Reviewerly/exHarmony huggingface dataset:
RankBooster: Visual Analysis of Ranking Predictions

Ranking is a natural and ubiquitous way to facilitate decision-making in various applications. However, different rankings are often used for the same set of entities, with each ranking method placing emphasis on different factors. These factors can also be multi-dimensional in nature, compounding the problem. This complexity can make it challenging for an entity which is being ranked to understand what they can do to improve their rankings, and to analyze the effect of changes in various factors to their overall rank. In this paper, we present RankBooster, a novel visual analytics system to help users conveniently investigate ranking predictions. We take university rankings as an example and focus on helping universities to better explore their rankings, where they can compare themselves to their rivals in key areas as well as overall. Novel visualizations are proposed to enable efficient analysis of rankings, including a Scenario Analysis View to show a high-level summary of different ranking scenarios, a Relationship View to visualize the influence of each attribute on different indicators and a Rival View to compare the ranking of a university and those of its rivals. A case study demonstrates the usefulness and effectiveness of RankBooster in facilitating the visual analysis of ranking predictions and helping users better understand their current situation.
Contributions of the Department of Engineering Sciences of the Bulgarian Academy of Sciences in Automation, Robotics and Computers during the Past Century

Technical, at the time called "positive" sciences take their place in Bulgarian Academy of Sciences (BAS) relatively late: at the end of the 19-th century and at the beginning of the 20th century.Then for first time their representatives are elected for full BAS members.Only in 1959 a state act forms the Department of Technical Sciences (DTS) as a self-dependent structural division within the range of the academy.Regardless of this delay the department succeeds very fast to realize significant achievements in the realized in the country industrialization and in particular -in the high-tech production.In DTS-BAS appear the first for our country scientific teams in the field of automation and cybernetics.The first automated systems and also the first Bulgarian system with a specialized computer and periphery for a real-time control of an industrial transport have been started and implemented there.Noteworthy are the successes of technical sciences in the field of initiation, development and the rapid and broad development of the serial production and distribution of the personal computers as a new highly efficient trend in the information technologies.Following an analogical scenario the technical sciences in Bulgaria initiated the research in the field of robotics the result of which was the industrial production and the implementation of industrial robots.All this to a considerable extent helped the creation and the development of hightech production in Bulgaria during the past century
Utilising Uncertainty for Efficient Learning of Likely-Admissible Heuristics

Likely-admissible heuristics have previously been introduced as heuristics that are admissible with some probability. While such heuristics only produce likely-optimal plans, they have the advantage that it is more feasible to learn such heuristics from training data using machine learning algorithms. Naturally, it is ideal if this training data consists of optimal plans, but such data is often prohibitive to produce. To overcome this, previous work introduced a bootstrap procedure that generates training data using random task generation that incrementally learns on more complex tasks. However, 1) using random task generation is inefficient and; 2) the procedure generates non-optimal plans for training and this causes errors to compound as learning progresses, resulting in high suboptimality. In this paper we introduce a framework that utilises uncertainty to overcome the shortcomings of previous approaches. In particular, we show that we can use uncertainty to efficiently explore task-space when generating training tasks, and then learn likely-admissible heuristics that produce low suboptimality. We illustrate the advantages of our approach on the 15-puzzle, 24-puzzle, 24-pancake and 15-blocksworld domains using Bayesian neural networks to model uncertainty.
Other Image Color Features

Color Coherence Vector (CCV) is a more complicated technique than color histogram. Conceptually, the coherence of color can be described as the degree to which pixels of that color are part of large regions of a similar color [, , ]. These essential regions can be termed as coherent regions, and they are efficient in image characterization.
Applications of Image Color Features

Color is an important and the vital visual feature for image recognition. The use of image color is one of the most interesting issues in creation efficient content-based image retrieval. Color feature cannot be defined exactly as defining the likeness among color feature is difficult []. Therefore, two steps are needed in color-based image recovery, i.e., image color feature extraction and similarity computation among the extracted features. Some of the applications of image retrieval using color are described in this chapter.
Machine Transliteration Using SVM and HMM

Name transliteration plays an important role in developing automatic machine translation and cross lingual information retrieval system because these systems cannot directly translate out-of-vocabulary (OOV) words. In this article, a SVM-based name transliteration approach has been presented. This approach considers transliteration task as a multi-class problem of pattern classification, where the input is a source transliteration unit (chunks of source grapheme) and the classes are the distinct transliteration units (chunks of target grapheme) in the target language. A study on using hidden Markov model (HMM) for solving machine transliteration problem viewed as a sequence learning problem has also been presented in this paper. Bengali-to-English forward and backward name transliteration have been considered in this study. Our proposed methods have been compared with some existing transliteration method that uses a modified version of joint-source channel model. After the systems have been evaluated, the obtained results show that our proposed SVM-based model gives the best results among the others. Our experiments also reveal that the performance of HMM-based system is comparable with the SVM-based system.
Co-Creation with Ceramic Practitioner for Improving the Marketing and Enhancing the Customer Purchase Experiences

Background: As China's porcelain capital, Jingdezhen has had a glorious history of producing ceramics for thousands of years. Nevertheless, the private ceramics sector industry is going through a development bottleneck nowadays. This research aims to utilize service design tools to co-create values with local ceramic practitioners, to improve marketing of ceramics and enhance user`s purchase experiences. Methodology: 1) Devised Likert's 7-point scale by open-ended interview approach to clarify the existing problems to collect quantitative data. 2) Analyzed the collected data by one-way ANOVA to identify the different opinions of 87 interviewed subjects. 3) Employed co-creation method and service design tools to design the online-offline service system. Findings: 1) Through qualitative and quantitative methods identified the target researched group was the young group (age range from 20 to 30). Their insights used to co-create and design an online-offline marketing system in four steps why, what, who and how. 2) Utilizing service design tools to clarify the service contents, main stakeholders, marketing models, touchpoints and how they are connected and interacting. Finally, designing an application to facilitate online purchase to improve user experience.
Identifying and Quantifying Coordinated Manipulation of Upvotes and Downvotes in Naver News Comments

Today, many news sites let users write comments on news articles, rate others' comments by upvoting and downvoting, and order the comments by the rating. Top-rated comments are placed right below the news article and read widely, reaching a large audience and wielding great influence. As their importance grew, upvotes and downvotes are increasingly manipulated by coordinated efforts to hide existing top comments and push certain comments to the top. In this paper, we analyze comment sections of articles targeted by coordinated efforts and identify a trace of vote manipulation. Based on the findings, we propose a parameterized classifier that distinguishes comment threads affected by coordinated voting. The classifier only uses the number of upvotes and downvotes of comments. Therefore it is widely applicable to general vote-based curation systems where contents are sorted by the difference of upvotes and downvotes. Using the classifier and our choice of parameters, we have examined six years of the entire commenting history on a leading news portal in South Korea. Manual inspection in partisan online communities could only identify a few hundreds of targeted articles. With our classifier, we have identified more than ten thousand comment threads with a high likelihood of manipulation. We also observe a significant increase in coordinated manipulation in recent years.
Analyzing and Avoiding Pathological Behavior in Parallel Best-First Search

Recent work has experimentally shown that parallelization of Greedy Best-First Search (GBFS), a satisficing best-first search method, can behave very differently from sequential GBFS. In this paper, we propose a theoretical framework to compare parallel best-first search with sequential best-first search, including both suboptimal (GBFS, Weighted A*) and optimal (A*) best-first search methods. We analyze the extent to which the search behavior of existing parallel best-first search methods differ from sequential best-first search, and show that existing methods are vulnerable to pathological behavior, and that they can expand nodes which would not be expanded by sequential search under any tie-breaking policy. We also propose PUHF, a parallel best-first search which is guaranteed to expand a node only if there is some tie-breaking strategy for sequential search which expands the node.
Scientist and Citizen: Participation of the Leading Scholars of the Siberian Branch of the Russian Academy of Sciences in the Great Patriotic War

It is emphasized that their intellectual power, talent, and obsession with science, which was not ruined by the war, made them people of great destiny, who played an important role in the formation of the Siberian branch of the Russian Academy of Sciences during the post-war period, and the development of world-class fundamental scientific research.Sources for the research were materials from the electronic photo archive of the SB RAS, a historiographical and informational resource of publications about the Siberian branch of the RAS, books from the series "Science of Siberia in faces", anniversary publications, interviews, and memoirs.In methodological terms, the research is guided by the basic principles of historical science, historicism and scientific objectivity, as well as the provisions of the new value field of sociohumanitarian sciences "mnemosophy" -the science of public memory.Heroic feats of arms and valiant work of scientists in the rear are considered as an important, existential part of the scientific heritage, which is transmitted as a realized model of behavior under dramatic conditions of epochal historical significance.The heritage is formed by collective social experience and with the help of science acquires the highest quality -it becomes a public memory that should serve society in solving modern problems and building a decent future.
New encryption strategy passes early test: Ghost polarization harnesses ultrafast fluctuations that occur in a light wave

Telecommunications can never be too secure. That's why researchers continue to explore new encryption methods. One emerging method is called ghost polarization communication, or GPC. Researchers at the Technical University of Darmstadt, in Germany, recently demonstrated this approach in a proof-of-principle experiment.
On Length Independent Security Bounds for the PMAC Family

At FSE 2017, Gaži et al. demonstrated a pseudorandom function (PRF) distinguisher (Gaži et al., ToSC 2016(2)) on PMAC with Ω(lq2/2n) advantage, where q, l, and n, denote the number of queries, maximum permissible query length (in terms of n-bit blocks), and block size of the underlying block cipher. This, in combination with the upper bounds of Ο(lq2/2n) (Minematsu and Matsushima, FSE 2007) and Ο(qσ/2n) (Nandi and Mandal, J. Mathematical Cryptology 2008(2)), resolved the long-standing problem of exact security of PMAC. Gaži et al. also showed that the dependency on l can be dropped (i.e. O(q2/2n) bound up to l ≤ 2n/2) for a simplified version of PMAC, called sPMAC, by replacing the Gray code-based masking in PMAC with any 4-wise independent universal hash-based masking. Recently, Naito proposed another variant of PMAC with two powering-up maskings (Naito, ToSC 2019(2)) that achieves l-free bound of O(q2/2n), provided l ≤ 2n/2. In this work, we first identify a flaw in the analysis of Naito’s PMAC variant that invalidates the security proof. Apparently, the flaw is not easy to fix under the existing proof setup. We then formulate an equivalent problem which must be solved in order to achieve l-free security bounds for this variant. Second, we show that sPMAC achieves O(q2/2n) bound for a weaker notion of universality as compared to the earlier condition of 4-wise independence. Third, we analyze the security of PMAC1 (a popular variant of PMAC) with a simple modification in the linear combination of block cipher outputs. We show that this simple modification of PMAC1 has tight security O(q2/2n) provided l ≤ 2n/4. Even if l &lt; 2n/4, we still achieve same tight bound as long as total number of blocks in all queries is less than 22n/3.
Topological Insights in Sparse Neural Networks.

Sparse neural networks are effective approaches to reduce the resource requirements for the deployment of deep neural networks. Recently, the concept of adaptive sparse connectivity, has emerged to allow training sparse neural networks from scratch by optimizing the sparse structure during training. However, comparing different sparse topologies and determining how sparse topologies evolve during training, especially for the situation in which the sparse structure optimization is involved, remain as challenging open questions. This comparison becomes increasingly complex as the number of possible topological comparisons increases exponentially with the size of networks. In this work, we introduce an approach to understand and compare sparse neural network topologies from the perspective of graph theory. We first propose Neural Network Sparse Topology Distance (NNSTD) to measure the distance between different sparse neural networks. Further, we demonstrate that sparse neural networks can outperform over-parameterized models in terms of performance, even without any further structure optimization. To the end, we also show that adaptive sparse connectivity can always unveil a plenitude of sparse sub-networks with very different topologies which outperform the dense model, by quantifying and comparing their topological evolutionary processes. The latter findings complement the Lottery Ticket Hypothesis by showing that there is a much more efficient and robust way to find winning tickets. Altogether, our results start enabling a better theoretical understanding of sparse neural networks, and demonstrate the utility of using graph theory to analyze them.
Speeding up regular elliptic curve scalar multiplication without precomputation

This paper presents a series of Montgomery scalar multiplication algorithms on general short Weierstrass curves over fields with characteristic greater than 3, which need only 12 field multiplications per scalar bit using 8 $ \sim $ 9 field registers, thus outperform the binary NAF method on average. Over binary fields, the Montgomery scalar multiplication algorithm which was presented at the first CHES workshop by López and Dahab has been a favorite of ECC implementors, due to its nice properties such as high efficiency (outperforming the binary NAF), natural SPA-resistance, generality (coping with all ordinary curves) and implementation easiness. Over odd characteristic fields, the new scalar multiplication algorithms are the first ones featuring all these properties. Building-blocks of our contribution are new efficient differential addition-and-doubling formulae and a novel conception of on-the-fly adaptive coordinates which varies in accordance with not only the base point but also the bits of the given scalar.
The Digital Score: Musicianship, Creativity and Innovation

June 01 2019 The Digital Score: Musicianship, Creativity and Innovation The Digital Score: Musicianship, Creativity and Innovation. CraigVear. Ross Feller Ross Feller Gambier, Ohio, USA Search for other works by this author on: This Site Google Scholar Author and Article Information Ross Feller Gambier, Ohio, USA Online Issn: 1531-5169 Print Issn: 0148-9267 © 2020 Massachusetts Institute of Technology.2020Massachusetts Institute of Technology Computer Music Journal (2019) 43 (2-3): 166–168. https://doi.org/10.1162/comj_r_00526 Cite Icon Cite Permissions Share Icon Share Facebook Twitter LinkedIn MailTo Views Icon Views Article contents Figures & tables Video Audio Supplementary Data Peer Review Search Site Citation Ross Feller; The Digital Score: Musicianship, Creativity and Innovation. Computer Music Journal 2019; 43 (2-3): 166–168. doi: https://doi.org/10.1162/comj_r_00526 Download citation file: Ris (Zotero) Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search Search Dropdown Menu toolbar search search input Search input auto suggest filter your search All ContentAll JournalsComputer Music Journal Search Advanced Search This content is only available as a PDF. © 2020 Massachusetts Institute of Technology.2020Massachusetts Institute of Technology Article PDF first page preview Close Modal You do not currently have access to this content.
UNIVERSITY STUDENTS� NEEDS OF WRITING COURSE MATERIALS: A CASE OF INDONESIA

The aim of this study is to explore the target needs (i.e. necessities, lacks and wants) of the students to inform academic writing courses materials. A case study design was employed as this design to provide in-depth data information. To collect the data, questionnaire and interviews were used. Twenty-three undergraduate students of English department at a private university in Mataram West Nusa Tenggara who take academic writing course in the 2019-2020 academic year participated in the study. The result of the study showed that the students need to learn the types of writing texts, vocabulary and construct sentences into paragraph, have good skills in writing different genres since they are lack of grammar knowledge and vocabularies, and improvement on the aspect of teaching writing. This finding may promise implications for updating the current curriculum and materials as practiced for tertiary level English department students in an attempt to keep up with the latest changes in the methodologies of English language teaching. This study recommends that lecturers and universities should conduct a need analysis regularly and updated the curriculum with such insightful needs.
Implementation of AES-128 and Token-Base64 to Prevent SQL Injection Attacks via HTTP

SQL Injection is an attack that can be applied to all database servers that support SQL commands.This attack cannot only occur in client-side applications, but can also occur through the process of data communication between client-side applications with server-side to access web services using HTTP GET or POST parameters.There is an alternative solution to create a security system from SQL Injection attacks during data communication process, that is by applying the cryptographic algorithm to the name and value parameters during the data communication process in the GET or POST method.This study proposes the use of the Advance Encryption Standard 128 (AES-128) algorithm combined with Token-Base64.AES-128 algorithm is used in the encryption process and description of name and parameter values, then Token-Base64 for encoding and decoding processes with Token at the binary ciphertext result from the AES-128 encryption process.The testing method used is blackbox testing.SQL Injection Tools used are Web Cruiser which is assisted with the Pentest-Tools URL-Fuzzer web application to find out the URL address of the web service that can be used as a SQL Injection attack gap.The results of this study are that the combination of AES-128 and Token-Base64 algorithms can prevent SQL Injection attacks with a percentage of 100% of 83 attempts on data communication through HTTP GET or POST parameters.This states that the security level obtained is in the application layer of the OSI Model.The implementation of this security process makes the web service load time performance last longer by 31.26% with the file size of the web services being 95%, compared to not using the security process.
The Relationship between Financial Performance of Banking Sector and Economic Growth: A Research on EU Countries

In this study, the effects of financial performance of banking sector on economic growth have been analyzed. The study covers the data for the period 1996-2017 of European Union countries. In the study in regard to economic growth, GDP growth (annual %); financial performance, bank ROA, bank ROE, bank cost to income ratio (%) and stock market capitalization to GDP (%) have been used. The relationship between financial performance and economic growth have been analyzed through panel data method. The results of the analysis suggest that the bank performance of European Union countries have positive effect on economic growth. A positive and significant relationship has been determined that the ROA, bank cost to income ratio and stock market capitalization and economic growth. EU countries will be able to expedite economic growth by increasing the financial performance of banks.
Iterative Repair of Social Robot Programs from Implicit User Feedback via Bayesian Inference

Creating natural and autonomous interactions with social robots requires rich, multi-modal sensory input from the user.Writing interactive robot programs that make use of this input can demand tedious and error-prone tuning of program parameters, such as tuning thresholds on noisy sensory streams for detecting whether the robot's user is engaged or not.This tuning process dealing with low-level streams and parameters makes programming of social robots time-consuming and inaccessible for people who could benefit the most from unique use cases of social robots.To address this challenge, we propose the use of iterative program repair, where programmers create an initial program sketch in our new Social Robot Program Transition Sketch Language (SoRTSketch), a domain-specific language that supports expressing uncertainties related to thresholds in transition functions.The program is then iteratively repaired using Bayesian inference based on corrections of interaction traces that are either provided by the programmer or derived from implicit feedback given by the user during the interaction.Based on experiments with a human simulator and with 10 human users, we demonstrate the ease and effectiveness of this approach in improving social robot programming and program outputs that represent three common human-robot interaction patterns.We also show how our approach helps programs adapt to environment changes over time.