher education, special education, continuous improvement

Procedia PDF Downloads 387

Authors: Yaeji Lim, Hee-Seok Oh

Abstract:

The coherence analysis measures the linear time-invariant relationship between two data sets and has been studied various fields such as signal processing, engineering, and medical science. However classical coherence analysis tends to be sensitive to outliers and focuses only on mean relationship. In this paper, we generalized cross periodogram to quantile cross periodogram and provide richer inter-relationship between two data sets. This is a general version of Laplace cross periodogram. We prove its asymptotic distribution under the long range process and compare them with ordinary coherence through numerical examples. We also present real data example to confirm the usefulness of quantile coherence analysis.

Keywords: coherence, cross periodogram, spectrum, quantile

Procedia PDF Downloads 390