Reviewerly/exHarmony huggingface dataset:
Evolution of representations on reasoning (three cultural starts)

This article analyzes the three cultural starts of reasoning (ancient, modern, and current). This analysis is preceded by the history of studying reasoning in the Moscow Methodological Group, the representatives of which set the task of creating the theory of mendacity, but failed to complete. It turned out that reasoning cannot be reduced to activity not explained by semiotics. The concept of Aristotle's reasoning (the first start) is explored. He completes the tradition of norming the discursive types of activity (reasoning, proof, cognition) that comes from Parmenides and Socrates, attributes the ability to reason to an individual, and along with Plato generates a new reality in mentality. The second start of reasoning is attributed to the Modern Age, which outlined the task getting hold of nature and formed a New European creative personality. In this case, reasoning is endowed with the characteristics of constructiveness, projectivity, eventfulness, perceived as a method of creating new nature and thingness by a person, and included into the context of formation of the culture of modernity. The third start, as the emergence of a new type of reasoning, is currently developing. It is substantiated by the crisis of the culture of modernity, which caused the emergence of new types of discursive practices (interdisciplinary research, collective forms of mental activity using the Internet, development of methodology). These new types of practices require further research and norming, so are the new functions and peculiarities of reasoning.
Pisces: A New Zero-Knowledge Protocol for Blockchain Privacy

Applications of blockchain in banking, health care, transportation, asset and supply chain require to maintain the privacy of transactions, which can be achieved through anonymity using generic non-interactive zero-knowledge proof systems. In this work, we design and evaluate a simple zero-knowledge argument protocol for arithmetic circuit satisfiability to present verifiable encryption proof, which can offer good concrete efficiency and sublinear communication in the circuit size when combined with the regular signing process of the blockchain transactions. The proposed zero-knowledge protocol is an improved and optimized version of the lightweight sublinear protocol called Ligero (CCS 2017). The proof system requires no trusted setup, is plausibly post-quantum secure and uses only lightweight cryptography. We report on experiments for evaluating the performance of our proposed protocol. For instance, for verifying a SHA-256 preimage in zero-knowledge with 128 bits security, the communication cost can be roughly reduced to 1/4 and the proof size can be shortened to 3/4, compared with the original protocol. While the prover running time has a slight improvement, the verifier running time is 4\(\times \) shorter than Ligero. This brings great advantages in practice, as the transactions conducted on a block (created by a miner in general) must be verified by the network (many nodes in general) before the block can be added to the chain.
Artemis: An Automatic Test Suite Generator for Large Scale OLAP Database

We design an automatic test suite generation tool Artemis for functionality test of Online Analytical Processing Databases (OLAP DBs). This is the first work which accomplishes the work of DB test by integrating three artifacts, i.e., data generation, workload generation and oracle generation, but promises the scalability, effectiveness and efficiency. The key idea of our approach is to design a deterministic random data generation mechanism, based on which we can instantiate the parameterized queries and calculate the oracles simultaneously by resolving the constraint chains along query trees. Since we provide deterministic random functions for data generations corresponding to a predefined schema, repetitive test and data migration become a trivial job. Random workload generation and automatic oracle calculation instead of differential comparison make abundant and massive scale of test possible. We finally provide extensive experiments to show the performance of Artemis.
Active Explicable Planning for Human-Robot Teaming

Intelligent robots are redefining autonomous tasks but are still far from being fully capable of assisting humans in day to day tasks. An important requirement of collaboration is to have a clear understanding of each other's expectations and capabilities. Lack of which may lead to serious issues such as loose coordination between teammates, ineffective team performance, and ultimately mission failures. Hence, it is important for the robot to behave explicably to make themselves understandable to the human. One of the challenges here is that the expectations of the human are often hidden and dynamically changing as the human interacts with the robot. Existing approaches in plan explicability often assume the human's expectations are known and static. In this paper, we propose the idea of active explicable planning to address this issue. We apply a Bayesian approach to model and predict dynamic human beliefs to be more anticipatory, and hence can generate more efficient plans without impacting explicability. We hypothesize that active explicable plans can be more efficient and more explicable at the same time, compared to the plans generated by existing methods. From the preliminary results of Mturk study, we find that our approach effectively captures the dynamic belief of the human which can be used to generate efficient and explicable behavior that benefits from dynamically changing expectations.
Research on the Application of Data Mining Technology in Smart Transportation

The level of automobileization in China is increasing year by year, and the pressure of urban traffic is increasing day by day, which brings a lot of inconvenience to people’s daily travel. Intelligent transportation based on big data can improve the timeliness and accuracy of traffic information acquisition, its diversified construction the traffic data network provides preconditions for the construction of intelligent transportation, and the application of big data technology has become the key to improving the urban traffic environment. This article explains the relationship between big data technology and intelligent transportation, analyzes the advantages of big data technology, shows the changes that big data brings to transportation, and conducts research on the application of big data in the field of intelligent transportation.
Fun with Formal Methods for Better Education

Is there a need to popularize Formal Methods in Software Engineering? Maybe industrial demand in Formal Methods is the best way to explain their utility and importance? – We try to argue educational and emotional role of popularization for a better comprehension and a positive attitude to Formal Methods and discuss several Math Olympiad problems that can be solved using Formal Methods (while, unfortunately, Mathematical education suffers of lack of Theoretical Computer science curricular) .
Ontology-based Document Recommendation System using Topic Modeling

For now, most search engines have limitations on finding the most suitable results from documents at a semantic level. This paper aims to provide users with more accurate document search results not only at a syntactic level but also on a semantic level. For example, when a user searches “coffee” on Amazon, does the user only want coffee? Coffee is a kind of functional drink, the user may also want to know other functional drinks such as tea or Redbull. Coffee helps people stay awake, the user may just want something to help him/her stay awake or focused. In this project, document data from a question-and-answer website called Stack Exchange is analyzed and compared by using the Latent Dirichlet Allocation (LDA) and Latent Semantic Analysis (LSA) topic modeling algorithm. After completing topic modeling, using an ontology built with Protégé, data is further processed at a semantic level. We utilize the ontology rules and instances to optimize the search results.
Minimizing Computation Time for Robot Path Planning Using Improvised Cuckoo Search Algorithm

Path planning for robots is one of the primary parameters to justify the implementation of robots in any particular application. Path planning hugely depends on the computation time required to derive the optimal path from the start point to the goal point. Most of the approach follows a linear approach to derive an optimal path for robots while traversing from source to goal. This chapter proposes a novel method of using a non-linear mechanism within the cuckoo search algorithm to approach the goal. Using the core concept of the Cuckoo Search algorithm for finding path, this chapter proposes an approach of implementing an alternative mechanism of selecting the next best solution in the given workspace. After getting stuck with the obstacles, the proposed approach opts an alternate way to get out of that obstacle, i.e. one-time considering the minimum distance and another time maximum distance from the obstacle. The proposed non-linear approach converges rapidly towards goal and similarly comes out of the obstacle zone. The proposed approach is implemented and compared with the original CS algorithm which shows a noticeable improvement in deriving path from source to goal and a considerable reduction in computation time required to derive the optimal path for robots traversal in the workspace (Sharma and Doriya, 2019 4th international conference on computing, communications and security (ICCCS), pp 1–4. IEEE (2019) []).
Extent of Faculty Adeptness and Viability of Gamified Learning in National University

Education has been a commodity for human society. As the Philippines value education almost more than anything, a multiple number of ways are being considered and utilized for the enhancement of the education system. National University as a contributing institution for educating Filipinos continue to explore innovative practices to provide its students an education that works. In this pursuit, a supplementary mode of learning, a branch of e-learning or computer aided instruction, Edugames is being considered. The possibility of using gamification in education within National University teaching methods would be keeping up to date with the global uptake on Edugames. Using an observational and imperative research, the study explores four key factors. Faculty adeptness, student willingness, technological operability and administration support. With the current resources, experience and practices, does National University's faculty have the inclination of using gamified learning and does NU have the means to facilitate such teaching methods? An attempt to elaborate a response is presented.
Semantic generation mechanism of news images based on Concept-Net

Online news is an important means of disseminating information, but some online news texts do not match the content described in the original news pictures, and even cause ambiguity among readers. This phenomenon has seriously affected the authority of news and the credibility of news media. In response to this problem, this paper proposes a rich news image description mechanism based on the Concept-Net knowledge graph. The model we provide consists of two parts, namely, extracting the image content and rendering with natural language to generate an accurate description of the news image.
Detection of Falsary Happening on Social Media Using Image Processing: Feature Extraction and Matching

In last decade and half, especially generation Z (Gen Z) has witnessed a drastic change in their communication pattern due to paradigm shift in digital media. Social media is the largest medium to connect any part of the world via internet is considered to be the trend changer. Increasing use of mobile internet and easy availability of mobile compatible softwares have changed the way of expression on social media in both apt and inept manner. Forged images known as memes are, nowadays, trending on social media like Facebook, Instagram, Twitter, Whatsapp and what not. These memes on social media are used to appreciate or to troll on particular cause to someone or group of people. The plethora of memes usage leads to image processing where feature extraction and feature matching can be done. Matching of features that are invariant to transformation includes geometric invariance and photometric invariance. This paper presents the comparative analysis of images (memes) matching algorithms of feature, which will definitely helpful for future researchers to identify the best matching technique to be fit in desired area. Authors have also included the implemented results of various traditional matching techniques invariant to translation, rotation, scaling, brightness and exposure.
Development of professional metacompetence of teachers in the process of mastering cloud technologies

Literature review of works by Russian and foreign scientists has been performed aiming at reveling essential properties of professional competence of teachers as the competence of the highest level. Course training program has been described, which is comprised of three modules covering urgent issues and technologies of media education, monitoring of quality assessment and efficiency of mastering program, various examples of electronic education products, publications, electronic resources and thesaurus of key notions. The results of the performed studies have been the disclosing of the notion essence of professional metacompetence of teacher, which is expressed in readiness to solve professional tasks under the conditions of mediatization of education system. On the basis of the experimental results, the efficiency of software and methodological support of development of professional metacompetence of teachers has been proved and reflected in diagrams. Therefore, it has been concluded that the development of professional metacompetence of teachers allows to apply interactive forms of education in various online learning environments and provides professional training of teachers of higher quality aiming at independent solution to education problems in the changing educational environment. Recommendations have been given for application of cloud technologies for activation of teacher’s activity in monitoring and estimation at various levels of education.
Quantum Key Distribution

This chapter is devoted to the fundamentals of quantum key distribution (QKD). The chapter starts with a description of key differences between conventional cryptography and QKD. In the section on QKD basics, after a historical overview, we review different QKD types. We then describe two fundamental theorems on which QKD relies, namely the no-cloning theorem and the theorem of the inability to unambiguously distinguish nonorthogonal quantum states. In the section on discrete variable QKD systems we describe BB84, B92, Ekert (E91), Einstein–Podolski–Rosen, and time-phase encoding protocols. In the section on QKD security, the secret-key rate (SKR) is represented as the product of raw key rate and fractional rate. Moreover, the generic expression for the fractional rate is provided, followed by a description of different eavesdropping strategies, including individual (independent or incoherent) attacks, collective attacks, coherent attacks, and quantum hacking/side-channel attacks. For individual and coherent attacks, the corresponding secrete fraction expressions are provided. After that, the decoy-state protocol is described together with corresponding SKR calculation. Next, the key concepts for measurement device-independent (MDI)-QKD protocols are introduced, including polarization-based and time-phase encoding-based MDI-QKD protocols as well as secrecy fraction calculation. Twin-field QKD protocols as further described, whose performance is evaluated against decoy-state and MDI-QKD protocols. The focus is then moved to the information reconciliation and privacy amplification steps. To facilitate the description of continuous variable (CV)-QKD protocols, the fundamentals of quantum optics and Gaussian information theory are introduced first. The topics include quadrature operators, Gaussian and squeezed states, Gaussian transformation, generation of quantum states, thermal decomposition of Gaussian states, two-mode Gaussian states, and measurements on Gaussian states. In the section on CV-QKD protocols, homodyne and heterodyne detection schemes are described first, following a brief description of squeezed states-based protocols. Given that the coherent states are much easier to generate and manipulate, the coherent states-based protocols are described in detail. For the lossy transmission channel, the corresponding covariance matrices are derived for both homodyne and coherent detection schemes, followed by SKR derivation for prepare-and-measure Gaussian modulation (GM)-based CV-QKD. Illustrative SKR results are provided for GM-based CV-QKD schemes. Next, relevant concluding remarks are provided, followed by a set of problems.
Blockchain Integration Into Supply Chain Operations

Following the globalization initiated by containerization of logistics, supply chains might be due another revolution by the integration of the disruptive blockchain technology that addresses the current issues with the management of complex global supply chains. Blockchains are distributed digital ledgers that require no central authority to operate while offering a tamper-proof and transparent history of each transaction from the very beginning. Distributed nature of these ledgers ensure that every participant of the supply chain has access to trusted data. The industry has already begun experimenting with blockchain integration into their operations. For the majority of the organizations, however, these experiments stay in proof-of-concept stages or small pilot studies. In this chapter, the authors discuss the supply chain characteristics that make blockchain integration favorable, lay the groundwork for how blockchain can be used for supply chain operations and how it has been used so far.
Selecting Algorithms Without Meta-features

The algorithm selection has been successfully used on a variety of decision problems. When the problem definition is structured and several algorithms for the same problem are available, then meta-features, that in turn permit a highly accurate algorithm selection on a case-by-case basis, can be easily and at a relatively low cost extracted. Real world problems such as computer vision could benefit from algorithm selection as well, however the input is not structured and datasets are very large both in samples size and sample numbers. Therefore, meta-features are either impossible or too costly to be extracted. Considering such limitations, in this paper we experimentally evaluate the cost and the complexity of algorithm selection on two popular computer vision datasets VOC2012 and MSCOCO and by using a variety task oriented features. We evaluate both dataset on algorithm selection accuracy over five algorithms and by using a various levels of dataset manipulation such as data augmentation, algorithm selector fine tuning and ensemble selection. We determine that the main reason for low accuracy from existing features is due to insufficient evaluation of existing algorithms. Our experiments show that even without meta features, it is thus possible to have meaningful algorithm selection accuracy, and thus obtain processing accuracy increase. The main result shows that using ensemble method, trained on MSCOCO dataset, we can successfully increase the processing result by at least 3% of processing accuracy.
CALLA 기반 한국어 발표 수업 사례 연구: 유학생들의 전공 발표를 중심으로

This study is undertaken to design a Korean presentation class for academic purposes based on CALLA (Cognitive Academic Language Learning Approach) and to find its effectiveness. In this study, 10 foreign graduate students participated in the class which teaches presentation strategies for 15 weeks. According to CALLA, some useful presentation strategies were introduced and practiced repeatedly, and the students’ presentations in Korean considering their major were completed gradually. As a result, positive effects from the presentation class on the perspective of language, non-language and data organization could be acquired through repetitive feedback and practice. Thus, the students could use the proper discourse for topics ranging from the introduction and development of the presentation to concluding presentation. The learners have shown a lot of improvements in presentation ability through the CALLA course regardless of language proficiency but the class design used in the study should be conducted in other presentation classes for academic purposes.
Formation of readiness for professional mobility in senior high school students

The prerequisites for the study are modern career concepts and the concept of preparing a person for the successful construction of a career path. The modern sphere of economic relations and the labor market are very changeable and dynamic. The structure and content of professions are changing quickly, which requires constant training and readiness from the individual to change professional roles. Therefore, the formation of readiness for professional mobility is an important research issue. However, the generally accepted position is that the formation of readiness for professional mobility among students should begin at a university or college. The purpose of the study is to test the assumption that the readiness for professional mobility can be formed in senior high school students by combining traditional and game forms of education. The experiment described used a three-week course based on traditional and active teaching methods and a complex multistep business game. The research methods included: the adapted test of “Career Anchors” by Edgar H. Schein, “Methodology for Diagnostics of Reflexivity” by A.V. Karpov and V.V. Ponomareva, the test “Study of Volitional Self-regulation” by A.V. Zverkov and E.V. Eydman, “Temperament Structure Questionnaire” by V.M. Rusalov, and the test “Communicative and Organizational Skills” by V.V. Siniavskii and V.A. Fedorishin. The results of the study showed a statistically significant positive change in the controlled parameters. In general, the conclusion about the promising nature of this direction of training can be considered partially confirmed. For a more confident conclusion, studies on larger samples are required.
Application and Development of Computer Software Development Technology in the New Period

At present, China’s economy has entered a state of rapid advancement, and the level of science and technology has also been effectively improved. At the same time, computer technology has also entered a new field of development and has been widely used in society to provide people with life, work and production. With the rapid development of network technology, the development level of computer software is also increasing, and it stands in the society as an independent industrial structure. Computer software has certain characteristics, the most obvious manifestation is that the software is updated faster and involves the range is wider. Therefore, in-depth research and development of computer software development technology in the development of the new era is of great significance to the healthy development of society. This article analyzes the application and development trend of computer software open technology in the new era, to lay a good foundation for the improvement of computer software development technology.