Reviewerly/exHarmony huggingface dataset:
A Pixel-Parallel Virtual-Image Architecture for High Performance and Power Efficient Graph Cuts Inference

A Pixel-Parallel Virtual-Image Architecture for High Performance and Power Efficient Graph Cuts Inference Tianqi Gao, University of Illinois Urbana Champaign Rob A. Rutenbar, University of Pittsburgh Contact: [email protected] Graph Cuts is a popular technique for Maximum A Posteriori inference in computer vision. It transforms a Markov Random Field problem into a network flow problem, solved via the Push-Relabel algorithm. While attractively simple, the large size of a typical image and the large number of necessary pixel-level iterations render the technique computationally expensive. Prior accelerator attempts have been reported with GPUs and FPGAs. In [1], the first pixel-parallel architecture was demonstrated in FPGA, but limited to only 256-pixel images. This paper extends this pixel-parallel concept and makes following contributions: a "Virtual Image" architecture solves the size limitation: large images are decomposed into "tiles", and "stacked" on the physical processor array; appropriate addressing mechanisms handle virtual pixels and a range of tile edge effects; scaling up the processor array to 1536 pixels; a novel and hardware-friendly heuristic shortens the convergence. We demonstrate the first working virtual-image Graph Cuts accelerator, applied to standard 640x480 images. Scaling up the hardware and the new heuristic bring 6.5x and 1.65x speedups respectively compared with [1]. The design is 7-20x faster than prior FPGA designs, and roughly comparable in speed to a modern GPU benchmark. However, the architecture also offers significant performance-per-unit-power advantages. Formulating a figure of merit particularly for Graph Cuts inference - Graph Cuts per second per Watt - our architecture is about 4 times better than other implementations. Keywords: FPGA; Machine learning; Hardware Acceleration; Computer Vision DOI: https://doi.org/10.1145/3289602.3293948
Understanding User Behavior in Online Banking System

Currently, online banking has become extremely popular all over the world and plays a significant role in people‘s daily lives. However, the user behaviors have yet to be studied carefully in existing works. In this paper, we provide a large-scale, comprehensive measurement study of online banking users based on a two-week long dataset consisting of transactions conducted by personal users in one of the top banks in China. We demonstrate the customer behaviors mostly comply with the heavy-tail distribution which implies abnormal activities. In further analysis of those activities, we figure out that most of them are generated by two types of accounts, i.e., corporate accounts paying salaries and dishonest bank employees plastering the achievement. We extract a set of features to classify the two types of abnormal accounts from the benign ones. The experimental result illustrates that our system can accurately detect them with only $$0.5\%$$ false positive rate.
Significance of Geographical, Hydrogeological, and Hydrogeochemical Origin for the Elemental Composition of Bottled German Mineral Waters

There are numerous classification systems which attempt to categorize mineral waters according to their suitability to contribute to the mineral nutrition of humans, pharmaceutical significance, and others. The categorization of classes within every classification system is based on measurable features; the attribution of water to a class reveals relevant information without the need for an individual analysis. It is the objective of this chapter to allocate water provenances on basis of their elemental composition in relation to stratigraphic, hydrogeological, and hydrogeochemical classifications thus providing additional value to the existing classification schemes. Analysis of geographical classes reveals that high concentrations of Be, Cs, Er, F, Ge, Lu, Mo, Sb, Si, Tm, U, Yb, and HCO3− are to expect in geologically older rocks, specifically from the Proterozoic. Hydrogeological classes reveal that high concentrations of La and Nb can be expected in waters from sources in the lowlands or in regions with unconsolidated rocks. The hydrochemical Piper classification has the largest amount of hidden information with 64% of significantly different elemental concentrations in comparison to the stratigraphic classification with 32%. Rare earth elements were ranked first for discriminating between classes of all three classification systems investigated in this study. In total, 16 elements proved to be suitable for discrimination, with Dy, Er, Gd, Lu, Sm, and Tm being identified most frequently.
An Approach to the Feature Selection in the Objects Detection Problem in Images

The objects detection problem in images has been considered. It is known that this problem can be solved using the SVM classifier development with application of the descriptors of the histograms of oriented gradients for creation of the training and test sets, but this technics deals with the significant time expenses for the formation of the histograms and the development of the SVM classifier. The application of the special tool known as the feature selection using the neighborhood component analysis algorithm for classification to determine the most informative features of objects has been investigated. It is shown that this approach allow to reduce the time expenses on solving the objects detection problem while maintaining acceptable values of the classification quality indicators. The experimental results on solving the objects detection problem have been presented.
MPEG column

The original blog post can be found at the Bitmovin Techblog and has been modified/updated here to focus on and highlight research aspects.
Core factors for software projects success

Objectives: To identify the most common success factors through reviewing a set of software project reports and case studies. Methods/Statistical Analysis: In order to fully understand reasons behind the project success, the reasons behind project failure and the definition of failure itself are discussed. Furthermore, case studies of successful and failed software projects are described. This paper also investigates techniques that have been developed to increase software project success rate and decrease probable failures. Findings: Six common factors reported in various studies and reports are selected to construct a success factors list. Factors that affect the project success or failure are identified for each project through content reviewing and analysis. Multiple reports and sources were reviewed for some projects to assure the accurate identification. We note that each of the identified success factors is common in at least four projects of this sample, and there is no project success for single factor. The frequencies of success factors for our data which contains 236 software projects are founded. The median number of projects for each factor is 103; with minimum of 72 and maximum of 131. For the investigated projects, the better project had significantly more success factors. We note that there is no successful project had just one success factor; all projects had multiple factors that led to their success. Application/Improvements: The constructed success factors list will be used in further research to develop prediction models that can be applied early through software development process in order to avoid project failure risks. Keywords: Project Performance, Software Project Failure, Software Project Success, Success Factors, Success Rate
Development of Information Systems for Scientific Research

Based on the conceptual model of the information system, which provides an abstract representation of entities and relationships (connections between entities), support is provided for the architecture of a universal information system related to a particular area of scientific knowledge. The conceptual model includes the basic entities: actors (persons, actors, organizations and other subjects of activity, including computer applications). An essential component of the conceptual model are documents, publications, dictionary articles, key terms, data and other objects of activity, including facts - a special kind of document. In turn, facts are understood as characteristics of entities described in the ontology of the information system, represented as a single value of data.
A Semantic Web SKOS Vocabulary Service for Open Knowledge Organization Systems

In this article, the Basel Register of Thesauri, Ontologies & Classications ( BARTOC.org ) is introduced to raise awareness for an integrated, full terminology registry for knowledge organization systems. Recently, researchers have shown an increased interest in such a single access point for controlled vocabularies. The paper outlines BARTOC’s technical implementation, system architecture, and services in the light of semantic technologies. Its central thesis is that if the KOS community agreed on BARTOC as one of their main terminology registries, all involved parties would benefit from linked open knowledge organization systems.
Categories of Big Data Analytics Algorithms

Nowadays, companies and researchers are facing a real challenge to process amounts of data generated daily from different sources. To remedy this major problem, a range of technical solutions BIG DATA [1] is offered today. This article provides a detailed study of the main Big Data methods namely supervised and unsupervised methods as well as an interpretation.
Research skills development in physics laboratories located in regional headquarters of the Universidad Industrial de Santander, Colombia

The Universidad Industrial de Santander developed in 2015 a novel methodology adopting Just-in-Time Teaching, active learning and mediated learning strategies for classical mechanics (Physics 1), electromagnetism (Physics 2) and, waves and particles (Physics 3) laboratories, with a focus on competencies for research formation, aimed at basic cycle engineering students. In 2017, the same methodology was implemented in three Universidad Industrial de Santander regional headquarters located in Malaga, Barbosa and Socorro cities. Initially, a first visit was made to recognize materials and equipment available in each regional headquarter, for the creation of virtual learning classrooms in Moodle platform. Then, in 2018 during a second visit, students and teachers who participated in the process were interviewed and the main difficulties and opportunities that they detected in the implementation were collected, thus allowing the action plan creation that contributes to the continuous improvement in the laboratory experiences.
Command and Order by Type Substitution: Another Way to Look at Word Order

Typed conception of surface-command and LF-command reveals a unique degree of freedom for specifying a verb in its combinatory capacity. It naturally brings in the question of word order in relation to its semantics. We exemplify from the Turkish verb and verbs of three other languages with different word order behavior. The differences are explainable in syntax if we assume that surface-command and LF-command are free to vary in a lexical correspondence, and that being the head of a construction also means determining its semantics. Turkish verbs are not heads of any construction; word-order variation has semantics arising from metrical grid and autonomous phonological events. Welsh verbs are heads of relativization; as such their logical forms must be different than their plain semantics. European Portuguese treats referentially dependent and independent arguments of the verb differently, exploiting word order for them but not to the extent of requiring a different category for the verb; therefore its word order is a complex interaction of referentiality and information structure. Tagalog leaves thematic structure and basic word order to voice rather than determine them in the verb root, which implies symmetry in the syntax of unvoiced verbs and asymmetry in others. These implications are not exceptions that require extra measures in grammar. They are made clear for the linguist and the child by a unique degree of freedom in CCG.
Improved Indifferentiability Security Bound for the Prefix-Free Merkle-Damgård Hash Function

The indifferentiability framework has been tailored to evaluate the security of cryptographic hash functions such that an iterative hash function must be indifferentiable from a random oracle in order to behave as a random oracle in cryptosystems. It was found that popular (strengthened) Merkle-Damgård transformation cannot satisfy the notion of indifferentiability from a random oracle due to a length-extension attack. Thus, a series of Merkle-Damgård variants have been proposed. This paper mainly revisits one of them, Prefix-Free Merkle-Damgård (PF-MDHF), which is to use a prefix-free message padding. Our main contribution is to provide a tighter security bound for prefix-free Merkle-Damgård with respect to the indifferentiability from a random oracle. More precisely, our bound is $$O( (\ell ^2q+\ell q^2)/{2^n})$$ , while in previous papers the bound is $$O(\ell ^2q^2/2^n)$$ , where $$\ell $$ is the maximum block length of queries, and q is the maximum number of queries.
Quantitative Research Methodology for Service-Oriented Architecture (SOA) Adoption in Organizations

In this chapter, the research methodology of the Service-Oriented Architecture (SOA) which is used in this research will be discussed. The questionnaire will be distributed among the SOA experts and the results will be explained at the end of this chapter.
A scale and shift paradigm for sparse interpolation in one and more dimensions

Sparse interpolation from at least 2 n uniformly spaced interpolation points t j can be traced back to the exponential fitting method [MATH HERE] of de Prony from the 18-th century [5]. Almost 200 years later this basic problem is also reformulated as a generalized eigenvalue problem [8]. We generalize (1) to sparse interpolation problems of the form [MATH HERE] and some multivariate formulations thereof, from corresponding regular interpolation point patterns. Concurrently we introduce the wavelet inspired paradigm of dilation and translation for the analysis (2) of these complex-valued structured univariate or multivariate samples. The new method is the result of a search on how to solve ambiguity problems in exponential analysis, such as aliasing which arises from too coarsely sampled data, or collisions which may occur when handling projected data.
Average Curve of n Digital Curves

Building on [23], we investigate the problem of defining and computing the average of digital curves. Given n digital curves that satisfy compatibility conditions, a set - called the gap - in which the average curve is looked for, is defined. The proposed definition rewrites the classical arithmetic mean for curves by (i) defining the distance between each point of the gap and its projection on each curve and (ii) computing the points that minimize the sum of squared deviations. We show that, algorithmically speaking, computing such projections comes down to computing a distance transform with visibility constraints. We propose a fast algorithm to compute a good approximation of these distance maps and finally show that the average curve can be obtained using classical watershed algorithm.
Speedup for Cryptography on CUDA Heterogeneous Architecture

Cryptography is an indispensable tool for protecting information in computer systems The Advanced Encryption Standard (AES) is one of the cryptography algorithms, which a well-known symmetric key algorithm, that utilizes the same secret key to encrypt and decrypt a message. It defeats that constraint of the more modest enter measure of the Data Encryption Standard (DES) toward using a greater and variable-length way. Moreover, It also determines those moderate preparing speed for triple DES (3DES), also uses more level assets of resources, therefore, it is preferred as the encryption and decryption standard by the U.S. government. AES is now being used worldwide for encrypting advanced information, including financial, telecommunications, and legislature data. In this paper, the AES scheme is implemented on Graphics Processing Unit (GPU) by parallelizing each step in the encryption algorithm of the AES using Compute Unified Device Architecture (CUDA). This allows enhancing the performance of the encryption algorithm execution to achieve a speedup factor of 61.36x on the multicore heterogeneous system.
Mining Approximate Primary Functional Dependency on Web Tables

We propose to discover approximate primary functional dependency (aPFD) for web tables, which focus on the determination relationship between primary attributes and non-primary attributes and are more helpful for entity column detection and topic discovery on web tables. Based on association rules and information theory, we propose metrics Conf and InfoGain to evaluate PFDs. By quantifying PFDs' strength and designing pruning strategies to eliminate false positives, our method could select minimal non-trivial approximate PFD effectively and are scalable to large tables. The comprehensive experimental results on real web datasets show that our method significantly outperforms previous work in both effectiveness and efficiency.
Active Learning for Conversational Interfaces in Healthcare Applications

In automated health services based on text and voice interfaces, there is a need to be able to understand what the user is talking about, and what is the attitude of the user towards a subject. Typical machine learning methods for text analysis require a lot of annotated data for the training. This is often a problem in addressing specific and possibly very personal health care needs. In this paper, we propose an active learning algorithm for the training of a text classifier for a conversational therapy application in the area of health behavior change. A new active learning algorithm, Query by Embedded Committee (QBEC), is proposed in the paper. The methods are particularly suitable for the text classification task in a dynamic environment and give a good performance with realistic test data.
Biometric Tools in Information Science. The Example of an Information Literacy Study – A Holiday Planning Experiment

Effective studies within interdisciplinary research fields, such as information literacy, require complex research methodologies. The purpose of the paper is to present the possibilities of biometric tools in the field of information science in triangulation with other methods and techniques. In addition to a literature review, the paper presents the project concerning information skills of young respondents in everyday life tasks. The study was conducted with the triangulation of a behavioral experiment, biometric measurements, and individual interviews. Results proved that young people are not as fluent in social media usage as it may seem. College students have limited communication and content creation skills. University students, however, present more advanced information skills. That might implicate the positive influence of university education and socialization on information literacy. During the project the biometric measures proved to be effective tools in exploring psychophysiological reactions while executing information tasks.
Measuring the radius of the earth. Integration between didactic transposition and information and communication technologies

The activities that foster a teaching mediation based on continuous reflection, involving didactic transposition and information and communication technologies, have generated a space for construction on the part of the student, which transcends outside the classroom and through the use of said technological tools is possible a meaningful and lasting learning. Said didactic transpositions, technological tools and integrating activities not only generate knowledge of value but also may involve the development of another type of competence and intelligences that are not the objective of the course, but that help in the integral formation of the student.
Open lesson in physics “the world of colours” – An alternative for teaching physics

This report presents the open lesson in Physics on the topic of “The World of Colours” which included theory, observation and experiments. The class was planned and realized as part of the full-time curriculum in the subject and with the active assistance of the students themselves. The planned and realized activities materialize the connection between theory and practice and together with it they spark students’ interest in experiments which is a step in the direction of developing skills in carrying out tests and analyzing results. The realized experiments are described in individual laboratory worksheets enclosed in the students’ notebooks. At the end of the class the students were given a task which had been developed in partnership with the History museum in the town of Chiprovtsi. The results of the open lesson are enabling students’ contribution, developing creative potential as well as extending theoretical and practical education in Physics.
Research on image screening model of ancient villages

Ancient villages are the carrier of a nation's profound history and culture. They are the integration of history, culture, architecture and sculpture, and have many value attributes. With the development of society, the protection of ancient villages is very important. The establishment of digital archives is an important means to protect ancient villages. Because of the large number and wide distribution of ancient villages, crowd sourcing can quickly and widely access the digital resources of ancient villages. Because of the uneven quality and repetition of the images collected from ancient villages, it is necessary to screen the images of ancient villages. Therefore, this paper proposes a screening model of ancient villages based on SIFT and convolution neural network. Firstly, this paper chooses edge gray change rate and NIQE quality score to evaluate the quality of ancient village image; secondly, extracts SIFT features of image for matching, calculates matching similarity to determine whether the matched image is myopic repetition. Finally, the image is filtered or preserved by using convolution neural network with the edge gray change rate, NIQE quality score and some image attributes as features. Experiments show that the ancient village image screening model designed in this paper has higher accuracy and recall rate than other methods, and has better screening effect.
Parallel Implementation of Nonparametric Clustering Algorithm HCA-MS on GPU Using CUDA

The present work explores nonparametric clustering algorithm HCA-MS. The combination of grid-based approach and Mean shift procedure allows the algorithm to discover arbitrary shaped clusters and to process large datasets, such as images. Parallel implementation of the HCA-MS algorithm on NVIDIA GPU using CUDA platform is presented. Provided experimental results on model data and multispectral images confirm the efficiency of the considered algorithm and its parallel implementation. The computation speedup on images was shown to be about 20x compared to 4 core CPU.