Miracle-dz/UniFAR-FTUs huggingface dataset:
Semi-automatic checklist-based quality assessment of natural language requirements = Avaliação semi-automática de qualidade de requisitos em língua natural baseada em checklist

Problems with the speci cation of software requirements are a common cause of software defects. In domains such as space applications, those defects are very costly, especially when detected after software deployment, when the product is already in the eld. It is imperative to ensure that software requirement documents are well written to avoid the introduction of these defects. The quality of software requirements is frequently assessed via reviews guided by checklists, based on standards, and on problems found in previous projects. Given the importance of quality assessment, and the fact that the reviews are performed manually, we propose a framework for assisting a checklist-based review of software requirements, using natural language processing techniques. A tool was developed under this framework, whose objetive is to diminish the reviewer's e ort, and to reduce the amount of uncaught errors during the reviewing process. Experiments were conducted to compare the checklist-based analysis performed manually, against the semi-automatic analysis guided by the developed tool, considering the analysis time and the amount of errors detected in the requirements under analysis. The results indicate that the semi-automatic analysis method, guided by the proposed framework, brings improvements to the existing manually conducted method.
Empirical Analysis and Validation of Security Alerts Filtering Techniques

System administrators cope with security incidents through a variety of monitors, such as intrusion detection systems, event logs, security information and event management systems. Monitors generate large volumes of alerts that overwhelm the operations team and make forensics time-consuming. Filtering is a consolidated technique to reduce the amount of alerts. In spite of the number of filtering proposals, few studies have addressed the validation of filtering results in real production datasets. This paper analyzes a number of state-of-the-art filtering techniques that are used to address security datasets. We use 14 months of alerts generated in a SaaS Cloud. Our analysis aims to measure and compare the reduction of the alerts volume obtained by the filters. The analysis highlights pros and cons of each filter and provides insights into the practical implications of filtering as affected by the characteristics of a dataset. We complement the analysis with a method to validate the output of a filter in absence of ground truth, i.e., the knowledge of the incidents occurred in the system at the time the alerts were generated. The analysis addresses blacklist, conceptual clustering and bytes techniques, and our filtering proposal based on term weighting.
Two algorithms for leader election and network size estimation in mobile ad hoc networks

Two Algorithms for Leader Election and Network Size Estimation in Mobile Ad Hoc Networks. (December 2004) Nicholas Gerard Neumann, B.S., Texas A&M University Chair of Advisory Committee: Dr. Jennifer Welch We develop two algorithms for important problems in mobile ad hoc networks (MANETs). A MANET is a collection of mobile processors (“nodes”) which communicate via message passing over wireless links. Each node can communicate directly with other nodes within a specified transmission radius; other communication is accomplished via message relay. Communication links may go up and down in a MANET (as nodes move toward or away from each other); thus, the MANET can consist of multiple connected components, and connected components can split and merge over time. We first present a deterministic leader election algorithm for asynchronous MANETs along with a correctness proof for it. Our work involves substantial modifications of an existing algorithm and its proof, and we adapt the existing algorithm to the asynchronous environment. Our algorithm’s running time and message complexity compare favorably with existing algorithms for leader election in MANETs. Second, many algorithms for MANETs require or can benefit from knowledge about the size of the network in terms of the number of processors. As such, we present an algorithm to approximately determine the size of a MANET. While the algorithm’s approximations of network size are only rough ones, the algorithm has the important qualities of requiring little communication overhead and being tolerant of link failures.
Fuzzy logic technique for congestion line identification in power system

Congestion problem is a significant issue in power system due to the increasing demand in this vicinity. Failure in properly managing the issue may lead to insecure power delivery to the consumer. Flexible Alternating Current Transmission (FACTs) can be a possible solution for the compensating purposes. This requires proper decision making so that proper sizing can be identified which in turns reducing monetary losses. This paper presents fuzzy logic technique for congested line identification as a decision tool. A pre-developed line voltage stability index, termed as fast voltage stability index (FVSI) is chosen as the incorporating instrument in this study. A sensitivity analysis equation is formulated termed as Fuzzy Congestion Index (FCI). Validation was conducted using the IEEE 30-Bus Reliable Test System (RTS). Results from the study revealed that the proposed technique managed to correctly identify the congested line. FCI was compared FVSI, indicating that the proposed technique revealed the suitability for identifying the congested line. This technique is also feasible for further implementation in larger and practical system.
SOCIAL BOOK SEARCH: A COMBINATION OF PERSONALIZED RECOMMENDATIONS AND RETRIEVAL

The Web and specifically Web 2.0 applications give us access to a wealth of information. In contrast to traditional collections, documents now contain both information contributed by professionals as well as end-users (user generated content). Furthermore, the volume of documents accessibly through many Web 2.0 applications often is several times larger. These different characteristics are challenging for search systems that are based on the classical model of topical relevance and ad hoc search. It is argued that solely relying on topic relevance is no longer enough to allow the information seeker to fulfill her information need. Taking other notions of relevance into account ‐ for example: how popular, well-written, recent or fun a particular document is ‐ may help in improving retrieval performance. This is information typically found in user generated content in the form of tags, reviews and ratings. In this paper we extend research done by participants of the INEX 2012 Social Book Search Track where a combination of social and professional metadata from LibraryThing and Amazon is used to suggest relevant books to LibraryThing members asking for book suggestions. By crawling LibraryThing’s user catalogues we collect transactional data that expresses a users preference for specific works. We utilize this data to successfully predict a user’s personal preference for books unknown to her. Subsequently we use different collaborative filtering techniques in combination with traditional information retrieval models to significantly improve the overall retrieval performance.
Development of small scale cluster computer for numerical analysis

In this study, two units of personal computer were successfully networked together to form a small scale cluster. Each of the processor involved are multicore processor which has four cores in it, thus made this cluster to have eight processors. Here, the cluster incorporate Ubuntu 14.04 LINUX environment with MPI implementation (MPICH2). Two main tests were conducted in order to test the cluster, which is communication test and performance test. The communication test was done to make sure that the computers are able to pass the required information without any problem and were done by using simple MPI Hello Program where the program written in C language. Additional, performance test was also done to prove that this cluster calculation performance is much better than single CPU computer. In this performance test, four tests were done by running the same code by using single node, 2 processors, 4 processors, and 8 processors. The result shows that with additional processors, the time required to solve the problem decrease. Time required for the calculation shorten to half when we double the processors. To conclude, we successfully develop a small scale cluster computer using common hardware which capable of higher computing power when compare to single CPU processor, and this can be beneficial for research that require high computing power especially numerical analysis such as finite element analysis, computational fluid dynamics, and computational physics analysis.
LOW COMPLEXITY ITERATIVE RECEIVER DESIGN FOR OFDM SYSTEMS

OF THE DISSERTATION Low Complexity Iterative Receiver Design for OFDM Systems By Vamadevan Namboodiri Advisor: Prof. Predrag Spasojevic Single Input Single Output (SISO) Orthogonal Frequency Division Multiplexing (OFDM) systems have been adopted in many of the recent wireless communication standards such as European terrestrial broadcast systems based on DVB-H, DVB-T, DVB-T2. For OFDM systems, cyclic prefix of sufficient length makes the receiver design simple in frequency-selective multipath environments. Wireless communication based on Multiple Input Multiple Output (MIMO) systems has also gained popularity due to the potential capacity increases it can provide. MIMO-OFDM based transmission systems can thus provide very high data rates with a relatively simple receiver design and are now adopted widely in recent wireless communication standards such as Long Term Evolution(LTE), LTE Advanced, WiMAX and WiFi. Modern wireless communication applications, both SISO and MIMO, require high data rates in a limited bandwidth at high carrier frequencies and at high levels of mobility. This results in less intercarrier spacing and severe time-varying frequency-selective multipath fading, which breaks the orthogonality of subcarriers and causes intercarrier interference (ICI) in the received signal thus severely impacting the BER performance of the receiver. In the trend of adopting higher carrier frequencies, higher bandwidth and higher mobility, ICI is expected to be more of a limiting factor in mobile OFDM systems. Therefore efficient
Iterative multiuser receiver for a coded DS-CDMA system

A new iterative multiuser receiver structure for a direct-sequence code division multiple access (DS-CDMA) system with forward error correction (FEC) coding is proposed. This structure employs the turbo multiuser detection principle in a soft multi-access interference cancellation scheme. The receiver first uses a Wiener filter to demodulate and de-spread the received signal, this process yields the initial coded data estimates. Based on these estimates, the parallel cancellation scheme and the channel decoding are coupled to exchange soft information in an interactive fashion. Simulation results show that performance approaches the single-user performance even in highly loaded systems. It is also shown that the use of Wiener filtering on the first iteration of the iterative receiver yields a substantial performance gain in the system.
A Framework to Facilitate Wireless Sensor NetworkApplication Development

Wireless sensor networks is a technology that was originally envisioned as a tool for broad range of purposes and target audiences. However, wireless sensor network software development is complicated, because it brings together the complexity of resource-constrained embedded system software and the complexity of distributed system software. This is one of the reasons why sensor networks have not yet become an ubiquitous technology. This problem is partially solvable by decreasing the accidental software development complexity that is at the moment present in the process of sensor network application development. The sensor network application developer must be provided with appropriate development tools, languages and libraries in order to allow him to focus on the essential complexity of software development. Therefore this dissertation presents a number of approaches that facilitate sensor network application programming, including: a new application development language that allows to write applications in more concise and less complex way, and an approach to increase the resource-efficiency of sensor network operating systems. The approaches are integrated in a unified framework, along with other software designed by the author and his research group. This framework is targeted towards two categories of users: firstly, novice programmers, secondly, professional programmers, including programmers with limited experience in wireless sensor networks. The evaluation shows that these approaches lead to applications with decreased resource usage and lower code complexity.
LOW RESOURCE HIGH ACCURACY KEYWORD SPOTTING

Keyword spotting (KWS) is a task to automatically detect keywords of interest in continuous speech, which has been an active research topic for over 40 years. Recently there is a rising demand for KWS techniques in resource constrained conditions. For example, as for the year of 2016, USC Shoah Foundation covers audio-visual testimonies from survivors and other witnesses of the Holocaust in 63 countries and 39 languages [1], and providing search capability for those testimonies requires substantial KWS technologies in low language resource conditions, as for most languages, resources for developing KWS systems are not as rich as that for English. Despite the fact that KWS has been in the literature for a long time, KWS techniques in resource constrained conditions have not been researched extensively. In this dissertation, we improve KWS performance in two low resource conditions: low language resource condition where language specific data is inadequate, and low computation resource condition where KWS runs on computation constrained devices. For low language resource KWS, we focus on applications for speech data mining, where large vocabulary continuous speech recognition (LVCSR)-based KWS techii
Efficient VLSIRealizable Decimators for SigmaDelta AnalogtoDigital Converters

This paper introduces a class of efficient linearphase FIR decimators for attenuating the out-of-band noise generated by a sigma-delta analog-to-digital modulator. These decimatora contain no general multipliers and very few data memory loeatlons, thereby making them easily VLSI-realizable. This is achieved by using several decimation stages with each stage containing a small number of delays and arithmetic operations. The output sampling rate of these decimators is the minimum possible one, unlike for most other existing designs and the proposed decimators Can be used, with. very slight changes, for many ovesampling ratios. Puthermore, these decimators attenuate highly the undesired out-of-band signal components of the input signal, thus significantly relaxing the anti-aliasing prefilter requirements.
Motion Based Background Subtraction and Extraction Using Decolor and K-Means Clustering for Providing Security

Video surveillance systems have long been in use to monitor security sensitive areas. The making of video surveillance systems “smart” requires fast, reliable and robust algorithm for moving object detection, classification, tracking and activity analysis. Moving object detection is the basic step for further analysis of video. It handles segmentation of moving objects from stationary background objects. Object classification step categorizes detected objects into predefined classes such as human, vehicle, clutter etc. It is necessary to distinguish objects from each other in order to track and analyse their actions reliably. In previous system we have performed background subtraction by using Canny Edge Detection. In Canny Edge Detection process we are taking background image and foreground image for comparison. In previous strategies we are conducting background subtraction only for images. In proposed system the background subtraction is done for moving objects, we propose a pixel wise background modeling and subtraction technique using multiple features. Hence, in this colour, gradient and digital image features are integrated to handle the variation pixel. Then the detected image is send to the mobile through GSM modem as a message and the detected image can be viewed through mobile using the IP address.
Monostatic CW SAR Concept for Microsatellites

Currently there is a considerable effort to design and build synthetic aperture radar (SAR) payloads for small (micro-)satellites. This is difficult to achieve with conventional pulsed SARs, as their peak power demands tend to make the payloads heavy and expensive to produce. Recent developments focusing on continuous wave (CW) techniques have proved successful in minimising the cost, weight and power consumption of SARs for small uncrewed air vehicles (UAVs), where the transmitter and receiver can be mounted separately on the same platform. Applying the same technology to space based SARs necessatitates a bi-static dual-spacecraft configuration in order to provide enough isolation between transmitter and receiver. This paper presents an alternative novel concept for using CW SAR in space - switched or interrupted CW SAR; employing a single antenna from a single microsatellite; along with highlighting the associated problems.
CREATING EVALUATION PROFILES FOR GAMES DESIGNED TO BE FUN: An Interpretive Framework for Serious Game Mechanics

Background. Games can be great pedagogical tools for educators and students. COTS games (commercial-off-the-shelf) are designed for the pure purpose of leisure but can also contain educational value. Aim. In this paper, we address the potential of COTS games as serious games. We develop an interpretive evaluation framework that can identify the educational value in COTS games. Application. The presented framework can create evaluative profiles of the learning, social, game, and immersive mechanics of COTS games as educational tools. Moreover, the framework can position COTS games between four intertwined dimensions, namely pedagogical, design, knowledge, and sociotechnical considerations. Demonstration. To validate the practical application of the interpretive framework, we apply it to a real-world example. Our demonstration reveals the usefulness of the framework. Conclusions. The framework enables critical reflection on the game mechanics; thereby capturing the complexity of the game mechanics that makes COTS game both educational and fun to play.
A Social Network Analysis of an Introductory Calculus-Based Physics Class with Comparisons of Traditional and Non-Traditional Students, FCI Scores, and Network Centralities

Sandt, Emily Nicole. M.S. Department of Physics, Wright State University, 2016. A Social Network Analysis of an Introductory Calculus-Based Physics Class with Comparisons of Traditional and Non-Traditional Students, FCI Scores, and Network Centralities. The use of social network analysis in physics education research seeks to advance understanding of how students’ collaborative tendencies influence trends of learning. Common useful measurements are network size, density of connections, and centrality measures that describe the importance of nodes’ positions. This study compared four different centrality measures at the beginning and end of seven sections of an introductory calculus-based physics course. The Force Concept Inventory was used as a measure of conceptual learning at preand post-course administrations. The main focus of this study was to identify if differences in network centralities and conceptual learning/knowledge exist with respect to students’ designations as non-traditional or traditional (age 22+). Various class sizes, styles, and instructors were included in the data. Results showed some common and conflicting trends for the different class types, with non-traditional students generally at a disadvantage in network position but comparable in conceptual scores.
New Data Encryption Standard Algorithm

A goal is the design of any encryption algorithm must be security against unauthorized attacks. Within the last decade, there has been a vast increase in the accumulation and communication of digital computer data in both the private and public sectors. Much of this information has a significant value, either directly or indirectly, which requires protection. The algorithms uniquely define the mathematical steps required to transform data into a cryptographic cipher and also to transform the cipher back to the original form. Performance and security level is the main characteristics that differentiate one encryption algorithm from another. Here introduces a new method to enhance the performance of the Data Encryption Standard (DES) algorithm is introduced here. This is done by replacing the predefined XOR operation applied during the 16 round of the standard algorithm by a new operation depends on using two keys, each key consists of a combination of 4 states (0, 1, 2, 3) instead of the ordinary 2 state key (0, 1). This replacement adds a new level of protection strength and more robustness against breaking methods. The New Comparative Study between DES, 3DES and AES within Nine Factors achieving an efficiency, flexibility and security, which is a challenge of researchers.
Extensible Hierarchical Method of Detecting Interactive Actions for Video Understanding

For video understanding, namely analyzing who did what in a video, actions along with objects are primary elements. Most studies on actions have handled recognition problems for a well‐trimmed video and focused on enhancing their classification performance. However, action detection, including localization as well as recognition, is required because, in general, actions intersect in time and space. In addition, most studies have not considered extensibility for a newly added action that has been previously trained. Therefore, proposed in this paper is an extensible hierarchical method for detecting generic actions, which combine object movements and spatial relations between two objects, and inherited actions, which are determined by the related objects through an ontology and rule based methodology. The hierarchical design of the method enables it to detect any interactive actions based on the spatial relations between two objects. The method using object information achieves an F‐measure of 90.27%. Moreover, this paper describes the extensibility of the method for a new action contained in a video from a video domain that is different from the dataset used.