Miracle-dz/UniFAR-FTUs huggingface dataset:
Effectiveness of Cybersecurity Competitions

—There has been a heightened interest among U.S. government agencies to fund cybersecurity workforce development. These efforts include offering universities funding for student scholarships, funding for building capacity in cyberse-curity education, as well as sponsoring cybersecurity competitions, games, and outreach programs. This paper examines the effectiveness of cybersecurity competitions in educating students. Our study shows that though competitions do pique students’ interest, the effectiveness of this approach in producing more high quality professionals can be limited. One reason is that the knowledge barrier to compete in these competitions is high. To be successful, students have to be proﬁcient in operating systems, application services, software engineering, system administration and networking. Many Computer Science and Information Technology students do not feel qualiﬁed, and consequently this reduces participation from a wider student audience. Our approach takes aims at lowering this barrier to entry. We employ a hands-on learning methodology where students attend lectures on background knowledge on weekdays and practice what they learn in weekend workshops. A virtual networking environment is provided for students to practice network defense in the workshops and on their own time.
Estimation of microseismic source parameters for 3D orthorhombic media by waveform inversion

Accurate event location and estimation of the source moment tensors are among the main goals of microseimic data processing. An improvement over conventional methods can be achieved by applying anisotropic waveform inversion (WI). Here, we extend our 3D elastic WI algorithm for anisotropic velocity model-building from microseismic borehole data to include estimation of event locations, moment tensors, and origin times. The methodology is designed for microseismic sources embedded in arbitrarily heterogeneous media with orthorhombic or transversely isotropic (TI) symmetry. We illustrate the performance of WI using synthetic data from layered orthorhombic media simulated for typical acquisition geometries. The tests confirm the ability of the algorithm to recover the source parameters provided that the velocity model is known with sufficient accuracy.
The Induced Membrane Technique for the Management of Segmental Tibial Defect or Nonunion: A Systematic Review and Meta-Analysis

Purpose To identify the predicting factors for union and infection after applying the induced membrane technique (IMT) for segmental tibial defects. Methods A systematic review was carried out following the PRISMA guidelines. All databases were searched for articles published between January 2000 and February 2018 using the keywords “Masquelet technique” and “induced membrane technique. ” Studies in English reporting more than 5 cases with accessible individual patient data were included. A meta-analysis was performed. Odds ratios (OR) with 95% confidence intervals were calculated. Results After reviewing, 11/243 studies (115 patients) were finally selected. The mean age of the patients was 43.6 years (range: 18-84 years), and the mean length of the tibial defect was 5.5 cm (range: 0-20 cm). The multivariate logistic regression analysis revealed that the risk factors of postoperative infection after IMT were infected nonunion (p = 0.0160) and defect length ≥ 7 cm (p = 0.0291). Patients with postoperative infection after IMT had a lower union rate (p = 0.0003). Additionally, the use of an antibiotic polymethyl methacrylate cement spacer reduced the need for surgical revision (p = 0.0127). Multiple logistic regression indicated no direct association between the union rate and length of the bone defect. Conclusions IMT is a reliable and reproducible treatment for segmental tibial defects. However, initial infected nonunion and defect length greater than 7 cm are risk factors for post-IMT infection, and post-IMT infection was statistically related to nonunion.
An Effective Detection Framework for Activities in Surveillance Videos

Recently some works are proposed to detect atomic actions of a single actor in unrealistic videos, such as movies. But they cannot be effectively applied to activity detection in surveillance videos. In this paper, we introduce an effective three-stage framework for spatiotemporal activity localization in surveillance videos. We devide the spatiotemporal activity localization task into three subtasks: spatial activity localization, activity tube tracking, and temporal activity detection. For spatial activity localization, we generalize Faster-RCNN to 3D form to localize activity regions in a short video clip. To the best of our knowledge, we are the ﬁrst to extend object detector to detect activity regions in videos. For activity tube linking, we extend the object tracking algorithm to track activity tubes. For temporal activity localization, we build efﬁcient temporal localization systems to detect activity instances. Experiments on VIRAT dataset demonstrate the effectiveness of our model. Besides, our framework is efﬁcient as we don’t need to process every frame of videos. With this effective and efﬁcient framework, we got w pmiss@0.15rfa 0.693 on TRECVID-ActEV test set in ActEV-Prize challenge.
Unawareness in Multi-Agent Systems with Partial Valuations

Public signature awareness is satisfied if agents are aware of the vocabulary, propositions, used by other agents to think and talk about the world. However, assuming that agents are fully aware of each other’s signatures prevents them to adapt their vocabularies to newly gained information, from the environment or learned through agent communication. Therefore this is not realistic for open multi-agent systems. We propose a novel way to model awareness with partial valuations that drops public signature awareness and can model agent signature unawareness, and we give a first view on definining the dynamics of raising and forgetting awareness on this framework.
An Empirical Assessment of Driver Motivation, Emotional Response and Driving Conditions on Driver Risk Decisions

Problem: Limited empirical evidence has been developed for models of motivation in driving. Approach: We used a high-fidelity driving simulator. Driver conformance with social norms was manipulated by varying traffic patterns. Time and performance-based payment systems were used to assess the effect of incentive on driver motivation. The complexity of the driving environment was investigated as a mediating factor. Findings: Risky behavior, specifically higher driving speed, was observed with the performanceversus time-based payment system. Drivers conformed with social norms associated with specific traffic patterns. Higher roadway complexity interacted with the motivational factor manipulations and produced lower driving speeds. Conclusion: Motivational models can be supported by empirical evidence on driver performance and are promising for explaining and understanding driver risk-taking behavior.
Vulcan: Classifying Vulnerabilities in Solidity Smart Contracts Using Dependency-Based Deep Program Representations

As domain specific languages such as Solidity for Ethereum have emerged to program blockchain distributed ledgers, domain-specific bugs and vulnerabilities have reciprocally arisen. In this thesis, I propose a machine learning approach to designing classifiers which can flag specific lines of programs containing such vulnerabilities. This classification task calls for reasoning beyond what tokens are in a line to reasoning about how each token lies within a control context (e.g. loop) and how its meaning depends on its preceding definition. We present a neural architecture, Vulcan, which employs a distributed representation in a latent feature space to express these properties, while ensuring that lines of similar meaning have similar features. Using paths of the program’s abstract syntax tree (AST), Vulcan inputs contextual information about tokens in a line to a bi-directional LSTM with an attention mechanism. It concurrently represents the meaning of a token in a line by recursively embedding all preceding lines where it is defined. In our experiments, Vulcan compares favorably with a state-of-the-art classifier that requires significant preprocessing of programs, suggesting the utility of using deep learning to model program dependence information. Thesis Supervisor: Una-May O’Reilly Title: Principal Research Scientist, Computer Science & AI Laboratory
Comparative Use of Cement and Katsi to Stabilize Laterite as a Liner in Containment Facility

Solid waste management has recently dominated the environmental scene in developing countries, everyday nearly three thousand tons of solid waste is generated in each state thereby causing environmental degradation. This research investigates the use of cement, and Katsi admixture to stabilize laterite used as a liner in containment facility. A trial pit of 1m at a waste disposal site was dug and soil sample were collected. The natural soil was subjected to test in accordance with BS 1377(1990). The sample was prepared by adding either cement or Katsi to the collected soil, at varying percentage. The geotechnical properties of unstabilized soil sample shows that the soil has a low to medium plasticity; its specific gravity of 2.44 indicates that the soil needs improvement for it to meet the range of value stipulated for clay minerals. Also the unconfined compressive strength UCS of the soil was observed to be 286.0 KN/m2, and coefficient of permeability K was found as 1.39 x 10-5 cm/s. Katsi was observed to have improved the Atterberg’s Limit of the soil as the percentage of Katsi is increased explaining cationic exchange between the Katsi and laterite. And 7.5% Katsi content is recommended as convenient for laterite –Katsi mixture within the content of this study. This is because at 7.5% Katsi content the LL remained the same and the PI was at peak, implying that the greater the dry strength and toughness at plastic limit; the permeability, the rate of volume change and compressibility will remain the same.
X-RAY RADIATION HIGH-VOLTAGE ELEMENTS OF THE TANDEM ACCELERATOR WITH VACUUM INSULATION

In Institute of Nuclear Physics SB RAS the epithermal neutron source is entered into operation based on the tandem – accelerator with vacuum isolation. There was evaluated the accelerating installation components of a xray field causing dark current and breakdowns in accelerating gaps. The estimated account of equivalent doze capacity on different distances from the accelerator in the protected hall and behind its limits is made. The experimental measurements were carried out and the study results of the doze capacity dynamics are submitted, depending on change of a dark current in tandem accelerating gaps at a complete working voltage 1 MV without a beam. The spectrum of x-ray radiation is experimentally measured. It is experimentally revealed and the occurrence of powerful X-ray radiation is investigated at substantial growth of the aperture of the accelerating channel. The design changes of installation for prevention of occurrence of powerful X-ray radiation are offered and realized. The carried research allows setting necessary parameters for designing medical installation on the basis of an accelerator tandem with vacuum isolation with the purpose of realization in oncological clinics neutroncapture therapy of malignant tumors.
International cooperation in foreign reserve policies in the presence of competitive hoarding

This paper analyzes international reserve accumulation in economies facing keeping-up-withthe-Joneses externalities. To examine this competitive hoarding hypothesis, I introduce a valueweighted Joneses index so that the standard Joneses variable—a sum of reserve-to-GDP ratios of neighboring countries in the same geographical region—is weighted according to each country’s relative market capitalization. Using this refined index, I find a significant Joneses effect in developing countries, particularly persistent in Asia and Latin America since the early 2000s. This peer-pressure motive could encourage excess reserve hoarding, providing a rationale for international cooperation. I develop a simple theoretical model of borrowing economy featuring the Joneses effect as well as the interdependence between risk-free reserves and risky domestic capital investment. Quantitative results show that the cooperation can induce welfare-enhancing allocations with fewer reserves and greater investment and relax the external debt constraint, thereby effectively internalizing negative externalities inherent in competitive hoarding.
Veterinary diagnostics on farm-a review

Good management, antibiotic resistance awareness, and biosecurity are increasingly important in dairy farming. One of the biggest challenges for a livestock veterinarian, however, is to educate and convince farmers to change management instead of using drugs to mask mistakes in their management. The confidence of the farmers and the willingness to adjust their management practices may increase if the veterinarian is able to demonstrate the possibilities for improvement on farm. Improvement of farm management can be achieved by the use of on-farm diagnostic tests. On-farm diagnostic tests make early detection of diseases possible and reduce inappropriate use of antibiotics. Examples of on-farm tests are the ATP meter for monitoring of drinking water quality, the California mastitis test for detection of subclinical mastitis and the ruminal pH test for investigation of feed management. The use of these tests may change the attitude of the dairy cattle farmer from curative thinking towards more preventive thinking.
UNIVERSIDADE PAULISTA –UNIP A ADMINISTRAÇÃO NO 18 DIA DA GESTAÇÃO DE RATAS DE LIPOPOLISSACARÍDEO (LPS) MODIFICA A INTERAÇÃO MATERNO-FILHOTE DA GERAÇÃO PARENTAL E DAS GERAÇÕES F1 E F2 SANDRA HELOISA NUNES WHITAKER PENTEADO

The effects of single prenatal LPS administration were investigated on maternal-pups interaction of parental, F1 and F2 generations. Thus, pregnant rats received on DG18 100 μg / kg of LPS or its vehicle (parental generation) and the behaviors of pups retrieval and the maternal and maternal aggressive. In the F1 generation the olfactory preference of pups to maternal odor was assessed. In addition, at a weaning these pups received an additional dose of LPS and the general activity observed in an open field as well as the serum TNFα was measured. When adult female rats of the F1 generation were mated with male rats without any treatment and its maternal care were observed. In the F2 generation the olfactory preference of pups to maternal odor were decreased. In adult age, the pups of F2 generation were examined to their general activity in an open field and in the plus maze. The results showed that in relation to the control group, the parental generation showed facilitation of maternal behavior and reduction in maternal aggressive behavior. In the male offspring of the F1 generation the animals from mothers treated with endotoxin had less preference for maternal odor, and a decreased levels of TNFα. In the open field behavior, these rats did not showed changes when compared to that of control animals. In the F1 generation there was increased latency to assume the maternal position and in the number and latency to attack the intruder in maternal aggressive behavior. In infancy, the olfactory preference of F2 generation for maternal odor was not modified, but the number of pups indifferent to this odor in the experimental group was higher than that of the control group. In adult age these rats showed a decreased anxiety-like behavior in the plus maze. It was concluded that exposure on day 18 of gestation to LPS acts as an imprinting, which interferes with the maternal programming of the maternal-pups interaction of two generations.
POPULARITY AND SELF-EFFICACY BELIEF AS CORRELATE OF ACADEMIC ACHIEVEMENT OF IN-SCHOOL ADOLESCENTS IN NIGERIA

This paper explored the relationship among popularity, self-efficacy and academic achievement of in-school adolescents in Nigeria. The study was a correlational study. The sample of the study was 498 hundred senior secondary school students (female students were 300 while male students were 198). The instruments for data collection were questionnaires titled Adolescents’ Popularity Rating Scale (APRS) and Self-efficacy belief rating scale (SERS). In analyzing the data, mean, standard deviation and linear regression analysis were used in answering the research questions while analysis of variance (ANOVA) was used in testing the three research hypotheses stated at 0.05 level of significance. The results of the study indicate that there is low relationship between popularity and academic achievement of in-school adolescents. The relationship between self-efficacy belief and academic achievement is high and positive. Significant relationship exists between in-school adolescents’ self-efficacy and academic achievement. No significant relationship exists between popularity and academic achievement of in-school adolescents. It is recommended that teachers should always make the students believe that they can achieve academically as this will help them since self-efficacy has positive relationship with academic achievement.
IDENTIFICATION OF UNCONVENTIONAL SHALE-GAS PLAYS AND RESERVOIR CHARACTERIZATION THROUGH ∆LOGR METHOD AND WELL LOG INTERPRETATION : A CASE STUDY FROM LOWER INDUS BASIN, PAKISTAN

Unconventional reservoirs mostly consist of fine-grained wealthy with organic shales trapped gas are considered as source, seal, and the reservoir rock. Integration of well logs played an important contribution in evaluation of unconventional reservoirs in order to identify the shale deposited basinward on the basis of their position in Basin, Total Organic
Learning Control Policies from Optimal Trajectories

The ability to optimally control robotic systems offers significant advantages for their performance. While time-dependent optimal trajectories can numerically be computed for high dimensional nonlinear system dynamic models, constraints and objectives, finding optimal feedback control policies for such systems is hard. This is unfortunate, as without a policy, the control of real-world systems requires frequent correction or replanning to compensate for disturbances and model errors.In this paper, a feedback control policy is learned from a set of optimal reference trajectories using Gaussian processes. Information from existing trajectories and the current policy is used to find promising start points for the computation of further optimal trajectories. This aspect is important as it avoids exhaustive sampling of the complete state space, which is impractical due to the high dimensional state space, and to focus on the relevant region.The presented method has been applied in simulation to a swing-up problem of an underactuated pendulum and an energy-minimal point-to-point movement of a 3-DOF industrial robot.
New 3D Integral Imaging Camera Viewing Parameters

3D Holoscopic imaging (also known as Integral imaging) is a technique that is capable of creating and encoding a true volume spatial optical model of the object scene in the form of a planar intensity distribution by using unique optical components. It is akin to holography in that 3D information recorded on a 2D medium can be replayed as a full 3D optical model, Typically, moving from cylindrical lens to the next cylindrical lens is carried out knowing the lens width, Lw, which defines the translation of the camera along the x optical axis and hence the position of the new camera cylindrical lens. This new renderer is represented in the paper by the term integral ray tracing (IRT). In this paper, a method of generation 3D integral images camera file parameters is proposed. The camera file is an important part of the process of generating micro-images and set up the camera position. The method is mainly based on Parallel Multiprocessor Ray Tracing System adapted "Tachyon" as renderer. Experimental results show validation of the new algorithm and the lenticular lens can be set up and tested on small-balls, gears, room, tree and teapot scenes.
A Proposed Model For Applying TQM In Syrian Banks: A Case Study In The Industrial Bank Of Syria

Syrian banks have witnessed an important changed since 2002 with applying the advanced technology. Industrial bank played a crucial role in developing the industrial sector which provides about 25% to the GDP and this sector is the main engine of the national economy in Syria. This research aims to apply total quality management (TQM) to industrial banks of Syria. A random sample of 120 bank employees from higher and middle management were selected to investigate the current situation of TQM in the bank and to develop a new suitable TQM Model. The results show the levels of implementing TQM criteria in the industrial bank, and provide a proposed TQM Model with an implementation plan that could help other Syrian banks to apply TQM in an effective way.
A Study on Islamic Tourism: A Malaysian Experience

Malaysia as an Islamic country is promoting tourism worldwide so as to attract more tourists to visit Malaysia. Islamic tourism is associated with the religious, spiritual and cultural aspects of tourism. Malaysia is a peaceful and harmonious country of various races and religions. There are also a lot of attractive destinations that are situated in every state in Malaysia. It was reported in 2009, a total of 284,890 Arab tourists came to Malaysia for various reasons such as for shopping, studying and experiencing the multicultural fiestas here. This paper is investigating the various features and popular destinations of Islamic tourism as practiced in Malaysia. Using a qualitative approach, the data was collected from books, journals, magazines, websites and documents. This paper will contribute towards a better understanding about Islamic tourism and Malaysia destinations for tourist.
Learning to Solve Vehicle Routing Problems with Time Windows through Joint Attention

Many real-world vehicle routing problems involve rich sets of constraints with respect to the capacities of the vehicles, time windows for customers etc. While in recent years first machine learning models have been developed to solve basic vehicle routing problems faster than optimization heuristics, complex constraints rarely are taken into consideration. Due to their general procedure to construct solutions sequentially route by route, these methods generalize unfavorably to such problems. In this paper, we develop a policy model that is able to start and extend multiple routes concurrently by using attention on the joint action space of several tours. In that way the model is able to select routes and customers and thus learns to make difficult trade-offs between routes. In comprehensive experiments on three variants of the vehicle routing problem with time windows we show that our model called JAMPR works well for different problem sizes and outperforms the existing state-of-the-art constructive model. For two of the three variants it also creates significantly better solutions than a comparable meta-heuristic solver.