Reviewerly/exHarmony huggingface dataset:
Progressive Network Grafting for Few-Shot Knowledge Distillation

Knowledge distillation has demonstrated encouraging performances in deep model compression. Most existing approaches, however, require massive labeled data to accomplish the knowledge transfer, making the model compression a cumbersome and costly process. In this paper, we investigate the practical few-shot knowledge distillation scenario, where we assume only a few samples without human annotations are available for each category. To this end, we introduce a principled dual-stage distillation scheme tailored for few-shot data. In the first step, we graft the student blocks one by one onto the teacher, and learn the parameters of the grafted block intertwined with those of the other teacher blocks. In the second step, the trained student blocks are progressively connected and then together grafted onto the teacher network, allowing the learned student blocks to adapt themselves to each other and eventually replace the teacher network. Experiments demonstrate that our approach, with only a few unlabeled samples, achieves gratifying results on CIFAR10, CIFAR100, and ILSVRC-2012. On CIFAR10 and CIFAR100, our performances are even on par with those of knowledge distillation schemes that utilize the full datasets. The source code is available at https://github.com/zju-vipa/NetGraft.
Measurement of Focal Length and Radius of Curvature for Spherical Lenses and Mirrors by Using Digital-Grating Moiré Effect

This paper proposes the use of digital-grating moiré effect for measuring the focal lengths and radius of curvatures of biconvex and biconcave spherical simple lenses and spherical mirrors. Based on Fresnel diffraction, the equation for the electric field of propagated light passing through the test samples was derived. Through digital image post processing, the recorded intensity on an observation screen was superimposed on a digital grating to generate a moiré pattern. On substituting the slant angle of the moiré pattern into the derived equation, the focal lengths and radius of curvatures could be determined. The experimental results successfully demonstrated the feasibility of the proposed method; the percent errors for focal length and radius of curvature measurement were less than 0.5%. The measurement uncertainty was analyzed and the correctness of the derived equation was confirmed through simulation. Because of the use of digital image post processing, the proposed method has advantages such as a simple set up, easy operation, high stability, high accuracy, and low cost. Thus, the method has considerable potential in relevant application.
Exploring the Effectiveness of Two Types of Virtual Reality Headsets for Teaching High School Mathematics

This study examines the integration of virtual reality (VR) information technology in the teaching of systems of linear equations in three variables in a high school mathematics class. More broadly, the study investigates the effectiveness of digital teaching with respect to the learning process. The study tests two auxiliary teaching systems: a desktop-based VR system and an all-in-one VR system. Before and after the experiment, participants were asked to complete a questionnaire, and post-experiment interviews were conducted with both students and teachers, both of which provided quantitative and qualitative data for analysis. The result of data show that VR technology is a suitable tool for teaching high school mathematics, when it combined with the tradition curriculum were well-received and facilitate effective learning. In addition, the desktop-based VR system is found to be superior to the all-in-one VR system in terms of learning effectiveness since the high-efficiency display and better control.
A New Approach to the Design and Implementation of a Family of Multiplier Free Orthogonal Wavelet Filter Banks

This paper presents a generalized novel design of a family of multiplier free orthogonal wavelet filter banks (FBs) with low complexity. In the proposed method, maximum number of zeros at <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$z=-1$ </tex-math></inline-formula> is ensured for a desired length of analysis and synthesis filters. A new class of technique is proposed to obtain dyadic filter coefficients based on double shifting orthogonality property with allowable deviation from original filter coefficients. This is achieved by slightly altering perfect reconstruction (PR) condition to obtain dyadic filter coefficient. A general closed form expression is formulated using double shifting orthogonality property to reduce the error between original filter coefficients and proposed dyadic filter coefficients. The designed wavelet FB improved time-frequency product, Sobolev regularity and frequency selectivity (low energy in error) over well known existing wavelet FBs. In addition, a fixed point VLSI architecture is proposed for the designed family of orthogonal wavelet FBs. The suggested architecture is designed and implemented on Kintex7 FPGA board. The proposed family of orthogonal wavelet FBs is multiplier less with significantly reduced adders, shifters and dynamic power dissipation. The performance of the proposed wavelet FB is validated on two different applications namely image compression and medical image retrieval. The proposed FBs are tested on well known datasets such as CLASSIC, EPFL, RAISE, and FiveK for image compression and on three different medical image databases such as NEMA, OASIS, and EXACT09 for image retrieval.
Evaluating Power Rehabilitation Actions Using a Fuzzy Inference Method

The older population faces a high probability of experiencing age-related problems, such as osteoporosis, immobility, gait disturbances, stroke, Parkinson's disease, and cognitive behavioral functional difficulties. Such problems negatively affect their lives. Thus, access to long-term care is a critical issue for older adults. In response to the aforementioned serious health issues, society must strive to provide a supportive and effective rehabilitation environment for older adults. This study designed an intelligent active and passive limb rehabilitation system to track and quantify the effectiveness of joint movements in patients automatically. The proposed method uses a camera and PoseNet to capture key feature information regarding human skeleton nodes and identify rehabilitation actions through joint movements. In addition, to solve the problem of joint occlusion during joint angle measurement, the designed system is equipped with a self-designed inertial measurement unit with GY-85 nine-axis sensors, which are mounted on the occluding part of the joints. A fuzzy inference system was developed to provide scores, suggestions, and encouragement for each rehabilitation session. This system also provides an interactive interface for users to monitor each rehabilitation session and examine whether rehabilitation is performed accurately.
The Space of Interaction

The space complexity of functional programs is not well understood. In particular, traditional implementation techniques are tailored to time efficiency, and space efficiency induces time inefficiencies, as it prefers re-computing to saving. Girard's geometry of interaction underlies an alternative approach based on the interaction abstract machine (IAM), claimed as space efficient in the literature. It has also been conjectured to provide a reasonable notion of space for the λ-calculus, but such an important result seems to be elusive.In this paper we introduce a new intersection type system precisely measuring the space consumption of the IAM on the typed term. Intersection types have been repeatedly used to measure time, which they achieve by dropping idempotency, turning intersections into multisets. Here we show that the space consumption of the IAM is connected to a further structural modification, turning multisets into trees. Tree intersection types lead to a finer understanding of some space complexity results from the literature. They also shed new light on the conjecture about reasonable space: we show that the usual way of encoding Turing machines into the λ-calculus cannot be used to prove that the space of the IAM is a reasonable cost model.
IITP@COLIEE 2019: Legal Information Retrieval using BM25 and BERT

Natural Language Processing (NLP) and Information Retrieval (IR) in the judicial domain is an essential task. With the advent of availability domain-specific data in electronic form and aid of different Artificial intelligence (AI) technologies, automated language processing becomes more comfortable, and hence it becomes feasible for researchers and developers to provide various automated tools to the legal community to reduce human burden. The Competition on Legal Information Extraction/Entailment (COLIEE-2019) run in association with the International Conference on Artificial Intelligence and Law (ICAIL)-2019 has come up with few challenging tasks. The shared defined four sub-tasks (i.e. Task1, Task2, Task3 and Task4), which will be able to provide few automated systems to the judicial system. The paper presents our working note on the experiments carried out as a part of our participation in all the sub-tasks defined in this shared task. We make use of different Information Retrieval(IR) and deep learning based approaches to tackle these problems. We obtain encouraging results in all these four sub-tasks.
Big Data Storage Technology for Smart Distribution Grid Based on Neo4j Graph Database

In the smart distribution grid, deep integration of power system and information system is the development direction. In order to effectively excavate the potential value of massive data generated in planning and operation phases, the storage of big data is one of the key technologies. This paper proposes a big data storage method for smart distribution grid based on neo4j graph database. Use the common information model (CIM) of power system for reference to establish topology model of smart distribution grid. The storage method of multivariate heterogeneous data is presented integrated the advantages of graph database and relational database. Simulation results on the IEEE standard test systems show that the proposed big data storage method is able to effectively improve data storage and analysis efficiency of smart distribution grid, and a practical citizen power grid is adopted to verified the effectiveness.
Inference Fusion with Associative Semantics for Unseen Object Detection

We study the problem of object detection when training and test objects are disjoint, i.e. no training examples of the target classes are available. Existing unseen object detection approaches usually combine generic detection frameworks with a single-path unseen classifier, by aligning object regions with semantic class embeddings. In this paper, inspired from human cognitive experience, we propose a simple but effective dual-path detection model that further explores associative semantics to supplement the basic visual-semantic knowledge transfer. We use a novel target-centric multiple-association strategy to establish concept associations, to ensure that the predictor generalized to unseen domain can be learned during training. In this way, through a reasonable inference fusion mechanism, those two parallel reasoning paths can strengthen the correlation between seen and unseen objects, thus improving detection performance. Experiments show that our inductive method can significantly boost the performance by 7.42% over inductive models, and even 5.25% over transductive models on MSCOCO dataset.
GCRC: A New Challenging MRC Dataset from Gaokao Chinese for Explainable Evaluation

Recently, driven by numerous publicly available machine reading comprehension (MRC) datasets, MRC systems have made some progress.These datasets, however, have two major limitations: 1) the defined tasks are relatively simple, and 2) they do not provide explainable evaluation which is critical to objectively and comprehensively review the reasoning capabilities of current MRC systems.In this paper, we propose GCRC, a new dataset with challenging and high-quality multi-choice questions, collected from Gaokao Chinese (Chinese subject from the National College Entrance Examination of China).We have manually labelled three types of evidence to evaluate MRC systems' reasoning process: 1) sentence-level relevant supporting facts in an article required for answering a given question, 2) error reason of a distractor (i.e., an incorrect option) for explaining why a distractor should be eliminated, which is an important reasoning step for multi-choice questions, and 3) types of reasoning skills required for answering questions.Extensive experiments show that our proposed dataset is more challenging and very useful for identifying the limitations of existing MRC systems in an explainable way, facilitating researchers to develop novel machine learning and reasoning approaches to tackle this challenging research problem.
Digital Currency in Broader Sense, Status, Regulation and Development Trends

The present article deals with one of the phenomena of the Industrial (Digital) revolution 4.0, which is digital currency in broader sense, respectively virtual currencies, as some authors refer to them. Despite the fact that this phenomenon is not such a novelty in society, it has demanded the focus of legal science only in recent years and the discussion has not subsided, it can be stated that it is only in the beginning. Along with digital currency in broader sense, there are several issues, such as the correctness of their naming, their legal status and, as far as the area of tax law is concerned, these are also questions of the manner and possibilities of taxing transactions with them. Authors set as a goal of this article to verify the following hypotheses: - the naming of digital currency in broader sense as a currency is incorrect given the existing knowledge of financial law science. - the legal regulation of digital currency in broader sense in selected Member States of the European Union is not sufficient. To verifying the above hypotheses, the authors used several methods of writing scientific works, but especially analysis, synthesis, the method of comparison and the historical method, which the authors used in combination with each other.
Visualization and Mapping of Knowledge and Science Landscapes in <i>Expert Systems With Applications</i> Journal: A 30 Years’ Bibliometric Analysis

The Expert Systems With Applications (ESWA) is a leading journal in the fields of computer science and engineering. Motivated by its outstanding performance, this paper seeks to develop a comprehensive overview of research activities in ESWA since its inception in 1990. In this regard, bibliometric techniques have been utilized to characterize the status quo, dynamics, and development trends of research patterns in ESWA. In doing so, the work used Scopus database as a source of data required. A data visualization software, visualization of similarities (VOS) viewer, was used to map the bibliographic material. The Scopus database yielded 12,254 documents published in ESWA from 105 countries with an average of 408 documents/year. The most productive country was Taiwan (2,069 documents; 17.0%). National Cheng Kung University, Taiwan, was the most productive institution (219 documents; 1.8%). The major topics which will continue to be active include genetic algorithms, data mining, neural networks, support vector machines, classification and machine learning, feature selection, particle swarm optimization, fuzzy logic, and clustering. The outcomes underline the significant growth of ESWA through time. The vitality of topics addressed in ESWA to solve real-world problems boosts the progress and advancements of knowledge in this journal.
Penerapan Model Pembelajaran Berbasis Masalah Berbantuan Media Power Point untuk Meningkatkan Aktivitas dan Hasil Belajar Siswa di SDN Pandean Lamper 02 Semarang

The purpose of this study was to increase student activity and learning outcomes using a problem-based learning model assisted by power point media for third grade students at SDN Pandean Lamper 02 Semarang. The research method used is classroom action research consisting of 3 cycles with 4 stages, namely planning, action, observation, and reflection. The subjects of this study were third grade students with a total of 30 people. The data collection techniques used were observation, interviews, tests, and documentation, while the data analysis techniques used descriptive analysis. The results showed that the average percentage of student activity classically increased. In the pre-cycle before treatment it was 65%, in the first cycle it was 70%, in the second cycle it was 74% while in the third cycle it was 87%. While the percentage of mastery learning outcomes in the pre-cycle is 37%, in the first cycle it is 57%, in the second cycle it is 73%, while in the third cycle it is 90%. Based on the results of the research that has been done, it can be concluded that learning in Theme 8 using a problem-based learning model assisted by power point media can improve student activities and learning outcomes.
Digital technologies in civic and patriotic education of students

The study deals with the problem of the effectiveness of digital technologies use in the civic and patriotic education of students. The relevance of the identified problem in the current conditions of social development is stated. The events of recent years show how important it is to solve the problems of civic and patriotic education of young people promptly. The implementation of the tasks of forming a citizen and a patriot should be carried out at all levels of the education system. The astudy analyzes the available material on digital support of the education system such as 3D games, teletandem, podcasts, social networks, video resources, and other innovative technologies for implementing e-learning. The methods and results of an empirical study are presented to assess the level of civic and patriotic development of student personality and to analyze the possibilities of using digital technologies in this respect. The digital technologies that can be used to solve the problem are described: a systematized bank of digital tools, the control and evaluation component and the activity component. The authors analyze their electronic educational resources. Conclusions are drawn about the effectiveness of the use of digital tools in the civic and patriotic education of students. It is stated that the modern approach to the civil-patriotic education of students involves the use of new technologies that meet their interests and preferences. Digital technologies have considerable didactic opportunities and their potential requires wide application in the educational process of the university.
Analysis of Needs for Core Competencies and the Development Competencies-based Extracurricular Educational Program for Outstanding Students through FGI Analysis: Focusing on the Case of S-university

본 연구는 대학생의 핵심역량을 향상시킬 수 있는 역량기반 비교과 교육 프로그램 개발을 목적으로 수행되었다. 이를 위하여 K-CESA를 활용하여 S대학교 학부생의 핵심역량의 수준을 분석하였고, 핵심역량에 영향을 미치는 요인을 분석하고자 진단에 참여한 학부생 136명을 대상으로 세부 영역별 핵심역량에 대한 Borich 교육요구도와 The Locus for Focus 분석을 수행하였다. 또한 K-CESA 진단 결과 영역별 역량 우수학생을 대상으로 인터뷰를 수행하여 역량 향상에 영향을 주었던 비교과 프로그램의 참여 경험을 분석하였다. 그 결과, 학생들은 의사소통 역량 중 말하기, 토론 조정 능력이 가장 필요하다고 인식하고 있었다. 또한 핵심역량 수준이 상대적으로 높았던 학부생 15명을 대상으로 포커스 그룹 인터뷰(Focus Group Interview)를 실시하여 핵심역량 향상에 영향을 미친 수업 내·외적 학습경험을 분석하였다. 교육요구도로 산출된 결과와 FGI에서 제시된 논의를 종합하여 학습자의 요구에 근거한 역량기반 비교과 프로그램을 도출하였다.This study was conducted with the purpose of developing a competency-based extracurricular educational program that can help develop the core competencies of undergraduate students. To this end, the K-CESA analysis tool was used to analyze the core competency levels of undergraduates at S-University. To better understand the elements that influence the development of core competencies, 45 undergraduates participated in an analysis involving the Borich needs assessment model and the Locus for Focus model, which were utilized in relation to core competencies for each division in relation to the 45 undergraduate participants. This revealed that, in the area of communication skills, students considered speaking and mediation skills as most important and necessary. Additionally, a Focus Group Interview was conducted with 15 undergraduate students that had relatively high core competencies. Through this, learning experiences inside and outside the classroom that influenced the improvement of core competencies were analyzed. Subsequently, a competency-based extracurricular program based on learners needs was derived from the results of the educational needs assessment and FGI.
ChrEnTranslate: Cherokee-English Machine Translation Demo with Quality Estimation and Corrective Feedback

We introduce ChrEnTranslate, an online ma chine translation demonstration system for translation between English and an endangered language Cherokee.It supports both statistical and neural translation models as well as pro vides quality estimation to inform users of re liability, two user feedback interfaces for ex perts and common users respectively, exam ple inputs to collect human translations for monolingual data, word alignment visualiza tion, and relevant terms from the Cherokee English dictionary.The quantitative evalu ation demonstrates that our backbone trans lation models achieve stateoftheart transla tion performance and our quality estimation well correlates with both BLEU and human judgment.By analyzing 216 pieces of expert feedback, we find that NMT is preferable be cause it copies less than SMT, and, in gen eral, current models can translate fragments of the source sentence but make major mistakes.When we add these 216 expertcorrected paral lel texts into the training set and retrain mod els, equal or slightly better performance is ob served, which demonstrates indicates the po tential of humanintheloop learning. 1
Participatory Design as the Temporal Flow of Coalescing Participatory Lines

Abstract This paper argues that the existing literature on participatory design (PD) tends to focus on frontstage design interactions (workshops, participants, methodologies, techniques, etc.) to facilitate PD ‘here and now’—referred to as the interactional approach . In contrast, the paper proposes to contribute to an evolving literature, referred to as the transformational approach , that takes a more longitudinal line and which attends to both the frontstage and backstage within an extended temporal frame. To do this the paper draws on the work of the social anthropologist Tim Ingold, in particular, his concept of the happening of ongoing life as a bundle of flowing lines. The paper argues that PD becomes possible when ongoing participation is conceived of as a set of corresponding (or coalescing) and conditioning lines of flow—each line with its own history, attentionality, rhythms, tempos and so forth. To illustrate what this reorientation might mean for PD the paper draws on an in-depth action research study of a PD initiative that sought to develop a digital service to address loneliness and social isolation in a rural location in the UK. The paper explores how project members, individual participants, non-governmental organisation, government representatives, evaluators and funders co-responded to each other (or not) as they engaged, or became implicated, in the PD process. The paper concludes with some practical implications of what such an Ingoldian reorientation might mean for the ongoing development of PD as a transformational methodology.