Reviewerly/exHarmony huggingface dataset:
Security for the next generation

Computer Fraud & SecurityVol. 2019, No. 12 RegularsSecurity for the next generationAzeem AleemAzeem AleemNTTSearch for more papers by this authorAzeem AleemPublished Online:6 Nov 2021https://doi.org/10.1016/S1361-3723(19)30129-0AboutSectionsView articleView Full TextPDF/EPUB ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareShare onFacebookTwitterLinked InEmail View article FiguresReferencesRelatedDetails 1 January 2019Volume 2019Issue 12ISSN (print): 1361-3723ISSN (online): 1873-7056 Metrics History Published online 6 November 2021 Published in print 1 January 2019 Information© MA Business Ltd.PDF download
Admission Policy In Universities: In Search Of Empirical Evidence

This study set out to verify the hypothesis that ‘mature undergraduate students, in termsof chronological age, would signifi cantly perform better than immature undergraduatestudents academically’. Data on 679 undergraduate students were utilised in the study,out of which 375 were females and 304 were males. Their age ranged from 14 to 22years with standard deviation of 1.2 while mean age was 17.05 years. The Grade PointAverages [GPA] for 100 level and 200 level first and second semesters, called alphaand omega semesters in this study, were utilised. The parametric statistics employedfor analysis was the analysis of variance [ANOVA] which compared the GPA of theleast, average and most mature students categorised with age range of 14-16, 17-18,19-22 years respectively. The result showed that the least mature students, in terms ofchronological age, consistently featured significantly higher academic performance thanthe average and most mature students (Mean Diff. = 0.153, p = 0.033 for 100 levelalpha; Mean Diff. = 0.192, p = 0.0 for 200 level alpha). This finding tends to put toquestion the rationale for the adoption of the policy of not admitting applicants belowage 16 into public universities on the ground of immaturity. © IJSTR 2019.
Emergent Systematic Generalization In a Situated Agent

The question of whether deep neural networks are good at generalising beyond their immediate training experience is of critical importance for learning-based approaches to AI. Here, we demonstrate strong emergent systematic generalisation in a neural network agent and isolate the factors that support this ability. In environments ranging from a grid-world to a rich interactive 3D Unity room, we show that an agent can correctly exploit the compositional nature of a symbolic language to interpret never-seen-before instructions. We observe this capacity not only when instructions refer to object properties (colors and shapes) but also verb-like motor skills (lifting and putting) and abstract modifying operations (negation). We identify three factors that can contribute to this facility for systematic generalisation: (a) the number of object/word experiences in the training set; (b) the invariances afforded by a first-person, egocentric perspective; and (c) the variety of visual input experienced by an agent that perceives the world actively over time. Thus, while neural nets trained in idealised or reduced situations may fail to exhibit a compositional or systematic understanding of their experience, this competence can readily emerge when, like human learners, they have access to many examples of richly varying, multi-modal observations as they learn.
Corrigendum to “Next-to-Minimal SOFTSUSY” [Comput. Phys. Comm. 185 (2014) 2322–2339] (New Version Announcement)

The article in CPC 185 (2014) 2322 contained errors in the one- and two-loop beta functions of the ξS parameter of the NMSSM. These errors are corrected here. Program Title: SOFTSUSY Program Files doi: http://dx.doi.org/10.17632/5d5bs49jxh.1 Licensing provisions: GNU General Public License 3 Programming language: C++, fortran Journal reference of previous version: B. C. Allanach, P. Athron, L. C. Tunstall, A. Voigt and A. G. Williams, Comput. Phys. Commun. 185 (2014) 2322. Does the new version supersede the previous version?: Yes. Reasons for the new version: On page 21 of the original publication, a spurious factor of μjl was introduced in Eq. (D.48); the correct expression should read: (1)βξS(1)=2(λ2+κ2)ξS+4(λaλ+κaκ)ξF+2μ′(2λm32+κmS′2)+4[λμ(mH22+mH12)+κμ′mS2]+4aλm32+2aκmS′2. There are also three types of error in Eq. (D.49), namely On lines 1-3 the ξF factors in the O(λ2) terms should be brought within the {…} braces; On lines 11-12, the coefficient of the O(m32) terms should be 2, not 3. On line 12, the coefficient of the O(λg22) term should be 6, not 3. Thus the correct expression for Eq. (D.49) should read: (2)βξS(2)=−4λ4{ξS+4(aλ∕λ)ξF}−8κ4{ξS+4(aκ∕κ)ξF}−6λ2{ξSTr(YuYu†)+2[(aλ∕λ)Tr(YuYu†)+Tr(UAYu†)]ξF}−6λ2{ξSTr(YdYd†)+2[(aλ∕λ)Tr(YdYd†)+Tr(DAYd†)]ξF}−2λ2{ξSTr(YeYe†)+2[(aλ∕λ)Tr(YeYe†)+Tr(EAYe†)]ξF}−8λ2κ2{ξS+2[(aλ∕λ)+(aκ∕κ)]ξF}−12λ{m32[(aλ∕λ)+μ′]Tr(YuYu†)+m32Tr(UAYu†)+μ{Mu2+[(aλ∕λ)+μ′]Tr(UAYu†)+[mH12+mH22]Tr(YuYu†)}}−12λ{m32[(aλ∕λ)+μ′]Tr(YdYd†)+m32Tr(DAYd†)+μ{Md2+[(aλ∕λ)+μ′]Tr(DAYd†)+[mH12+mH22]Tr(YdYd†)}}−4λ{m32[(aλ∕λ)+μ′]Tr(YeYe†)+m32Tr(EAYe†)+μ{Me2+[(aλ∕λ)+μ′]Tr(EAYe†)+[mH12+mH22]Tr(YeYe†)}}−8λ3{m32[2(aλ∕λ)+μ′]+μ[Mλ2+(aλ∕λ)[(aλ∕λ)+μ′]+mH12+mH22]}−8λ2κ{mS′2[(aλ∕λ)+(aκ∕κ)+μ′]+μ′[Mλ2+(aλ∕λ)[(aκ∕κ)+μ′]+2mS2]}−8κ3{mS′2[2(aκ∕κ)+μ′]+μ′[Mκ2+(aκ∕κ)[(aκ∕κ)+μ′]+2mS2]}+65λg12{2m32[(aλ∕λ)+μ′−M1]+2μ[mH12+mH22−(aλ∕λ)M1−μ′M1+2M12]+λ[2ξF[(aλ∕λ)−M1]+ξS]}+6λg22{2m32[(aλ∕λ)+μ′−M2]+2μ[mH12+mH22−(aλ∕λ)M2−μ′M2+2M22]+λ[2ξF[(aλ∕λ)−M2]+ξS]}. Summary of revisions: See release 4.1.8 at https://softsusy.hepforge.org/. Declaration of competing interest: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Homo Digital: Formula of Consumption (A Shirt Organum)

An attempt to outline the issues that the digital age poses to art studies has been made; upon completing his research journey, the author tries to solve the digital culture coordinates equation, its configuration and consumption formula, based on the author and someone else’s empirical observation of already partially digitized consciousness and inherent art consumption forms.
Adaptive Estimation of Spatial Clutter Measurement Density Using Clutter Measurement Probability for Enhanced Multi-Target Tracking

The point detections obtained from radars or sonars in surveillance environments include clutter measurements, as well as target measurements. Target tracking with these data requires data association, which distinguishes the detections from targets and clutter. Various algorithms have been proposed for clutter measurement density estimation to achieve accurate and robust target tracking with the point detections. Among them, the spatial clutter measurement density estimator (SCMDE) computes the sparsity of clutter measurement, which is the reciprocal of the clutter measurement density. The SCMDE considers all adjacent measurements only as clutter, so the estimated clutter measurement density is biased for multi-target tracking applications, which may result in degraded target tracking performance. Through the study in this paper, a major source of tracking performance degradation with the existing SCMDE for multi-target tracking is analyzed, and the use of the clutter measurement probability is proposed as a remedy. It is also found that the expansion of the volume of the hyper-sphere for each sparsity order reduces the bias of clutter measurement density estimates. Based on the analysis, we propose a new adaptive clutter measurement density estimation method called SCMDE for multi-target tracking (MTT-SCMDE). The proposed method is applied to multi-target tracking, and the improvement of multi-target tracking performance is shown by a series of Monte Carlo simulation runs and a real radar data test. The clutter measurement density estimation performance and target tracking performance are also analyzed for various sparsity orders.
The rwandan miracle

A quarter of a century after the terrible genocide of 1994, Rwanda is turning a new page in its history. Following a long period of national unification and reconciliation, it is investing in economic growth and focusing on new technologies, with the hope of becoming an ICT hub in Africa.
Analisis dan Desain Sistem Informasi Penelitian dan Pengabdian Masyarakat (Simpenmas) Politeknik Negeri Lhokseumawe

Information systems of research and community service need to be developed to improve the management of research outputs and community service outcomes by lecturers while making it easier to evaluate tertiary accreditation. This system was developed using the waterfall model. This article aims to describe the stages of system development consisting of: (1) investigating user needs; (2) data and needs analysis in the process of making a system; (3) design; and (4) implementation. The result is the need for a system that specifically can provide facilities for uploading research outputs and community service such as journal publications, textbooks / texts, and scientific forum speakers. In addition to other mandatory menus, menus that are also being developed are the daily notes menu and the progress report menu. The design stages produce the design of the menu flow. The implementation stages of the research and community service information system use PHP language using the Laravel framework. Future studies need to test the use of systems that can use Apache jmeter and Selenium.
ANALISIS KEKERINGAN PADA DAERAH ALIRAN SUNGAI (DAS) BEDADUNG BERBASIS SISTEM INFORMASI GEOGRAFIS (SIG)

The reduced of water availability toward the needs is one thing that indicates the occurrence of a drought. The drought has received more attention from Government of Jember Regency in the form of a drought disaster area management direction. The location of this research is in the Bedadung River Basin with 13 rainfall station located in the upstream of Rowotamtu AWLR Station. Drought analysis uses the Palmer Drought Severity Index method in the form of index that informs the level of drought in an area. The results of the study showed that drought with extreme dry classification occurs from June to October with drought index values ranging from -1,82 (on June) to -14,14 (on October). Patrang, Jelbuk, Arjasa and Panti sub-districts are areas that have experienced drought with a duration of 5 months. Palmer method meteorological drought index and hydrological drought index (value of AWLR Discharge Standardized Box Cox Transformation (Z)) have unidirectional relationship and high degree of relationship, with the Pearson correlation coefficient, r = 0,91
The Research University’s Dilemma: Resource Sharing and Research in a Transinstitutional Environment

Rising publication costs and declining financial resources have resulted in renewed interest among librarians in resource sharing. Although the idea of sharing resources is not new, there is a sense of urgency not seen in the past. For many libraries, obtaining even basic works has become a challenge and frequency of use is playing a greater part in library decisions, ranging from where books are shelved (on or off site), which books go to the head of the queue for preservation, and even which books are acquired. Driven by rising publication costs and static and often shrinking budgets, librarians are embracing resource sharing as an idea whose time may finally have come.
NARX-NN MODEL OF 2-DOF ROBOT ARM DYNAMICS DRIVEN BY FLUIDIC MUSCLES

The article contains the results of identification of manipulator arm dynamics that is driven by pneumatic artificial muscles (specifically, fluidic muscles).The NARX architecture model -a multilayer perceptron network (MLP model) was selected for identification.Simulations were realized using MATLAB, especially with use the System Identification Toolbox.The simulation results were tracked at 3 different delays for the upper and lower axis of the manipulator separately.The NRMSE criterion (Normal Root Mean Square Error) serves to compare simulation results by comparing output of simulations and measured output data.
Hyperspectral image classification with imbalanced data based on oversampling and convolutional neural network

Data imbalance is a common problem in hyperspectral image classification. The imbalanced hyperspectral data will seriously affect the final classification performance. To address this problem, this paper proposes a novel solution based on oversampling method and convolutional neural network. The solution is implemented in two steps. Firstly, SMOTE(Synthetic Minority Oversampling Technique) is used to enhance the data of minority classes. In the minority classes, SMOTE method is used to generate new artificial samples, and then the new artificial samples are added to the minority classes, so that all classes in the training dataset can reach to the balanced distribution. Secondly, According to the data characteristics of hyperspectral image, a convolutional neural network is constructed for classifying the hyperspectral image. The balanced training data set is used to train the convolutional neural network. We experimented with the proposed solution on the Indian Pines, Pavia University dataset. The experimental results show that the proposed solution can effectively solve the problem of imbalanced hyperspectral data and improve the classification performance.
Identity Management Controls in the Cyber Kill Chain

Managing and appropriately governing identities using an Identity Governance solution can make a big difference to the security posture of an organization. To best understand how, we must first learn from our collective past mistakes and omissions. Looking back over recent data breach reports and examining the forensic and post-incident analysis, we notice two things relative to the discussion on identity management controls. The first is that threat sophistication is increasing at a furious rate. The adversary is persistent and well funded and knows where best to attack and pursue persistence. The second is that these forensic reports clearly show that identity management mistakes and weaknesses are the common faults in many breaches. These identity management mistakes and process weaknesses are things like poor account controls; weak passwords; orphan, dormant, and rogue accounts; weak inventory of entitlements; and the over-assignment of user privileges. These mistakes and management missteps tend to be spread across the Cyber Kill Chain.
Mapping the internal structures of fault zones of the sedimentary cover: a tectonophysical approach applied to interpret TDEM data (Kovykta gas condensate field)

The article presents the results of studying the internal structures of platform fault zones with the use of a new tectonophysical approach to processing and interpretation of electrical exploration data obtained by the transient elec‐ tromagnetic method in the near field zone (TEM). In the study of the central part of the Kovykta gas condensate field (East Siberia, Russia), we applied the ideas of tectonophysics envisaging three stages of fault formation, which determine the three‐membered transverse zoning of a fully formed fault zone. Each subzone is characterized by a certain level of rock disturbance and corresponding electrical conductivity. Based on the analysis of electrical conductivity values, the boundaries can be determined between locations differing by the degrees of rock disturbance of the sedimentary stra‐ tum. Using a map of this parameter, it becomes possible to generally establish the boundaries of fault zones and specify internal subzones. The new approach was applied to assess the electrical conductivity of the reservoirs of the Kovykta field. It is established that there are several zones of faulting in the sedimentary stratum, which have not reached a final stage of development when a single fault plane is formed. Currently, these are zones of increased fracturing and dense occurrence of second‐order ruptures that are typical of platform settings due to their relatively weak tectonic activity. The zones are structurally non‐uniform, as evidenced by rheological layering of the sedimentary cover in the vertical cross‐section. A 3D electrical conductivity model of the largest fault zone in the study area shows alternating segments with more or less developed internal structures. Such segments are confined to layers that differ with respect to frac‐ turing. Exploration and development of hydrocarbon deposits can benefit from 3D modeling of large fault zones with the use of the tectonophysical approach for processing and interpretation of the TEM data. The models can provide addition‐ al arguments for improved decision making about locations for trouble‐free well drilling, as well as for selecting more effective methods for drilling sedimentary strata composed of complex horizontal layers.
Planning and Implementing Inclusive Designs

Implementing accessibility/inclusivity and making changes to workflow can come with many opportunities. Change does not often come easily. Making swift changes can cause friction between teams and individuals. Implementing change needs to be approached with understanding for what each team will need to address. Laying out how people can participate in the process is helpful. Whether you are a designer or developer, the tips in this chapter will guide you in these areas.
PCN429 THE GENERATION OF SYNTHETIC CLINICAL TRIAL DATA

Making clinical trial data available for secondary analysis and building innovative AI/machine learning models requires addressing privacy concerns. These concerns exist whether the data is shared internal or external to the organization. An effective way to address these concerns is through the creation of synthetic data. Synthetic data was generated for a trial that assessed the efficacy of a new adjuvant chemotherapy for patients with gastrointestinal stromal tumors (available via Project Data Sphere). A classification tree method was used to create a synthetic data that retains the distributions and dependencies in the trial data. A comprehensive analysis of the data utility of the synthesized data was performed to determine if similar conclusions can be drawn from the synthetic dataset as from the original dataset. Utility tests included: comparisons of distributions, descriptive statistics, complex multivariate models, including propensity scores and the model’s associated predictive error. The synthetic data had almost identical distributions as the original data. Absolute differences in bivariate correlations were very small across all comparisons. The differences in the area under the ROC curve across all possible multivariate models built using CART were less than 0.05, and the absolute relative differences for continuous outcomes had a median below 20%. Global propensity scores statistics indicate that there was no substantial difference between the original and synthetic data. The utility analysis indicated that the synthetic data preserved the relationships between variables from the original data, using a simple data generation method. Synthetic data methods should be considered at least for exploratory secondary analysis on clinical trial data as they are relatively efficient to operationalize while mitigating privacy concerns.
USING OF METHODS OF CROSS-CORRELATION AND REGRESSIVE ANALYSIS FOR DETERMINATION OF FUNCTIONAL DEPENDENCE BETWEEN SIZES

In article it is told about use of methods of correlation and regression analysis when determining functional dependence between values. When studying different objects of a research in laboratory or working conditions there is a need of establishment of the most probable interrelations and interdependence between two or more variable. Sometimes it happens simply as communication easily is found or is in advance known from any theoretical premises. However identification of such communications between different indicators, factors is much more often, signs is extremely difficult task. Researchers face need of introduction of some hypothesis of the nature of communication in the form of functional dependence, i.e. approximation by its some rather simple mathematical expression, for example, linear equation or a polynomial. Methods of correlation and regression analyses are very useful to search of such mathematical functional or structural dependences between two or more variable (on the saved-up experimental data).
The Influence of the Device on User Performance in Handheld Augmented Reality

Augmented Reality applications, which were known to require sophisticated hardware, can now be run on handheld devices. Although such devices provide the required computer power, the size or weight of some of them may become a barrier to user performance, mainly when the interaction is by the touch on the screen. Inserted in this context, this research consists of applying a set of subjective experiments in which volunteers use an application that runs on devices with different sizes and weights. These experiments aim to measure how much the type of handheld device influences the performance of the user in Augmented Reality applications. The main contributions of this study are (i) we concluded by subjective experiments that users with previous knowledge of how to interact with a similar AR application or a game are able to improve their performance when the device is larger and (ii) we demonstrated the age of the participant was also a good indicator of the user performance in AR applications.
Three-dimensional Region Forgery Detection and Localization in Videos

Nowadays, with the extensive use of cameras in many areas of life, every day millions of videos are uploaded on the internet.In addition, with rapidly developing video editing software applications, it has become easier to forge any video.These software applications have made it challenging to detect forged videos, especially with forged videos have duplication of three-dimensional (3-D) regions.Recently, there has been increased interest in detecting forged videos, but there are very limited studies to detect forged videos which were duplicated 3-D regions.So, our research focused on this weakness and proposed a new method, which can be used for detecting and locating 3-D duplicated regions in videos based on the phase-correlation of 3-D regions residual more efficiently.To evaluate the efficiency of the proposed method, we experimented with two realistic datasets VFDD-3D and REWIND-3D.The results of the experiments proved that the proposed method is efficient and robust for detecting small 3-D regions duplication and frame sequences duplication, especially localization of duplication forgery in videos has shown impressive results.
PENERAPAN MODEL PEMBELAJARAN SAVI UNTUK MENINGKATKAN AKTIVITAS BELAJAR SISWA

The background of this research is still low student learning activities in learning where students with high learning activities that is 34%, while students who low learning activies that is 66%. This research was conducted in one elementary school of Bandung with the subject of the study were students as many as 23 students, consisting of 9 male students and 14 female students. PTK is done by applying SAVI learning model consisting of 4 stages, namely: (1) preparation stage, (2) delivery stage, (3) stage of training, (4) stage of delivery of results. Indicators of learning activities measured in this study, namely: (1) Students learn in the form of groups to solve the problem. (2) Every student participates in carrying out their learning tasks in various ways. (3) Students dare to submit an opinion. (4) Students do learning activity analysis, synthesis, assessment and conclusion. (5) Each student has the opportunity to use the various learning resources available. (6) There is an effort from the students to ask the teacher and ask the teacher's opinion in the effort of learning activity. The results of this study found that there is an increase in learning activities by applying SAVI learning model, and showed an increase in student learning activities from cycle I of 72% to 88% in cycle II. This research can reference about the application of SAVI learning model to improve the activity of learning class V SD