Miracle-dz/UniFAR-FTUs huggingface dataset:
A theory of benchmarking with applications to software reverse engineering

Benchmarking has been used to compare the performance of a variety of technologies, including computer systems, information retrieval systems, and database management systems. In these and other research areas, benchmarking has caused the discipline to make great strides. Until now, research disciplines have enjoyed these benefits without a good understanding of how they were achieved. In this dissertation, I present a theory of benchmarking to account for these effects. This theory were developed by examining case histories of successful benchmarks in computer science, my own experience with community-wide tool evaluations in software reverse engineering, and the literature from philosophy of science. According to the theory, it is the tight relationship between a benchmark and the scientific paradigm of a discipline that is responsible for the leap forward. A scientific paradigm, as described by Thomas S. Kuhn, is the dominant view of a science consisting of explicit technical facts and implicit rules of conduct. A benchmark operationalises a scientific paradigm; a benchmark is a statement of the discipline's research goals and it emerges through a synergistic process of technical knowledge and social consensus proceeding in tandem. The theory of benchmarking is validated empirically against extant benchmarks and analytically against a hierarchical set of criteria. An important implication of the theory is that benchmarking can be used to cause a scientific discipline to make advances. To this end, a process model has been developed as a guide for others wishing to undertake a benchmarking project within their research communities. Also provided are a Benchmarking Readiness Assessment and criteria for evaluating the benchmarking process. The application of the theory and these process model is illustrated using two benchmarks that I have developed with the software reverse engineering community. These are the xfig benchmark for program comprehension tools and C++ Extractor Test Suite (CppETS), a benchmark for comparing fact extractors for the C++ programming language.
A technique for automated arrythmia detection of Holter ECG

Describes a fast and very effective feature extraction technique for detection and discrimination of QRS on a microprocessor-based Holter ECG analysis system. The technique converts long term (up to 24 hours) recorded ECG into a positive waveform by signal preprocessing. Three characteristic factors, the duration, the areas, and the original slope of the positive waveform, are detected when the onset and end points of each pulse have been detected by threshold detection. The prominent feature is extracted from a product of these three factors. This method has been examined using 10 different patients' ECG signals. The accuracy of QRS detection was 99.8 percent in validation. The identification sensitivity of PVC beats was 93.2 percent with 6 different arrhythmia patients. The method has also been implemented on a PC-486 based computer system. A three-channel 24-hour recorded ECG can be completely analyzed within 5 minutes for reporting the heart rate variations, ST level analysis, heartbeat classifications and arrhythmia analysis.
Performance of turbo coded multicarrier CDMA with iterative multiuser detection and decoding

The performance of a turbo coded MC-CDMA uplink with iterative multiuser detection is evaluated. Optimal likelihood ratios are computed based on the maximum a posteriori criterion using the multiuser signal structure and a priori information of code bits of all other users available from channel decoders. Combining turbo coding and multiuser detection in MC-CDMA has shown performance close to the single user bound with a few iterations of joint detection and decoding. Additionally, a suboptimal approach using soft interference cancellation is also implemented for the uplink transmission and compared with the conventional methods. Simulation results are presented in a Rayleigh multipath fading environment for a typical data transmission scheme.
Boosted Statistical Relational Learners: From Benchmarks to Data-Driven Medicine

This SpringerBrief addresses the challenges of analyzing multi-relational and noisy data by proposing several Statistical Relational Learning (SRL) methods. These methods combine the expressiveness of first-order logic and the ability of probability theory to handle uncertainty. It provides an overview of the methods and the key assumptions that allow for adaptation to different models and real world applications. The models are highly attractive due to their compactness and comprehensibility but learning their structure is computationally intensive. To combat this problem, the authors review the use of functional gradients for boosting the structure and the parameters of statistical relational models. The algorithms have been applied successfully in several SRL settings and have been adapted to several real problems from Information extraction in text to medical problems. Including both context and well-tested applications, Boosting Statistical Relational Learning from Benchmarks to Data-Driven Medicine is designed for researchers and professionals in machine learning and data mining. Computer engineers or students interested in statistics, data management, or health informatics will also find this brief a valuable resource.
Security issues in 5G device to device communication

5G is a promising technology that will support high connectivity and device to device communication. It also promises to improve the existing technologies and will support them. Existing LTE-A utilize centralized communication scheme where all the authentication mechanisms need to go through the base station. This centralized authentication mechanism may generate authentication and key management overhead as well as computational complexity, thus not in line with the 5G requirements. On the other hand, distributed communication scheme lacks hop by hop authentication, thus, it is challenging to share the initial security credentials within the relay stations at multi-hop. Secondly, distributed communication scheme required decode and forward relays, a partial intelligent relays that can act as a semi base stations. Such relays are known as non-transparent relays. However, inclusion of such intelligent relays can leads towards a ROGUE RELAY STATION (RRS) attacks, which consequently generate Replay attacks, DoS and the MITM (where mutual authentication is absent). RRS can generate interleaving attack even in the presence of mutual authentication.
Convolutional operators in the time-frequency domain

This dissertation addresses audio classification by designing signal representations which satisfy appropriate invariants while preserving inter-class variability. First, we study time-frequencyscattering, a representation which extract modulations at various scales and rates in a similar way to idealized models of spectrotemporal receptive fields in auditory neuroscience. We report state-of-the-artresults in the classification of urban and environmental sounds, thus outperforming short-term audio descriptors and deep convolutional networks. Secondly, we introduce spiral scattering, a representationwhich combines wavelet convolutions along time, along log-frequency, and across octaves. Spiral scattering follows the geometry of the Shepard pitch spiral, which makes a full turn at every octave. We study voiced sounds with a nonstationary sourcefilter model where both the source and the filter are transposed through time, and show that spiral scattering disentangles and linearizes these transpositions. Furthermore, spiral scattering reaches state-of-the-art results in musical instrument classification ofsolo recordings. Aside from audio classification, time-frequency scattering and spiral scattering can be used as summary statistics for audio texture synthesis. We find that, unlike the previously existing temporal scattering transform, time-frequency scattering is able to capture the coherence ofspectrotemporal patterns, such as those arising in bioacoustics or speech, up to anintegration scale of about 500 ms. Based on this analysis-synthesis framework, an artisticcollaboration with composer Florian Hecker has led to the creation of five computer music
Investigating the impact of sample size on cognate detection

In historical linguistics, the problem of cognate detection is traditionally approached within the frame-work of the comparative method. Since the method is usually carried out manually, it is very flexible regarding its input parameters. However, while the number of languages and the selection of comparanda is not important for the successfull application of the method, the sample size of the comparanda is. In order to shed light on the impact of sample size on cognate detection, an automatic method that closely mimics the comparative method is applied to a large dataset of varying sample sizes. The results clearly show that an increase in sample size is also accompanied by an increase in accurracy of the automatic method.
MODELING THE PSYCHOLOGICAL FACTORS AFFECTING COMPUTER PROGRAMMING SELF-EFFICACY / BİLGİSAYAR PROGRAMLAMA ÖZ-YETERLİLİĞİNİ ETKİLEYEN PSİKOLOJİK FAKTÖRLERİN İNCELENMESİ

We live in such an age that computer technologies and machines are one of the most crucial parts of human beings lives that our need and dependency to them growing exponentially day by day. This leads to increased need of more human power and involvement in programming computers and machines. Despite the increasing need however, studies indicate that number of students that prefers departments regarding computer and machine programming, software developing and engineering is declining. In this direction, it is necessary to examine the factors that are related to computer programming and to investigate the reasons of developments mentioned earlier. Therefore, this study aimed to examine the psychological factors that are thought to be related to computer programming self-efficacy. In order to do that, relationships between computer programming self-efficacy, attitude toward computer programming, psychological resilience and problem solving were investigated by using correlation test and structural equation modeling. Students from four different departments and state universities filled out a questionnaire that contains Computer Programming Self-Efficacy Scale (CPSES), Attitude Scale Toward Computer Programming (ATCP), Brief Resilience Scale (BRS), Social Problem Solving Inventory-Short Form (SPSI-SF) voluntarily and anonymously. As a result of the analyses, it was observed that computer programming self-efficacy was related positively to confidence and motivation in learning computer programming, psychological resilience, positive problem orientation and rationale problem solving, and also it was negatively related to negative problem orientation. The findings were discussed in the light of existing literature.
An Efficient and Modular Transmultiplexer Design

A new transmultiplexer design is presented in which reliability is achieved by adopting a tree structure. A working principle based upon analytic signals results in a modular structure. The usage of FIR filters designed to have coefficients which are sums of a limited and prescribed number of powers of two together with an efficient, low-sensitivity interpolating structure results in a very efficient design. When these interpolators are used to implement all processing functions required, a highly modular design is obtained which is based solely upon the elementary all-pass cell. Simulation results for a four-channel transmultiplexer are presented together with a performance evaluation for the translation between two 30 channel TDM primary groups and one 60 channel FDM supergroup and for the translation between one 24 channel North American TDM unit and two 12 channel FDM groups. The design is found to have the reliability and modularity attributes which can be obtained from a tree structure, and at the same time its efficiency compares favorably with that of transform-based trans-multiplexers.
High Definition Video Compression Usin Saliency Features

High Definition (HD) devices requires HD-videos for the effective uses of HD devices. However, it consists of some issues such as high storage capacity, limited battery power of high definition devices, long encoding time, and high computational complexity when it comes to the transmission, broadcasting and internet traffic. Many existing techniques consists these above-mentioned issues. Therefore, there is a need of an efficient technique, which reduces unnecessary amount of space, provides high compression rate and requires low bandwidth spectrum. Therefore, in the paper we have introduced an efficient video compression technique as modified HEVC coding based on saliency features to counter these existing drawbacks. We highlight first, on extracting features on the raw data and then compressed it largely. This technique makes our model powerful and provides effective performance in terms of compression. Our experiment results proves that our model provide better efficiency in terms of average PSNR, MSE and bitrate. Our experimental results outperforms all the existing techniques in terms of saliency map detection, AUC, NSS, KLD and JSD. The average AUC, NSS and KLD value by our proposed method are 0.846, 1.702 and 0.532 respectively which is very high compare to other existing technique.
MODELING INSTRUCTION AND THE NATURE OF SCIENCE

__________________________________ __________________________________ iii Acknowledgements I would like to thank my colleagues at Oregon High School. Dr. Robert Scott, the principal, broke precedent when scheduling my classes for a full year rather than by semester. Tim Martinelli, student services, assigned students random numbers for the study and kept guard over the assignment list. Kim Manny, english teacher, provided valuable suggestions that improved the readability of this thesis. Dave Ebert, math teacher, provided guidance with the statistical analysis. My gratitude goes to Sara, my wife, for freeing up nights and weekends and for spending extra time with Jaison, our son, so that I could pursue this endeavor. Without her support, this work would not have been completed. I would also like to thank the faculty at the University of Wisconsin-Whitewater for giving me the tools to create and complete this action research. In particular, I would like to thank my advisor, Dr. Virginia Epps, for tapping in to my potential and pushing me to pursue a thesis. Early in my Master's program, Dr. Epps planted the seed for this work while I was a student in her Issues and Perspectives course. That was when I first became uncomfortable with my notion that science was the search for truth. Lastly, I would like to thank " Modeling Central " for giving me the gift of modeling physics. Malcolm Wells and Dr. David Hestenes have created a wonderful approach to physics, one that saved my teaching career.
Elements of modern Igbo grammar: A descriptive approach

The Live Book Show Series One: Part Eighteen History \u0026 Language In St Lucia 1654-1915 Text preparation #PDF editing|Unicode Typing|Voice Typing|Translation|Font Conversion Grammar check Learn Igbo Phrases 53 Useful Everyday Phrases in Igbo Language JESUS Film For IgboIGBO CLASS 2 LEARNING THE IGBO LANGUAGE | HOW TO SPEAK IGBO | JANE EZEANAKA Chuka Obi \u0026 unique Singers The Anglican Pride Nigerian Gospel Music NWA ENUGU Latest 2020 Nigerian Igbo Movies| Latest Igbo Movies| Igbo Movies| African Movies Crafting the Igbo World: Igbo Cosmology in Literary LandscapesChigozie Obioma with Louisa Egbunike OLD IGBO SONGS -WORSHIP AND PRAISE Learn the Igbo Alphabet Learn Igbo Language Easily Learning Igbo: Question Words (WHAT is Gini? ) IGBO CLASS 1 LEARNING THE IGBO LANGUAGE | HOW TO SPEAK IGBO | JANE EZEANAKA The Igbo/Israel connection \u0026 the Lost Tribes of Israel The 12 Tribes Found in Igbo Land. Amazing! IGBO CLASS 3 LEARNING THE IGBO LANGUAGE | HOW TO SPEAK IGBO | JANE EZEANAKA Izuru keme Chineke mo | Non-stop Best of Igbo Worship song Vol 1 | Best Morning Worship song. 12 Reasons Yorubas and Igbos Should NOT InterMarry The amazing Ibo landing storyHow to learn Igbo Igbo Dialects and the Igboid Language Family (Ezaa, Ekpeye, Ika, Ikwerre +) IGBO HIGH PRAISE MINISTRATION (A) Learn Some Romantic Words in Igbo Language #IgboLanguage101 ' Igbo b? Igbo ' by Chimamanda Ngozi Adichie Keynote Speaker: 7th Igbo Conference Origin of the Igbo People Introduction to the Novel Things Fall Apart by Chinua Achebe Learn how to Speak Igbo Language Plus PRAISE AND WORSHIP IN IGBO LANGUAGE ||Episode 02 HSC English 1st Paper Syllabus \u0026 Marks Distribution I According to New Syllabus I Rafique Sir Akaeze 1\u00262 2018 Latest Nigerian Nollywood Igbo Movie Full HD HILARIOUS IGBO DIALECT CHALLENGE || PATRICIA OZOR This Movie will make you like Igbo Language 2 -2018 Latest Nigerian Nollywood Igbo Movie Full HD Elements Of Modern Igbo Grammar Emenanjo, 'Nolue (1976) Elements of Modern Igbo Grammar. Ibadan: Oxford University Press. ISBN 978-154-078-8; Emenanjo, Nolue. A Grammar of Contemporary Igbo: Constituents, Features and Processes. Oxford: M and J Grand Orbit Communications, 2015. Green, M.M. and G.E. Igwe. 1963. A Descriptive Grammar of Igbo.
The Influence of Tablet-Based Technology on the Development of Communication and Critical Thinking Skills: An Interdisciplinary Study

Abstract The purpose of this interdisciplinary study was to explore the impacts of tablet technology in a college classroom on students' perceptions of their own learning. Students were asked about oral, written, and graphical communication and critical thinking skills. Mid-semester and end-of-semester surveys were administered to tablet-enabled classes for collection of self-report data. Additionally, objective performance data were gathered from sections of the same courses taught using traditional methods and compared with learning outcomes of those taught using tablets. Students reported that using tablet technology was beneficial for all three types of communication skills. Findings also indicated that tablet usage contributed to a positive effect on dimensions of critical thinking. Implications for these findings are discussed.
High-Dimensional Fused Lasso Regression Using Majorization–Minimization and Parallel Processing

In this article, we propose a majorization–minimization (MM) algorithm for high-dimensional fused lasso regression (FLR) suitable for parallelization using graphics processing units (GPUs). The MM algorithm is stable and flexible as it can solve the FLR problems with various types of design matrices and penalty structures within a few tens of iterations. We also show that the convergence of the proposed algorithm is guaranteed. We conduct numerical studies to compare our algorithm with other existing algorithms, demonstrating that the proposed MM algorithm is competitive in many settings including the two-dimensional FLR with arbitrary design matrices. The merit of GPU parallelization is also exhibited. Supplementary materials are available online.
The Strength of Numbers

This paper investigates four different inclusion strategies used to recruit women to computer science: achieving a critical mass, educational reform, redefining the gendered symbolism of computer science and changing the content of the discipline. The relationship between and the relative importance of these four strategies are explored by looking at the extensive and successful Women and Computing Initiative (WCI) that was run by the Norwegian University of Science and Technology (NTNU), starting in 1996, to recruit and retain more women in computer science. The findings suggest that a direct effort to increase the relative number of women is the most important strategy. While raising the number of women recruited seems to affect the symbolic perception of computer science, this effect is difficult to achieve through attempts to directly change the symbolic image of the discipline. In addition, a substantial increase in the number of women appears to cause an improvement in their learning environment, probably because minority problems such as too much visibility and unwanted attention became less prominent.
A deadlock prevention method for a class of FMS

In this paper we propose a deadlock prevention method for a class of FMS called System of Simple Sequential Processes with Resources (S/sup 3/PR). This method is based on structural theory of Petri nets and it is composed by two phases. The first phase adds local control places to the S/sup 3/PR net such that all uncontrolled siphons of the S/sup 3/PR net become controlled. We then obtain the augmented S/sup 3/PR net. When deadlock-freeness of the augmented S/sup 3/PR net is not guaranteed, we modify initial markings of local control places. Thus, we obtain the controlled S/sup 3/PR net. We demonstrate that the controlled net cannot reach a dead-marking and by exploiting its structure, we state its liveness.
ComPAIR: A New Online Tool Using Adaptive Comparative Judgement to Support Learning with Peer Feedback

Peer feedback is a useful strategy in teaching and learning, but its effectiveness particularly in introductory courses can be limited by the relative newness of students to both the body of knowledge upon which they are being asked to provide feedback and the skill set involved in providing good feedback. This paper applies a novel approach to facilitating novice feedback: making use of students’ inherent ability to compare. The ComPAIR application discussed in this article scaffolds peer feedback through comparisons, asking students to choose the “better” of two answers in a series of pairings offered in an engaging online context. In contrast to other peer-feedback approaches that seek to train novices to be able to provide expert feedback (such as calibrated peer review) or to crowdsource grading, ComPAIR focuses upon the benefits to be gained from the critical process of comparison and ranking. The tool design is based on the longstanding psychological principle of comparative judgement, by which novices who may not yet have the compass to assess others’ work confidently can still rank content as “better” with accuracy. Data from 168 students in pilot studies in English, Physics and Math courses at the University of British Columbia are reviewed. Though the use of ComPAIR required little classroom time, students perceived this approach to increase their facility with course content, their ability assess their own work, and their capacity to provide feedback on the work of others in a collaborative learning environment.
Scalable models of microwave system responses using sequential sampling on unstructured grids

This paper presents two sequential sampling algorithms for the macromodeling of parameterized system responses in model‐dependent sampling frameworks. The construction of efficient algorithms for the automatic selection of samples for building scalable macromodels of frequency‐domain responses is addressed in this paper. The sequential sampling algorithms proposed here are tailored toward the application of local scalable macromodeling schemes on unstructured design space grids. Two pertinent examples are considered. For the first one, different algorithms are applied, and a comparison is made in terms of the number of samples generated, accuracy and CPU time. As a second example, four design variables are taken into account with one of the proposed algorithms, and the generated model is used in a frequency‐domain optimization. Copyright © 2013 John Wiley & Sons, Ltd.