Reviewerly/exHarmony huggingface dataset:
Constrained Low-Tubal-Rank Tensor Recovery for Hyperspectral Images Mixed Noise Removal by Bilateral Random Projections

In this paper, we propose a novel low-tubal-rank tensor recovery model, which directly constrains the tubal rank prior for effectively removing the mixed Gaussian and sparse noise in hyperspectral images. The constraints of tubal-rank and sparsity can govern the solution of the denoised tensor in the recovery procedure. To solve the constrained low-tubal-rank model, we develop an iterative algorithm based on bilateral random projections to efficiently solve the proposed model. The advantage of random projections is that the approximation of the low-tubal-rank tensor can be obtained quite accurately in an inexpensive manner. Experimental examples for hyperspectral image denoising are presented to demonstrate the effectiveness and efficiency of the proposed method.
Improving Evidence Detection by Leveraging Warrants

Recognizing the implicit link between a claim and a piece of evidence (i.e.warrant) is the key to improving the performance of evidence detection.In this work, we explore the effectiveness of automatically extracted warrants for evidence detection.Given a claim and candidate evidence, our proposed method extracts multiple warrants via similarity search from an existing, structured corpus of arguments.We then attentively aggregate the extracted warrants, considering the consistency between the given argument and the acquired warrants.Although a qualitative analysis on the warrants shows that the extraction method needs to be improved, our results indicate that our method can still improve the performance of evidence detection.
Zero-Shot Cross-lingual Name Retrieval for Low-Resource Languages

In this paper we address a challenging crosslingual name retrieval task.Given an English named entity query, we aim to find all name mentions in documents in low-resource languages.We present a novel method which relies on zero annotation or resources from the target language.By leveraging freely available, cross-lingual resources and a small amount of training data from another language, we are able to perform name retrieval on a new language without any additional training data.Our method proceeds in a multi-step process: first, we pretrain a language-independent orthographic encoder using Wikipedia inter-lingual links from dozens of languages.Next, we gather user expectations about important entities in an English comparable document and compare those expected entities with actual spans of the target language text in order to perform name finding.Our method shows 11.6% absolute Fscore improvement over state-of-the-art methods.
JBNU at MRP 2019: Multi-level Biaffine Attention for Semantic Dependency Parsing

This paper describes Jeonbuk National University (JBNU)'s system for the 2019 shared task on Cross-Framework Meaning Representation Parsing (MRP 2019) at the Conference on Computational Natural Language Learning.Of the five frameworks, we address only the DELPH-IN MRS Bi-Lexical Dependencies (DP), Prague Semantic Dependencies (PSD), and Universal Conceptual Cognitive Annotation (UCCA) frameworks.We propose a unified parsing model using biaffine attention (Dozat and Manning, 2017), consisting of 1) a BERT-BiLSTM encoder and 2) a biaffine attention decoder.First, the BERT-BiLSTM for sentence encoder uses BERT to compose a sentence's wordpieces into word-level embeddings and subsequently applies BiLSTM to word-level representations.Second, the biaffine attention decoder determines the scores for an edge's existence and its labels based on biaffine attention functions between roledependent representations.We also present multi-level biaffine attention models by combining all the role-dependent representations that appear at multiple intermediate layers.
Audit Implications of AI &amp; Blockchain

Some of the most high profile work that has taken place, especially as it pertains to the accounting subset of the financial services landscape, is the work that has taken place linked to audit and attestation work. The audit process, as currently constituted, is an almost perfect fit for the increased efficiency and automation provided for by a variety of blockchain tools. Audits, and these similarities tend to exist across geographic and firm lines, tend to contain several of the same core components. An engagement letter is composed, outlining the services to be provided by the external audit organization, including but not limited to the testing of certain assets, verification of financial statement amounts, and then the issuance of an opinion based on these amounts. Even with these tests and analyses, some of which may be quite sophisticated in nature, there is a fundamental time lag issue that usually remains unaddressed despite how efficient the audit process is. Put simply, the amount of time that passes between when the data is actually generated or produced, and the time that the audit actually occurs can stretch into months. Even with interim work, or work performed at different times during the year, there is still often a substantial lag between when data (and potential errors) happen, and when that data and potential errors are reported to management. The figure below represents areas in a financial transaction (trading) in which potential audit and attestation implications will arise, and can be aided by the implementation of emerging technologies (Fig. 13.1).
IMPROVING READING COMPREHENSION ACHIEVEMENT OF THE TENTH GRADE STUDENTS OF SMA NEGERI 2 PALEMBANG BY USING ONLINE MIND MAPPING

The objectives of this study were to find out (1) whether or not there was a significant improvement in reading comprehension achievement of the tenth grade students of SMA Negeri 2 Palembang after they were taught by using online mind mapping, and (2) whether or not there was contribution of each sub-skill of reading comprehension to reading comprehension achievement of the tenth grade students of SMA Negeri 2 Palembang. In this study, Time Series design was applied. The sample of this study was 40 tenth grade students of SMA Negeri 2 Palembang, who belong to the experimental group. To collect the data, the experimental group was given a pretest and a post test. The result showed that (1). the mean difference between pre-test and post-test of the experimental group was 34.70 at the significance level of p value &lt;0.05. Since t obtained was higher than t table (18.2111&gt;2.023), H01 was rejected and there was a significant improvement in reading comprehension achievement after they were taught by using online mind mapping, (2).The highest contribution of reading sub-skill was given by sequence (39.4%) and then it was followed by vocabulary (23.3%), detail (17.3%), main idea (9.1%), inference (5.6%) and cause and effect (5.2%).Keywords: reading comprehension, online mind mapping
Images Similarity based on Bags of SIFT Descriptor and K-Means Clustering

The content based image retrieval is developed and receives many attention from computer vision, supported by the ubiquity of Internet and digital devices. Bag-of-words method from text-based image retrieval trains images’ local features to build visual vocabulary. These visual words are used to represent local features, then quantized before clustering into number of bags. Here, the scale invariant feature transform descriptor is used as local features of images that will be compared each other to find their similarity. It is robust to clutter and partial visibility compared to global feature. The main goal of this research is to build and use a vocabolary to measure image similarity accross two tiny image datasets. K-means clustering algorithm is used to find the centroid of each cluster at different k values. From experiment results, the bag-of-keypoints method has potential to be implemented in the content based information retrieval.
Obstacle Avoidance Based on Virtual Repulsive Potential Fields under Limited Perceptions

Aiming at the unknown obstacle environment, an online obstacle avoidance method, which is based on the model-based artificial potential field (MAPF) method and only depends on the information detected by onboard sensors, is proposed. First, the entire mission space is discretized. According to the relative position relation between the detection sector and the detected obstacle surface in the discrete space, the virtual repulsive potential fields (VRPFs) and the corresponding total force fields are constructed to make the robot avoid the detected obstacles and gradually move to the destination. Then, to avoid the local optimum, the memory mechanism for VRPFs and its corresponding path planning solution are introduced. Finally, the effectiveness of the proposed method is demonstrated by the simulation.
Future Teachers’ Instrumental Metaprofessional Competencies Development as Way of Their Methodical Competence Establishment

Topicality of the research is determined by the main goal of education, stated in the Federal State Educational Standard for Higher Professional Education in Russia, that is mastering both academic and professionally oriented competencies, and universal, metaprofessional (instrumental, interpersonal, general system-based) competencies. Modern higher education makes implementation of competence-based professional standards one of the dominant activities in educational institutions. Raising the level of methodical competencies for undergraduates, as a result of high quality professional education, becomes one of the targets. In this context, the objective of the article is to consider the "Primary Education" methodical competence-based components ¬– theoretic-methodological and technological – through universal metaprofessional competencies development; generalization of scientific methodical data. The material is focused on the theoretical proof and experimental evidence of the methodical competence establishment for future primary school teachers on the basis of fundamental academic disciplines. This research was based on the methods of theoretical analysis of scientific literature, testing, educational experiment and lesson observation, qualitative analysis of students’ work. The article presents a theoretical model of the levels for methodical competence among future teachers, with the criteria and their nominative and specific indicators. This model enables teachers to track the dynamics of methodical competence development among students of pedagogical departments at various stages of education. The methodical materials presented in the article will help teachers in designing assignments that ensure instrumental metaprofessional competencies development at lecture classes for students.
Implementasi Metode Waterfall Pada Perancangan E-Recycle Bank Pada Dinas Lingkungan Hidup Kabupaten Asahan

Asahan Regency is a national strategic area because it has superior sectors such as plantation, marine, agriculture, fisheries and industry. This caused a lot of waste to arise in Asahan Regency. One of the efforts made by the Department of Environment to reduce the volume of waste is to make the Waste Bank an innovative program of community-based waste management. The Waste Bank at the Environmental Service was given the name "Srikandi" which was still less effective and efficient. Because at this time the process is done manually. For that we need to design a system by implementing the waterfall method, which is a sequential software development process, where progress is seen as continuously flowing down (such as waterfalls) through the phases of planning, modeling, implementation (construction), and testing. Hunger by implementing the waterfall method and the C2C e-commerce model in designing and building the E-Recycle Bank system. As a result, the system will make it easier for "Srikandi" Waste Bank officers to manage waste data so as to produce more effective and efficient data, besides that it can also be used as a container for the promotion of waste recycling products for the Asahan Regency
Automatic Topic Labeling for Facilitating Interpretability of Online Learning Materials

To reduce the cognitive overhead of understanding and organizing online learning materials using topic models, especially for new learners not familiar with related domains, this paper proposes an efficient and effective approach for generating high-quality labels as better interpretation of topics discovered and typically visualized as a list of top terms. Compared with previous methods dependent on complicated post-processing processes or external resources, our phrase-based topic inference method can generate and narrow down label candidates more naturally and efficiently. The proposed approach is demonstrated and examined with real data in our corporate learning platform.
Blockchain-Powered Service Migration for Uncertainty-Aware Workflows in Edge Computing

In edge computing, the workflow is used to simulate and manage computing tasks as well as information exchange for compute-intensive and data-intensive application, which is convenient for the various complex process to work orderly. However, the resource conflict among cooperative works of multiple mobile edge computing (MEC) nodes by workflow, together with the service failure and the performance degradation, bring about additional uncertainties of scheduling strategies. Consequently, such uncertainties delay the completion of tasks and spoil the user experience. To deal with that issue, we propose a blockchain-powered resource provisioning (BPRP) method to design policies for workflows in the edge computing environment. Technically, we use the directed acyclic graph to indicate workflows of each edge node and regard its scheduling strategy as an individual gene to adapt to the following algorithm. Then, we use the non-dominated sorting genetic algorithm-III (NSGA-III) to optimize the workflow scheduling strategies on the basis of tasks' timely completion with good quality. A large number of experiments were carried out to verify the effectiveness of our method.
SISTEM PENYIRAMAN DAN PENGUSIR HAMA OTOMATIS PADA DAUN MINT BERBASIS MIKROKONTROLER ARDUINO UNO

Water requirements for mint / peppermint leaves are important so that mint / peppermint leaves grow and multiply well. Not only that, mint leaf protection from pests / insects is also important so that mint / peppermint leaves can live and have perfect leaf quality until harvest time. But in practice, humans are often negligent in watering and protecting pests on plants. To overcome these problems, mint / peppermint watering and automatic pest control use an arduino uno microcontroller as one solution. Automatic watering uses RTC as a schedule for minting and PIR sensors for detecting the movement of pests / insects approaching the mint leaves. The purpose of making this tool is to design hardware, software, and to find out the performance of an arduino uno microcontroller-based automatic watering pest control system. The making of this tool is based on arduino uno microcontoler combined with RTC (Real Time Clock) sensor and PIR (Passive Infrared) sensor. Here Arduino Uno as the main microcontroller, relay as a pump and fan switch, RTC as a regulator of mint leaves watering schedule, and PIR sensor to detect any movement of pests / insects that approach the mint leaves. Based on the results of the tests carried out, the automatic pest control and sprinkler system on the arduino uno microcontroller-based mint leaves has been successful. All programs run well according to the previous plan. And for the performance of mint leaves as a whole is in accordance with the established functions. For further research watering and repelling pests on mint leaves can automatically be added to the temperature sensor for use during the rainy season. Because in this study the tool is only used during the dry season.
Visibility Enhancement during Severe Weather—Object Tracking with Bounding Box

A large number of vehicle accidents are caused by low visibility during severe weather conditions.According to the US Department of Transportation, there are more than 1,259,000 crashes each year caused by severe weather conditions.These accidents could be significantly prevented if real time visibility enhancement systems were to exist.This work is aimed to improve driver safety during severe weather conditions.We propose a method to improve driver's visibility during harsh weather conditions: a multistage framework based on Retinex algorithm and followed by a detection process of the vehicles in the front view of the driver.Retinex is an algorithm that has a capability to maintain a good dynamic range compression and spectral rendition effect.Retinex is used because it has the ability to overcome the loss of background details which occur during severe weather conditions scenes.We present simulation results of different visibility degradation.We also evaluate our method by using peak signal to noise ratio (PSNR) and Structural SIMilarity (SSIM) parameters.
Feasibility of Chatbot for Mehran UET Examination Department

A chatbot system enables communication between computer and users through natural language. The university students face many problems for the queries and details regarding their examination and it is also difficult for them to physically visit the examination department frequently. The concerned authorities find it challenging to handle thousands of student queries in parallel, thus, consuming a lot of time. At present, majority of the chatbot system are available in English language. Therefore, people who are not fluent in English language cannot use these systems due to the obvious reason of language barrier. This paper focuses on the viability of a chatbot system for the examination department of Mehran University of Engineering Technology (MUET) Jamshoro. The chatbot discussed in this paper has been designed to support both Urdu and English languages. Three chatbot interfaces have been developed, Urdu typing based chatbot, English typing based chatbot and English voice based Chabot. The typing based chatbots (both English and Urdu) have been developed using AIML, and voice based chatbot is based on dialogflow called as API.ai. This study is not only concerned with the development of three interfaces of chatbot systems, but also covers their evaluation. To find best chatbot interface, a survey was conducted with engineering students of MUET Jamshoro. The results revealed that the among the three chatbot interfaces, English typing-based interface is the best due to the usability, easiness and the general understanding of queries.
DEMO: Using gameplay data to classify cybersickness level in virtual environments

Virtual Reality is an upcoming trend in games and entertainment applications as the use of head-mounted displays becomes accessible for the mass market. These systems aim to provide immersive experiences, but they still do not offer a completely seamless experience, mostly due to sickness symptoms that can be experienced by the players. Cybersickness is one of the most critical problems that make the game industry fearful of higher investments. In this demo we developed a plugin for a commercial game engine to collect relevant data in a virtual reality game to use as a database to future research approaches to enhance user experience in head-mounted displays.
Design of Virtual Campus Card System Based on Micro-Service Architecture

Based on the analysis of the application status of campus card and aiming at the design of virtual campus card system under the architecture of micro-service, taking the newly-built campus card system of New Cape as an example, this paper analyses the overall requirements, system architecture, data center, system network and system performance, etc. By vertical splitting of the monolithic application, the platform's concurrent capability is greatly improved, the complexity of the monolithic application is solved, and the business response is more agile and fast. The application of the micro-service architecture will greatly improve the service capability and security level of the virtual campus card system, which can provide important reference function for the research and construction of the new generation campus card system.
Hybridized Feature Extraction for Facial Age Estimation using SVM

Forging of age is increasing dramatically these days, especially in areas such as military, industry, crime, processing of visa, job application, etc. One of the areas of human-PC-interaction is developing an application for the automated estimation of age using face pictures. Typically, an age estimation system consists of the extraction and classification of aging features; both of which are important to improve efficiency. For the ageing feature extraction, the hybrid features extraction, which are a mixture of Active Appearance Models (AAM), Local Binary Patterns (LBP) and Gabor filter is applied. As global facial features, the shape of human faces is extracted with AAM. The local facial features are the features of the skin textures extracted with LBP and wrinkle extracted with Gabor filter. An age classification utilizing Support Vector Machine (SVM) classifies age in groups. Eight age group class is used for the age estimation. The result is represented in Cumulative Score. The higher the Cumulative Score (CS) becomes, the age estimate becomes accurate as well. Our system is implemented using Object Oriented Programming (OOP) with the help of Open Computer Vision (OpenCV) library and private dataset from Department of Computer Science, Ignatius Ajuru University of Education (IAUE). The result shows 93% accuracy on age classification and age estimation from facial images which is better than the former method.
Application of 3D Design Technology Based on BIM in Substation Design

Abstract With the information technology era of intelligent grid of the new concept of deepening, substation as an important part of the smart grid has been sustained attention, substation design technology is also constantly improved to meet the new requirements of the national grid, building information model (referred to BIM) is one of the more widely used design techniques. This article briefly describes the use of Revit for three-dimensional design process, the establishment of family and so on. In addition, the advantages and limitations of the current three-dimensional design in the design of electrical specialty, civil engineering design and collaborative design are also discussed.
Auto-generated Test Paper Based on Knowledge Embedding

Auto-Generated Test Paper (AGTP) has been deeply studied for many years, however, it is still a difficult problem and the certainty to access the best test paper (TP) is not guaranteed yet.In this paper, we put forward a method for AGTP based on knowledge embedding, which makes AGTP easier and faster.The knowledge to be embedded is studied and the mechanism behind it is analyzed.The embedded knowledge in this paper is from both the constraints of TP and the information of question repository (QR).The experiments validated the proposed method and found it is not only faster but also costs less computational resources to access the best TP than other method, such as evolutionary algorithm.What impressed is that the cost time to access the optimum does not rapidly increase with the size of QR.The knowledge plays the important role in AGTP, especially to efficiently improve the performance of the algorithms.