Reviewerly/exHarmony huggingface dataset:
Reservoir Transformers

We demonstrate that transformers obtain impressive performance even when some of the layers are randomly initialized and never updated. Inspired by old and well-established ideas in machine learning, we explore a variety of non-linear "reservoir" layers interspersed with regular transformer layers, and show improvements in wall-clock compute time until convergence, as well as overall performance, on various machine translation and (masked) language modelling tasks.
APLIKASI SISTEM INFORMASI PELAYANAN PUSKESMAS BERBASIS ANDROID

Online Health Services at this time have become a mass phenomenon in all segments of society. The health service application is not always about consulting a doctor but also about ordering a room or buying medicine, the Puskesmas service sees that it is difficult to maintain health during a pandemic or to avoid spreading the virus. The manual system causes the work obtained to be deemed less fulfilling because the entire process depends on human resource factors, which means that the percentage of errors in the human resource segment is quite high and is detrimental to the Puskesmas manager. The method used is the System Development Life Cycle (SDLC), starting from the planning, analysis, application design, and system implementation phases and producing computerized and integrated cellular applications that will immediately generate data and bookkeeping reports which are of course needed by the health center so that services Puskesmas can be more controlled and more faster.
특허 소송에서 빅데이터 분석의 활용

In Korea, a plan to reduce the gap between big data analytics technology and IP services or legal services that can be used in patent litigation was proposed. In IP services, domestic companies are inferior in terms of data volume and quality compared to foreign companies, so domestic companies that provide IP services need to enhance information processing technology for data to secure competitiveness. In addition, it is necessary to enhance the utilization of research results by providing a platform to disclose algorithms and data in an open-source manner that can utilize various research on patent big data analytics techniques. In order to increase the utilization of IP services, objectivity and transparency in data and algorithms will need to be secured. In legal services, industrial investment and infrastructure expansion to foster the legal tech industry must be initiated in order to advance the legal industry and discover new growth engines. In addition, it is necessary to establish a database that researchers can easily access for judgments that have been de-identified at an appropriate level. Considering that unlike the Anglo-American law, Korea does not have a Discovery system and basically adopts written law, it is necessary to focus on what is needed for the Korean system, such as public services to search for retrieving judgments. Under the current Lawyer Act, non-lawyers are prohibited from using big data analytics technology to deal with legal affairs with clients for a fee. However, considering that the ultimate purpose of Article 109 (1) of the Attorney-At-Law Act is to protect the general public, it is necessary to allow individuals or companies other than lawyers use big data analytics technology to provide legal services on the premise that at least transparency of algorithms and objectivity of data are secured. In addition the same needs to be considered for regulation under the Patent Attorneys Act.
A Categorisation of Post-hoc Explanations for Predictive Models

The 2019 Association for the Advancement of Artificial Intelligence (AAAI) Spring Symposia on Combining Machine Learning with Knowledge Engineering (AAAI-MAKE 2019), Palo Alto, California, 25-27 March 2019
IsiSPL: Toward an Automated Reactive Approach to build Software Product Lines

Over the past decades, Software Product Lines (SPLs) have demonstrated the benefits of systematic reuse to increase software development productivity and software product quality. Of the three adoption approaches, i.e. extractive, proactive and reactive, the reactive approach seems the most suitable for software development in practice. The strength of this approach is that it remains close to classical software development practices. In fact, it avoids a complete analysis of the business domain and its variability (i.e. proactive approach), and avoids requiring a set of product variants that covers this domain (i.e. extractive approach). Nevertheless, despite these advantages, we believe that the main obstacle of the reactive approach adoption is the lack of automation of its re-engineering process. This paper proposes isiSPL: a reactive-based approach that facilitates both construction and maintenance of an SPL. The construction of the SPL is based on a quasi-automatic process. The maintenance of the SPL can be made on a white-box SPL implementation, generated by isiSPL. isiSPL is based on two steps: first, the identification and integration of the artefacts of a newly created product into the structure of the SPL; second, the selection of a set of artefacts and their composition to generate a new product that can either partially or completely meet the requirements provided for a product intended by a developer. We have implemented isiSPL and validated its integration and generation using the two different sets of products from ArgoUML-SPL and Soduko-SPL.
Analisis kerusakan pada pipeline Circulating Water Booster Pump terhadap air laut

There are several problems of damage that’s often occur in PLTU Banten 3 Lontar, one of wich is the problem of the Circulating Water Booster Pump. The purpose of testing and analysis in this study is to determine the cause and mechanisms of damage to the pipeline Circulating Water Booster Pump, the test method in this study uses the visual method, metallography test, hardnest test, SEM-EDS test and XRD test. In the SEM test results there are elements of oxygen (O) and chloride (CI), in the XRD test there is a content of carbonic acid (CO3) wich is formed by presence of carbon dioxide (CO2) gas dissolved in seawater, carbon dioxide gas is produced by the large number of marine life. After the research and testing was carried out, it was found that main cause of damage to the pipeline of the Circulating Water Booster Pump was the result of the presence of oxygen and chloride in seawater wich triggered corrosion of the pipes, aws well as the presence of carbon dioxide gas dissolved in seawater so that it became an element of carbonic acid. Wich will increase the level of seawater corrosivity to the pipe surface
Communication in the Digital World: An Evaluation of Orthography of WhatsApp Messaging

Life has been changed due to the proliferation of social media. Social media influences our modes of life because everything is now dependent to the internet-based technology and stepped up in the digital world. This digital world has filled the gaps among peoples across the borders. Communication among people has taken the new form in the digital world. Language of communication has been influenced greatly and still continued. Due to the contact with people belonged to different linguistic backgrounds, variations in language of communication are taking place at different levels. These variations make language of digital communication more different and unique due to some specifications.This research will explore the categorical specifications of computer-mediated communicationat the world level of English language. WhatsApp (a social media application) is selected to take the sample of messages for investigation.As a qualitative study, use of abbreviations,shortening of words, numerical expressions, under change in orthographywill beanalyzed in this study. Under quantification, frequency of each mentioned features will be calculated to see the recurrence and on the other hand,mean values will enable us tosee the comparison of variables of study.These quantifications will be done through SPSS software. This research will contribute towards the repertoire of digital communication and support the existing studies by providing different contextual diversity of data. Moreover, it will open different avenues of research in this regard under the parasol of internet-based communication on social media.
Classification of Consumer Belief Statements From Social Media.

Social media offer plenty of information to perform market research in order to meet the requirements of customers. One way how this research is conducted is that a domain expert gathers and categorizes user-generated content into a complex and fine-grained class structure. In many of such cases, little data meets complex annotations. It is not yet fully understood how this can be leveraged successfully for classification. We examine the classification accuracy of expert labels when used with a) many fine-grained classes and b) few abstract classes. For scenario b) we compare abstract class labels given by the domain expert as baseline and by automatic hierarchical clustering. We compare this to another baseline where the entire class structure is given by a completely unsupervised clustering approach. By doing so, this work can serve as an example of how complex expert annotations are potentially beneficial and can be utilized in the most optimal way for opinion mining in highly specific domains. By exploring across a range of techniques and experiments, we find that automated class abstraction approaches in particular the unsupervised approach performs remarkably well against domain expert baseline on text classification tasks. This has the potential to inspire opinion mining applications in order to support market researchers in practice and to inspire fine-grained automated content analysis on a large scale.
GuidedMix-Net: Learning to Improve Pseudo Masks Using Labeled Images as Reference

Semi-supervised learning is a challenging problem which aims to construct a model by learning from a limited number of labeled examples. Numerous methods have been proposed to tackle this problem, with most focusing on utilizing the predictions of unlabeled instances consistency alone to regularize networks. However, treating labeled and unlabeled data separately often leads to the discarding of mass prior knowledge learned from the labeled examples, and failure to mine the feature interaction between the labeled and unlabeled image pairs. In this paper, we propose a novel method for semi-supervised semantic segmentation named GuidedMix-Net, by leveraging labeled information to guide the learning of unlabeled instances. Specifically, we first introduce a feature alignment objective between labeled and unlabeled data to capture potentially similar image pairs and then generate mixed inputs from them. The proposed mutual information transfer (MITrans), based on the cluster assumption, is shown to be a powerful knowledge module for further progressive refining features of unlabeled data in the mixed data space. To take advantage of the labeled examples and guide unlabeled data learning, we further propose a mask generation module to generate high-quality pseudo masks for the unlabeled data. Along with supervised learning for labeled data, the prediction of unlabeled data is jointly learned with the generated pseudo masks from the mixed data. Extensive experiments on PASCAL VOC 2012, PASCAL-Context and Cityscapes demonstrate the effectiveness of our GuidedMix-Net, which achieves competitive segmentation accuracy and significantly improves the mIoU by +7$\%$ compared to previous state-of-the-art approaches.
Various Approaches Proposed for Eliminating Duplicate Data in a System

The growth of big data processing market led to an increase in the overload of computation data centers, change of methods used in storing the data, communication between the computing units and computational time needed to process or edit the data.Methods of distributed or parallel data processing brought new problems related to computations with data which need to be examined.Unlike the conventional cloud services, a tight connection between the data and the computations is one of the main characteristics of the big data services.The computational tasks can be done only if relevant data are available.Three factors, which influence the speed and efficiency of data processing are -data duplicity, data integrity and data security.We are motivated to study the problems related to the growing time needed for data processing by optimizing these three factors in geographically distributed data centers.
영어 3음절 이상 다음절어의 철자에 근거한 강세패턴 분석

The purpose of this paper is to provide formal stress patterns of basic English words, which have more than three syllables, for Korean learners’ understanding of English rhythm. The basic assumption for this paper is that it might be effective for Korean learners of English to comprehend the English stress patterns of frequently used English words. Under this assumption, 495 English polysyllabic words (having more than three syllables) are chosen as the data of this paper from the list of basic vocabulary in the 7th English curriculum for Korean primary and secondary education. Those English polysllabic words are analyzed using mainly four basic spelling-based stress rules by Hahn and Dickerson (1999). Based on the evidence in this paper, it is assumed that a systematic exposure to spelling-based stress patterns will not only provide Korean learners of English with pronunciation learning practices that allow them to improve their production of English polysyllabic words, but also help them teach themselves on their own pace.
Construction of digital twins based on knowledge bases for analyzing the functioning of spacecraft onboard systems

The article presents an approach to the construction of digital twins, combining industry knowledge bases, software-mathematical models of technical systems and data tests. The constructed digital twins are used to simulate and analyze the technical characteristics and methods of operation of the spacecraft onboard systems.
Development of Image Shredder Tool

Image media distortion is a process in which media is damaged so that it cannot be viewed any longer. The tool distorts the image by overwriting metadata header. Even with a single overwritten data, the image will be damaged. Consequently, a tool that allows making corrupted images restorable even after being deleted in Recycle Bin is important to be developed because there are numerous risks that people might face if personal photos are leaked to the wrong hand. Thus, the objective of this paper is to develop a tool for shredding several types of image media. PADI model involves four phases including Planning, Analysis, Development, and Implementation in developing the tool. As a result, all image file types that have been chosen can be shredded using the Image Shredder Tool. Some of the file types can be viewed by Image Shredder Tool and can be shredded using Image Shredder Tool. The file types are BMP, GIF, JPEG, PNG and TIFF.
Project Turkey V2.0 [1.38]

The project includes Turkey YKSRSK and road connections Changelog fixed falling through the map next to Edirne the name is the same but in mod ...
The Influence Of Using Word Wall towards Students' Vocabulary Mastery At UPTD SMP N 2 Tanjung Tiram Academic Year 2020/2021

The objective of the research is to find out whether there is significant influence ofusing Word Wall towards Students‟ Vocabulary Mastery of the seventh grade inUPTD SMP N 2 Tanjung Tiram. The methodology of the research was quantitativeresearch especially a quasi-experimental research. This research population is astudent of UPTD SMP N 2 Tanjung Tiram. This research was conducted with twogroups, namely experimental group (36 students) and control group (36 students).Then the researcher taught in the experimental class using Word Wall Media and inthe control class using Crossword Puzzle Media. After treatment, the researchers gavepost-test for both classes. The pre-test and post-test scores were collected from twentyThen the questions were analyzed using SPSS V 20. The results showed that teachingvocabulary using the Media Word Wall is effective. It proved with the t value (5,766)which is higher than the t table at the 5% significance level (2,030). Furthermore,testing the hypothesis shows that sig 2 tailed (p) is 0,000 while alpha (α) 0.05 (0.000<0.05) means that Ha (Hypothesis Null) is rejected and Hα (Alternative Hypothesis)is accepted. In other words, use Word Wall Media at Vocabulary teaching has asignificant effect on students' vocabulary mastery.
IT Support Challenges in Efforts to Increase Effectiveness and Efficiency in Manufacturing Companies

Information technology has changed the perspective of business actors, both small and large scale businesses. Most business actors have used information technology for various things, from making PO, receiving goods, planning production, production processes, sending finished goods to customers, making invoices, tax invoices and others. To support optimal computerization, adequate infrastructure is needed, starting from hardware / software, computer networks, telecommunications networks and others. Information technology infrastructure must be properly maintained and maintained so as not to experience interference during use. One part that plays an important role in maintaining information technology is IT Support. IT Support is under the IT department and is responsible for the smooth running of all devices, both hardware and software. It is undeniable that information technology is developing rapidly and this is a challenge for an IT Support. Therefore, IT Support must have technical and non-technical capabilities in order to keep up with the constantly evolving technology so that it can work effectively and efficiently. IT Support skills need to be improved starting from hardware / software maintenance, computer network installation and trouble shooting, server and client computer installation, internet / cyber security, preventive and predictive maintenance, CCTV maintenance, hardware service / repair, ISO knowledge, graphic design and maintenance PABX.
A design theory for holistic student self-service university management system

The role of Information System Design Theory in software development is enormous. With the help of design theory, developers could estimate what the system will be and what the system will do. The focus of the article is to establish the design theory of a self-service university management system. The objectives of this publication are to identify the most relevant publication that will act as a guideline to generate the design theory artefacts and to establish the artefacts which will consists of three components named kernel theories, meta-requirements and meta-design for the stated system. The system scope will be focused on enabling self-service functions. Validation will be done through a traceability matrix between the meta-requirement and meta-design against the real-world user requirement. The significant of this article is to provide an initial set of design theory artefacts to be utilization software developer in development or evaluation of a University Management System.
An Experimental Comparison of the Geometry of Models Trained on Natural Language and Synthetic Data

Deep learning models have been used successfully to solve many Natural Language Processing problems, but less is known about the mechanisms that make them work.Unlike simpler models that can be understood mathematically, experimental comparisons and probing tasks are being used on deep neural net model attributes to try and determine how the syntactic and semantic information is being represented.In this work, we focus on models that produce contextual word vectors and sentence vectors.To determine how the information in these embeddings is being represented, we use a class of feed-forward neural networks to design a set of experiments that are run on the normal downstream tasks of two common Natural Language Inference benchmarks and one Sentiment Analysis benchmark, together with the classification tasks of a set of synthetic datasets that we have created.A quantitative analysis of these experiments shows that the behaviour of the models trained on the natural language benchmark data match those of the synthetic data in many cases.We suggest that this similar behaviour implies that the decomposition of semantic and syntactic data in the models trained on the language data are similar to the known structures of the synthetic data.
Learning Multimodal VAEs through Mutual Supervision

Multimodal VAEs seek to model the joint distribution over heterogeneous data (e.g.\ vision, language), whilst also capturing a shared representation across such modalities. Prior work has typically combined information from the modalities by reconciling idiosyncratic representations directly in the recognition model through explicit products, mixtures, or other such factorisations. Here we introduce a novel alternative, the MEME, that avoids such explicit combinations by repurposing semi-supervised VAEs to combine information between modalities implicitly through mutual supervision. This formulation naturally allows learning from partially-observed data where some modalities can be entirely missing -- something that most existing approaches either cannot handle, or do so to a limited extent. We demonstrate that MEME outperforms baselines on standard metrics across both partial and complete observation schemes on the MNIST-SVHN (image-image) and CUB (image-text) datasets. We also contrast the quality of the representations learnt by mutual supervision against standard approaches and observe interesting trends in its ability to capture relatedness between data.
국내 중소기업의 스마트공장 구축을 위한 조직역량과 조직성과에 관한 연구

Recently, smart manufacturing innovation is practically increasing due to the adoption of new ICT application in 4th industrial revolution era. Small and medium enterprises (SMEs) in Korea is facing the limit of the growth in traditional manufacturing industry. Most researches related to smart factory have conducted as a conceptual and descriptive study. Because of data collection and information security of the company to adopt smart factory, there is not so many empirical study. To find out the approaches to implement smart factory project, more case studies are required. Thus, in this study, to solve the problem from the limit of previous studies, this study try to conduct two approaches. One is case study on smart factory implementation of SMEs in Korea. The other is an empirical study to identify the relationship between management strategy, smart factory, and organizational performance.
Mudflaps For Own Trailers V3.0

This mod adds 29 types of mudflaps for your own trailers to the game store. Support for all your own trailers: standard SCS trailers and Krone Trailer ...
Why Justification Logic?

A summary is not available for this content so a preview has been provided. Please use the Get access link above for information on how to access this content.
Review Classification Approach for User Sentiment Analysis

Sentiment analysis or opinion mining is one of the fastest growing fields with its demand and benefits that is increasing day by day. With the availability of the internet and modern technology, there has been a tremendous growth in the amount of data. The text that has been posted by people to express their sentiment on social media ,can be analysed and used in order to draw benefits and quality information. In this paper, the focus is on cyber-hate classification based on for public opinion or views, since the spread of hate speech using social media can have disruptive impacts on social sentiment analysis. In particular, here proposing a modified fuzzy approach with two stage training for dealing with text ambiguity and classifying three type approach positive, negative and neutral sentiment, and compare its performance with those popular methods as well as some existing fuzzy approaches.