Reviewerly/exHarmony huggingface dataset:
An optimal algorithm analysis of signal transitive random signal without noise feedback

Abstract This article used the way of stochastic processes statistics to raise and study a kind of optimization of signal transitive stochasic system without noise feedback, and it did the optimum operation to permit coding function of the signal and solved the measuring question of the optimum coding and decoding of the signal. It could contributs an ideal way of mathematical.
A Study on Application and Utilization method of Smart Logistics

Purpose : The introduction of IT technology in the logistics sector is expected to expand in order to expand smart logistics as advanced intelligent services become more diversified with the development of IT technology. However, there is still a lack of research on the introduction or introduction of technologies considering the traditional logistics infrastructure, and there is a dearth of research on smart logistics among the various factors of the fourth industrial revolution. Therefore, this study looks at smart logistics and how to use it based on real-world technology. Research design, data, methodology : In this study, smart logistics aims to establish a comprehensive logistics service that provides analysis results to the international logistics service field, parcel delivery, and third-party logistics based on big data collected in relation to transport products.With the aim of efficient construction of new smart logistics, it is possible to reduce logistics costs and enable flexible, adaptable and proactive responses to rapidly changing and complex logistics environments. Results : The logistics industry will change in the direction of achieving intelligent customercentered services, advanced technology, eco-friendliness, security, and high efficiency, and as a whole society, the 4th industrial revolutionChanges in the work environment and opportunities are expected, and in the technology environment, changes and expansions in AI, big data, IoT, cloud, etc. Conclusions : In the logistics industry, Korea has a high level of infrastructure and industrial base in the IT field, but its competitiveness is low compared to advanced countries, and more efforts to strengthen competitiveness are needed based on the development of logistics technology and intelligent logistics information management.
Water billing management system

Water billing system is an online project which allows the water billing management to post the bill of each and every customer and any other transactions related to water billing such as customer information, service record module, statement of accounts and all details. The online system can be accessed by the administrators and other staff of the association and as well as the customers of the water billing. The administrator can access all the modules of the project where as the customers can only view their payment history and billing records. Water bill goes to the customer house. This paper talk about the major findings of the challenges of the manually operated billing and payment system and suggests a possible solution that will help solve the challenges that are currently faced. The solution to above difficulties is to install prepaid water billing system which consists of smart meters. These meters shall be present in every house and each and every customer will be in position to pay for what he/she can afford and payment shall be at any time of convenience using any payment mode offline specific objectives. Analyze the existing system. To give fast and accurate access of customer. To avoid work load.
Rethinking the Role of External Representation in Problem solving

Newer approaches like situated action and distributed cognition, question the information-processing approach to the understanding of human problem solving and knowledge. They emphasize external representation, both in the physical and social world, over internal representation in various kinds of human activities. Studies by J. Zhang and his colleagues showed the positive effect of externalizing rules in solving traditional cognitive problems. Some pairs solved the problem through representing the problem solving in tree diagrams, while others used production rules, or actual manipulation of drawn balls. Verbal protocols between pairs of participants were coded into six categories for the analysis of the quality of their problem solving. Three of the categories are good indicators of problem solving, i.e. Meta-rule, Both Possible Outcomes Evaluated, and Path Ruled Out, that help the participants move toward the solution.
Pengembangan BAM Matakuliah Analisis Kebijakan Pendidikan Berbasis Online

Responding to the development of the Covid-19 virus, the Ministry of Education and Culture, Director General of Higher Education, and State University of Surabaya published a letter related to online learning at home. In order for online learning activities to run smoothly, it is necessary to develop teaching books that are in accordance with the needs of online learning, one of which is in the form of Student Teaching Books (BAM). Based on the results of previous research, BAM has a significant role in learning activities, especially online learning. BAM development is carried out in the Course of Education Policy Analysis using ADD (Analysis, Design, and Development) method. Online learning is implemented using the Google Classroom platform. Based on the results of the analysis carried out, the development of this student teaching book was developed based on 4 aspects, namely aspects of content feasibility, feasibility of presentation of materials, feasibility of language, and feasibility of graphation. The development of this teaching book is validated by 2 experts, namely content experts and linguists. Based on the validation results, the textbook developed obtained a score of 86.5 with excellent assessment criteria, so it is feasible to be a teaching material for students in the Education Policy Analysis Course.
강남역 살인사건 이후 젠더/여성/페미니즘 관련 번역서에 나타난 이데올로기의 변화 : 표지 이미지와 책제목을 기반으로

This study aims to show ideology in the front covers of translated feminist books that have been published since the so-called “Gangnam murder case”. For this purpose, the cover images and titles of 151 Korean translations are compared in detail with those of the original books and of 70 Korean translations published before the murder case, respectively. Findings show that the visual/verbal elements of the book covers are transcreated in a way that accentuates feminism, expands the female readership, or strengthens the emotional bond between author and reader. Specifically, the images and titles emphasise lexis evoking positive feelings, the first-person pronouns identifying the reader as a feminist, images with higher levels of sensory modality (but with lower levels of naturalistic modality), friendly illustrations (rather than actual images), rich colours with higher emotional temperature, typefaces conveying a good mood, and/or social actors encoded as friendly or active women. Many of these multimodal features differ from those of the book covers published before the post-2016 feminist movement.
A Formal Proof of Modal Completeness for Provability Logic.

This work presents a formalized proof of modal completeness for Godel-Lob provability logic (GL) in the HOL Light theorem prover. We describe the code we developed, and discuss some details of our implementation, focusing on our choices in structuring proofs which make essential use of the tools of HOL Light and which differ in part from the standard strategies found in main textbooks covering the topic in an informal setting. Moreover, we propose a reflection on our own experience in using this specific theorem prover for this formalization task, with an analysis of pros and cons of reasoning within and about the formal system for GL we implemented in our code.
Probabilistic Constraints for Optimization-based Motion Planning

We present a novel method to formulate constraints over probability distributions within optimization-based motion planning, enabling robots to plan for uncertainty in dynamic environments. Typical approaches for motion planning in dynamic environments involve predictions of the environment (e.g., moving obstacles), so that the robot can plan around anticipated environmental changes. Uncertainty in predictions is a challenge that pervades these approaches. As such, properly modeling environmental uncertainty is crucial to obtain valid motion plans. We propose a general method of propagating uncertainty in environmental predictions to a probabilistic constraint in optimization-based motion planning. We demonstrate the efficacy of this approach for uncertainty in predicted human motions in the context of simultaneous manipulation in a shared workspace with a 7-DoF robot arm.
Synthesis of Safe Pointer-Manipulating Programs (Invited Talk)

Low-level pointer-manipulating code is ubiquitous in operating systems, networking stacks, and browsers, which form the backbone of our digital infrastructure. Unfortunately, this code is susceptible to many kinds of bugs, which lead to crashes and security vulnerabilities. A promising approach to eliminating bugs and reducing programmer effort at the same time is to use program synthesis technology to generate provably correct low-level code automatically from high-level specifications.In this talk I will present a program synthesizer SuSLik, which accepts as input a specification written in separation logic, and produces as output a provably correct C program. SuSLik is the first synthesizer capable of generating a wide range of operations on linked data structures (such as singly- and doubly-linked lists, binary trees, and rose trees) without additional hints from the user. It is also the first synthesizer to automatically discover recursive auxiliary functions required for nested data structure traversal. To make this possible, SuSLik relies on a novel proof system - synthetic separation logic - to derive correct-by-construction programs directly from their specifications. Program proofs generated by SuSLik can be automatically translated into three foundational verification frameworks embedded in Coq: Hoare Type Theory (HTT), Iris, and Verified Software Toolchain (VST).
Power, Hate Speech, Machine Learning, and Intersectional Approach

The advent of social media has increased digital content and, with it, hate speech. Advancements in machine learning algorithms help detect online hate speech at scale; nevertheless, these systems are far from perfect. Human-annotated hate speech data, used to train automated hate speech detection systems, is susceptible to racial/ethnic, gender, and other bias. To address societal and historical biases in automated hate speech detection, scholars and practitioners need to focus on the power dynamics: who decides what comprises hate speech. Examining inter- and intra-group dynamics can facilitate understanding of this causal mechanism. This intersectional approach deepens knowledge of the limitations of automated hate speech detection systems and bridges social science and machine learning literature on biases and fairness.
The Gap on Gap: Tackling the Problem of Differing Data Distributions in Bias-Measuring Datasets

Diagnostic datasets that can detect biased models are an important prerequisite for bias reduction within natural language processing.However, undesired patterns in the collected data can make such tests incorrect.For example, if the feminine subset of a gender-bias-measuring coreference resolution dataset contains sentences with a longer average distance between the pronoun and the correct candidate, an RNN-based model may perform worse on this subset due to long-term dependencies.In this work, we introduce a theoretically grounded method for weighting test samples to cope with such patterns in the test data.We demonstrate the method on the GAP dataset for coreference resolution.We annotate GAP with spans of all personal names and show that examples in the female subset contain more personal names and a longer distance between pronouns and their referents, potentially affecting the bias score in an undesired way.Using our weighting method, we find the set of weights on the test instances that should be used for coping with these correlations, and we re-evaluate 16 recently released coreference models.
Efficient Training of Visual Transformers with Small-Size Datasets

Visual Transformers (VTs) are emerging as an architectural paradigm alternative to Convolutional networks (CNNs). Differently from CNNs, VTs can capture global relations between image elements and they potentially have a larger representation capacity. However, the lack of the typical convolutional inductive bias makes these models more data-hungry than common CNNs. In fact, some local properties of the visual domain which are embedded in the CNN architectural design, in VTs should be learned from samples. In this paper, we empirically analyse different VTs, comparing their robustness in a small training-set regime, and we show that, despite having a comparable accuracy when trained on ImageNet, their performance on smaller datasets can be largely different. Moreover, we propose a self-supervised task which can extract additional information from images with only a negligible computational overhead. This task encourages the VTs to learn spatial relations within an image and makes the VT training much more robust when training data are scarce. Our task is used jointly with the standard (supervised) training and it does not depend on specific architectural choices, thus it can be easily plugged in the existing VTs. Using an extensive evaluation with different VTs and datasets, we show that our method can improve (sometimes dramatically) the final accuracy of the VTs. The code will be available upon acceptance.
Students’ Perceptions on the Personality Competence of Native and Non-Native Lecturer in IAIN Palangka Raya

The purpose of this study was to determine students 'perceptions of the personal competence of native and non-native lecturers at IAIN Palangka Raya, as well as students' perceptions in terms of improving English language abilities after studying with native non-native lecturers and their hopes for their teachers.50 students as samples to answered questionnaire and 5 students as the main speakers in the interview to explain more deeply about the personal competence of native speakers and not native speakers. To collect data, researchers used questionnaires and interviews. The main research findings have shown that: (1) most students have positive perceptions or with the presence of native and non-native lecturers who have provided good benefits in learning English. Student have benefited greatly from learning with native speakers (77%) or non-native speakers (81%). (2) Students agree that their English language skills develop after being taught by native and non-native lecturers (72%) with agreed upon categories. (3) While the students' expectation of native-speaking lecturers is also able to understand Indonesian language and culture, while Non-native speakers are expected to be able to further improve their achievements in the field of English (84%). Moreover, the students also found some problems during the learning process with both native and non-native teachers.
File Fragment Type Classification by Bag-Of-Visual-Words

File fragment’s type classification in the absence of header and file system information, is a major building block in various solutions devoted to file carving, memory analysis and network forensics. Over the past decades, a substantial amount of effort has been put into developing methods to classify file fragments. Meanwhile, there has been little innovation on the basics of approaches given into file and fragment type classification. In this research, by mapping each fragment as an 8-bit grayscale image, a method of texture analysis has been used in place of a classifier. Essentially, we show how to construct a vocabulary of visual words with the Bag-of-Visual-Words method. Using the n-gram technique, the feature vector is comprised of visual words occurrence. On the classification of 31 file types over 31000 fragments, our approach reached a maximum overall accuracy of 74.9% in classifying 512 byte fragments and 87.3% in classifying 4096 byte fragments.
The Dilemma of Copyright Law and Artificial Intelligence in India

The rising potential and versatility of the technology of Artificial Intelligence, they are no strangers to their capacity of creating autonomous works. This raises a concern regarding their implications on the Intellectual Property Right of copyright available for their work. This article explores the possibility of assigning of ‘authorship’ as under the understanding of Copyright laws. Along with the factum of originality, as required by the copyright laws, in such creations. The creative works of music and Arts have been stressed to deliberate upon the same. Drawing inspiration from the jurisdictions across the globe that have proffered a stance regarding the incorporation of the technology into their legal regimes, this paper endeavours to contemplate the possibility of assigning ownership to the AI technology in the Indian legal framework. Nonetheless furthering the debate regarding the essence of copyright laws and the suitability and the possibility of making copyrights available to AI technology. It should be noted here that Artificial Intelligence has been used as a broad category and the author intends to touch upon the specific forms of this technology, being algorithms, blockchains and/or others. The author discusses the traditional Indian copyright laws and the possibility of incorporation, not forgetting to send out a word of caution in the event altered interpretations seem desirable.
Deep Understanding of Runtime Configuration Intention

The runtime environment and workload of software are constantly changing, requiring users to make appropriate adjustments to accommodate these changes. The runtime configuration, however, as the interface for users to manipulate software behavior often requires domain-specific knowledge to understand. This usually results in users spending a considerable amount of time wading through document and user manuals trying to understand the runtime configuration. In this paper, we study the possibility of understanding the intention of runtime configuration options through their documents, even sometimes it is difficult for users to understand. Based on these studies, we classify the runtime configuration option’s intention into six categories. Accordingly, we design runtime Configuration Intention Classifier (CIC), a supervised approach based on CNN to classify the runtime configuration option’s intention according to its document. CIC integrates the features of runtime configuration names and descriptions according to different levels of granularity and predicts the intention of runtime configuration options accordingly. Extensive experiments show that our approach can achieve an accuracy of 85.6% and outperform nine comparative approaches by up to 16.6% over the dataset we customized.
The Study of Cheating among Academic Fields for Medan University Students

We are delighted to introduce the Virtual Conference on Social Science In Law, Political Issue And Economic Development 2020 with theme “Realizing Society 5.0 for a Better Life”. The technical program has brought researchers and practitioners around the world to a good forum for discussing, leveraging and developing all scientific and technological aspects that are relevant to economic business, education and humanities. Moreover, it is a great pleasure to have the keynote and invited speakers of VCOSPILED 2020, Prof. Dr. Pujiono, Assoc. Prof. Ilham Sentosa, Ph.D and Dr. Siska Diana Sari, S.H., M.H who will share their knowledge and best innovative research findings in economic business, education and humanities. This conference is held by Kresna Acitya Media Nusantara in collaboration with Universitas Muhamadiyah Sidoarjo and Relawan Jurnal Indonesia. Kresna Acitya Media Nusantara is a company that is dedicated to maximize the impact of scientific publication, and Relawan Jurnal Indonesia, is a non-profit organization in the field of scientific publication. The conference will be held virtually using Zoom webinar on October 15, 2020. This conference has successfully acquired 180 participants and 55 presenters from 4 countries, Indonesia, Malaysia, Taiwan and Uzbekistan. Thus, all selected papers will be
Sosyal Medyanın Tüketicilerin Satınalma Davranışları Üzerinde Etkisi: Türkiye ve İran’daki Üniversite Öğrencileri Üzerine Bir Uygulama

Purpose – The aim of the study is to reveal the differences and similarities between the citizens of two countries with different cultural and demographic structures, although they are located in similar geographies, and among the purchasing behaviors of university students, who are undoubtedly the highest social media users. Although different technological infrastructures are used, the main purpose of the study is to reveal how social media affects purchasing behavior. Design/methodology/approach – In the research, a quantitative research method was applied. Depending on the purpose of this research in the types of quantitative research exploratory through correlational research types it is thought to be appropriate to the correlational research and in making the purchase of customers in the two countries accordingly views and through the use of questionnaires in order to benefit from the experience 400 in Iran, 400 in Turkey In total, face-to-face interviews were conducted with 800 people. Findings – According to the findings of the study, it was examined whether there is a differentiation in the pre-purchase consumer behaviors of Turkish and Iranian consumers participating in the research on social media and a significant difference was determined at the 0.05 significance level. Although Iranian consumers spend more time on the internet, their time on social media is less than Turkish consumers. In both countries, the rate of sharing on social media after purchasing the product is around 50% and there is a similarity in the consumers of the two countries. Discussion – As seen in the literature, many studies have been conducted in the last decade to show that social media affects consumer behavior. This study specifically different cultural and technological infrastructure, although geographical proximity to Turkey and both countries such as Iran, reveals similarities and differences in the behavior of consumers in specific age ranges and social media response. In this process, although different social media tools are popular in their countries, it is seen that the effect of social media phenomenon is largely similar. These and similar multicultural comparative studies are important in understanding the impact of social media on marketing processes.
대학생의 위험 음주 행동과 건강증진요인, 안전의식수준 간의 관련성

Objectives: This study analyzed the association with risk drinking behaviors, health promotion factors, and safety awareness levels among college students. Methods: The data was collected from 2,713 college students by the health and safety survey. It examined the association between health-related factors and risk drinking behavior, such as high-risk drinking, monthly binge drinking, and alcohol use disorder, by multiple logistic regression. Results: The factors affecting high-risk drinking, monthly binge drinking, and alcohol use disorder among college students were age, breakfast eating, current smoking, and life safety awareness. Risk drinking behavior was the higher rate in the group between 19~20 years old or the 1st to 2nd grade. Risk drinking behaviors were related to breakfast eating, current smoking, physical activity, and life safety consciousness level. The high rate of monthly binge-drinking rate among female students is a very remarkable result. Conclusion: Health promotion of college students is an essential task as it affects their adaptation to university life and academic achievement. It should establish campus-based university health and safety policies to prevent the risk of drinking.