Miracle-dz/UniFAR-FTUs huggingface dataset:
A Contract-based Slicer for Boogie Programs

In the context of the Informatics Engineering MSc. degree (MEI), second year, this document describes and discusses a master thesis project in the area of source code analysis using slicing and program verification techniques. Design-by-Contract is an approach that allows a programmer to specify the expected behaviour of a component by the means of preconditions, postconditions and invariants. These annotations (or contracts) can be seen as a form of enriched software documentation and they are used to verify that the program is correct with respect to these contracts. On one hand, slicing the program to extract the code that is relevant for the contracts reduce the size of the program and improves its verification. On the other hand, using the contract to slice a program in a finer, more sensible semantic way, enables to optimise the code reducing it to the minimum necessary to keep the postcondition true. Following the last research direction, Daniela da Cruz introduced in her Ph.D. thesis the concepts of Assertion-based Slicing and Contract-based Slicing to explore (at an intra-procedural or interprocedural level) the optimisation of code according to the semantics expressed by contracts. Her approach is based on the source code analyses and her slicing uses annotations present in the procedures. This thesis focuses on the study of BoogiePL language and its use as an intermediate representation for annotated programs in order to build slices of Boogie programs (instead of slicing the source code). Boogie compiler is used to generate the verification conditions in SMT just for the computed slice; these conditions can be then passed to the Z3 Prover to ensure that all contracts are preserved when invoking annotated procedures. The final objective is to make possible the comparison between the SMT code produced by this approach and the code currently generated by GamaSlicer, expecting to obtain a more efficient solution. To implement that idea, a tool called GamaBoogie was developed. That tool, at the end, offers more than its main functionality in slicing and verifying. Actually it allows to inspect and visualise boogie programs; this functionality seems to be very useful for Boogie program comprehension.
Accurate Comparison of Binary Executables

As the volume of malware inexorably rises, comparison of binary code is of increasing importance to security analysts as a method of automatically classifying new malware samples; purportedly new examples of malware are frequently a simple evolution of existing code, whose differences stem only from a need to avoid detection. This paper presents a polynomial algorithm for calculating the differences between two binaries, obtained by fusing the well-known BinDiff algorithm with the Hungarian algorithm for bi-partite graph matching. This significantly improves the matching accuracy. Additionally a meaningful metric of similarity is calculated, based on graph edit distance, from which an informed comparison of the binaries can be made. The accuracy of this method over the standard approach is demonstrated.
A CNN Vehicle Recognition Algorithm based on Reinforcement Learning Error and Error-prone Samples

Focused on the issue that in the latter part of training the recognition accuracy of convolutional neural network increased slowly and the training process was time-consuming, a reinforcement learning error training samples and error prone training samples CNN recognition algorithm was proposed. The algorithm uses the advantage that the network error rate decreases rapidly in the initial epochs of training. In the initial stage of training, reduce the training epochs and after each training, error training samples and error prone training samples are updated to the training set. Apply this algorithm to vehicle recognition. The accuracy of the experiment was 98.33%, and the training time was shortened to 30.97% of the original algorithm. Experimental results show that in the process of training learning error samples and error prone samples repeatedly improves the recognition accuracy and reduces the training time of CNN.
A Theory of Defensive Skill-Biased Innovation and Globalization

This paper considers a dynamic model of innovations in which  rms can endogenously bias the direction of technological change. Both in a North–North and North–South context, we show that, when globalization triggers an increased threat of technological leapfrogging or imitation,  rms tend to respond to that threat by biasing the direction of their innovations towards skilled-labor-intensive technologies. We show that this process of defensive skill-biased innovations generates an increase in wage inequalities in both regions. We then discuss suggestive empirical evidence of the existence of defensive skill-biased technical change. (JEL F12, O33, J31)
The Detection of Internal Fingerprint Image Using Optical Coherence Tomography

Abstract Recently, optical coherence tomography (OCT) has been tested as a contactless technique helpful for damaged or spoofed fingerprint recovery. Three dimensional OCT images cover the range from the skin surface to papillary region in upper dermis. The proposed method extracts from cross-sections of volumetric images (B-scans) high intensity ridges in both air-epidermis and dermis-epidermis interfaces. The extraction is based on the localisation of two OCT signal peaks corresponding to these edges. The borders are spline smoothed in two orthogonal planes of the image space. The result images are presented and compared with camera views.
Research on Image Network Retrieval Application Based on Swarm Optimization Algorithm

The traditional image retrieval adopts a text-based method, which requires a lot of manual annotation of the images in the image library and matches according to the keywords when searching. Already not suitable for the modern image network retrieval, this paper proposes a network model based on the particle swarm optimization algorithm, and then establishes a mathematical model based on swarm intelligence. Using images' low-level visual features to retrieve images is the core of content-based image retrieval. Content-based image retrieval is an approximate matching technique that combines computer vision, image processing, and database and other technical achievements in many fields. The feature extraction can be done automatically by computer, avoiding the subjectivity of traditional manual annotation, and can also improve the accuracy. degree.
A physical mobile radio channel model

A semiempirical model for macrocellular mobile radio channels typically encountered in different outdoor environments is presented. The influence of terrain structure on the time- and frequency-selective channel behavior is analyzed. General functional forms are derived in a parametrized form characterizing the channel impulse response. The relevant parameters are extracted from measured data collected with a narrowband system (resolution 5 mu s, f/sub c/=150 MHz) and a broadband system (resolution 150 mu s, f/sub c/=900 MHz) in different regions of Switzerland. Relations between the parameters and the corresponding physical propagation environment can be shown. This is demonstrated for the amplitude distribution and the scattering function, allowing a classification of possible macrocellular channels. Extensions of this method to microcellular channels is also demonstrated. <<ETX>>
Game-Based Introductory Learning: Teaching Digital Skills to Older Citizens

This paper gives a brief description of an exploratory study in which older citizens were introduced to interactive technology by playing games on touch-screens, playing in pairs with the assistance of a mentor. We focus on two principle aspects, the peer-to-peer interaction during these sessions, and the role of the mentor in progressing the sessions. In the case of peer-to-peer interaction we looked for ways in which players supported each other during interaction to assess the role of peer interaction in this context. In the case of mentoring, contrasting approaches taken in the sessions were analysed for their relative efficacy, both in managing instrumental learning, and in fostering confidence and positivity in participants. We found that peer interaction was broadly a positive influence within sessions. Mentors primarily have a strategic role in providing encouragement and support for the flow of exploratory interaction, rather than providing proactive tutoring.
Dietary fiber and its effect on obesity: A review article

Obesity is a prominent health problem in the developed world, and leads to other metabolic diseases. Besides exercise and physical activity, a dietary regimen of fiber-rich food could be a primary solution to overcome obesity. Over the past decades, scientists have been investigating the role of dietary fiber to prevent obesity through innumerable experimental or observational studies. Epidemiological evidences showed that dietary fiber in either soluble or insoluble form helps to reduce weight among overweight or obese adults. This review explores studies that used dietary fiber in different forms to provide a probable conclusion. The objective of this review is to demonstrate the relationship between intake of dietary fiber and its effect on obesity. A comprehensive search for all published academic articles and peer-reviewed up to August 2018 was carried out through a systematic electronic search of several databases. Any interventional, cross-sectional or prospective cohort study from 1980 to 2018 that examined the association between intake of dietary fiber and obesity was included. All the cross-sectional and cohort studies suggested a significant relationship between fiber intake and a reduction in obesity or a classification of being overweight. Within interventional studies, some treatment groups showed no association with fiber supplementation, whereas other studies with longer interventional periods showed a significant association with obesity. Though increased consumption of dietary fiber has an impact on health, it depends on the sources or functionality of the fiber, supplementation or consumption dosage of the fiber, and both the duration of the study and follow-up time points. This suggests that fiber in an edible form or from its mixing with other foods may contribute to prevent the prevalence of obesity.
Biotechnological Approaches for Treating Viral Diseases in Orchids

Viral diseases of orchids cause major losses in productivity and quality. Host plant resistance offers an effective means of controlling plant diseases caused by viruses. It minimizes the necessity for the application of pesticides. However, in most orchids no natural disease resistance is available. Genetic engineering allows the introduction of specific, in some instances broad spectrum, disease resistance derived from other species or even from the pathogen itself into plant genotypes that have been selected for desirable horticultural properties. This manuscript broadly provides an overview of these themes. _____________________________________________________________________________________________________________
Efficient multidimensional volume rendering

In many medical fields, volume rendering is beneficial. For the effective surgery planning, interior objects as well as the surface must be rendered. However, direct volume rendering is computationally expensive and surface rendering cannot represent inside objects of the volume data. In addition, surface rendering has a disadvantage that the huge amount of generated polygons cannot be easily managed even on high-end graphics workstations. This paper presents a way of generating multi-planar imags efficiently. Multi-planar rendering consists of two parts, surface and cutting plane. To efficiently generate surface, our algorithm uses image- based rendering. Image-based rendering generates an image in constant time regardless of the complexity of the input scene. To speed up the performance, our algorithm uses intermediate image space instead of final image space. To reduce the space complexity , we use a new data structure that is based on delta-tree to represent volume. The algorithm was implemented on a Silicon Graphics Indigo 2 workstation with a single 195 MHz R10000 processor and 192MB Main Memory. For the experiments, we use 3 volume data sets, UNC head, engine and brain. Our algorithm takes 5-20 milliseconds to project reference images to the desired view. Including the warping time, 40 milliseconds are required to generate an image.
A Domain Independent Technique to Generate Feature Opinion Pairs for Opinion Mining

The rapid growth of e-commerce and social media services in recent times have opened up many interesting Opinion mining research problems. Among others, Aspect/Feature based Opinion extraction have managed to grab researcher’s attention. Towards this direction, many researchers have proposed techniques that are supervised and domain dependent for extracting opinions. In this paper, a novel technique that is unsupervised and domain independent is proposed for generating relevant Feature Opinion pairs with good accuracy. Technique employs grammatical relationships obtained by using typed dependency parsers to further refine the pairs extracted by Part of Speech taggers. It also focusses on words that are verbs and nouns which in some cases imply opinions, unlike other existing work which mainly focusses on adjectives and adverb expressions for Opinion analysis. The proposed technique was tested on 9 data sets of different domains. The result demonstrated a good percentage reduction in number of irrelevant Feature Opinion pairs and the relevancy of retained pairs was found to be considerably high.
Intel ® 64 and IA-32 Architectures Software Developer ’ s Manual

NOTE: The Intel® 64 and IA-32 Architectures Software Developer's Manual consists of five volumes: Basic Architecture, Order Number 253665; Instruction Set Reference A-M, Order Number 253666; Instruction Set Reference N-Z, Order Number 253667; System Programming Guide, Part 1, Order Number 253668; System Programming Guide, Part 2, Order Number 253669. Refer to all five volumes when evaluating your design needs.
The impact of correlation on delay performance of high speed networks

This paper focuses on the impact of correlation on the delay performance of high speed networks. Markov-modulated Poisson process (MMPP), which captures both burstiness and correlation between interarrival times, is used to model packet arrival processes in high speed networks. Only one hop of a high speed network is studied since queueing networks can be approximately analyzed by decomposing the network into several separate elements. For simplicity, the authors model this one hop of the network as an MMPP/M/1 queue. The delay performance of MMPP/M/1 queue is investigated in terms of the MMPP correlation. A comparison among correlation, burstiness, and utilization impacts on delay performance is presented. <<ETX>>
The mediating effect of team‐level knowledge creation on organizational procedural justice and team performance improvement

This study examines how organizational procedural justice affects team performance through team-level knowledge creation practices and the extent to which these practices mediate the association between organizational procedural justice and team performance. The target samples were drawn from six organizations in Korea. A total of 348 cases were used for this study. Structural equation modeling was used to test the proposed research framework. The results indicate that all the direct paths among the research variables were statistically significant. In addition, this research confirms the mediating effect of knowledge creation practices in the relationship between organizational procedural justice and team performance. Conclusions, implications for human performance technology, limitations of the study, and further research also are discussed.
Estimation of Turboprop Engine Parameters for Various Fuels

Abstract The analysis of work parameters of a turboprop engine fuelled by various fuels was done in the article. The turboprop engine model was presented in the beginning. The main feature of this model is description of the flow in the engine as semi-perfect gas model. By this way, the change of fumes chemical composition influence the gas properties as heat constant and isentropic index are determined. Next energy balance of a compressor and turbine was analysed and turbine pressure drop was evaluated. Finally, engine output power was determined. It was done for selected fuels, which could be applied in the aero engines. The results of analyse were presented in the tables and charts and discussed. Summary of the test results with the results for contemporary applied fuel allows drawing the conclusions about the turboprop engine performance change by various fuel application. Main of them refers to the point that higher combustion heat value of fuel and higher heat constant of fumes cause better engine work conditions By this way the hydrogen seems to be perspective fuel of future, because its combustion heat value is three times JET A-1 and by this way it is possible the engine fuel consumption will be lower.
FPGA implementation of a high-speed, real-time, windowed standard deviation filter

Characterisation of the standard deviation of a time-series signal has uncommon, yet widespread applications. The usual requirement for a representation of signal standard deviation in real-time implies a high computation speed. A method based on a field programmable gate array (FPGA) implementation is presented. The technique is benchmarked against conventional computational approaches and shows a single windowed standard deviation update calculation of a 16 bit sample can be achieved in 11 ns on a modern CPU. The FPGA implementation is found to be superior to all other approaches examined with an operation time of below 10 ns, and thus provides a useful tool for the real-time measurement of the standard deviation of signals above 100 MHz.
META-ANALYSIS OF RELATION BETWEEN CORPORATE GOVERNANCE AND EARNINGS QUALITY *

ABSTARCT The aim of this research is meta-analysis execution of relation between corporate governance and earnings quality on basis of results of performed researches in listed companies in Tehran’s securities exchange. For the meta-analysis with studying performed researches about corporate governance and earnings quality from scientific information database (Sid.ir), 3 researches selected that totally had included 25 hypotheses in relation to mechanisms of corporate governance and earnings quality criterions. The reason of selecting these 3 researches was accessibility of information related to statistics and other needed information for performing meta-analysis. Results of studying these researches imply that these studies are heterogenous. In the direction of identifying cause of this heterogeneity, by dividing researches on basis of different criterions of earnings quality (quality of accrual items, earnings stability and earnings forecast ability) and also different indexes of corporate governance measurement (percent of outside board members, percentage ownership of institutional investors, type of auditor, type of ownership, and giving dual responsibility to single people) and calculating intra group χ statistic, we found that these different criterions applied in researches are one of the contradiction factors in results of researches. In continuation of study, by calculating effect size and confidence interval, it was observed that there is a meaningful relation between corporate governance and quality of accrual items. But results show lack of existence of meaningful relation between corporate governance and earnings stability and also corporate governance and earnings forecast ability. Also by dividing researches on basis of corporate governance indexes and calculating effect size and confidence interval, it was observed that there is a meaningful relation between percentage ownership of institutional investors and earnings quality. But in other categories, results imply lack of existence of a meaningful relation between independent variable (percent of outside board members, type of auditor, type of ownership and giving dual responsibility to single people) and earnings quality.
Corpuscle – a new corpus management platform for annotated corpora

Corpuscle is a new corpus query engine and Web-based corpus management system. The main design goals were the ability to handle very large corpora, support for structured data (XML), and seamless integration of manual corpus annotation and editing. New algorithms have been developed, among them a technique for running finite state automata from edges with lowest corpus counts, and an implementation of regular expressions on suffix arrays for fast reverse index lookup. These algorithms allow for a clean and elegant implementation of multi-valued and set-valued attributes. The web interface offers rich functionality for concordancing, collocations, distribution statistics, and more. Queries can be input in a graphical, menu-driven way, freeing the user from dealing with the complexities of the query language.
Hierarchical model-based fault diagnosis with application to vehicle systems /

In the context of complex plants, a fault diagnosis system for on-line applications must provide guaranteed response times completing the diagnosis in a deterministic amount of time, it must be able to reason about time because much information can be deducted from time events, and it must use all the information available for improving and speeding the diagnosis. The fundamental issues of how to model the system and develop a diagnostic procedure arise in this context. In the case of complex system, the application of model-based FDI algorithms becomes computationally very difficult or even intractable. In this dissertation, we present a new framework for hierarchical model-based fault diagnosis in complex systems that combines qualitative and quantitative method­ ologies and allows great flexibility, modularity, and fault isolation with a reduced computational effort. The presented framework is structurally divided into a passive and an active com­ ponents. The model-based passive component represents knowledge about the fault behavior of the system under analysis, and consists of a Hierarchical Fault Propaga­ tion Digraph and a Hierarchical Model-Based FDI scheme. The active component is constituted by a Fault Location and Isolation Process and a Supervisory Process that use the model-based knowledge for diagnosis. The fundamental novelties in the presented method with respect to the past are related to the use of fault propagation ii Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. digraphs having weighted arcs with fault propagation probabilities and upper/lower bounds on fault propagation times, and nodes corresponding to active/activatable fault detection units. The introduction of these properties and components in the digraph, not only makes the proposed scheme more valuable than approaches as FMEA, event trees and FTA. but also allows the use of model-based FDI to compen­ sate for the absence of system dynamics modeling, making the scheme more simple, attractive and powerful than signed digraphs. The combination of a quantitative methodology with a qualitative methodology constitutes the innovative idea in this dissertation and contributes to fill one of the biggest gaps in the current literature on fault diagnosis. The methodology is applied to a vehicle brake-by-wire and steer-by-wire systems with simulations and experimental results that shown the validity of the presented approach.