Reviewerly/exHarmony huggingface dataset:
Discovery of New Words in Tax-related Fields Based on Word Vector Representation

&lt;p&gt;New words detection, as basic research in natural language processing, has gained extensive concern from academic and business communities. When the existing Chinese word segmentation technology is applied in the specific field of tax-related finance, because it cannot correctly identify new words in the field, it will have an impact on subsequent information extraction and entity recognition. Aiming at the current problems in new word discovery, it proposed a new word detection method using statistical features that are based on the inner measurement and branch entropy and then combined with word vector representation. First, perform word segmentation preprocessing on the corpus, calculate the internal cohesion degree of words through statistics of scattered string mutual information, filter out candidate two-tuples, and then filter and expand the two-tuples; next, it locks the boundaries of new words through calculate the branch entropy. Finally, expand the new vocabulary dictionary according to the cosine similarity principle of word vector representation. The unsupervised neologism discovery proposed in this paper allows for automatic growth of the neologism lexicon, experimental results on large-scale corpus verify the effectiveness of this method.&lt;/p&gt; &lt;p&gt;&amp;nbsp;&lt;/p&gt;
Investigating Failure Patterns in Machine Learning-based Object Detection Tasks in Software Development Courses

&lt;p&gt;Object detection, one of the popular tasks in computer vision, is to find all objects of interest in an image and determine their category and location. When people use deep learning frameworks to implement object detection networks, defects are often caused by human-introduced faults. These defects may cause different types of failures. Exploring frequent failure patterns in object detection programs can help developers detect and fix defects more effectively and efficiently. Therefore, we conducted an empirical study on failure patterns in deep learning-based object detection programs submitted in university software development courses. By exploring 101 submissions of a Yolov4 object detection task completed by 104 students, we found the most frequent 13 failure patterns in these submissions and six types of root causes of these failures. To help students and entry-level software engineers avoid possible faults in object detection programs, 13 concrete suggestions that belong to six classes are given in this paper. These results can reveal some basic laws of failures and mistakes in the development of deep learning-based object detection programs and provide guidances to assist students and entry-level developers in improving their skills in developing object detection programs. &lt;/p&gt; &lt;p&gt;&amp;nbsp;&lt;/p&gt;
AN ANALYSIS OF THE USE OF BRITISH ENGLISH AND AMERICAN ENGLISH TOWARD SPEAKING ABILITY IN THE STUDENTS’ TELEGRAM ACCOUNTS OF STKIP PGRI UNIVERSITY OF SIDOARJO

This research examines the use of British and American English in speaking skills on STKIP PGRI Sidoarjo University student accounts. The goal of this study was to examine the vocabulary of British English and American English on the Telegram accounts of STKIP PGRI Sidoarjo University students. This study employs a qualitative approach with descriptive analysis techniques. Purposive sampling from group voice calls used to practice speaking English was used for the sampling technique. The Telegram accounts examined are those of STKIP PGRI Sidoarjo University students. The accounts examined were five STKIP PGRI Sidoarjo student accounts. According to the findings of this study, the researcher examined the differences between British and American English speech accents on students' Telegram. Second, the researcher examines the skills of speaking about grammatical suitability, accent conversation, and sentence context.&#x0D; Keywords: British dan American English; speaking; telegram voice call group
Non-linear Science University Course Building Variant

The non-linearity science is a still hard-boning discipline often unrecognized or denied to exist. That is not wondering due to the literature flow with many ideas in many words but with no formulas at all. Due to the lack of efficient material, one needs to complexly revise the current core of formal models (and formal fact-knowledge) to build a maybe single possible current art state standard course core.
Optimization-Inspired Deep Network for Image Restoration from Partial Random Samples

Image Restoration from Partial Random Samples (RRS) has been studied in many image restoration works. There are also some attempts to use convolutional neural networks (CNNs) to handle it. However, most existing neural network-based methods perform poorly in generalization and we need to train a specific model for each degradation situation. Besides, the sampling mask which represents the positions of the sampled pixels is not used effectively in these methods. To address the problems, we propose an optimization-inspired network called RRSNet based on our derivation of the iterative optimization formulas for RRS. In our method, we design a CNN with two encoders and one decoder for training, setting up a flexible and effective prior. To make the most of the sampling information, we concatenate the degraded image with the mask and input them into one encoder for better generalization. Then we split the pixels into two groups according to the mask and extract their features as the input of another encoder. Experiments demonstrate that our RRSNet with the mask input can handle various sampling ratios using only one trained model and achieve the best restoration performance among all comparison methods.
Current Status of Business Chinese Education and Research : Focusing on Universities in Korea

This study is aimed at investigating the current status of Business Chinese courses offering in China-related Departments among universities and the publication status of Business Chinese textbooks in Korea. The survey results were compared with Bae Jae-seok and Kim Jeong-eun(2011). In addition, the current status of research, including journal articles and dissertations, on Business Chinese was identified. Focusing on the basic status, research method, research subject, and research topic, we analyzed trends of the research. The analysis results are summarized as follows.BR First, more than 72% of China-related departments in domestic universities offer business Chinese-related courses. The opening period is concentrated in the 3rd and 4th grade, generally aimed at intermediate and advanced Chinese learners.BR Second, from 2011 to 2022, the published textbooks co-authored by Korean and Chinese authors tend to increase, while the quantity of translated textbooks decrease. Textbooks that focus on conversational contents are still being published the most, and the textbooks related to expression, reading comprehension, and BCT are gradually decreasing.BR Third, after 2015, scholars are becoming more interested in Business Chinese, and related studies are actively proceeding. Journal articles are mainly based on theoretical research methodology and focus on teaching and learning methods. Dissertations are mainly based on mixed research methodology and focus on the analysis and development of textbooks.
APLIKASI PENGENALAN ANATOMI SISTEM PENCERNAAN PADA TUBUH MANUSIA MENGGUNAKAN TEKNOLOGI AUGMENTED REALITY

Natural Sciences (IPA) is a science related to human endeavors in understanding and finding out about the universe through precise observations and using procedures that can be explained by reasoning so as to get a clear conclusion. There are 5 main branches in Natural Sciences, namely Astronomy, Biology, Chemistry, Earth Sciences, and Physics. Science learning should be able to provide direct experience so as to increase the ability to understand and apply the concepts that have been learned. Anatomy is a branch of biology that deals with the structure of living things, in the anatomy of the human body, there are organs that support the formation of the body as a whole. The organs of the body such as bones, joints, skeletal muscles, brain, digestive system, and circulatory system and other organs. The digestive system is a process of mechanically and chemically breaking food into a form that is easier for the body to absorb. interactively in real time. The existence of technology in the form of Augmented Reality will facilitate the process of introducing information and displaying Anatomy Learning objects. This research aims to introduce anatomy to a digestive system in the human body using Augmented Reality technology which can facilitate students in the learning process. The software development method used to design and implement traditional musical instrument recognition applications is the Rational Unified Process method. Application testing is carried out using black-box testing and user testing. User testing was carried out by distributing questionnaires at SMP Negeri 2 Pedamaran Timur. Testing user satisfaction is calculated using a Likert scale and the results of questionnaire questions which can have a final score of 87% which is included in the strongly agree category
A Neural Architecture Search Method using Auxiliary Evaluation Metric based on ResNet Architecture

This paper proposes a neural architecture search space using ResNet as a framework, with search objectives including parameters for convolution, pooling, fully connected layers, and connectivity of the residual network. In addition to recognition accuracy, this paper uses the loss value on the validation set as a secondary objective for optimization. The experimental results demonstrate that the search space of this paper together with the optimisation approach can find competitive network architectures on the MNIST, Fashion-MNIST and CIFAR100 datasets.
Quality-Diversity Optimization

tutorial Open Access Share on Quality-Diversity Optimization Authors: Antoine Cully Dept of Computing, Imperial College London, London, United Kingdom Dept of Computing, Imperial College London, London, United Kingdom https://orcid.org/0000-0002-3190-7073View Profile , Jean-Baptiste Mouret Inria Nancy - Grand Est, CNRS, Université de Lorraine, Villers-lès-Nancy, France Inria Nancy - Grand Est, CNRS, Université de Lorraine, Villers-lès-Nancy, France https://orcid.org/0000-0002-2513-027XView Profile , Stéphane Doncieux ISIR, Sorbonne University, Paris, France ISIR, Sorbonne University, Paris, France https://orcid.org/0000-0003-1541-054XView Profile Authors Info & Claims GECCO '23 Companion: Proceedings of the Companion Conference on Genetic and Evolutionary ComputationJuly 2023Pages 913–937https://doi.org/10.1145/3583133.3595048Published:24 July 2023Publication History 0citation30DownloadsMetricsTotal Citations0Total Downloads30Last 12 Months30Last 6 weeks21 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteeReaderPDF
生産ラインにおける異常検知・非定常サイクル同定のオンラインシステム

In a factory production line, if abnormal signals can be automatically detected from time-series fluctuations in power consumption, the defect rate of products can be reduced, and productivity can be improved. Individual period estimation is often needed to detect the abnormals because deviations from the mean period provide valuable information about the failures and the abnormals. This study proposes an online system that estimates individual cycles and detects anomalies from quasi-periodic time series data represented by energy consumption data. The proposed system extracts local patterns by convolution and identifies individual cycles and abnormal signals based on similarity vectors calculated by an attention mechanism. Experimental results show that the proposed system outperforms existing methods on several simulated data sets.
CMA-ES and Advanced Adaptation Mechanisms

tutorial Share on CMA-ES and Advanced Adaptation Mechanisms Authors: Youhei Akimoto University of Tsukuba, Tsukuba, Japan University of Tsukuba, Tsukuba, Japan https://orcid.org/0000-0003-2760-8123View Profile , Nikolaus Hansen Inria and Ecole Polytechnique, Palaiseau, France Inria and Ecole Polytechnique, Palaiseau, France https://orcid.org/0000-0001-7788-4906View Profile Authors Info & Claims GECCO '23 Companion: Proceedings of the Companion Conference on Genetic and Evolutionary ComputationJuly 2023Pages 1157–1182https://doi.org/10.1145/3583133.3595054Published:24 July 2023Publication History 0citation24DownloadsMetricsTotal Citations0Total Downloads24Last 12 Months24Last 6 weeks19 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteGet Access
RGB Peg Mirror

In SIGGRAPH 2000 I debuted my piece Wooden Mirror. Over the past 23 years I have been expanding my series of Mechanical Mirrors to include tens of pieces utilizing various materials and techniques to examine the creation and perception of images and computer graphic concepts in a physical, interactive manner. Recently I have introduced color to my Mechanical Mirrors, the piece RGB Peg Mirror is my first piece that reproduces a full color reflection of the viewer by mechanically controlling 1555 motorized Red, Green, Blue aluminum pegs. I thought it would be appropriate to show this milestone piece where the series began. RGB Peg Mirror has two modes of operation and those change every two minutes: The first mode is the interactive reflective mode where the viewer is reflected on the piece in real time. The second mode is the generative mode, in this mode the piece displays various animations that were designed to take advantage of the colorful/ dynamic nature of the piece.
A Transformer-based Neural Architecture Search Method

This paper presents a neural architecture search method based on Transformer architecture, searching cross multihead attention computation ways for different number of encoder and decoder combinations. In order to search for neural network structures with better translation results, we considered perplexity as an auxiliary evaluation metric for the algorithm in addition to BLEU scores and iteratively improved each individual neural network within the population by a multi-objective genetic algorithm. Experimental results show that the neural network structures searched by the algorithm outperform all the baseline models, and that the introduction of the auxiliary evaluation metric can find better models than considering only the BLEU score as an evaluation metric.
Hyborg Agency: Cultivating Conversational AI Creatures through Community Connections

Hyborg Agency, an interactive art installation, integrates a digital forest with a human discord chat channel, enabling communication with AI deer or 'hyborgs'. The forest metaphorically represents human society, where AI agents use the large language model (LLM) ChatGPT to learn and grow by summarising conversations and updating their knowledge base, assimilating community thoughts as enriching nutrients.
A blockchain-based log storage model with efficient query

Server logs are always essential in website maintenance. The services maintained may encounter various problems, and the logs generated by the server are the core data for locating the problem. However, existing log storage systems are susceptible to single points of failure, which can lead to potential log leakage. Meanwhile, external adversaries can tamper with logs to avoid tracking, and administrators can also tamper with logs to evade responsibility. In order to solve these tough shortcomings effectively, introducing blockchain networks seems to be an appropriate solution due to their immutability and decentralized nature. Traditional blockchains lack scalability in storing large files, but this can be tackled by storing log data in the interplanetary file system (IPFS). In this paper, we propose a log data storage scheme combined with blockchain networks and the IPFS technique. First, we utilize the IPFS to store extensive file log data and combine blockchain systems to realize decentralized log data storage in a secure manner. Second, to optimize the query efficiency of log data, we propose two improved Merkle tree methods, providing rapid queries of log data with a timestamp as query keywords (only one-third of the BBT in range query time). Finally, our comprehensive experimental results show that the two proposed methods have better log retrieval efficiency.
Applications of the Lambert–Tsallis W<sub>q</sub> function in QKD

The Lambert–Tsallis W q function has found applications in several areas of physics, such as quantum optics, astronomy, and semiconductor physics. In this work, we discuss some applications of W q in quantum key distribution (QKD). Three problems are considered: (i) the quantum access network, (ii) analysis of an on-chip SiO 2 amplitude modulator used in continuous-variable QKD (CV-QKD), and (iii) parameter estimation of a stochastic quantum channel. In quantum access networks, QKD and classical data travel on the same optical fiber. In this case, an increase of the quantum bit error rate is caused mainly by the spontaneous Raman scattering (SRS) produced by classical data. The amount of SRS produced depends on the fiber length. In the present work, we use the Lambert–Tsallis W q function to calculate analytically the fiber length needed to produce a given level of SRS. Thus, our formula allows the calculation of the QKD channel’s length when the probability of a click on the receiver side without having any incident photons from the quantum transmitter is defined a priori . On the other hand, a crucial step in the security of CV-QKD is the correct channel transmissivity and excess noise estimations. These parameters can be overestimated or underestimated when real devices do not behave as predicted by their models. In this direction, using the W q function, we provide an equation for calculation of the fluctuation of the concentration of free carriers in an integrated amplitude modulator and another equation for calculation of the parameter that models a stochastic quantum channel. These equations are useful in building strategies to avoid quantum hacking.
A Conjunctional Approach for Enhanced and Extended Security in Big data Environment

Today people’s live in the "Era of Data". The data has been tortured and indulged in confession in many ways. The term big data deals with large volumes of data that streams in a fraction of a second and of-course in the format of unstructured data. As the data are big the challenges are high and the process of handling data is becoming so daunting. And the security issues of big data are becoming a great threat to the data which is very critical for the development of many organizations. As the security solution cannot be given as a one-stop solution a layered methodology has been proposed in this work for securing confidential data. It is a combination of heavy encryption traditional algorithm RSA and data masking technique which will lead to better security for the data. The reason why the RSA algorithm is proposed is that by using this algorithm it is very safe to exchange data over the internet, it maintains the confidentiality of the data to a high extent and this algorithm will maintain high toughness because breaking the keys through interceptors is difficult. The results and discussions of our proposed methodology will lead to an enhanced security system with fuzzy procedures which efficiently strengthen the system.
Benefits of Implementing an Ad-Hoc Network for Hospitality Businesses with IoT Smart Devices

As a result of digitization, the barriers between policy and engineering have blurred, making way for new types of businesses to emerge that use digital technologies and management practices. The purpose of the proposed research was to examine how IoT and Big Data factor into the digital transformation processes of various companies. It is argued in this study that the proliferation of IoT devices and Big Information has led to a chaotic tangle of information. To sort through the clutter, researchers conducted a literature study of articles covering the period from 2008 to 2019 that looked at the intersection of IoT and Big Data. The findings reveal that Internet of Things (IoT) and Big Data play a predominate role in reengineering corporate processes, goods, and services; nevertheless, a lack of public understanding and acceptance has caused research to progress along many, inconsistent pathways. This research has important ramifications for company managers and marketers since it shows how Big Data and Internet of Things are facilitating a digital revolution that is improving many areas of operation. With the goal of guiding future research and practice, this paper examines Big Data and Internet of Things (IoT) as two sides of the same coin.
Digital Secure Storage for Healthcare Data Information Using Blockchain

Healthcare Blockchains grant access to a modern technique to accumulate healthcare information, achieve healthcare, and make a belief for medical records distribution and records combination in a decentralized unlock healthcare network surroundings. Even though the healthcare blockchain technologies have paid attention to extroverted benefits in addition to a concentration in assiduousness, management as well as university circles, the safety and confidentiality concerns stay behind the center of attention of deliberate while organizing Blockchains for information sharing across company operations and research collaboration in the healthcare sector. Medical data sharing via Blockchains are the subject of research that focuses on security and privacy needs. Together with technological solution techniques and strategies, the research provides a complete evaluation of the safety and confidentiality risks, requirements, and technology solutions. In the beginning, we discuss the security and privacy requirements for using healthcare Blockchains to share electronic medical records. Second, we group current initiatives into three reference blockchain procedure scenarios for the sharing of electronic medical records. We consider the technologies that can be used to implement this secure store for healthcare data properties in the two categories of healthcare Blockchains procedure scenarios, including anonymous signatures, and attribute-based encryption. Source to implement the access control for hospital, patient, doctor, admin.