Miracle-dz/UniFAR-FTUs huggingface dataset:
Security Monitoring of Components Using Aspects and Contracts in Wrappers

The re-usability and modularity of components reduce the cost and complexity of the software design. It is difficult to predict run-time scenarios covering all possible circumstances to ensure that the components are fully compatible with the system. Given that, monitoring run-time behaviours of components presents a close view of the component qualities. The existing monitoring approaches either implement applications with built-in monitoring features, or observe the external resources and events to predict the status of the components. In this paper, we propose an approach to monitor the runtime behaviours of components using aspect-oriented wrappers and contracts. We design monitoring wrappers to encapsulate the monitored components. We use contracts to define the mutual obligations of two interacting components. The policies implemented in contracts are woven into component wrappers as separate aspect modules. If the component contains any flaws or vulnerabilities, the wrappers can monitor some behaviours and prevent failures propagating into the wrapped components and the rest of the system. This approach assures that the system is running in a safe environment with the erroneous behaviours detected appropriately. We conducted experiments on the run-time monitoring of SQL Injection, Cross Site Scripting attacks, and access control policies. The results show that the framework is very flexible to impose separate policies as aspects on component wrappers without the modifications of the underlying components.
MSTK - A Flexible Infrastructure Library for Developing Mesh Based Applications

MSTK is a powerful framework for low-level creation and manipulation of unstructured meshes. MSTK is not a mesh generator but it can be used to develop advanced mesh generation software and other mesh-based applications. The salient feature of MSTK is that it is allows multiple mesh representations while presenting a common functional interface to the developer. This allows application developers to use a mesh representation optimized for their particular algorithms. MSTK allows developers to focus on their applications rather than on the details of mesh data structures.
Distributed Price-based Optimal Control of Power Systems

This paper proposes a new control scheme for achieving optimal power balancing in electrical power systems. Optimality is defined via economical criteria related to steady-state operation requirements. Limits on the capacity of the power lines are taken into account via inequality constraints that are added to the optimization problem. Due to these inequality constraints, the resulting control law has a piecewise affine structure. Furthermore, the control action is distributed in the sense that a controller is assigned to each node and each controller communicates only with the controllers associated with the neighboring nodes. We prove that the resulting steady-state solution is optimal. The proposed control structure is a relaxation and an extension of classical "automatic generation control" in power systems, and can be interpreted as a fast acting real-time market for electrical power.
Classification of Elliptic/hyperelliptic Curves with Weak Coverings against GHS Attack under an Isogeny Condition

The GHS attack is known to map the discrete logarithm problem(DLP) in the Jacobian of a curve C0 defined over the d degree extension kd of a finite field k to the DLP in the Jacobian of a new curve C over k which is a covering curve of C0, then solve the DLP of curves C/k by variations of index calculus algorithms. It is therefore important to know which curve C0/kd is subjected to the GHS attack, especially those whose covering C/k have the smallest genus g(C) = dg(C0), which we called satisfying the isogeny condition. Until now, 4 classes of such curves were found by Thériault in [35] and 6 classes by Diem in [3][5]. In this paper, we present a classification i.e. a complete list of all elliptic curves and hyperelliptic curves C0/kd of genus 2, 3 which possess (2, ., 2) covering C/k of P under the isogeny condition (i.e. g(C) = d · g(C0)) in odd characteristic case. In particular, classification of the Galois representation of Gal(kd/k) acting on the covering group cov(C/P) is used together with analysis of ramification points of these coverings. Besides, a general existential condition of a model of C over k is also obtained. As the result, a complete list of all defining equations of curves C0/kd with covering C/k are provided explicitly. Besides the 10 classes of C0/kd already known, 17 classes are newly found.
Selection Criteria for Preparatory Object Rotation in Manual Lifting Actions

ABSTRACT Participants lifted a canister by its handle while balancing a ball on the lid. Experiment 1 allowed object rotation prior to lifting. A lifting comfort zone was measured by the variability in object orientation at lift; its size depended on the object mass and required task precision. The amount of prelift rotation correlated with the resulting change in lifting capability, as measured for different object orientations. Experiment 2 required direct grasping without preparatory rotation. Task completion time and success rate decreased, and initial object orientation affected prelift time. Results suggest that lifting from the comfort zone produces more robust performance at a cost of slower completion; moreover, physical rotation could be replaced by mental planning when direct grasping is enforced.
Species turnover drives the spatial distribution of frog beta diversity in farmland ponds

Abstract Studies integrating variation in species composition among sites are useful in understanding the impacts of land-use changes on the spatial distribution of biodiversity. However, the failure to recognize the distinction between beta diversity components, dissimilarity due to species replacement (i.e. turnover) and dissimilarity due to species loss from site to site (i.e. nestedness), can lead to inappropriate use of some indices. Here, we evaluated how the spatial distribution of anuran beta diversity components, turnover and nestedness, is associated with local and landscape descriptors in a tropical agricultural landscape with a recent history of agriculture expansion in south-eastern Brazil. Overall, 27 anuran species were found in the region with average ± SD species richness in each pool of 9.5 ± 3.5 species, ranging from 4 to 15 species. We observed that species turnover was the major component for anuran dissimilarity among pools, indicating that anuran species occurring in species-poor pools are not subsets of anuran species occurring in species-rich pools. Local variables and geographic distance were not important descriptors explaining the variation of anuran beta diversity. In contrast, the distance of the pools to the nearest forest fragment explained 16% of the variance in total beta diversity, 5% of the nestedness component and 2% of spatial turnover. Our results show that pools distributed across farmland landscapes are harbouring different anuran species composition, and together, these pools are contributing to the regional diversity of anurans in this region which is considered one of the most deforested and fragmented within Brazil.
Hierarchical Reinforcement Learning for Robot Navigation using the Intelligent Space Concept

Navigation in an unknown environment is a difficult task, because mobile robots need topological maps in order to operate in the environment. Another fundamental problem is that robot programming is a time-consuming process, so it is better to use a learning method with reinforcement. In previous work we proposed a learning framework, which used the capability of the Intelligent Space in order to build a topological map of the environment. In this paper we present an extension of this framework to decompose the learning problem into sub-problems, which can be learned faster.
An efficient multi-server password authenticated key agreement scheme using smart cards with access control

Due to the rapid development of science and techniques, people can remotely access computers over the networks. Thus, user authentication and key agreement become more and more important to ensure the legality of the user and the security of later communications, respectively. Because the number of servers providing the facilities for the user is usually more than one, the concept of multi-server protocols is introduced. On the Internet, each server usually provides various services, and each service provided by the server may not be accessed by the user. Hence, access control is required in the multi-service environment. In 2004, Juang proposed a multi-server authentication scheme with key agreement. However, access control is not taken into account in Juang's proposed scheme, so we propose an efficient multi-server password authenticated key agreement scheme with access control in this article.
First Observations of the Magnetic Field Geometry in Prestellar Cores

We present the first published maps of magnetic fields in prestellar cores to test theoretical ideas about the way in which the magnetic field geometry affects the star formation process. The observations are JCMT-SCUBA maps of λ850 μm thermal emission from dust. Linear polarizations at typically 10 or more independent positions in each of three objects, L1544, L183, and L43, were measured, and the geometries of the magnetic fields in the plane of the sky were mapped from the polarization directions. The observed polarizations in all three objects appear smooth and fairly uniform. In L1544 and L183 the mean magnetic fields are at an angle of ~30° to the minor axes of the cores. The L43 B-field appears to have been influenced in its southern half such that it is parallel to the wall of a cavity produced by a CO outflow from a nearby T Tauri star, while in the northern half the field appears less disturbed and has an angle 44° to the core minor axis. We briefly compare our results with published models of magnetized cloud cores and conclude that no current model can explain these observations simultaneously with previous ISOCAM data.
Pulmonary mechanics and gas exchange during exercise in Kenyan distance runners.

PURPOSE The purpose of this study was to determine arterial blood gases, the mechanical limits for generating expiratory flow and the work performed by the respiratory muscles during treadmill exercise in Kenyan runners. METHODS Kenyan runners (10 men and 4 women; mean ± SD age = 25.2 ± 1.3 yr) were instrumented with a radial artery catheter, an esophageal balloon-tipped catheter, and an esophageal temperature probe for the determination of blood gases, the work of breathing and core temperature, respectively. Testing occurred at 1545 m above sea level. RESULTS There were significant decreases in the arterial partial pressure of O2 and oxyhemoglobin saturation and a widening of the alveolar-to-arterial difference in O2 from rest to peak exercise. The mechanical work of breathing increased with increasing minute ventilation and was commensurate with values expected for treadmill running in elite athletes. During heavy exercise, significant expiratory flow limitation was present in half of the subjects while the remaining subjects demonstrated impending flow limitation. CONCLUSIONS Pulmonary system limitations were present in Kenyan runners in the form of exercise-induced arterial hypoxemia, expiratory flow limitation, and high levels of respiratory muscle work. It appears that Kenyan runners do not possess a pulmonary system that confers a physiological advantage.
An exploratory study of coach and players' emotion regulation in a female volleyball team

Kokkini Eleana, 2018. An exploratory study of coach and players’ emotion regulation in a female volleyball team. Master’s Thesis in Sport and Exercise Psychology. Faculty of Sport and Health Sciences. University of Jyväskylä. 72p. During the past few decades, the strategies followed by athletes in order to initiate, maintain, modify or display emotions before and during competition have received extensive attention in sport settings (Gross and Thompson, 2007). The coach’s determinant role in the athlete’s pursuit of optimal performance is yet another topic of scientific interest (Chelladurai, 2007). The aim of the present study was to explore the emotion regulation strategies that Greek female volleyball players tend to follow before and during competition as well as the coach’s emotion awareness and contribution to the players’ regulation of emotion. The study’s sample consisted of ten Greek female volleyball players currently competing in the regional semi-professional championship of Western Greece and their coach. Data for both the players and the coach were collected using semistructured interviews. Additional qualitative information was gathered through an observation protocol, which included the researcher’s descriptive and reflective notes. The collected data were thematically analyzed (Boyatzis, 1998). Themes and codes were developed using the inductive and deductive approach and the participants’ cues were compared to each other in search of similarities and differences between the players’ followed emotion regulation strategies and the coach’s awareness and interpersonal emotion regulation. The inductive and deductive analysis revealed eleven main themes for the players’ perceptions and emotion regulation strategies and eight main themes for the coach’s perceptions, emotion awareness and contribution to the players’ regulation of emotion. The results revealed that the participant players perceived pleasant emotions as more functional for their performance and described under which circumstances unpleasant emotions like stress turned from functional to dysfunctional. The players’ cues related to emotion regulation strategies supported the existing literature and disclosed self-talk, positive reappraisal, listening to music, putting into perspective, seeking others’ help and emotion sharing as the most frequent followed strategies. Interestingly, the results showed a high consistency between the coach’s and the players’ statements when compared. The coach was presented as an emotionally intelligent person who developed stable relationships in the team, was able to adapt in challenging situations and to manage the players’ emotions. The researcher’s observation notes supported the interview results. The study supported the existing literature and shed more light on the ongoing scientific flow regarding the integration of the emotion regulation (ER) and emotional intelligence (EI) traditions.
Identification of Low Back Injury from EMG Signals using a Neural Network Model

We propose a novel neural network model for the identification of low back injury using electromyography (EMG) data. By connecting task condition variables to the second hidden-layer of the neural network, the importance of those variables can be improved. A 4-muscle method and a 10-muscle method are discussed. A higher classification accuracy was achieved by the 10-muscle method since it takes the correlation between muscle activities into account. We also found that identification accuracy decreases when the object weight or the lifting height increases. The obtained results improve our understanding of low back disorders and provide important guidance for future experimental studies.
Static, dynamic and active interaction structures in the web: providing semantic annotations in the virtual knowledge space

The aim of the article is to enhance a cooperative working and learning environment, a so-called virtual knowledge space, with additional semantic annotations. To do so, we first consider two prominent approaches to illustrate how machine processable data for web search can be obtained: either by explicit semantic mark-up (as practiced in the Semantic Web) or by cooperative filtering of user activities. As both can be described with the help of an interaction model, the first approach leads to static, the second to dynamic interaction structures. As a third alternative, we show how machine processable annotations can be created during co-operative activities. We refer to this innovative approach as active semantic structuring of the web. These annotations are integrated into virtual knowledge spaces and theoretically substantiated by the media functions approach. To illustrate the practical relevance of this approach, two possible examples of application will be touched, metadata and ontologies.
Quantifying the Risk of Deflation

We propose formal and quantitative measures of the risk that future inflation will be excessively high or low relative to the range preferred by a private sector agent. Unlike alternative measures of risk, our measures are designed to make explicit the dependence of risk measures on the private sector agent's preferences with respect to inflation. We illustrate our methodology by estimating the risks of deflation for the United States, Germany, and Japan for horizons of up to 2 years. The question of how large these risks are has been subject to considerable public debate. We find that, as of September 2002 when this question first arose, there was no evidence of substantial deflation risks for the United States and for Germany, contrary to some conjectures at the time. In contrast, there was evidence of substantial deflation risks in Japan.
Abacus : A High-Performance Architecture forVisionMichael

Abacus is a second generation distributed bit-parallel (DBP) architecture based on a reconngurable mesh. A DPB organization distributes each bit of a data item to a diierent processor to exploit bit-level parallelism. This paper describes details of the VLSI-oriented architecture, the implementation of several arithmetic operations, and performance gures for various early vision tasks. A single IC in a non-aggressive technology is capable of 1-5 billion 16-bit operations per second (GOPS). A prototype machine currently under construction, with a completion date of October 1994, is expected to deliver approximately 250 GOPS.
Spatial modelling of claim frequency and claim size in non-life insurance

In this paper, models for claim frequency and average claim size in non-life insurance are considered. Both covariates and spatial random effects are included allowing the modelling of a spatial dependency pattern. We assume a Poisson model for the number of claims, while claim size is modelled using a Gamma distribution. However, in contrast to the usual compound Poisson model, we allow for dependencies between claim size and claim frequency. A fully Bayesian approach is followed, parameters are estimated using Markov Chain Monte Carlo (MCMC). The issue of model comparison is thoroughly addressed. Besides the deviance information criterion and the predictive model choice criterion, we suggest the use of proper scoring rules based on the posterior predictive distribution for comparing models. We give an application to a comprehensive data set from a German car insurance company. The inclusion of spatial effects significantly improves the models for both claim frequency and claim size, and also leads to more accurate predictions of the total claim sizes. Further, we detect significant dependencies between the number of claims and claim size. Both spatial and number of claims effects are interpreted and quantified from an actuarial point of view.
Face Recognition: Today's Security Tool

Face and facial feature detection plays an important role in various applications such as human computer interaction, video surveillance, face tracking, and face recognition. Efficient face and facial feature detection algorithms are required for applying to those tasks. Recently face recognition is attracting much attention in the society of network multimedia information access. Face recognition not only makes hackers virtually impossible to steal one's "password", but also increases the user-friendliness in human-computer interaction. Face recognition systems are now replenishing the need for security to cope up with the present day crime. It is really convincing with the market report which clearly depicts the growing popularity of the face recognition system. The face recognition system is proving to be very efficient in the present day market. In today's networked world, the need to maintain the security of information or physical property is becoming both increasingly important and increasingly difficult. From time to time it has been noticed about the crimes of credit card fraud, computer hackings, or security breaches in a company or government building. Government agencies are investing a considerable amount of resources into improving security systems as result of recent terrorist events that dangerously exposed flaws and weaknesses in today’s safety mechanisms.
Short Term Traffic Forecasting Using the Local Linear Regression Model

Author(s): Sun, Hongyu; Liu, Henry X. ; Xiao, Heng; Ran, Bin | Abstract: Traffic data is highly nonlinear and also varies with time of day. It changes abruptly when entering or leaving a congestion hour. Therefore,the prediction of travel time requires accurate models. This leads to the problem of approximating nonlinear and time-variant functions. In this paper, we propose and apply local linear regression models to short-term traffic prediction. Local linear regression is one type of local weighted regression methods. It has been applied to many problems, including artificial intelligence, dynamic system identification and data mining. It can be used for nonlinear time series prediction under certain mixing conditions. The performance of the proposed model is compared with previous nonparametric approaches, such as nearest neighborhood and kernel methods using 32-day traffic speed data collected on the Houston, Texas, US-290 Northwest Freeway. We found that the local linear methods consistently outperform the nearest neighborhood and kernel smoothing methods.
Framework of real-time car detection using calibrated camera and LRF

This paper proposes a framework for a real-time car detection method using calibrated system of camera and Laser Range Finder (LRF). Car candidates are extracted from the LRF data using a gridding method. The points sensed by LRF are grouped into 2D grid. Two adjacent occupied grid elements are marked with same label, forming an object. The objects formed by the labeling method are filtered out based on their size. A region of interest (ROI) in camera image is generated for each object located in 2D grid using the property of the calibrated camera and LRF system. From each ROI, Histogram of oriented gradient (HOG) features are extracted. In order to achieve a faster computation time, the dimension of the HOG feature is reduced using genetic algorithm approach, with a machine learning approach as the validation method. Experiments result shows that the proposed framework achieves around 68 fps of processing speed.