Reviewerly/exHarmony huggingface dataset:
Virtual Display and Interaction System Design of Bingxi Scroll Painting Based on Augmented Reality Technique

The Bingxi scroll painting depicts the grand scene of royal ice activities in Qianlong period of Qing Dynasty. It adopts augment reality technique to synthesis the material background and three-dimensional dynamic figures, which could display the combined original painting replica and digital performance of ice activities in virtual space, so as to restore the simulation experience of royal scene in Qing Dynasty. The interactive method which abided by multi-sensory integration design philosophy could construct a realistic environment and historical culture charm for audience intuitively. Through the comprehensive evaluation of the system, it is found that the character modeling proportion is the most important factor which influenced virtual display. This work could invigorate the Chinese traditional ice sports and transform the multivariate culture in contemporary era.
A Study on Annotation Efficient Learning Methods for Segmentation in Prostate Histopathological Images

Cancer is a leading cause of death worldwide. The detection and diagnosis of most cancers are confirmed by a tissue biopsy that is analyzed via the optic microscope. These samples are then scanned to giga-pixel sized images for further digital processing by pathologists. An automated method to segment the malignant regions of these images could be of great interest to detect cancer earlier and increase the agreement between specialists. However, annotating these giga-pixel images is very expensive, time-consuming and error-prone. We evaluate 4 existing annotation efficient methods, including transfer learning and self-supervised learning approaches. The best performing approach was to pretrain a model to colourize a grayscale histopathological image and then finetune that model on a dataset with manually annotated examples. This method was able to improve the Intersection over Union from 0.2702 to 0.3702.
Onto4AIR2: An ontology to manage theses from open repositories

This paper describes Onto4AIR2, an ontology to manage theses from open repositories, this fosters unique and formal definitions of concepts from the Mexican repositories domain in English and Spanish languages, its goal is to support the construction of machine-readable datasets that are semantically labeled for further consultations in educational organizations. The ontology instances are sample data of theses from the National Repository of Mexico, an initiative promoted by the National Council of Science and Technology. The paper describes advantages derived from the formalisms of the ontology, and describes an assessment technique where participants are developers and potential users. Developers followed a competency questions-based approach and determined that the ontology represents questions and answers using its terminology; whereas potential users participated in a satisfaction survey; the results showed a positive perception. At present, the level of the ontology is proof of concept.
Implementation Of Fuzzy Tsukamoto Algorithm for Registration Students

Becoming a new student in junior high school requires a registration process from the elementary level. However, information on new student admissions has been documented manually, so there are difficulties and errors in determining grade and files of student document are often lost caused by the files is not archived properly. The purpose of this research is to model a computer-based new admissions information system using the Fuzzy Logic method and this system purposed to assist officers in dealing with the obstacles faced in conducting the selection of new student admissions, however by the information system that has been made, it is expected to solve problems related to the admission of new students. The modeling of this new admissions information system uses the Fuzzy Logic method, which consists of the stages of system design, database design and fuzzy logic design. The results of the system application test can be seen that the system application on the system of implementing the Fuzzy Tsukamoto algorithm on New Student Admissions for Junior High School can carry out the process properly and correctly. Tests are also carried out on the rules of Fuzzy Logic that have been made to find out whether the system can work properly and correctly.
Visual Question and Answering System for NLP and Computer Vision Problems

The purpose of this work is to develop a Visual question and answering system. Several neural networks of different architectures were traine. Ensembles of convolution neural networks and fully connected network, convolution neural networks and Long short-term memory, MobileNetv2 and Long short-term memory and MDETR are used. The MDETR model shown the best prediction accuracy. It made a lot of mistakes when it came to counting objects in a photo, but on other types of questions, it showed good results.
Untrimmed Operator Standard Cleaning Action Parsing Based on Deep Learning Method

For the process in the clean room, small particles will not only cause environmental pollution, but also lead to the decrease of product yield. Therefore, it is important to clear away the particles from the body before entering the clean room. This paper described an existing approach for automated monitoring cleaning action on real-time camera. The current method of performing action recognition uses 3D convolutional neural network (3DCNN) and real-time object detection which uses You Only Look Once (YOLO) as backbone. To achieve untrimmed standard cleaning action parsing, our research proposes a new approach by combining the two methods with proposed mechanisms. In addition to considering coarse-grained analysis of different actions, this paper also proposed a fine-grained measure of action completion.
The Role of Crosstalk in Enhancing Chinese Language Learning

Crosstalk (相声) is a very popular folk performing art in China. Its popularity with the people derives from its frequent use of puns and humorous monologues or dialogues through cleverly crafted plots and choice of words. Thus, performing and writing crosstalk afford ample opportunities to learn and refine Chinese language skills. It is therefore small wonder that crosstalk as a form of co-curricular activity has been quite popular in Singapore schools, usually organized by the Chinese Language teachers for their students.
Empirical Risk Assessment in Major Graphical Design Software Systems

Security vulnerabilities have been reported in major design software systems such as Adobe Photoshop and Illustrator, which are recognized as de facto standard design tools in most of the design industries.Companies need to evaluate and manage their risk levels posed by those vulnerabilities, so that they could mitigate the potential security bridges in advance.In general, security vulnerabilities are discovered throughout their life cycles repeatedly if software systems are continually used.Hence, in this study, we empirically analyze risk levels for the three major graphical design software systems, namely Photoshop, Illustrator and GIMP with respect to a software vulnerability discovery model.The analysis reveals that the Alhazmi-Malaiya Logistic model tends to describe the vulnerability discovery patterns significantly.This indicates that the vulnerability discovery model makes it possible to predict vulnerability discovery in advance for the software systems.Also, we found that none of the examined vulnerabilities requires even a single authentication step for successful attacks, which suggests that adding an authentication process in software systems dramatically reduce the probability of exploitations.The analysis also discloses that, for all the three software systems, the predictions with evenly distributed and daily based datasets perform better than the estimations with the datasets of vulnerability reporting dates only.The observed outcome from the analysis allows software development managers to prepare proactively for a hostile environment by deploying necessary resources before the expected time of vulnerability discovery.In addition, it can periodically remind designers who use the software systems to be aware of security risk, related to their digital work environments.
Research on Collaborative Utilization of Electronic Archives in the Management of Large-scale Cross-sea Projects

As the foundation of highway engineering project, electronic archives are the key to supporting modern management and digital transformation of project construction. Based on the needs of electronic archives management for large-scale cross-sea projects, this paper conducts research on management and utilization electronic archives. A workflow on the management platform is established to automatically drive the core management process of the project through electronic files. The automated management level of large-scale cross-sea project is greatly improved.
An Extension of Kannan’s Embedding for Solving Ring-Based LWE Problems

The hardness of the learning with errors (LWE) problem supports the security of modern lattice-based cryptography. Ring-based LWE is the analog of LWE over univariate polynomial rings that includes the polynomial-LWE and the ring-LWE, and it is useful to construct efficient and compact LWE-based cryptosystems. Any ring-based LWE instance can be transformed to an LWE instance, which can also be reduced to a particular case of the shortest vector problem (SVP) on a certain lattice by Kannan’s embedding. In this paper, we extend Kannan’s embedding for solving the search version of the ring-based LWE problem. Specifically, we propose a new extended lattice to include multiple short errors that are amplified by rotation operations for the coefficient vector of an error polynomial. Since multiple short errors have the same length and are embedded in our extended lattice, our extension could increase the success probability of solving the ring-based LWE problem by using the Block Korkine-Zorotarev (BKZ) algorithm that is widely used in cryptanalysis. We demonstrate the efficacy of our extension by experiments for solving various ring-based LWE instances.
A Corpus of Czech Essays from the Turn of the 1900s

Abstract A literary essay is an interesting unit for language analyses, as its stylistic means often exceed the boundaries of the genre of an artistic essay. The article presents a new corpus of Czech literary essays covering approximately fifty years from 1890 to 1940. Along with the characterisation of the corpus and its annotation, the paper focuses on the TxM corpus tool: In the second part of the study, we use selected texts to conduct an analysis of seven various authors through multidimensional cluster analysis, factorial correspondence analysis and a specificity score. The main parameter of the analyses was usage of parts of speech in texts by individual authors. At present, the Corpus of Czech Essays contains 40 essayist titles written by 15 authors covering various topics (music, visual arts, theatre, literature, etc.).
The studies of strategies for ensuring the functional safety of hardware and software complexes based on system archetypes and architecture models

The properties of distributed computing and communication systems are critical factors for the effective management of distributed complex systems within the network-centric approach. In different sources, devoted to the construction of computing and communication systems, it is emphasized that the quality of hardware and software complexes (network nodes), is determined by the quality of project management of its creation, one of the components of this is functional safety. The author emphasizes the uniqueness of projects, the distinctive features of software systems from complex systems of a different nature, which results in the specifics of project management for the creation of hardware and software complexes. The conceptual basis of this work is the well-known principle of complementarity by N. Bohr. This is expressed in the fact that the focus of the study is the generality of problem situations that occur in the managing of complex systems of different nature. Formal models of problem situations are system archetypes. The structures of architectures corresponding to the reactive and proactive strategies for ensuring the functional safety of hardware and software complexes are proposed. It is shown that the structures of architectures serve as the basis for the identification of system archetypes. This, in turn, creates the basis for the adaptation of algorithmic and parametric models developed for the study of complex systems of a different nature in the field of functional safety of components of computing and communication systems.
Quantum Cost-Efficient Design of Synchronous Reversible Shift Registers using Reversible Logic

Reversible circuits are one of the most promising technologies for replicating inputs from recorded outputs, and it results in lower power dissipation. All gates such as NAND, AND, OR, NOR etc. are irreversible in nature and consume energy during calculations. Similar to quantum circuits, reversible logic circuitry does not consume energy throughout the calculation cycle. Due to this, reversible circuits can be used for quantum communication and other low-power applications. Registers are one of the most important storage components utilised in a wide range of real-time operations. Using expressions of exclusive-or sum of products (ESOP) and modified Fredkin gates, this work presents a novel way for creating a quantum cost-effective universal register circuit. The designed universal register circuitry for left and right shifts are tested in the Xilinx Vivado simulator to ensure that they are functional and logically correct. The proposed universal registers outperform the standard designs in terms of garbage outputs (GO), quantum cost (QC), gate count (GC), and Ancilla inputs (AI), according to the comparative analysis.
Design and Implementation of Voting System Based on Ethereum

Electronic voting can greatly reduce the cost of voting activities and solve many problems of voting information leakage caused by traditional paper voting. As the development and extension of blockchain technology, Ethereum technology can well solve the centralization problem of traditional electronic voting. This solution proposes an electronic voting system based on Ethereum technology to meet the security requirements of electronic voting, and uses Ethereum smart contract technology to replace the traditional trusted third party, which solves the possible drawbacks of the centralized voting system and improves Security and voters' trust in the voting system reduce voting costs. Finally, the electronic voting function is realized, and the normal operation of the system is guaranteed through the test.
FSE: a Powerful Feature Augmentation Technique for Classification Task

Neural networks are powerful at discovering the hidden relation, such as classifying facial expressions to emotions. The performance of the neural network is typically limited by the number of informative features. In this paper, a novel feature augmentation is proposed for generating new informative features in an unsupervised manner. Current data augmentation focuses on synthesizing new samples according to data distribution. Instead, our approach, Feature Space Expansion (FSE), enriches data feature by providing their distribution information, which brings benefit based on model performance and convergence speed. To the best of our knowledge, FSE is the first feature augmentation method, which is developed based on feature distribution. We evaluate FSE performance on face emotion dataset and music effect dataset. We provide diverse comparisons with different alternative baselines. The experimental results indicate FSE provides significant improvement in model's prediction accuracy when the number of features in original dataset is relatively small, and less remarkable improvement when the number of features in original dataset is large. In addition, training on FSE augmented training set can have at least ten times faster convergence speed than training on original training set.
Implementation of Automatic Mesh Rules Generation by Word Features Relationship (AMRG-WFR) for Word Sense Disambiguation for Marathi Language

One common feature of natural languages is a single word having the different meanings. Detecting the correct sense of the word in the given context is known as word sense disambiguation. In Natural language processing WSD is always a challenging and difficult task. The accuracy of many systems like information retrieval, machine translation text summarization depends upon the module used to identify the correct sense of the word. In this paper we proposed an automatic mesh rule generation technique by word feature relationship for the task of word sense disambiguation for Marathi language. Marathi is one the most popular and morphologically rich language in India. We conducted all the experiments on the benchmark WordNet dataset developed at Indian Institute of Technology Bombay (IIT Bombay). The proposed algorithm contains three sections.In the first section supervised learning technique is used to create training data set. Mesh rules of object were created in second section and in last section the correct sense of ambiguous word matched with the given context. Results show that the proposed method has superior performance as compared with already developed approaches.
Trends and Technologies in Big Data Processing

Data type and amount in human society is growing at an amazing speed, which is caused by emerging new services such as cloud computing, internet of things, and location-based services. The era of big data has arrived. As data has been a fundamental resource, how to manage and utilize big data better has attracted much attention. Especially with the development of the internet of things, how to process a large amount of real-time data has become a great challenge in research and applications. Recently, cloud computing technology has attracted much attention to high performance, but how to use cloud computing technology for large-scale real-time data processing has not been studied. In this chapter, various big data processing techniques are discussed.
Based on ICNet image matching system for gold powder distribution on the surface of the ankle ring

In this paper, an image matching system is proposed for gold powder distribution on the ankle ring surface of pigeons, which uses ankle ring segmentation and then gold powder location identification. The ankle ring is segmented using ICNet, then apply OpenCV SimpleBlobDetector to the area to be discriminated to get the number of gold powder and its position. The YCbCr hue is used to make the gold powder features more visible and stable. Finally, the processed images are imported into our matching system. The results show that the processing speed can reach 12 frames per second(fps) and the Mean Intersection over Union(MIoU) of semantic segmentation can reach 93%.
Green IT: cybersecurity cost or benefit?

Abstract Tony Proctor CITP, Principal Lecturer at the University of Wolverhampton and Emily Proctor, Post-Graduate Student in International Security, discuss whether green IT and cybersecurity can be mutually beneficial.
Proof of Freezing Time Algorithm Based on IOTA with Hierarchical Structure

IOTA is the most widely used blockchain technology in Internet of Things (IoT) but it uses Proof-of-Work (PoW) algorithm to avoid attacks from malicious nodes, which is a big burden for resource-constrained IoT devices. To solve this problem, we present a Proof of Freezing Time (PoFT) algorithm based on IOTA network with hierarchical structure. We propose a credit value-based PoFT algorithm for agent nodes, which reduces the energy consumption of agent nodes while achieving the balance of security and efficiency of IOTA. In order to reduce the amount of communication between agent nodes and gateways, we adopt a hierarchical structure in IOTA, which also reduces the dependence of agent nodes on gateways. Simulation results show that credit value-based PoFT algorithm and hierarchical structure are effective in IOTA.
International Exchange Program as a Viewed from Skill of the Liberal Arts

Global education is professed to be at a technical college and the university, and the international exchange program is carried out in many educational institutes. I make clear what kind of effect there was in each program for a student because various programs were classified by contents. The short-term internship in the laboratory of the university and the presentation of the research with overseas students bring a student many profits. The participation in international exchange programs that technical college and the university provides is an opportunity to know the liberal arts for a student, and is the most suitable opportunity to get a skill of the liberal arts for a student.
Deep Learning Methods for Tumor Segmentation and Detection in X-Ray Breast Imaging

Recently there have been a series of machine learning methods or deep learning architectures that have been developed and used in the field medical imaging. In this study, we focus on the use of AI in the field of breast imaging and the methods with the highest accuracy results for breast tumor segmentation and classification are presented, achieving robust results in detection. Extensive research which included more than 150 related published papers was performed, containing results published between 2016 to 2020 resulting in a review of 4 selected models all at the forefront of current progress.
Investigation on Teachers’ Perception of Augmented Reality as Interactive Media for Science Learning

This article aims to find out the teacher's perception of Augmented Reality (AR) as an interactive science learning medium that can stimulate students' curiosity, passion and motivation, especially in the era of Covid-19 learning where learning is limited. This article used qualitative methods with a descriptive approach. The subjects in this study were 10 junior high school teachers with different grade levels in the city of Makassar. The study data was obtained using questionnaires sent via google form links with 20 question items. The results showed that indicator method used of science lessons, media used od science lesson, knowledge of AR media, fesibility AR media as science lesson, got an average score of 70 with excellent categories, 83 with excellent categories, 62 with Good categories, and 80 in excellent categories. So it can be said by applying AR media to Science materials believed to be able to foster the spirit and motivation of students so as to create an effective learning atmosphere. Keywords: teachers’ perception, augmented reality, covid-19 pandemic. Abstrak : Artikel ini bertujuan untuk mengetahui persepsi guru mengenai Augmented Reality (AR) sebagai media pembelajaran Science yang bersifat interaktif yang dapat menstimulus rasa ingin tahu, semangat dan motivasi siswa, khususnya di era pembelajaran Covid-19 yang pembelajarannya terbatas. Artikel ini menggunakan metode kualitatif dengan pendekatan deskriptif. Subjek dalam penelitian ini 10 guru SMP dengan tingkat kelas yang berbeda di kota Makassar. Data penelitian ini didapatkan dengan menggunakan kuesioner yang dikirimkan melalui link google form dengan 20 item pertanyaan. Hasil penelitian menunjukkan bahwa indicator method used of science lessons, media used od science lesson, knowledge of AR media, fesibility AR media as science lesson, mendapatkan rata-rata skor 70 dengan kategori sangat baik, 83 dengan kategori sangat baik, 62 dengan kategori Baik, dan 80 pada kategori sangat baik. Sehingga dapat dikatakan dengan menerapkan media AR pada materi Sains dipercaya mampu menumbuhkan semangat dan motivasi siswa sehingga dapat menciptakan suasana pembelajaran yang efektif. Kata kunci: persepsi, augmented reality, pandemi covid-19. DOI: http://dx.doi.org/10.23960/jpmipa/v22i2.pp245-255