Reviewerly/exHarmony huggingface dataset:
Augmented Reality Dalam Mendeteksi Produk Rotan Menggunakan Metode Multimedia Development Life Cycle (MDLC)

The furniture business has developed quite well every year, but the promotions used by the company still use the usual methods, such as using brochures that only display 2D information and images. With so much competition, consumers want something unique and different so they can find out more detailed and real product information offered. Augmented reality is the right technology to meet these consumer needs. Augmented reality is a technology that combines the virtual world with the real world directly. Therefore, an application was designed that functions as a company profile as well as displays 3D rattan chair products using Augmented reality technology on android devices. The method used in this research is the Multimedia Development Life Cycle (MDLC) which includes Concept, Design, Material Collecting, Assembly, Testing, and Distribution. This Augmented reality application requires streaming video taken from a smartphone camera as an input source, then this application will track and detect markers using a tracking system, after the marker is detected, the 3D chair model in the catalog will appear above the marker as if it were a chair model. it's real. the results of the hypothesis test with a significant level of 0.139, which is greater than 0.05, then what is accepted is H1. It can be stated that an augmented reality-based electronic catalog application can increase buying interest in potential consumers of Raffi cushion rotan
Discourse Comprehension: A Question Answering Framework to Represent Sentence Connections

While there has been substantial progress in text comprehension through simple factoid question answering, more holistic comprehension of a discourse still presents a major challenge (Dunietz et al., 2020).Someone critically reflecting on a text as they read it will pose curiosity-driven, often open-ended questions, which reflect deep understanding of the content and require complex reasoning to answer (Ko et al., 2020;Westera et al., 2020).A key challenge in building and evaluating models for this type of discourse comprehension is the lack of annotated data, especially since collecting answers to such questions requires high cognitive load for annotators.This paper presents a novel paradigm that enables scalable data collection targeting the comprehension of news documents, viewing these questions through the lens of discourse.The resulting corpus, DCQA (Discourse Comprehension by Question Answering), captures both discourse and semantic links between sentences in the form of free-form, open-ended questions.On an evaluation set that we annotated on questions from Ko et al. (2020), we show that DCQA provides valuable supervision for answering openended questions.We additionally design pretraining methods utilizing existing questionanswering resources, and use synthetic data to accommodate unanswerable questions.
Nested Graph Neural Networks

Graph neural network (GNN)'s success in graph classification is closely related to the Weisfeiler-Lehman (1-WL) algorithm. By iteratively aggregating neighboring node features to a center node, both 1-WL and GNN obtain a node representation that encodes a rooted subtree around the center node. These rooted subtree representations are then pooled into a single representation to represent the whole graph. However, rooted subtrees are of limited expressiveness to represent a non-tree graph. To address it, we propose Nested Graph Neural Networks (NGNNs). NGNN represents a graph with rooted subgraphs instead of rooted subtrees, so that two graphs sharing many identical subgraphs (rather than subtrees) tend to have similar representations. The key is to make each node representation encode a subgraph around it more than a subtree. To achieve this, NGNN extracts a local subgraph around each node and applies a base GNN to each subgraph to learn a subgraph representation. The whole-graph representation is then obtained by pooling these subgraph representations. We provide a rigorous theoretical analysis showing that NGNN is strictly more powerful than 1-WL. In particular, we proved that NGNN can discriminate almost all r-regular graphs, where 1-WL always fails. Moreover, unlike other more powerful GNNs, NGNN only introduces a constant-factor higher time complexity than standard GNNs. NGNN is a plug-and-play framework that can be combined with various base GNNs. We test NGNN with different base GNNs on several benchmark datasets. NGNN uniformly improves their performance and shows highly competitive performance on all datasets.
Common Interactive Style Guide for Designers and Developers Across Projects

Advanced user interfaces continue to improve through better design which in turn translates to more effective development and end use. The intent of this work is to provide design guidelines that can be used across all new applications. An interactive prototype toolkit called the User Interface Prototyping Toolkit (UIPT) was developed to allow sponsors, customers, end users, designers, engineers, and software developers to work together in an iterative fashion to achieve a tailored but guided user interface for the application of interest. Modern styles were applied with a consistent and common look and feel while adhering to solid principle of design, workflow, tasks, layout, coloring, size, animation, and user cues. The design required a general repeatable structure for designers and developers with the intent to allow each new project to understand the overall design and incorporate the features and functionality in accordance with style guide principles. UIPT integrates multiple domains within in the same software application with the ability to efficiently transition an end user’s role from one display presentation to another. To date, several projects and user roles have been integrated into the UIPT. In support of this design philosophy an interactive style guide is in continuous development to apply a common reusable design across the multiple projects that utilize the UIPT-based interface. Both the UIPT application and the interactive style guide were built with Unity, a 2D and 3D game engine. Styles for size, color, layout, and other design factors are laid out in the style guide itself which can be run to visualize and examine interactions. This is advantageous for new and experience software developers because the guide itself contains the code and styles necessary to implement the various components of the user interface while supporting design consistency with reusable code for rapid deployment.
CoReS: Compatible Representations via Stationarity

Compatible features enable the direct comparison of old and new learned features allowing to use them interchangeably over time. In visual search systems, this eliminates the need to extract new features from the gallery-set when the representation model is upgraded with novel data. This has a big value in real applications as re-indexing the gallery-set can be computationally expensive when the gallery-set is large, or even infeasible due to privacy or other concerns of the application. In this paper, we propose CoReS, a new training procedure to learn representations that are \textit{compatible} with those previously learned, grounding on the stationarity of the features as provided by fixed classifiers based on polytopes. With this solution, classes are maximally separated in the representation space and maintain their spatial configuration stationary as new classes are added, so that there is no need to learn any mappings between representations nor to impose pairwise training with the previously learned model. We demonstrate that our training procedure largely outperforms the current state of the art and is particularly effective in the case of multiple upgrades of the training-set, which is the typical case in real applications.
Survey on Android Application Advancement and Security

As of late as the mechanical pace has elevated the general working economies of the cellular telephones, the innovation pattern is going towards the most extreme utilization of very solid cell phones. As the cell phone utilization is expanding step by step, individuals are expecting a ton from their cell phones by expanding dependability, security, execution along these lines numerous this sort of characteristics. Therefore, to satisfy the client's prerequisites, one of the pioneers in the business sector of cell phones thinks of the advancement in the innovation and that pioneer is Google Android Operating System. Android Application Development is an evolving area, changing and improving constantly. It has been a concentrate in the examination for the last couple of decades due to its wide potential applications and its essentialness to meet the security needs of the present day's reality. Regardless, the framework is incredibly eccentric and therefore it is tricky to prepare. In this paper, presented an open-source approach for creating an android application with thinking of some as specialized security issues.
Penilaian Alternatif pada Keterampilan Berbicara Bahasa Inggris di Sekolah Menengah Kejuruan Kota Pontianak

English speaking skill is an important communication skill and must be mastered by students to be able to interact actively, convey ideas and provide responses in both formal and informal situations. Alternative assessment provides benefits for students and teachers in improving students' speaking skill in English. This research focuses on an alternative assessment of English speaking skill in Vocational High Schools in Pontianak City, especially South Pontianak. The objectives of this research are (1) to determine problems related to the English speaking skill of vocational school students in South Pontianak, (2) to identify and analyze alternative assessments applied in overcoming the problems of English speaking skill of vocational school students in South Pontianak, and 3) to find a solution to the English speaking skill problems of vocational school students in South Pontianak by using alternative assessments. This research was a qualitative research, and data were collected from interviews with English teachers and documents analysis. Data were collected through interviews with English teachers at SMK in south Pontianak and analysis of related documents. The stages of data analysis include data reduction, display data, and conclusion drawing / verification. The results showed that the problems faced by students related to English speaking skill were limited ability of students caused by several factors, namely grammar, pronunciation, vocabulary and self-confidence. The alternative assessments that were applied include performance - assessment, peer - assessment and portfolio. The solutions taken were to involve students in providing assessments to other students and the teacher focuses on conveying information clearly and conveying the moral values that are learned without focusing too much on grammar. The suggestions that the researchers gave were in the form of matriculation for students in the early year of school, knowledge sharing between teachers, determining priority aspects of speaking that were assessed and implementing self-assessment as an additional form of alternative assessment that could motivate and encourage students to gradually improve their speaking skills in English.
Methodology for determining opportunities in the applica-tion of Microsoft Solutions Framework software testing using neutrosophic numbers

For software development companies, deciding which development methodology to use at the beginning of a project, is in many cases an important task to perform. The selectionof development methodology can be modeled as a decision making problem. This article describes a proposed methodology selection using neutrosophicnumbers from which the development met-hodology proposal is decided.
Building a Real-Time Web App

This chapter promptly introduces you to ostensibly constructing real-time interactive web apps with Python, with a responsive navigation bar, sidebar, charts, tables, callbacks, and URL routing. After referring to the unique contents of this chapter, you should be skilled in developing a functional and responsive dashboard as web apps by implementing key web frameworks centered on HTML and Bootstrap technologies (i.e., Dash, Dash Core Components, Dash HTML Components, and Dash Bootstrap Components), alongside the Plotly interactive charting library. It sufficiently acquaints you with a holistic approach for implementing CSS to customize as a web app. And it includes functionalities like search, including report generation, and download functionality.
Do Language Models Know the Way to Rome

The global geometry of language models is important for a range of applications, but language model probes tend to evaluate rather local relations, for which ground truths are easily obtained. In this paper we exploit the fact that in geography, ground truths are available beyond local relations. In a series of experiments, we evaluate the extent to which language model representations of city and country names are isomorphic to real-world geography, e.g., if you tell a language model where Paris and Berlin are, does it know the way to Rome? We find that language models generally encode limited geographic information, but with larger models performing the best, suggesting that geographic knowledge can be induced from higher-order co-occurrence statistics.
Facial Expression Recognition from Video Sequence Using Self Organizing Feature Map

Automatic analysis of facial expressions is rapidly becoming an area of intense interest in computer vision and artificial intelligence research communities. In this paper an approach is presented for facial expression recognition of the six basic prototype expressions (i.e., joy, surprise, anger, sadness, fear, and disgust) based on Facial Action Coding System (FACS). The approach utilizes the topological ordering patterns produced by Kohonen Self Organizing Map, in which implemented on expression image sequence for each prototype facial expression. The map will compute the topological relationship between the particular expression sequences, starting from the neutral expression to peak. This method tried to find a topological ordering pattern (shape) for each expression; it will not require any pre-processing tedious work such as normalization. The only requirement is that, image background must be kept constant, also with non-rigid head motion. The feature extraction phase had been performed by this method, while the classification phase done by especially designed procedures for shape and direction finding to recognize the pattern of the shape, thereafter the type of the expression also backpropagation neural network is implemented for the classification task. An average recognition rate of 88.7% was achieved for six basic expressions, where different databases had been used for the test of the method.
An Extensive Evaluation of Fuzzy Weak Ku Ideal Algebra

The evolution of the fuzzification of mathematical concepts can be broken down into three stages:1. straightforward fuzzification during the sixties and seventies, 2. the explosion of the possible choices in the generalization process during the eighties, 3.the standardization, axiomatization, and L-fuzzification in the nineties. Usually, a fuzzification of mathematical concepts is based on a generalization of these concepts from characteristic functions to membership functions. Let A and B be two fuzzy subsets of X. The intersection A ∩ B and union A ∪ B are defined as follows: (A ∩ B)(x) = min(A(x), B(x)), (A ∪ B)(x) = max(A(x), B(x)) for all x in X. Instead of min and max one can use t-norm and t-conorm, respectively, for example, min(a, b) can be replaced by multiplication ab. A straightforward fuzzification is usually based on min and max operations because in this case more properties of traditional mathematics can be extended to the fuzzy case. An important generalization principle used in fuzzification of algebraic operations is a closure property. Let * be a binary operation on X. The closure property for a fuzzy subset A of X is that for all x, y in X, A(x*y) ≥ min(A(x), A(y)). Let (G, *) be a group and A a fuzzy subset of G. Then A is a fuzzy subgroup of G if for all x, y in G, A(x*y−1) ≥ min(A(x), A(y−1)). A similar generalization principle is used, for example, for fuzzification of the transitivity property. Let R be a fuzzy relation on X, i.e. R is a fuzzy subset of X × X. Then R is (fuzzy-)transitive if for all x, y, z in X, R(x, z) ≥ min(R(x, y), R(y, z)).
A Single Image Super Resolution using Deep CNN for natural images

In this research work presented a Modified Very Deep Convolutional Networks (MVDCN) for single image super resolution (SISR). The proposed method based on modified CNN, in which apply different image feature for training also apply up-sampling as well as residual Images that is fundamental step of SISR, and dept of network is 20. For the improvement of presented method result apply fusion of two bicubic method attributes with Very Deep Convolutional Networks. The presented method shows better result in terms of two base parameters of proposed method that is PSNR and SSIM. There are different data set available in the for training and testing of presented method such Test data set Datasets ‘Set5’ [15] and ‘Set14’ [26] both are mainly used by different researcher, benchmark in other works data set ‘Urban100’, that’s very interesting as it contains many challenging images failed by many of the existing methods.The proposed method compare with different methods, they are Ground Truth data set image A+, RFL, SelfEx, and VDSR. The proposed and presented method “Modified Very Deep Convolutional Networks (MVDCN) for single image super resolution (SISR)” shows better result as compare to other previous methods.
Development of the Domestic Certification System through the Expansion of the ICQ-MRA Mutual Reciprocity Agreement: Focusing on the Acceleration of WTO/FTA TBT System and US-China Digital Trade

Manufacturing companies whose main purpose is to export are recognizing the importance of utilizing knowledge-based resources as a means to replace their very scarce resources and capabilities and are increasingly emphasizing them. This research studied the contribution and expansion strategies of companies that obtained international certification qualification to trade export performance due to the conclusion of the ICQ-MRA mutual reciprocity agreement. There are a number of AEO-MRA researches in the previous studies that reviewed MRA, but relatively a few researches specifically identified the actual relationship to ICQ international certified exporters through the conclusion of ICQ-MRA. Therefore, this thesis has been researched to present the effects that companies can actually feel from the economic point of view.
On collectively assigning features to artifacts

The common notion of artifacts characterizes them as the products of successful activities of their makers, guided by intentions that such objects would instantiate certain features, such as their specific functions. Many counterexamples, however, reveal the unsuitability of the common notion. In the face of this acknowledgment, the paper explores the possibility that features of artifacts, and more specifically, the possession of their functions, may arise, at least partially, from collective assignments. In order to achieve the mentioned goal, the paper critically examines some notions and theses put forward by John Searle (1996; 2010) and others. Its main result, however, consists in offering and elucidating an original thesis, namely, that the functions of many artifacts would be maintained, partially, by forms of continuous collective intentionality, which can involve conscious or unconscious, active or inactive collective intentional states. Keywords: Artifacts, assignment of function, collective intentionality, maintenance of function.
Analysis of Similar Object Classification Performance of Deep Neural Network-Based Object Recognition Technique

In this study, deep neural networks were applied to a similar object classification method, and the classification performance was analyzed. For the similar object classification performance analysis, ResNet50 and DenseNet169 models, which are known to show similar behaviors, were selected. To verify the performance of these deep neural networks, a bolt recognition for smart factories and an armored fighting vehicle recognition were performed. In addition, image preprocessing methods to improve the similar object classification performance were proposed. The experimental results confirmed that appropriate image preprocessing methods should be applied according to the type of similar object to be classified.
Daemons at a Glance

Generally, there are only two main types of daemons: daemons (root) and user agents (user).
KFCNet: Knowledge Filtering and Contrastive Learning Network for Generative Commonsense Reasoning

Pre-trained language models have led to substantial gains over a broad range of natural language processing (NLP) tasks, but have been shown to have limitations for natural language generation tasks with high-quality requirements on the output, such as commonsense generation and ad keyword generation. In this work, we present a novel Knowledge Filtering and Contrastive learning Network (KFCNet) which references external knowledge and achieves better generation performance. Specifically, we propose a BERT-based filter model to remove low-quality candidates, and apply contrastive learning separately to each of the encoder and decoder, within a general encoder–decoder architecture. The encoder contrastive module helps to capture global target semantics during encoding, and the decoder contrastive module enhances the utility of retrieved prototypes while learning general features. Extensive experiments on the CommonGen benchmark show that our model outperforms the previous state of the art by a large margin: +6.6 points (42.5 vs. 35.9) for BLEU-4, +3.7 points (33.3 vs. 29.6) for SPICE, and +1.3 points (18.3 vs. 17.0) for CIDEr. We further verify the effectiveness of the proposed contrastive module on ad keyword generation, and show that our model has potential commercial value.
A Study on the Preliminary Feasibility Study of Information System based on Blockchain Technology Using Fuzzy AHP Technique

초록·키워드 목차 오류제보하기 The government"s standard guidelines of preliminary feasibility study stipulate that the AHP method should be used to finally determine whether to invest in the information sector by synthesizing the 3 evaluation results of economic feasibility, technical feasibility, and policy feasibility. But in the case of early technologies such as blockchain, the answers to technology and policy evaluation items realistically may be vague or unclear and the AHP technique, which forcibly imposes a crispy value, it can only increase bias in the analysis. In this study, we propose a fuzzy AHP technique that allows ambiguous and uncertain values as a new methodology to evaluate the feasibility of introducing an information system based on 4th industrial technology through a preliminary feasibility study. In this study, the evaluation items of the blockchain-based information system were identified, the questionnaire response data were analyzed, and the implementation was determined using the fuzzy AHP technique. As a result of the analysis, economic feasibility is the most important determinant of adoption and total result of the preliminary feasibility study, the implementation of the block chain-based information system construction project was adopted as an appropriate alternative. As a result of analyzing the importance ranking for each item between the AHP technique and the fuzzy AHP technique, there were some differences, showing that the selection of the technique can have a significant effect on the selection. #4th Industrial Technologies #Fuzzy AHP #Blockchain System #Preliminary Feasibility Study AbstractⅠ. 서론Ⅱ. 이론적 배경Ⅲ. 연구방법론Ⅳ. 사례 적용Ⅴ. 결론참고문헌