Reviewerly/exHarmony huggingface dataset:
Makassarese and English Affirmative Sentences Pattern : A Linguistic Contrastive Study

This research aims to determine the differences between Makassarese and English structure. This research is a descriptive qualitative research with ten samples of native speakers of Makassarese in urban village of PAI, Biringkanaya Makassar. The method used is contrastive method and using sentence function theory from Verhaar and the theory of tree diagram from Bornstain. The results of this research indicate the existence of different Makassarese and English structurally in terms of sentence function. The affirmative sentences in Makassarese generally begins with the predicate (P) then followed by subject (S) whils English sentences begins with subject (S) then followed by predicate (P). Verb in Makassarese also cannot change or get modification because it is not affected by an adverb and context of the sentence. While the verb in English can change depending on an adverb and context of the sentence.
Coordination Privacy Protection of Multi-agent Systems

This paper considers differential privacy consensus of multiple agent systems with fixed interaction topologies. The differential privacy cooperative control algorithm is proposed. Both uniform convergence and differential privacy are studied in the algorithm. By analyzing the privacy protection consensus algorithm, the algorithm can protect the interaction information of multi-agent systems and make the mean square of multi-agent systems converge to the average of the initial states of all agents. Simulation results show the effectiveness of our update schemes.
GCNIllustrator

An increasing number of real-world applications are using graph-structured datasets, imposing challenges to existing machine learning algorithms. Graph Convolutional Networks (GCNs) are deep learning models, specifically designed to operate on graphs. One of the most tedious steps in training GCNs is the choice of the hyperparameters, especially since they exhibit unique properties compared to other neural models. Not only machine learning beginners, but also experienced practitioners often have difficulties to properly tune their models. We hypothesize that having a tool that visualizes the effect of hyperparameters choice on the performance can accelerate the model development and improve the understanding of these black-box models. Additionally, observing clusters of certain nodes helps to empirically understand how a given prediction was made due to the feature propagation step of GCNs. Therefore, this demo introduces GCNIllustrator - a web-based visual analytics tool for illustrating the effect of hyperparameters on the predictions in a citations graph.
An assertion and alignment correction framework for large scale knowledge bases

Various knowledge bases (KBs) have been constructed via information extraction from encyclopedias, text and tables, as well as alignment of multiple sources. Their usefulness and usability is often limited by quality issues. One common issue is the presence of erroneous assertions and alignments, often caused by lexical or semantic confusion. We study the problem of correcting such assertions and alignments, and present a general correction framework which combines lexical matching, context-aware sub-KB extraction, semantic embedding, soft constraint mining and semantic consistency checking. The framework is evaluated with one set of literal assertions from DBpedia, one set of entity assertions from an enterprise medical KB, and one set of mapping assertions from a music KB constructed by integrating Wikidata, Discogs and MusicBrainz. It has achieved promising results, with a correction rate (i.e., the ratio of the target assertions/alignments that are corrected with right substitutes) of 70.1 %, 60.9 % and 71.8 %, respectively.
Blockchain and Consensus Algorithms

Blockchain is a publicly distributed ledger system that provides access to all records for everyone participating in the network. All the additions to the block are permanent and unchangeable. All major or minor changes are reported in a new block and cannot be reversed. Since the ledger is being distributed, there is no centralized authority. By eliminating the need for intermediaries, blockchain enables parties to trace transactions quickly and easily. The transactions occurring on a blockchain are transparent, reliable, authenticated and secured with the help of cryptography. The biggest advantage of the distributed ledger of blockchain is reduced operating costs. Blockchain is already being used by companies like IBM, Barclays, and Kodak etc. Blockchain can contain details of transactions for resources other than money such as land, automobiles, agricultural products etc. Any adjustment must be accepted by most people in the network, and this is achieved using Consensus algorithms. This paper discusses some of the core algorithms for consensus used in blockchain systems.
LibGuides: Research Data Management: Research Data Management Repositories (other than our RU Figshare Research Data)

A guide to define and explore Research Data Management A list of some of the most popular Research Data management repositories
Morphological annotation of social media corpora with reference to its reliability for linguistic research

This paper presents the results of the study devoted to the applicability of SOTA methods for morphological corpus annotation (based on GramEval2020) for analytical sociolinguistic research.The study shows that statistically successful technologies of morphosyntactic annotation for such purposes create a number of problems for researchers if they are used purely i.e. without any linguistic knowledge.In this paper, methods for improving the morphological annotation, successfully implemented in GICR, from the point of view of its reliability are presented.
Implementasi Arsitektur Hierarchical Model View Controller (HMVC) Dalam Portal Akademik

Rapid development in information technology directly impact on the education system in Indonesia, including on technology and vocational education. Computerized process used at every level of the education system makes information technology as an integral part of the education system in various countries, including Indonesia. SMKN 1 Padang as one of a big educational institutions and vocational technology in the city of Padang. However, the utilization of information technology in SMK 1 Padang is still very minimal. Data management process and learning activities are still carried out manually. With the large number of membership programs and number of students, this wayof process less efficient considering the chance of the possibility of error, either in the form of data inconsistencies as a result of the mistake input process value by teachers as well as the possibility of errors in data processing of other student's academic. Coupled with the length of time required to process the data and the number of resources required. Hence the need for a system that manages all the data management process in SMK 1 Padang. In terms of the development and management of the system, often found difficulty in developing the system further. One effort that can be done is to design and implement a system of academic portal as a means of academic activities management at SMK 1 Padang. Academic Portal was designed and developed based on architecture HMVC using the programming language PHP and MySQL database, with CodeIgniter framework, bootstrap framework, javascript, ajax, HTML5 and CSS3. Implementation of HMVC architecture in academic portal at SMK 1 Padang is one of solution to the problem of data management academic at SMK 1 Padang. The system was designed and developed the portal is expected to support process optimization performance of academic services at SMKN 1 Padang. HMVC architecture implemented in the portal system for further development of the portal system.
Textual computer-mediated communication tools used across cultures : A study about the issues and consequences that arise from this type of communication

Globalisation is increasing, reason for people working more and more cross-culturally and with the use of computer-mediated tools. The field of research on both of these individual topics is existe ...
Extended Version of Reactive Task Allocation and Planning of A Heterogeneous Multi-Robot System

This paper takes the first step towards a reactive, hierarchical multi-robot task allocation and planning framework given a global Linear Temporal Logic specification. In our scenario, legged and wheeled robots collaborate in a heterogeneous team to accomplish a variety of navigation and delivery tasks. However, all robots are susceptible to different types of disturbances including locomotion failures, human interventions, and obstructions from the environment. To address these disturbances, we propose task-level local and global reallocation strategies to efficiently generate updated action-state sequences online while guaranteeing the completion of the original task. In addition, these task reallocation approaches eliminate reconstructing the entire plan or resynthesizing a new task. Lastly, a Behavior Tree execution layer monitors different types of disturbances and employs the reallocation methods to make corresponding recovery strategies. To evaluate this planning framework, dynamic simulations are conducted in a realistic hospital environment with a heterogeneous robot team consisting of quadrupeds and wheeled robots for delivery tasks.
Online respondent-driven detection for enhanced contact tracing of COVID-19

Abstract Background Contact tracing (CT) is a core intervention in the global COVID-19 response, but it is a laborious task for the public health professionals (PHPs) who execute CT. In many countries, the workload associated with CT of COVID-19 exceeded available resources for CT. Online respondent-driven detection (RDD) is an innovative method for case finding that can enhance CT efficiency, through active involvement of index cases and contacts in the execution of CT. This can accelerate CT and decrease PHPs' workload. However, it is unclear if and why (not) PHPs want to apply RDD for CT of COVID-19 and what they need to this purpose. Methods This mixed methods study is undertaken in the Netherlands and Germany. We developed an interview guide based on the ‘reasoned action approach' to elicit factors that influence PHPs' intention to apply RDD for CT of COVID-19 and their needs. We conducted 17 semi-structured interviews with Dutch PHPs - and will conduct 6-10 interviews with German PHPs involved in CT of COVID-19. Based on the interviews, an online questionnaire is developed to validate the qualitative findings in a larger population of PHPs. Preliminary results Dutch PHPs believe that RDD facilitates autonomous participation of index cases and contacts and, conversely, less control of PHPs in CT. PHPs anticipated that this could impact the quality and efficiency of CT, and the delivery of - and compliance with - control measures. Several factors, e.g. the available CT-capacity and the anticipated skills and willingness of index cases and contacts to participate in RDD, influenced PHPs' intention to apply RDD for CT of COVID-19. PHPs expressed a need to retain opportunities to support and guide index cases and contacts in CT and to maintain oversight over the CT-process. Conclusions RDD can support PHPs and enhance CT during the ongoing COVID-19 pandemic and future large scale outbreaks of infectious diseases. In order to be properly applied, PHPs' needs should be addressed.
Gait stage classification of children with Duchenne muscular dystrophy

It is well known that the circular flow number of a bridgeless cubic graph can be computed in terms of certain partitions of its vertex set with prescribed properties. In the present paper, we first study some of these properties that turn out to be useful in order to make an efficient and practical implementation of an algorithm for the computation of the circular flow number of a bridgeless cubic graph. Using this procedure, we determine the circular flow number of all snarks on up to 36 vertices as well as the circular flow number of various famous snarks. After that, as combination of the use of this algorithm with new theoretical results, we present an infinite family of snarks of order 8k+2 whose circular flow numbers meet a general lower bound presented by Lukot’ka and Škoviera in 2008. In particular this answers a question proposed in their paper. Moreover, we improve the best known upper bound for the circular flow number of Goldberg snarks and we conjecture that this new upper bound is optimal.
IMPLEMENTING READING TO LEARN (R2L) TO SCAFFOLD THE TEACHING OF WRITING ANALYTICAL EXPOSITION TEXT FOR DISADVANTAGED STUDENTS

One of the mandated basic competencies for vocational high school is to write analytical exposition text. It has been observed that many students with disadvantaged background have difficulties in coping with the competencies due to limited access to linguistic and academic resources. These disadvantaged students are less prepared to write academically valued texts. Rapid growth of research about Reading to Learn and scaffolding in international contexts show promising results that this approach could accelerate disadvantaged students’ literacy development. This study is aimed at figuring out how the implementation of R2L can scaffold the mandated basic competencies for disadvantaged students and how they improve students’ writing competency. The data were gained from six focal students at a vocational high school through qualitative case study design. The analysis shows that Reading to Learn in the context of this study shows its affordability in scaffolding the teaching of writing analytical exposition text on macro and micro skills and improved students competency depicted from the 14 R2L’s descriptors. The analysis shows some challenges and opportunities for future research direction in Indonesian contexts.;Salah satu kompetensi dasar yang diamanatkan untuk sekolah menengah kejuruan adalah untuk menulis teks eksposisi analitis. Berdasarkan hasil pengamatan, banyak siswa dengan latar belakang yang kurang beruntung memiliki kesulitan untuk mencapai kompetensi yang ada karena terbatasnya akses terhadap literatur akademik dan kebahasaan. Siswa yang kurang beruntung ini kurang siap untuk menulis teks akademis. Penelitian tentang Reading to Learn dan scaffolding dalam konteks internasional menunjukkan hasil yang menjanjikan bahwa pendekatan ini dapat mempercepat perkembangan literasi siswa yang kurang beruntung ini. Penelitian ini bertujuan untuk mengetahui bagaimana implementasi R2L dapat membantu pengajaran kompetensi dasar yang diamanatkan ini, terutama bagi para siswa yang kurang beruntung dan bagaimana pendekatan ini dapat meningkatkan kompetensi menulis siswa. Data diperoleh dari enam siswa fokus di sekolah menengah kejuruan melalui desain penelitian kualitatif khusunya studi kasus. Hasil analisis menunjukkan bahwa R2L dalam konteks penelitian ini mampu membantu pengajaran menulis teks eksposisi analitis pada keterampilan makro dan mikro dan menigkatkan kompetensi siswa yang digambarkan melalui 14 deskriptor dari R2L. Analisis dalam penelitian ini menunjukkan beberapa tantangan dan peluang untuk arah penelitian di masa yang akan datang terutama dalam konteks Indonesia.
Guides: Faculty and Staff Library Resources and Services: About the Learning Commons

This guide gathers resources to assist faculty and staff in using Western's library tools, resources, and services.
Research on the Present Situation and Development Characteristics of Missile Penetration Technology

From the traditional perspective, the conventional penetration technology of ballistic missile mainly includes anti identification, anti-interception and system penetration technology.With the development of missile defense system and information technology, the traditional penetration technology is based on digitization, automation and networking, and gradually enters the intelligent level.This paper mainly analyzes the current situation of military ballistic missile penetration technology, analyzes the multi warhead group intelligent penetration technology, intelligent mobility and intelligent stealth materials, and discusses the development direction of intelligent penetration technology of ballistic missile in the future.
Pengembangan Sistem Pelaporan Data Hasil Inspeksi Barang Berbasis Web

The purpose of this study is to describe the application and manage data of the system of reporting for goods in PT. Amindoway Jaya web-based. With descriptive qualitative methods, it allows product results that have a high level of checking and reduce errors. Then check the products from beginning to end and have their own SOP for products that are defective or damaged and cannot be used anymore. The results of a good analysis show that the company has undergone good quality control well, but the quality control reporting process and the search for defect reports take a long time because they have to recap one by one the less systematic checking forms. To overcome this problem, it is necessary to develop an information system for quality control and defect reports. Descriptive qualitative method to analize data and Unified Modelling Language (UML) to analize the design of the system to be developed. With the system design that will be developed, it is hoped that it can overcome the problems faced by PT Amindoway Jaya related to monitoring quality control reports and defective products
Grafiskt användargränssnitt i spel : Hur grafisk design kan gestalta ett spel om spelskapande

This Bachelor Thesis explored the potentials with graphic user interfaces through the methods participatory design, usability and pluralistic usability walkthrough in order to create a graphic user ...
Scalable Components: The Heart of the Quantum Industry

Kelvin Nanotechnology is an internationally recognised provider of advanced photonics and quantum components. Founded in 1997 and based in Glasgow, Scotland; Kelvin Nanotechnology has built up an extensive global blue-chip customer base and provided services in over 20 countries worldwide. Proud to be one of the first suppliers of miniaturised quantum components in the market, Kelvin Nanotechnology drives forward innovation in the fabrication of quantum components to support quantum systems for information processing and computing, chip scale cold atom systems, sensors, and high precision timing and navigation.
Pemanfaatan Media Filter Kearifan Lokal dalam Meningkatkan Kualitas Air dengan Proses Filtrasi

The need for clean water continues to increase with changing times and the passage of time, however, clean water that is suitable for consumption is not easily available in some areas, considering that the physical conditions of regional geomorphology and hydrology have different forms. Water that is suitable for drinking must be clean and minimal from pollutant loads and substances that can interfere with the health of the body, this is different from the water obtained by people in Rantau Karya Village, Geragai District, Tanjung Jabung Timur Regency, because the hydrological conditions of the area are dominated by peatlands so that the water consumed is included in peat water, where the majority of the people use dug well water, therefore a simple technology is needed in dug well water treatment by utilizing local wisdom filter media. The results showed the efficiency of removal of organic substances (KMnO4) where the initial parameter was 22.5 mg / l to be 11.218 mg / l. The efficiency of turbidity reduction is 56%, where the initial result of the turbidity parameter is 31 NTU and the final result is 15 NTU, and the final pH of well water is 6.26, where the initial test shows the number 5.6. Each thickness of the filter media to get optimum results with a thickness of 15 cm.
Research on the Dissemination Characteristics of Public Opinion on Weibo in COVID-19: Based on Emotional Analysis and Social Network

With the rapid spread of COVID-19, how to deal with the public opinion caused by COVID-19 epidemic situation and correctly guide public emotion has become an urgent problem to be solved. This paper collects more than 90 000 Weibo and more than 600000 Weibo comments from January 1 to February 29, 2020. Through web crawler technology, social network analysis, SnowNLP emotion analysis and text clustering, this paper analyzes the public opinion related topics of COVID-19, shows the evolution of public opinion in time, and finds that the change of Weibo emotion in this period is roughly divided into four stages. That is, the initial panic and anxiety about the unknown virus, the temporary relaxation after official clarification, the emotional ups and downs during the worst period of the epidemic and finally the confident and stable period of fighting the epidemic, at the same time, the emotional changes of key users will affect the overall emotional changes in the same direction during this period.
Noise-Augmented Privacy-Preserving Empirical Risk Minimization with Dual-Purpose Regularizer and Privacy Budget Retrieval and Recycling

We propose Noise-Augmented Privacy-Preserving Empirical Risk Minimization (NAPP-ERM) that solves ERM with differential privacy (DP) guarantees. Existing privacy-preserving ERM approaches may be subject to over-regularization with the employment of a $$l_2$$ term to achieve strong convexity on top of the target regularization. NAPP-ERM improves over the current approaches and mitigates over-regularization by iteratively realizing the target regularization through appropriately designed noisy augmented data and delivering strong convexity via a single adaptively weighted dual-purpose $$l_2$$ regularizer. When the target regularization is for variable selection, we propose a new regularizer that achieves privacy and sparsity guarantees simultaneously. Finally, we propose a strategy to retrieve the privacy budget when the strong convexity requirement is met, which can be returned to users such that DP is guaranteed at a lower privacy cost than originally planned, or be recycled to the ERM optimization procedure to reduce the magnitude of injected DP noise and improve the utility of DP-ERM. From an implementation perspective, NAPP-ERM can be achieved by optimizing a non-perturbed object function given noise-augmented data and can thus leverage existing tools for non-private ERM optimization. We illustrate through extensive experiments the mitigation effect of the over-regularization and private budget retrieval by NAPP-ERM on variable selection and outcome prediction.
Multiclass Colorectal Texture Classification Using Ensemble of Pre-trained Networks

An algorithm for the classification of colorectal textures is presented in this work. Histopathological image classification is useful in identifying cancer in the breast, colon and other organs. If data is sufficiently available, classification with deep learning approaches is easy. Most of the histopathological image classification algorithms fall under texture classification. In this work, an ensemble of selected pre-trained networks is used for classifying the multiclass colorectal texture. Features are extracted from the pre-trained networks and are given to an ECOC classifier with SVM as a base learner. Average classification accuracies of various pre-trained networks are computed initially. The best three networks are chosen for model ensembling. Most of the pre-trained models are trained on ‘imagenet’ dataset. However, in order to maintain diversity in the models, one model is chosen from ‘efficientnet’ category, one model is selected from ‘resnet’ category and the other model is chosen from ‘resnet’ but trained on ‘imagenet11k’ dataset. It is demonstrated that by appropriately choosing the individual pre-trained networks, and with ensemble prediction, it is possible to get significant improvement in the classification accuracies. The proposed approach is justified by considering Kather’s multiclass colorectal dataset and Warwick-QU dataset. The proposed algorithm is compared with the state-of-the-art approaches and the superiority of the proposed method is demonstrated.