Miracle-dz/UniFAR-FTUs huggingface dataset:
Fraud Detection Using Data Mining Techniques

- Data mining technology is applied to fraud detection to establish the fraud detection model, describe the process of creating the fraud detection model, then establish data model with ID3 decision tree, and establish example of fraud detection model by using this model. As e-commerce sales continue to grow, the associated online fraud remains an attractive source of revenue for fraudsters. These fraudulent activities impose a considerable financial loss to merchants, making online fraud detection a necessity. The problem of fraud detection is concerned with not only capturing the fraudulent activities, but also capturing them as quickly as possible. This timeliness is crucial to decrease financial losses.
Enhancing throughput and load balancing in software-defined networks

Software Defined Networks decouples the control plane and data plane of a network. Using the capabilities of SDN a network manager can enhance the performance, efficiency and throughput of a network. Traditional networks cannot resourcefully utilize a mesh topology or a topology having multiple paths available. In this paper we used two different approaches to utilize a multi-path topology; the forwarding strategy which we used is a proactive strategy which assigns different flows over multiple paths. We also performed experiments to measure throughput and the impact on performance by increasing the TCP window size. It was observed that increasing TCP window size with 5000 bytes improved performance minimum of 11.11% and maximum of 20% in terms of data transfer.
Prevalence of hepatitis C virus infection and response to hepatitis B vaccination among Egyptian school children

Background: A prevalence of hepatitis C virus (HCV) infection is relatively low in children as it was 3% and 9% in the upper and lower Egypt areas, respectively. Most chronic hepatitis C patients are asymptomatic and unaware of their disease before diagnosis. Similarly, hepatitis B virus (HBV) is a major cause of chronic liver disease, particularly cirrhosis and hepatocellular carcinoma, though HBV incidence and infection has been markedly reduced after mass vaccination programs. Objectives: To identify the prevalence and risk factors of asymptomatic HCV infection and evaluate response of hepatitis B vaccination among Egyptian children. Materials and Methods: Six hundred children (6-17 years) were screened for HCV antibodies (HCV Ab) and hepatitis B surface antibody concentration (HBsAb) was quantitated by enzyme-linked immunosorbent assay. HCV Ab-seropositive was tested for HCV ribonucleic acid by real-time-polymerase chain reaction, complete blood count, and liver function tests. Results: 4.7% were diagnosed as HCV Ab-seropositive and 58.5 % as HBsAb-seroprotective (HBsAb ≥10 mIU/ml). History of exposure to blood transfusion, frequent intravenous injection, history of prior hospitalization and blood exposure were significantly more likely to be among HCV seropositive. Blood transfusion was considered the most predictable risk factor for HCV infection. There was a significant decrease in HBsAb concentration with increasing age. Conclusion: Booster dose of hepatitis B vaccine should be considered to enhance immune protection of the vaccine especially in our endemic area.
Neighborhood Associations and Social Capital

In the United States, the past 50 years have witnessed a remarkable expansion of formal associations in residential neighborhoods, including homeowners associations, condo associations, crime watch groups, tenant associations, and special-interest neighborhood coalitions. Despite their prevalence and growing role in neighborhood governance, the relationship of these associations to interpersonal trust and networks among residents and outsiders remains understudied. Drawing on the Social Capital Community Benchmark Survey (SCCBS), we estimate the impact of neighborhood association membership on bonding and bridging social capital in a nationally representative sample of residents. Among non-homeowners, our findings suggest that neighborhood association membership is linked to bonding social capital (such as a propensity to socialize and cooperate with neighbors and a positive perception of impact on community conditions), as well as bridging social capital (such as a greater likelihood of trust in racial out-groups). These benefits from neighborhood association membership are attenuated or reversed among homeowners. The results underscore the need for social scientists to consider the inherent tension in neighborhood associations, as institutions that ensure the protection of property values, on the one hand, and that promote neighborhood cooperation and quality of life, on the other.
Gas sensor based on a metal oxide nanowire forest built on a suspended carbon nano-heater

This paper reports a novel metal oxide nanowire (MOx NW) based gas senor built on a suspended carbon nanowire heater allowing ultra-low power consumption. This sensing platform was fabricated using only wafer level batch fabrication processes such as carbon-MEMS, atomic layer deposition, and hydrothermal growth processes. Owing to the mechanical rigidity, the suspended carbon nanowire allows selective circumferential growth of MOx NWs on its surface. The suspended carbon NW and MOx NWs are electrically separated with a thin HfO2 layer. In addition, the suspended high-aspect-ratio geometry of the carbon NW enables MOx NWs to be heated with ultra-low power Joule heating. The architecture of the suspended nanowire forest ensures efficient gas access to the sensing sites, detecting NO2 as low as 100 ppb.
A Review of Big Data Processing in GeoLocation Based Cost Minimization

Cost minimization is important issue in the processing of big data for geo-located data centers. For the minimization of cost used switched network group for the estimation of nearest data centers. The selection of nearest data center for the storage and retrieval of data precede huge amount of traffic on local server. For the processing of these server required large expansion for the maintains such as power backup and cooling system. For the optimization of cost the processing of data divided into three section task assignment, data placement and data movement. The process of task assignment optimized by different optimization algorithm for proper selection of path for data delivery. In the process of optimization used independent algorithm and hybrid algorithm. In this paper presents the review of cost optimization process and function of big data over data centers.
Disaster Recovery as a Cloud Service: Economic Benefits & Deployment Challenges

Many businesses rely on Disaster Recovery (DR) services to prevent either manmade or natural disasters from causing expensive service disruptions. Unfortunately, current DR services come either at very high cost, or with only weak guarantees about the amount of data lost or time required to restart operation after a failure. In this work, we argue that cloud computing platforms are well suited for offering DR as a service due to their pay-as-you-go pricing model that can lower costs, and their use of automated virtual platforms that can minimize the recovery time after a failure. To this end, we perform a pricing analysis to estimate the cost of running a public cloud based DR service and show significant cost reductions compared to using privately owned resources. Further, we explore what additional functionality must be exposed by current cloud platforms and describe what challenges remain in order to minimize cost, data loss, and recovery time in cloud based DR services.
Analyzing recognition: identification, acknowledgement and recognitive attitudes towards persons

There is a wide consensus today that ‘recognition’ is something that we need a clear grasp of in order to understand the dynamics of political struggles and, perhaps, the constitution and dynamics of social reality more generally. Yet the discussions on recognition have so far often been conceptually rather inexplicit, in the sense that the key concepts have remained largely unexplicated or undefined. Since the English word ‘recognition’ is far from unambiguous, it is possible, and to our mind also actually the case, that different authors have meant different things with this word. In what follows, we will make a number of conceptual distinctions and clarificatory proposals that are intended to bring to more sharply focus the field of phenomena that are being discussed under the catchword ‘recognition. ’ This is meant to serve a dual purpose: to suggest a number of distinctions that are of help in formulating rival views, and to propose what strikes us as the best overall position formulated in terms of those distinctions. Our proposals are meant to be, by and large, compatible with Axel Honneth's work on recognition, which to us is the most ambitious and differentiated account of recognition available. Where we propose something that seems to us to be in compatible with Honneth's explicit formulations, we indicate it in the footnotes.
Personal Authentication based on Angular Geometric Analysis using Finger Back Knuckle Surface

In this paper a new authentication system using Finger Back Knuckle Surface is examined. This paper is intended to propose an effectual method for personal authentication using Finger Back Knuckle Surface. This method take advantage of the less number of features extracted from the Finger Back Knuckle Surface and the Angular geometric analysis is done to mine the distinguishable feature information which is computationally less complex. This is achieved by the determination of convex curves from the finger back knuckle surface. From the recognized feature curves, the subset features like Knuckle Edge points, Knuckle Tip points and Knuckle Base Points are identified. From these features, geometrical structures like scalene triangles were constructed to obtain feature information in terms of angle. This method reduces critical problems that arise due to the extraction of more number of features. Also reduces the computational complexity of the feature extraction and recognition process.
Object manipulation of a humanoid robot based on visual Servoing

Vision is a very important noncontact sensor for humanoid robots. In this paper, a method combining visual feedforward and visual feedback is proposed to implement reach-to-grasp task for a humanoid robot. Visual feedforward facilitates the reach-to-grasp task and reduces the manipulation time. Visual feedback increases the robustness by compensating the weak calibration error. The combination of two control strategies facilitates reach-to-grasp task for a humanoid robot. The robustness of the system is confirmed by the experiment results.
Insulin receptor in the brain: Mechanisms of activation and the role in the CNS pathology and treatment

While the insulin receptor (IR) was found in the CNS decades ago, the brain was long considered to be an insulin‐insensitive organ. This view is currently revisited, given emerging evidence of critical roles of IR‐mediated signaling in development, neuroprotection, metabolism, and plasticity in the brain. These diverse cellular and physiological IR activities are distinct from metabolic IR functions in peripheral tissues, thus highlighting region specificity of IR properties. This particularly concerns the fact that two IR isoforms, A and B, are predominantly expressed in either the brain or peripheral tissues, respectively, and neurons express exclusively IR‐A. Intriguingly, in comparison with IR‐B, IR‐A displays high binding affinity and is also activated by low concentrations of insulin‐like growth factor‐2 (IGF‐2), a regulator of neuronal plasticity, whose dysregulation is associated with neuropathologic processes. Deficiencies in IR activation, insulin availability, and downstream IR‐related mechanisms may result in aberrant IR‐mediated functions and, subsequently, a broad range of brain disorders, including neurodevelopmental syndromes, neoplasms, neurodegenerative conditions, and depression. Here, we discuss findings on the brain‐specific features of IR‐mediated signaling with focus on mechanisms of primary receptor activation and their roles in the neuropathology. We aimed to uncover the remaining gaps in current knowledge on IR physiology and highlight new therapies targeting IR, such as IR sensitizers.
of Geophysical Research : Atmospheres Subregional inversion of North African dust sources

The emission of mineral dust aerosols in arid and semiarid regions is a complex process whose representation in atmospheric models remains crude, due to insufficient knowledge about the aerosol lifting process itself, the lack of global data on soil characteristics, and the impossibility for the models to resolve the fine-scale variability in the wind field that drives some of the dust events. As a result, there are large uncertainties in the total emission flux of mineral dust, its natural variability at various timescales, and the possible contribution from anthropogenic land use changes. This work aims for estimating dust emissions and reduces their uncertainty over the Sahara desert and the Arabian Peninsula—the largest dust source region of the globe. We use a data assimilation approach to constrain dust emission fluxes at a monthly resolution for 18 subregions. The Moderate Resolution Imaging Spectroradiometer satellite-derived aerosol optical depth is assimilated in a regional configuration of a general circulation model coupled to an aerosol model. We describe this data assimilation system and apply it for 1 year, resulting in a total mineral dust emissions flux estimate of 2900 Tg yr−1 over the Sahara desert and the Arabian Peninsula for the year 2006. The analysis field of aerosol optical depth shows an improved fit relative to independent Aerosol Robotic Network measurements as compared to the model prior field.
Therapeutic potential to reduce brain injury in growth restricted newborns

Brain injury in intrauterine growth restricted (IUGR) infants is a major contributing factor to morbidity and mortality worldwide. Adverse outcomes range from mild learning difficulties, to attention difficulties, neurobehavioral issues, cerebral palsy, epilepsy, and other cognitive and psychiatric disorders. While the use of medication to ameliorate neurological deficits in IUGR neonates has been identified as warranting urgent research for several years, few trials have been reported. This review summarises clinical trials focusing on brain protection in the IUGR newborn as well as therapeutic interventions trialled in animal models of IUGR. Therapeutically targeting mechanisms of brain injury in the IUGR neonate is fundamental to improving long‐term neurodevelopmental outcomes. Inflammation is a key mechanism in neonatal brain injury; and therefore an appealing target. Ibuprofen, an anti‐inflammatory drug currently used in the preterm neonate, may be a potential therapeutic candidate to treat brain injury in the IUGR neonate. To better understand the potential of ibuprofen and other therapeutic agents to be neuroprotective in the IUGR neonate, long‐term follow‐up information of neurodevelopmental outcomes must be studied. Where agents such as ibuprofen are shown to be effective, have a good safety profile and are relatively inexpensive, they can be widely adopted and lead to improved outcomes.
ULTRASIMPLE CALCULATION OF VERY-LOW-ENERGY MOMENTUM-TRANSFER AND ROTATIONAL-EXCITATION CROSS SECTIONS : E-N2 SCATTERING

The calculation of electron-molecule cross sections at scattering energies well below 0.1 eV using conventional algorithms for solving the Schroedinger equation is often rendered problematic by severe numerical problems. Here we describe and implement an alternative procedure that combines known analytic properties of the body-frame electron-molecule scattering matrix, as codified in the modified effective range theory, with an analytic correction that imposes physically correct threshold laws. This approach eliminates completely the need for numerically solving the Schroedinger equation at energies below about 0.1 eV. Instead, one uses scattering matrices above this energy to determine parameters for an extrapolation to subthermal energies. We apply this method to the calculation of e-N{sub 2} momentum-transfer and rotational excitation cross sections from threshold to 1.25 eV. The results resolve a long-standing apparent anomaly in the analysis of experimental data for very low-energy electron scattering from N{sub 2}. Finally, we use linear regression to present our theoretical results in a user-friendly form. {copyright} {ital 1997} {ital The American Physical Society}
Assessment of Left Ventricular Function and Volume in Patients Undergoing 128-Slice Coronary CT Angiography with ECG-Based Maximum Tube Current Modulation: a Comparison with Echocardiography

Objective To compare multi-detector CT (MDCT) using 128-slice coronary CT angiography (Definition AS+, Siemens Medical Solution, Forchheim, Germany) with ECG-based maximum tube current modulation with echocardiography for the determination of left ventricular ejection fraction (LVEF), end-diastolic volume (EDV), end-systolic volume (ESV), as well as assessing coronary artery image quality and patient radiation dose. Materials and Methods Thirty consecutive patients (M:F = 20:10; mean age, 57.9 ± 11.4 years) were referred for MDCT for evaluation of atypical chest pain. EF, EDV and ESV were determined for both MDCT and echocardiography, and the correlation coefficients were assessed. Coronary artery segment subjective image quality (1, excellent; 4, poor) and radiation dose were recorded. Results Left ventricular EF, EDV, and ESV were calculated by MDCT and echocardiography and the comparison showed a significant correlation with those estimated by echocardiography (p < 0.05). Consistently, the LVEFs calculated by MDCT and echocardiography were not statistically different. However, LV, EDV and ESV from MDCT were statistically higher than those from echocardiography (p < 0.05). The average image quality score of the coronary artery segment was 1.10 and the mean patient radiation dose was 3.99 ± 1.85 mSv. Conclusion Although LV volume was overestimated by MDCT, MDCT provides comparable results to echocardiography for LVEF and LVV, with a low radiation dose.
False-Positive Psychology

In this article, we accomplish two things. First, we show that despite empirical psychologists’ nominal endorsement of a low rate of false-positive findings (≤ .05), flexibility in data collection, analysis, and reporting dramatically increases actual false-positive rates. In many cases, a researcher is more likely to falsely find evidence that an effect exists than to correctly find evidence that it does not. We present computer simulations and a pair of actual experiments that demonstrate how unacceptably easy it is to accumulate (and report) statistically significant evidence for a false hypothesis. Second, we suggest a simple, low-cost, and straightforwardly effective disclosure-based solution to this problem. The solution involves six concrete requirements for authors and four guidelines for reviewers, all of which impose a minimal burden on the publication process.
Running title : Hydraulic Vulnerability Segmentation in Grapevine

been through the copyediting, typesetting, pagination and proofreading process which may lead to differences between this version and the Version of Record. Please cite this article as doi: 10.1111/pce.12688 This article is protected by copyright. All rights reserved. Grapevine petioles are more sensitive to drought induced embolism than stems: evidence from in vivo MRI and microCT observations of hydraulic vulnerability segmentation. Running title: Hydraulic Vulnerability Segmentation in Grapevine Uri Hochberg, Caetano Albuquerque, Shimon Rachmilevitch, Herve Cochard, Rakefet DavidSchwartz, Craig R. Brodersen, Andrew McElrone, and Carel W. Windt
A Graph-Based Approach for Containment Checking of Behavior Models of Software Systems

In the development of complex and large scale software systems, it is important to detect and fix the deviations of systems' behaviors at different abstraction levels in early phases. Our main focus here is the containment checking-a special type of consistency checking-that verifies whether the behavior (or functions) described by a low-level behavior model encompasses those specified in the high-level counterpart. As shown in our previous work, containment checking can be realized based on model checking, but not always the costly exhaustive searches employed by model checking are necessary for addressing the containment checking problem, leading to potentials for optimization. In addition, model checking and similar techniques often yield the checking results as true (satisfied) or false (unsatisfied) with error traces (e.g., Counter-examples). Unfortunately, such feedback is rather not helpful for users with limited background on the underlying formal methods to analyze and understand the causes of consistency violations. In this paper, we propose a lightweight graph-based approach for addressing the aforementioned problems of containment checking. The theoretical complexity of our approach is a cubic polynomial of the number of elements of the input behavior models. Additionally, we aim at generating feedbacks that are relevant and easy-to-understand for the stakeholders. Our approach is illustrated and evaluated on UML activity diagrams-that are widely used for modeling behaviors of software systems-using use cases derived from industrial scenarios.
Human behaviour and economic growth: A psychocultural perspective on local and regional development

A renewed emphasis on behavioural traits has emerged as a means of explaining regional and local differences in economic performance and development. Given this, the aim of this study is to identify distinct local psychocultural behavioural profiles, and to examine the extent to which these are associated with economic growth. Combining theories of community culture and personality psychology into a holistic spatially oriented perspective, the paper argues that the types of human behaviour found across local places emerges from the co-evolution of cultural and personality factors. An empirical analysis of localities in Great Britain identifies and explores three underlying psychocultural profiles: Diverse Extraversion; Inclusive Amenability and Individual Commitment. It is found that inclusive amenable and individually committed psychocultural behaviour generally appear to hold back local economic growth, with the exception of recessionary periods. The reverse relationship is somewhat the case for diverse extravert behaviour. It is concluded that a better understanding of the holistic relationship and co-evolution of the cultural and psychological behavioural make-up of localities and regions has the potential to provide new insights into expected development outcomes as well as the forms of policy intervention that are required within regions and localities, each of which has its own individual psychocultural character.
Performance Anxiety among Professional Musicians in Symphonic Orchestras: A Self-Report Study:

155 of 650 professional musicians playing in symphonic orchestras in The Netherlands completed a self-report questionnaire concerning performance anxiety. 91 of the 155 respondents reported experiencing or having experienced performance anxiety seriously enough to affect their professional or personal lives. There appeared to be no difference in prevalence between men and women. Substantial percentages of the anxious musicians reported considerable anticipation anxiety days (36%), weeks (10%), or even months (5%) prior to a performance. The results indicate that performance anxiety is a significant professional problem. It is suggested that teaching explicit coping strategies should be incorporated in the curricula of schools of music.