Miracle-dz/UniFAR-FTUs huggingface dataset:
A Weighted Dynamic Data Replication Management for Cloud Data Storage Systems

In cloud storage systems, data replication is widely used to ensure the availability of data and to reduce the space and cost of storage. In Hadoop, the file systems are managed by Hadoop Distributed File System (HDFS), which manages storage resources with its default set up, which has several architectural and implementation bottlenecks. This will affect the overall performance of the system. In this paper, we have proposed an efficient data replication strategy which dynamically replicates data based on its access popularity. This strategy classifies the data to hot, warm and cold by considering the access pattern of the data and dynamically manages the replication of each category. The replication factor of hot and warm data is maintained according to its availability requirement and a minimum replica is set for the cold data and erasure coding is applied on it. We implemented the proposed strategy in HDFS and the experimental results shows that proposed method is efficient and cost effective and outperforms the default replication management of HDFS.
Consumer Resistance∗

This paper shows that reference-dependent preferences trigger consumer resistance and studies how such consumer behavior impacts pricing and cost communication. We show that consumer resistance reduces the pricing power and profit of the firm. We also show that consumer resistance may provide an incentive for the firm to engage in cost transparency. While cheap communication does not affect consumer behavior, we demonstrate that persuasive communication may increase sales and profit. Finally, we establish that a firm can benefit from operational transparency if cost is monotone increasing in the quality of the production process.
Chapter 15 Network Analysis in Translational Research

Networks, where nodes/vertices denote entities and links/edges denote associations, provide a unified representation for a variety of complex systems, from social relationships to molecular interactions. In general, network analysis has proved useful in applications such as prediction of protein function, guiding the design of wet-lab experiments, and discovery of biomarkers of disease. Driven by the availability of large-scale data sets and appropriate informatics’ tools, the research community has begun to apply network analysis of these data to define underlying causes of pediatric diseases. This will almost certainly lead to more effective strategies for prevention and treatment. In this chapter, we will introduce classic and the state-of-the-art network analysis methodologies, approaches and their applications. We then provide three examples of recent research, where network analysis is being applied in pediatrics. These include identification of targets M. Zhang, Ph.D. • J. Deng • L. Tan School of Computing Sciences and Informatics, University of Cincinnati College of Engineering & Applied Science, Cincinnati, OH, USA Division of Biomedical Informatics, Cincinnati Children’s Hospital Medical Center, 3333 Burnet Avenue, MLC 7024, Cincinnati, OH 45229-3039, USA Y. Chen Division of Biomedical Informatics, Cincinnati Children’s Hospital Medical Center, 3333 Burnet Avenue, MLC 7024, Cincinnati, OH 45229-3039, USA School of Electronics and Computing Systems, University of Cincinnati College of Engineering & Applied Science, Cincinnati, OH, USA L.J. Lu, Ph.D. ( ) Division of Biomedical Informatics, Cincinnati Children’s Hospital Medical Center, 3333 Burnet Avenue, MLC 7024, Cincinnati, OH 45229-3039, USA Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, USA e-mail: long.lu@cchmc.org J.J. Hutton (ed.), Pediatric Biomedical Informatics: Computer Applications in Pediatric Research, Translational Bioinformatics 2, DOI 10.1007/978-94-007-5149-1 15, © Springer ScienceCBusiness Media Dordrecht 201 265
A Scalable Unified Fault Tolerance for HPC Environments

Reliability is one of the major issues in High Performance Computing (HPC) systems today. It is expected to become even a greater challenge in the next generation peta-scale systems. The traditional fault tolerance mechanisms (e.g., checkpoint/restart mechanisms) may not be efficient in every scenario in such large scale systems due to the scalability and performance issues. In this paper, we aim to provide a distributed scalable Unified Fault Tolerance (UFT), which consists of Proactive Fault Avoidance (PFA) and traditional Reactive Fault Tolerance (RFT) for HPC systems based on fault prediction and virtualization technologies. The results from simulation suggest the performance improvement over the existing solutions.
FOOD TRACEABILITY SYSTEMS AND INFORMATION SHARING IN FOOD SUPPLY CHAIN Ionuţ ANICA-POPA

The food quality and safety is influenced by all food operators from the food supply chain, therefore there are numerously factors that must be observed and taken into consideration. Moreover, if accidentally the food becomes dangerous for human consumption, it is necessary to be taken actions to pull out the compromised food from the market and to identify where is located all other compromised food batches across the food supply chain in order to eliminate the possibility to spread the compromised food and to minimize the consequences. The basic requirement in order to facilitate those actions is represented by the inter-organizational communication and sharing information between all organizations across food supply chain, consequently by the existence of an information system that must allow those capabilities. This paper presents main aspect related to data and information quality, sharing information and will discuss the possibility to share information between organizations involved in food supply chain in order to enhance capabilities of food traceability systems. Conclusions and future directions of the research are discussed.
Sociodemographic Predictors of Obesity among Patients Seen in the Family Medicine Geriatric Clinic of the University of Calabar Teaching Hospital , Calabar , Nigeria

Ita Bassey Okokon1*, Udoezuo Kingsley Ogbonna2, Udeme Essien Asibong1, Elvis Mbu Bisong1 and Edu Ime Udoekwere3 1Department of Family Medicine, Faculty of Medicine, College of Medical Sciences, University of Calabar, PMB 1115, Calabar, Nigeria and Department of Family Medicine, University of Calabar Teaching Hospital, PMB 1278, Calabar, Nigeria 2Shell Medical Service, Shell BP, Port Harcourt, Nigeria 3Department of Family Medicine, University of Calabar Teaching Hospital, PMB 1278, Calabar, Nigeria
ISSUED BY THE JAPAN INSTITUTE OF LABOUR

On September 27, the Survey on the Circumstances of Job-Searchers was released by the Ministry of Public Management, Home Affairs, Posts and Telecommunications. The survey focuses on the difficulties unemployed people have in making ends meet financially. This survey found that more than half of all the unemployed had no income: among those who did have income, more than half depended on pension payments or unemployment benefits. At the same time, the survey revealed that in many cases jobless heads of households financed their living expenses from their unemployment benefits, pension payments or withdrawing from savings. In Japan, the number of unemployed has continued to increase sharply since the mid-1990s. In particular, the increase in the number of long-term unemployed — those without a job for more than a year — is regarded as one of the most serious issues facing society. The survey, designed to shed light on the plight of the unemployed, was first conducted in April and May 2002. The subjects were unemployed people in approximately 20,000 households; questions included their sources of income, whether or not they receive unemployment benefits, and what activities they have undertaken to improve their skills. Those who had no jobs but had stayed in the job market (the unemployed) were asked about the progress of their job-searching activities, while those who had given up looking for a job and left the labor market were asked about the prospects of resuming job-hunting and other questions. According to the survey, of the 3.74 million unemployed, 1.9 million (51%) had no income in the month prior to when the survey was taken, followed by 760,000 people whose main income source was unemployment benefits, and 330,000 with income from pension payments. With the exception of those 55 years old and older, the majority of all other age groups received no income. This is particularly noticeable in the groups comprising those aged 25 to 34 and 15 to 24, at 600,000 and 540,000 people, respectively. On the other hand, the largest proportion, 300,000, of those aged 55 and older cited pension payments or benefits as their main income source. (See Statistical Aspect on page 3.) Where households with unemployed heads are concerned, the largest proportion, 23.6 percent, financed their living expenses in the month prior to the survey with pension payments, followed by 22.2 percent who
Climate change, migration, and irrigation

Climate change will affect both international and internal migration. Earlier work finds evidence of a climate-migration poverty trap: higher temperatures reduce agri- cultural yields, which in turn reduce emigration rates in low-income countries, due to liquidity constraints. We test whether access to irrigation modulates the climate- migration poverty trap, since irrigation protects crops from heat. We regress measures of international and internal migration on decadal averages of temperature and rain- fall, interacted with country-level data on irrigation and income. We find that irri- gation access significantly weakens the climate-migration poverty trap, demonstrating the importance of considering alternative adaptation strategies when analyzing climate migration.
Effect of Recognition and Promotion on Employees ’ Job Satisfaction of Selected Outsourced Service Providers In Jos , Plateau State , Nigeria

Rewards and job satisfaction for over decades have been issues of concern to employers and employees in various organizations worldwide. Insufficient reward factors such as recognition and promotion are some of the major reasons responsible for employees’ dissatisfaction and intention to leave their current organizations. This research sought to examine the effect between recognition and promotion on employees’ job satisfaction of selected outsourced service providers in Jos Plateau State. A survey research design was adopted. The population of the study was 541 employees which consisted of all the employees of the five (5) selected outsourced service providers in Jos, Plateau State. The sampling technique used was census. A total of 541 copies of the questionnaire were distributed; out of which a total number of 448 (82%) were properly filled and returned.Data was analyzed using simplelinear regression analysis and Pearson product moment correlation test the relationship between recognition, promotion and job satisfaction.The findings of this study revealed that Recognition (R 2 = 0.558, p<0.05) and Promotion (R 2 = 0.683, p<0.05) have positive significant effect on employees’ job satisfaction of selected outsourced service providers in Jos, Plateau State.The study concluded that recognition and promotion factors had a significant positive effect on employees’ job satisfaction of the outsourced service providers in Jos, Plateau State. It is therefore recommended, that management of these outsourced companies improve on recognition and promotion in order to reduce the level of dissatisfaction among employees.
Designing a prefabricated sandwich composite roofing system Made up of resisting facings and light-weight concrete core with truss-shaped connectors

In this paper, a new roofing system is introduced, which is constructued using the precast composite sandwich panels. This roofing sandwich panels system consists of three kinds of precast concrete sandwich panels including capital panels, beam or between columns panels, and slab or middle panels. The panels are composed of three layers; A high strength reinforced concrete top layer. A thick layer of lightweight concrete as the intermediate layer or core. And a tensile resistant reinforced concrete bottom layer. The panels are connected together by special connectors at the edges. In this research, the influence of shear connector stiffness is studied which is measured according to their diameter on ultimate resistant and combined performance of the panels. The results of finite element analysis by ABAQUS software show a logical behavior of load-deflection curves in shear connectors. Based on the economic and weight comparisons the dead and live loads, the proposed sandwich panel roofing is approximately 44 percent lighter than the conventional steel joist and concrete blocks. This comparison shows the superiority of this roofing system to joists and concrete blocks system and seems to be a good alternative for it. Due to the possibility of prefabrication and industrial production of the panels under factory conditions, and various other technical, economic, and constructional advantages of this roofing system, it is concluded that it can be viable substitute for current roofing systems in low to high-rise buildings and can save a considerable amount of material, labor, time, and cost in building construction.
Privacy concerns in Ambient Assisted Living systems for home environments

By 2060 it is estimated that 30% of the European population will be 60 years or older. An aging society will put a heavy strain on the healthcare system. To mitigate this strain and enable elderly to live autonomously in their homes the AAL program was formed. With healthcare and health monitoring systems operating in home environments questions regarding privacy and security should be among the top priorities. The aim with this systematic literature study is to identify common privacy concerns, analyze and map them to areas within the eld of computer science. 1000 studies were reviewed and passed through a three step inclusion process. Leading to 30 included studies representing di erent research elds and user surveys. Included studies were categorized regarding privacy concerns and ended up as 18 vagueand 12 strong concerns and 8 solutions. Most common privacy concern among users were the unspeci ed privacy concern which might be a hindrance for acceptance of AAL systems in home environments. Other signi cant ndings include the need for further research in representing data ow for users, user consent gathering and privacy vs. usability trade-o s.
Using Support Vector Machine for Classifying Insulator Leakage Current

153603-7474-IJECS-IJENS © June 2015 IJENS I J E N S  Abstract— This paper proposes a support vector machine (SVM)-based technique for data classification and estimation. The correlation between insulator leakage current and weather conditions was used to establish classifier models for estimating insulator leakage current. This study adopted a remote monitoring system installed in two transmission towers, Tower 51 (161 kV) on Sihu First Road and Tower 4 (69kV) at Lunbei Line, Qiao Cun, which are located on the key lines in the heavily salt-fog-polluted regions of Yunlin, Taiwan. This system monitors the power lines and the damages caused by salt-fog pollution, and combines meteorological data with insulator leakage current data and spark discharge images collected through automatic monitoring. These data were employed in a multivariate linear regression analysis to identify the correlation between leakage current and weather conditions. Various meteorological parameters were used to construct regression models for determining the parameters imposing the greatest influence on leakage current. Subsequently, the proposed SVM classifiers were employed to combine various meteorological parameters with leakage current parameters generated by insulators of dissimilar specifications. Finally, the optimal parameter combination for classifying leakage current was determined, thus verifying the applicability and effectiveness of the leakage current classifier models proposed in this study.
Financial Development and Economic Nexus in Nigeria : The Role of the Stock Market

The stock market has been touted as catalyst for economic growth as a result of its capacity to provide access to long term capital for industrialization and other projects requiring long term capital, especially in developing countries as Nigeria. In order to establish the pattern of the finance-growth nexus in Nigeria by adopting a time series technique and applying regression model estimation, this study sought to evaluate how the stock market has impacted economic growth in Nigeria following the recent liberalization and the subsequent market integration resulting from globalization. The study found long run relationship between the Gross Domestic Product per Capital Growth Rate (GDPGR) and the explanatory variables (stock market capitalization ratio; total value of shares traded, stock turnover ratio and financial liberalization). The Granger Causality Test results showed that there is a bi-directional relationship that runs from turnover ratio (TNVR) to stock market capitalization 9SMCR) and vice versa within 5% and 10% level of significance. Also, the results also showed that gross domestic product per capital growth rate (GDPGR), stock market capitalization ratio (SMCR), total value of shares traded (STR), and financial liberalization (FINLIB) jointly have causal effects on stock turnover ratio 9TNVR). The study concluded that economic growth and development has not been found invariant to dis-equilibrium in the stock market in Nigeria. It was, therefore, recommended that a policy rethink should be fashioned out to strengthen the stock market so as to enable it to play its pivotal role in the economic growth and development of Nigeria.
Modifications and Implications of Pricing Models : A Study of Assessed Property Values in Durham County , North Carolina

Determinants of property values have long been a central concern of urban economics. This paper explores the potential utility of using stochastic frontier functions, which assume the existence of a second, one-sided error term generated by inefficiency, to explain differentials in assessed property values. The reported empirical analyses employ both frontier functions and ordinary least-squares regressions to estimate the effects of standard property and community characteristics, such as acreage and distance from the city center, on property valuations. Additionally, the paper investigates the relationship between property values and land-use regulations, a relatively understudied factor in the shaping of local property markets. Data from Durham County, N.C. , suggest that frontier functions are not particularly suited to analyzing well-publicized property valuations, implying that systematic inefficiency contributes little to these figures. Nevertheless, the results reaffirm the importance of incorporating zoning designations, which have highly statistically and economically significant effects on home values, into future research on property prices.
Towards a Dedicated Data Model for Seamless Pedestrian Navigation

Awareness of one’s location at any given time is a fundamental human need. To navigate vehicles or persons, geodata are indispensable for calculating the route. At present, there is a lack of a proper database that meets the specific requirements for spatially inclusive and comprehensive pedestrian navigation. Therefore, firstly, real-world objects relevant for pedestrian navigation need to be determined. The selected and captured data, secondly, need to be structured and stored in an application-specific database to make proper use of them for orientation and navigation purposes. This paper deals with a pedestrian-focused data model and feature catalogue and selected aspects of data quality relevant for pedestrian navigation.
Retinal Prosthesis Effective : January 1 , 2019

PLEASE NOTE: Contracts exclude from coverage, among other things, services or procedures that are considered investigational or cosmetic. Providers may bill members for services or procedures that are considered investigational or cosmetic. Providers are encouraged to inform members before rendering such services that the members are likely to be financially responsible for the cost of these services.
A Study of Mammogram Classification using AdaBoost with Decision Tree, KNN, SVM and Hybrid SVM-KNN as Component Classifiers

In this article, authors focus on designing an algorithm using Hybrid SVM-KNN as component classiﬁer for AdaBoost. To obtain a set of eﬀective SVM-KNN component classiﬁers, algorithm adaptively adjusts the kernel parameters of KNN us-ing optimized parameters of SVM to form Hybrid SVM-KNN as component classiﬁer. In the proposed method, ﬁrst SVM is applied on training samples with σ = 1000. Initially equal weights are assigned to each tuple and updated weights are obtained. The updated weights from SVM are used as initial weights for KNN. Weighted average of predictions from both the models is obtained. Mammograms are represented by Grey Level Co-occurrence Matrix (GLCM) texture features. High dimensionality of feature space reduces the classiﬁcation accuracy. Extraction of relevant features to distinguish between benign and malignant class is important to improve the classiﬁcation performance. Au-thors use K-means clustering algorithm for features optimization to remove the redundant and irrelevant features from the original feature set. The performance of the AdaBoost with DT, KNN and SVM as component classiﬁer is compared with AdaBoost with Hybrid SVM-KNN in terms of accuracy and area under Receiver Operating Characteristic curve (ROC) value. Mammogram images from standard Digital Database for Screening Mammography (DDSM) and Mammography Image Analysis Society (MIAS) datasets are used. The experimental results demonstrated that AdaBoost with Hybrid SVM-KNN as a component classiﬁer gives better performance compared to other ensemble methods for mammogram classiﬁcation.
Values Embedded in Legal Artificial Intelligence

<bold>Increasingly, governments are</bold> using technological systems in the application and administration of law <xref ref-type="bibr" rid="ref6">[6]</xref>, <xref ref-type="bibr" rid="ref22">[22]</xref>. For example, officials use computer systems to sentence criminal defendants, approve or deny government benefits, predict the location of future crimes, and disallow border entry <xref ref-type="bibr" rid="ref6">[6]</xref>, <xref ref-type="bibr" rid="ref22">[22]</xref>. In each instance, technology is used to make substantive decisions about law, individual legal rights, or allocation of government resources. Let us refer to any automation system used in the administration or application of law as a “legal technological system. ” Notably, some of these legal technological systems use machine learning and other artificial intelligence techniques to achieve their goals <xref ref-type="bibr" rid="ref13">[13]</xref>. Let us refer to those as “legal AI systems. ”