Miracle-dz/UniFAR-FTUs huggingface dataset:
Preventing Intrusions through Non-Interference

The ability to prevent and to detect intrusions in computer systems is often heavily conditioned by having som e knowledge of the security flaws of the system under analysis. Discover intrusions is particularly hard in concurrent systems, which contain several interactions among their components ; suspicious interactions are usually studied manually by se curity experts which need to establish if they are dangerous. In thi s paper, we present an automated method to prevent intrusionsin concurrent systems that does not require any previous knowl edge of the flaws. We study the behaviour of an abstract model of the system that captures its security-related behaviors; the model contain the trusted components of the system such as the file system, privileged processes, etc. We then check all possib le interactions with unprivileged processes to decide if the s ystem contain security flaws. This is accomplished by introducinga non-interference security property which holds for modelswhere unprivileged processes do not have direct or indirect writeaccess to resources with an high security level. The property is bas ed on traces and can be decided by using standard concurrency tools. Our method applies even to models containing informa tion flows among their components; this turns out to be a necessary condition for analyzing interactions of actual computer systems, where privileged processes usually have both read and write access to low resources.
A Fuzzy-Based Cluster-Head Selection System forWSNs Considering Different Parameters

Cluster formation and cluster head selection are important problems in sensor network applications and can drastically affect the network's communication energy dissipation. However, selecting the cluster head is not easy in different environments which may have different characteristics. In order to deal with this problem, we have proposed a power reduction algorithm for sensor networks based on fuzzy logic and node movement. The proposed system different from our previous systems uses 4 input linguistic parameters: Remaining Power of Sensor (RPS), Degree of Number of Neighbor Nodes (D3N), Distance from Cluster Centroid (DCC) and Sensor Speed (SS) for cluster-head decision. By considering the moving speed of the sensor we are able to predict if the node will leave the cluster. We evaluate the proposed system by simulations and show that it has a good cluster-head selection.
Comparative analysis of space-time processing algorithms for GNSS receivers

the article discusses two algorithms of space-time signal processing in GNSS receiver with an antenna array. Such signal processing algorithms can receive weak signals from GNSS satellites when exposed to interference. In a synthesis of such algorithms, the formulation of the problem and the presence of a priori information about characteristics of interference play an important role. A comparison and simulation of algorithms for observations in the complex form and for observations in the "quadrature" form. The results of research show that the algorithm when observing in the "quadrature" form is inferior to the algorithm with complex observations in amount of simultaneously suppressed interference, however, it requires significantly less hardware resources in practical implementation.
Predictive Factors of Development of Graves' Ophthalmopathy for Patients with Juvenile Graves' Disease

Background. Due to low incidence of Graves' ophthalmopathy (GO) among children, the manifestation is poorly analyzed, posing a risk to late identification of insidious disease. Purposes. To identify predictive factors that may influence the development of GO in pediatric and young patients with Graves' disease (GD). Methods. A cross-sectional study of patients newly diagnosed with pediatric or juvenile GD during 2002–2012 was conducted at the Hospital of Lithuanian University of Health Sciences. Ocular evaluation was based on European Group on Graves' Orbitopathy survey. The ocular manifestations were analyzed in relation to demographic, environmental, and clinical factors. Results. In total, 130 patients with juvenile GD were included; 29.2% had GO. Median age at GD onset was 17 yrs (IQR 4–29). Main symptoms of GO were eyelids retraction (73.7%), proptosis (65.8%), injection of conjunctiva (42.1%), and eyeball motility disturbance (21.1%). Major significant and independent risk factors for GO development were high initial concentration of FT4 (OR = 5.963), TTHAb (OR = 6.358), stress (OR = 6.030), and smoking (OR = 7.098). Conclusion. The major factors that could influence GO development were smoking, stress, and increased levels of initial TRAb, FT4. Slight proptosis, retraction of eyelids, and conjunctive injection were found as predominant ophthalmological symptoms in juvenile GO.
Speed Sensorless PMSM Driven Single-Stage SMC Controlled Solar Water Pumping System

In this paper, a speed sensorless vector controlled permanent magnet synchronous motor (PMSM) driven single-stage solar water pumping system is proposed. The back-emf based rotor position estimation technique is used. The PMSM speed is controlled through sliding mode controller (SMC) based vector control. The solar photovoltaic (PV) array feeds power to a voltage source inverter (VSI), which drives the PMSM. The PV array is regulated at maximum power point by VSI, which also controls the armature winding currents. The hysteresis current controller produces switching signals for VSI. The reference speed command is generated using output of DC link SMC controller and DC link feed-forward term. The proposed system is designed, modeled and simulated on MATLAB/Simulink platform. The performance of proposed system is obtained for starting, steady-state and dynamic conditions under variable solar irradiations. Test results are obtained on a developed prototype of the system in the laboratory to validate the control algorithm and modeling of the system.
Generation of Parametrically Uniform Knowledge Bases in a Relational Probabilistic Logic with Maximum Entropy Semantics

In a relational setting, the maximum entropy model of a set of probabilistic conditionals can be defined referring to the full set of ground instances of the conditionals. The logic FO-PCL uses the notion of parametric uniformity to ensure that the full grounding of the conditionals can be avoided, thereby greatly simplifying the maximum entropy model computation. In this paper, we describe a system that realises an approach transforming an FO-PCL knowledge base consisting of relational probabilistic conditionals into a knowledge base having the same maximum entropy model that is parametrically uniform. The implemented system provides different execution and evaluation modes, including the generation of all possible solutions, and is available within an integrated development environment for relational probabilistic logic.
A Grid Interactive Microgrid Based on Wind Driven DFIG and Solar PV Array with Regulated Power Flow Functionality

This paper presents a microgrid based on wind turbine driven doubly fed induction generator (DFIG) and solar photovoltaic (PV) array connected to the grid with regulated power flow capabilities. The grid side converter (GSC) control is modified to feed constant power to the grid irrespective of wind speed and insolation patterns. A novel phase locked loop (PLL) is introduced, which reduces the DC components and harmonics that exist in the PLL input, which helps in proper generation of reference currents through both GSC and rotor side converter (RSC) control. The RSC control is designed to achieve maximum power from the wind and to maintain unity power factor at the DFIG stator terminals. The battery energy storage (BES) connected at DC link, plays vital role in feeding regulated power to the grid. An incremental conductance based maximum power point tracking algorithm is used to extract peak power from a solar PV array. The simulation of the microgrid is performed under variable wind speed, solar insolation, nonlinear unbalanced loads connected at point of common coupling and step change in grid active reference power. The DFIG stator voltages and currents, grid currents, are found sinusoidal and balanced, comply the IEEE 519 standard. Moreover, the microgrid is tested on a developed prototype in the laboratory to verify its performance both in steady state and dynamic scenarios.
Stable isotope tracer reveals that viviparous snakes transport amino acids to offspring during gestation

SUMMARY Viviparity and placentation have evolved from oviparity over 100 times in squamate reptiles (lizards and snakes). The independent origins of placentation have resulted in a variety of placental morphologies in different taxa, ranging from simple apposition of fetal and maternal tissues to endotheliochorial implantation that is homoplasious with mammalian placentation. Because the eggs of oviparous squamates transport gases and water from the environment and calcium from the eggshell, the placentae of viviparous squamates are thought to have initially evolved to accomplish these functions from within the maternal oviduct. Species with complex placentae have also been shown to rely substantially, or even primarily, on placental transport of organic nutrients for embryonic nutrition. However, it is unclear whether species with only simple placentae are also capable of transporting organic nutrients to offspring. Among viviparous squamates, all of the snakes that have been studied thus far have been shown to have simple placentae. However, most studies of snake placentation are limited to a single lineage, the North American Natricinae. We tested the abilities of four species of viviparous snakes – Agkistrodon contortrix (Viperidae), Boa constrictor (Boidae), Nerodia sipedon (Colubridae: Natricinae) and Thamnophis sirtalis (Colubridae: Natricinae) – to transport diet-derived amino acids to offspring during gestation. We fed [15N]leucine to pregnant snakes, and compared offspring 15N content with that of unlabeled controls. Labeled females allocated significantly more 15N to offspring than did controls, but 15N allocation did not differ among species. Our results indicate that viviparous snakes are capable of transporting diet-derived amino acids to their offspring during gestation, possibly via placentation.
3D Body and Background Reconstruction in a Large-scale Indoor Scene using Multiple Depth Cameras

3D reconstruction of indoor scenes that contain non-rigidly moving human body using depth cameras is a task of extraordinary difficulty. Despite intensive efforts from the researchers in the 3D vision community, existing methods are still limited to reconstruct small scale scenes. This is because of the difficulty to track the camera motion when a target person moves in a totally different direction. Due to the narrow field of view (FoV) of consumer-grade red-green-blue-depth (RGB-D) cameras, a target person (generally put at about 2–3 meters from the camera) covers most of the FoV of the camera. Therefore, there are not enough features from the static background to track the motion of the camera. In this paper, we propose a system which reconstructs a moving human body and the background of an indoor scene using multiple depth cameras. Our system is composed of three Kinects that are approximately set in the same line and facing the same direction so that their FoV do not overlap (to avoid interference). Owing to this setup, we capture images of a person moving in a large scale indoor scene. The three Kinect cameras are calibrated with a robust method that uses three large non parallel planes. A moving person is detected by using human skeleton information, and is reconstructed separately from the static background. By separating the human body and the background, static 3D reconstruction can be adopted for the static background area while a method specialized for the human body area can be used to reconstruct the 3D model of the moving person. The experimental result shows the performance of proposed system for human body in a large-scale indoor scene.
3D Point Cloud Matching Based on Its 2D Representation for Visual Odometry

Fast and accurate pose estimation of non-textured 3D objects based on 3D point cloud is emerged as important for the application of vision to industrial automation. There have been proposed a number of global and local 3D geometric features that can be extracted from 3D point cloud. However, they are either too inefficient or too inaccurate to be viable. In this paper, we presents a fast and accurate method of 3D pose estimation based on transforming 3D point cloud into 2D image, where the azimuth and elevation angles of as well as the distance to 3D points are converted to 2D pixels and their image intensities, respectively. The experiments show that the proposed method provides faster and more accurate 3D pose estimation, two orders of magnitude and over 25% of improvements in processing time and accuracy, respectively, compared to a top performance conventional 3D geometric feature based approach.
An Optimal Combination Modulation Strategy for a Seven-level Cascade Multilevel Converter Based STATCOM

This paper proposes an optimal modulation strategy for a static synchronous compensation (STATCOM) using a seven-level cascade multilevel converter without any filter. Cascade multilevel converters have been used in STATCOM application due to its ability to reduce harmonics and increase output power by increasing the level of output voltages for a given semiconductor device without device series connection. Challenges in high power application include relatively low switching frequency (few hundred hertz to 1 kHz) limited by the thermal handling capability of semiconductor switch, and the low harmonic requirement specified by IEEE 519 standard. With carrier based PWM, the STATCOM can generate lower current harmonic distortions at the expense of working at higher switching frequency. If step modulation strategy is used, the inverter works with lower switching frequency, but the STATCOM injects higher current harmonic distortions to power system, which generally leads to usage of extra filters. The proposed optimal combination modulation strategy works with low switching frequency and has low current harmonic distortions. The simulation results show that it can satisfy the device thermal requirements and IEEE 519 harmonic requirements simultaneously
Fault Diagnosis of the Newfangled Cascaded H-Bridge Multilevel Inverter

In recent years multilevel inverters have been extensively worn in high voltage and high power applications for their unique performance. Reliability of the power electronic equipment is very essential to make sure that inverter operation should be stable and it is most important to detect and locate the faults as speedily as possible. This paper deals with open switch-fault finding method in a multilevel inverter using wavelet transformation tool. A fault diagnosis procedure is proposed and executed using MATLAB.
Understanding Billions of Triples with Usage Summaries

Linked Data is a way to share and consume interlinked semantic web datasets. Usage summaries can help to understand the structure within and across interlinked datasets by partitioning entities based on how they are described, such as grouping entities that are instances of the same types and described with the same predicates. Because Linked Data is growing to billions of triples, scalable techniques for generating usage summaries are essential. In this work, we implement a novel Hadoop-based technique for generating usage summaries of billions of triples. We analyze and compare usage summaries generated for the entire BTC 2010 and 2011 datasets. We generate usage summaries involving classes and predicates, and of recommended patterns, such as for inferencing and interlinking.
A Three Phase Grid Connected SPV System using Synchronverter

The rising demand for energy invites the contribution of renewable sources as alternative sources of energy. The major drawback of these sources is their inherently varying nature. They depend mostly on power converters for energy conversion and maximum power point tracking (MPPT). The increased penetration of such power converter based generation is degrading the stability of the existing grid, since synchronous generators based conventional energy generation is no longer capable of maintaining the grid stability. Synchronverter technology is a promising solution to this problem. To contribute to the stability of the system, here, synchronous machine dynamics is used to control the grid connected inverter. This paper aims to integrate a Solar Photovoltaic (SPV) system into the grid using synchronverter technology. It also reviews the modelling of the converter controller and analyses its performance under continuously varying input conditions. The capability of the converter to maintain synchronism under extreme conditions were also investigated. The results presented were based on a simulation study done in MATLAB/Simulink.
Towards a catalog of aspect-oriented refactorings

In this paper, we present a collection of aspect-oriented refactorings covering both the extraction of aspects from object-oriented legacy code and the subsequent tidying up of the resulting aspects. In some cases, this tidying up entails the replacement of the original implementation with a different, centralized design, made possible by modularization. The collection of refactorings includes the extraction of common code in various aspects into abstract superaspects. We review the traditional object-oriented code smells in the light of aspect-orientation and propose some new smells for the detection of crosscutting concerns. In addition, we propose a new code smell that is specific to aspects.
Ensemble Composition and Activity Levels of Insectivorous Bats in Response to Management Intensification in Coffee Agroforestry Systems

Shade coffee plantations have received attention for their role in biodiversity conservation. Bats are among the most diverse mammalian taxa in these systems; however, previous studies of bats in coffee plantations have focused on the largely herbivorous leaf-nosed bats (Phyllostomidae). In contrast, we have virtually no information on how ensembles of aerial insectivorous bats – nearly half the Neotropical bat species – change in response to habitat modification. To evaluate the effects of agroecosystem management on insectivorous bats, we studied their diversity and activity in southern Chiapas, Mexico, a landscape dominated by coffee agroforestry. We used acoustic monitoring and live captures to characterize the insectivorous bat ensemble in forest fragments and coffee plantations differing in the structural and taxonomic complexity of shade trees. We captured bats of 12 non-phyllostomid species; acoustic monitoring revealed the presence of at least 12 more species of aerial insectivores. Richness of forest bats was the same across all land-use types; in contrast, species richness of open-space bats increased in low shade, intensively managed coffee plantations. Conversely, only forest bats demonstrated significant differences in ensemble structure (as measured by similarity indices) across land-use types. Both overall activity and feeding activity of forest bats declined significantly with increasing management intensity, while the overall activity, but not feeding activity, of open-space bats increased. We conclude that diverse shade coffee plantations in our study area serve as valuable foraging and commuting habitat for aerial insectivorous bats, and several species also commute through or forage in low shade coffee monocultures.
Web Structure Mining : A Novel Approach to Reduce Mutual Reinforcement

Finding an authorized and relative webpage is a huge task in this rapidly growing web. Basically, this task is divided into three categories like web content mining, web structure mining and web usage mining. Web structure mining plays a vital role in web page ranking. There have been so many algorithms developed to find web page ranking but most of the algorithm has similar problem of mutual reinforcement. Mutual reinforcement plays a significant role in web page ranking. In this paper we attempt to reduce mutual reinforcement effect through web page ranking. We have created one demo graph and applied two basic algorithm HITS and AHPA. We have compared original HITS and AHPA with proposed HITS and AHPA. We have also created a graph which represent position of web pages through we can easily find the position of mutual reinforced page. This paper gives an idea about how to remove mutual reinforcement in web page ranking algorithm.
Forecasting Foreign Exchange Rate Using Robust Lagueree Neural Network

In this article, single layer based functional basis neural network has been used for foreign exchange rate prediction. In general, foreign exchange rate problem is one of the most complex problems with high non linearity and data irregularity. From many studies it is found that foreign exchange rate prediction always fluctuates with economic growth, interest rate and influence rates and therefore it is very difficult for researcher to predict foreign exchange rate. Therefore, foreign exchange rate prediction becomes a challenging task for every researcher for both academic and industrial communities. In this article two type of single layer functional link artificial neural network Functional-link Artificial Neural Network (FLANN) and Laguerre Polynomial Equation ( LAPE) were applied to forecast foreign exchange data. With high data irregularity, FLANN and LAPE both the models provide extremely precise outcome for complex time series model. The single layered based functional basis neural network architectures results matched strongly with ARIMA with very less Mean Square Error (MSE). From the Simulation study, single layer based functional basis neural network models provide improved results compare to ARIMA model with less Root Mean Square Error (RMSE) and performs as universal approximator.
Phoneme-based automatic speech recognition: Towards a demonstrator for information retrieval using Dutch hi-fi speech

Phoneme-based speech recognition for the Dutch language, using hi-fi recorded sentences as input, was investigated in this Master Thesis. This study was performed in the framework of a project called Talking Heads, in which KPN Research and TNO-TPD are involved. In that project it will be studied whether integration of automatic speech recognition and information retrieval can be combined in a single system. A speech database was collected, and context-independent phoneme models were trained and tested. Two topologies, use of a bigram, and several parameter settings were investigated. The best phoneme recognition score achieved, was 52.46%. The models and parameter settings used to obtain this score were applied for exploratory purposes in the Talking Heads project to test a database containing 10,500 words. The phoneme recognition strings thus obtained, served as input for an Information Retrieval System. The models were applied in a demonstrator.