Reviewerly/exHarmony huggingface dataset:
Introduction and Personality of Chinese Nationalized History Textbook Zhong Wai Li Shi Gang Yao

In 2017, China confirmed the nationalized history textbooks, and the history curriculum was divided into three stages: mandatory, selective, and optional subjects. The nationalized history textbook Zhong wai Li Shi Gang Yao(『中外歷史綱要』, The Outline of Chinese and Foreign History) is planned to be used as the only history textbook in general high schools across China from 2022. This study paid attention to history education among the causes of the historical conflict between Korea and China, and considered the background, influence, and problems of the appearance of Gang Yao.&#x0D; The fact that Gang Yao appeared in a situation where the U.S.-China hegemony competition accelerated and became more isolated internationally suggests many points. In order to overcome this situation, China has put a lot of effort into strengthening patriotism education, and through this, it is promoting internal unity. In this situation, the Gang Yao that appeared includes such political intentions in China.&#x0D; China's political intentions are strongly projected, and Gang Yao has several problems such as a narrative method based on materialistic views, a lecture on the theory of a unified multi-ethnic state, and a historical narrative centered on the country. Considering that all general high school students across the country will be educated through this in the future, our position should be actively expressed. It is necessary to observe and analyze the contents related to us in more detail in China's history textbooks, and to continuously present opinions and coordinate the contents through active exchange and communication between Korea and China.
The Poetic World of Yang-sim-dang Cho Seong

This study aims to comprehend the poetic world and the historical background of the literature of Cho Seong, a literary scholar in the early Choseon Dynasty from Joongjong to Myeongjong. Before the full-fledged study, I created a framework to categorize his poems according to motive by using the motive for writing the poetry and the subject matter that was key to embodying the subject of the poetry as the reference line for the compartment. Based on this reference line, I created four categories as follows. Type A: The motive of delivery prevails, and the subject matter is about human beings. Type B: The motive of delivery prevails, and the subject matter is about material phenomena. Type C: The motive of expression prevails, and the subject matter is about human beings. Type D: The motive of expression prevails, and the subject matter is about material phenomena. All four categories involved each type, and the poet expressed his intention and emotion similarly in the poems assigned to each. In Type A, poems mainly showed the intention to encourage the recipient to be diligent and wakeful. In Type B, the sentiment of aspiring to intimacy and companionship with the recipient was the main focus. In Type C, the poet's voice was prominent in expressing his hardships and anguish. In Type D, the assurance of self-sufficiency and prudence formed the principal emotion. In his poetry, Cho Seong faithfully represented the reflective human figure living in personal suffering and unhappy times. This aspect was deeply applicable to him, as despite being afflicted with several diseases throughout his life, he devoted his life to academic exploration and student education. Besides producing typical literary works, he wrote poems that were unconventional in terms of form, content, and theme due to his extraordinary personal and historical condition. In particular, epistolary poetry was a disparate and specific style that stands out in his literature. Simply by creating this form, he made a significant contribution to Korean literature.&#x0D;
Quantum Number

Quantum mistake rectification code has a significant task to carry out in shielding the data from blunders coming about because of de lucidness and other quantum commotion sources. This method plays an urgent viewpoint in accomplishing quantum calculation. Quantum key dispersion utilizes singular photons for the safe transmission among transmitter and beneficiary. In the event that a photon goes in a free space, its polarization state stays unaltered, believing the air choppiness to be immaterial. However, on the off-chance that a similar photon goes in an optical fiber, its polarization state changes radically. In this exploration quantum encryption and decoding is accomplished by misusing the properties of quantum articles like photon.
Pre-trained deep learning models for content-based image classification and retrieval

Content-based image retrieval (CBIR) is a process of finding similar images from a large dataset of images for a given input image. Retrieving comparatively similar images which feature to be considered is an important task in the whole CBIR process. Since the evolution of CBIR, there is a lot of work on the features extraction part so as to reduce the semantic gap and improve image retrieval results. In the initial stage of image retrieval, low-level features like colour, texture, shape, borders, etc. are considered and after the evolution of deep learning, high-level features were extracted from images proved to be better than earlier methods of image retrieval. In this paper, we propose to use features pre-trained CNN model combinations, which are trained for large image database classification. This approach produces superior results of classification and retrieval for various datasets by considering original query images and acceptable results by considering rotated query images.
IoT Security Enhancement Using Blockchain

Internet of Things (IoT) is one of the most common technology used in home automation as well as in smart industry. There is exponential growth in IoT applications in recent past. Industry and researchers are actively working on new and creative applications of IoT. Though IoT become one of the most popular technology, it still suffers from strong privacy and security vulnerabilities. Exploitation of IoT vulnerabilities can be devastating as it brings serious threats on industry automation and critical infrastructures like nuclear power plant, gas pipeline etc. Because of underpower and resource-constrained, conventional security measures seems to be infeasible for IoT devices. Blockchain is one of the promising technologies which can be used for enhancing the overall security features of IoT. However, blockchain is resource intensive process and cannot be integrated directly with IoT devices. Hence, there is a need to design the architecture to achieve the objectives as well as balance the resource constraints. This paper implements the blockchain to enhance the IoT security and validates the proof of concept with experimental results.
An Approach on Image Steganography Based on the Least Significant Bit Algorithm

Steganography is the practice of communication by covering information within other information mediums. The goal of steganography is to hide information in such a way that it remains hidden so that it looks normal from a commoner's perspective. It has been prevalent since ancient times, with the first use dating back to 440 BC in Greece. The etymology of steganography is a combination of the Greek words: steganos, “covered,” and graphia, “writing.” The modern usage of steganography, termed digital steganography, hides information in files stored on a computer. A standard steganography algorithm has three essential components: carrier, message, and key. Carrier is the file that carries the message and an optional key to add a layer of authentication. Researchers have implemented steganography utilizing different carriers, for example, image, audio, and text. The carrier may or may not have any relation with the confidential information. Image steganography is a type of steganography that deals with hiding a message in an image file. The image, as a result, ends up with noise.
Hacking the System

In this paper, I explore how teaching can be an act of activism; a way of hacking the neoliberal university. In doing so, I draw on our experiences with the course “Resistance, Power and Movements.” I argue that activist teaching not only involves teaching about issues related to social justice and resistance, but also engaged, horizontal teaching methods, as well as self-reflection. This implies a process of double contention. On the one hand, the course resists the outcome-oriented university that we work in by focusing on learning as a process and a form of reflection. On the other hand, the lecturers of the course seek to equip students with tools and knowledge to not only understand social change, but also become part of it.
Eye Typing-Vision Based Human Activity Control

In real world applications, the computer is just an extension of human body to complete tasks in a fast and efficient manner. The primary task performed by a computer user is to type. It is not possible for people with severe motor disabilities like paralysis to communicate effectively using their hands. The aim of the work described in this paper is to provide an on-screen keyboard where a user can type and communicate just by coordinating the blinking of his or her eye. This is achieved through face detection followed by focus on the eye region of the facial image. This facilitates capture and mapping of the eye gaze coordinates to the corresponding key on a keyboard. To achieve this, DLib toolkit has been used. DLib is a trained model majorly used for face detection and facial landmark detection using Support vector machine algorithm. Transfer learning approach is used here to achieve efficiency. The outcome of the work described is the integration of the eye-typing platform with a variety of other features, which has led to an improvement in software usability and productivity.
AI-based assistant with security

In recent years, virtual personal assistants (VPA) widely used. The era of digitalisation has made sure that no one needs to rely on anyone when one can just depend on more efficient and reliable systems which can take care of our basic needs. The demand for such speech-enabled personal assistants is constantly growing primarily due to the fact that they make our life so much easier. The devices such as Amazon’s Alexa, Microsoft’s Cortana, Apple’s Siri have gained massive popularity because of their ability to interact with the user and supply them with network-based services. VPAs are more than just a bot, they make life easier for the user in different ways. This conjointly poses a number of security threats when one needs to implement that in a sensitive.
Remodeling Environments: Anthropological Perspectives on the Limits of Computational Models

Computational models play central roles in the politics of the Anthropocene.Whether used to design seawalls or to project climate futures, we encounter them across a variety of sites of response to anthropogenic climate change and other environmental ills.In this paper, we reflect on the limits of contemporary computational modeling, particularly when it comes to representing coupled socioecological systems or human-nonhuman relations.Modeling practices naturalize specific assumptions about what counts as data, can be represented, and counts as legitimate knowledge regarding environments and their contents.They are also shaped by and reinforce contingent forms of computational logic and infrastructure that could, we suggest, be otherwise.As a result, their projections frequently grind against other ways of imagining environments and their futures, such as those developed through long-term inhabitation or embedded within different ecologies and infrastructures of knowledge production.They also materialize in infrastructures that can be part of the problem rather than the solution.
The Use of Technology to Deliver Virtual Grocery Store Tours

Grocery store tours are potentially a useful approach to improving educating consumers. However, this approach may be limited by barriers to access to grocery stores. Virtual grocery stores tours (VGST) may offer an alternative approach to providing GSTs. Several methods could be used to provide a VGST and differences between these methods on the user experience need to be elucidated. The purpose of this study was to determine participant experiences in a VGST provided using different technologies. A VGST was created by using the Unity Game Engine. An avatar, voiced by a registered dietitian, provided nutrition education at various locations in the virtual grocery store (e.g., produce, dairy, meat or grains sections). In a repeated measures design. 13 individuals experienced this VGST using 3 different technologies: immersive virtual reality (IVR), a PC monitor or a tablet. After baseline physiological measurements were collected (using an Empatica wristband), the participant viewed a VGST that lasted approximately 15 minutes. Then, they completed a questionnaire about their feelings of presence (feeling they were present in a supermarket), nausea, enjoyment of the VGST and the likelihood they would recommend the VGST to a friend. Responses were captured on a 7-point scale. Participants experienced a greater sense of presence in the IVR condition (IVR = 5.8, PC = 2.6, tablet = 2.6; p < 0.05). In the IVR session participants experienced greater feelings of nausea (IVR = 1.7, PC = 0.4, tablet = 0.4; p < 0.05). Users enjoyed the IVR medium more than the tablet medium (IVR = 5.3, PC = 4.6, tablet = 4.1; p < 0.05). There was no differences in the participants willingness to recommend the VGST to a friend (IVR = 6.4, PC = 7, tablet = 5.5; p > 0.05). Future analysis will examine the physiological differences during each treatment. These data indicate that VGSTs are a feasible approach to provide nutrition education. IVR creates a greater sense of presence which has been linked to improved learning outcomes. The effect of different electronic mediums on the ability to learn and retain nutrition information requires investigation. None.
Critical Review on Breast Cancer Classification

In recent days, most common disease which causes death is breast cancer. Worldwide, it is a second common disease causing more death. Around 4.5 to 5% new cases are recorded every year and at worldwide, morbidity is increased. Patient’s survival rate can be increased by cancer’s early detection with proper treatment and diagnosis. Classification accuracy and feature selection are major issues in available techniques. Various available optimization and data mining techniques are analyzed for rectifying above mentioned issues. From breast cancer dataset, hidden knowledge are obtained using those techniques. For enhancing specified breast cancer dataset’s accuracy significantly, classification process, feature selection and pre-processing are performed in this work. Every algorithm’s shortcomings and advantages are also analyzed in this survey. Different classification methods like FE-BkCapsNet, Convolution Neural Network (CNN), K Nearest Neighbor (KNN), Support Vector Machine (SVM) are used for making comparative analysis. With respect to f-measure, sensitivity, specificity, accuracy metrics, better performance are provided by FE-BkCapsNet approach when compared with other techniques as indicated in experimental results.
Multiple regression

Regression is used for three purposes: explanation, prediction and control. Multiple regression uses the same concepts, and extends them to the case where there is more than one IV. The basic idea is that a DV can be expressed as a linear function of one or more IVs, which are assumed to be free from random variation, plus some random variation. The dependent variable must be at least a good approximation to an interval scale, and so must the majority of the independent variables. Regression is a method where we usually need a large dataset, though the size depends as usual on the required power, the strength of the relationships between the IVs and the DV, the intrinsic variability of the DV and whether there are relationships among the IVs. If one value of a predictor variable lies well beyond the range of most of the other values, this observation may have a very large influence on the resulting regression.
IntelliTC: Automating Type Changes in IntelliJ IDEA

Developers often change types of program elements. Such refactoring often involves updating not only the type of the element itself, but also the API of all type-dependent references in the code, thus it is tedious and time-consuming. Despite type changes being more frequent than renamings, just a few current IDE tools provide partially-automated support only for a small set of hard-coded types. Researchers have recently proposed a data-driven approach to inferring API rewrite rules for type change patterns in Java using code commits history. In this paper, we build upon these recent advances and introduce IntelliTC — a tool to perform Java type change refactoring. We implemented it as a plugin for IntelliJ IDEA, a popular Java IDE developed by JetBrains. We present 3 different ways of providing support for such a refactoring from the standpoint of the user experience: Classic mode, Suggested Refactoring, and Inspection mode. To evaluate these modalities of using IntelliTC, we surveyed 22 experienced software developers. They positively rated the usefulness of the tool.The source code and distribution of the plugin are available on GitHub: https://github.com/JetBrains-Research/data-driven-type-migration. A demonstration video is available on YouTube: https://youtu.be/pdcfvADA1PY.
The methods of data processing according to the measurement/classification procedure for quality indicators of objects

The measurement/classification procedure of object properties, such as quality indicators, is used for determination of object quality category. According to measurement uncertainty, the fuzzy classification scale is constructed. In accordance with this scale, fuzzy classification results are obtained. The use of fuzzy averaging for multiple measurements of individual quality indicators are proposed. The fuzzy logic operators that can be used in the construction of group quality indicators are considered and recommendations for their application are given. As an example of application of the proposed method, the definition of water quality categories on its biochemical properties is used.
Fighting Disability Condition in Andrew Solomon’s Novel Far Away From Tree (2012)

This article is about the analysis of a novel Far Away from Tree (2017) by Andrew Solomon. There are two keywords that need to be explained in this study: Fighting and disability condition. According to Merriam-Webster (2018) fight means to put effort as determined effort. While according to Merriam Webster Dictionary disability means a physical, mental, cognitive, or developmental condition that impairs, interferes with, or limits a person’s ability to engage in certain tasks or actions or participate in typical daily activities and interaction. According to Merriam Webster Dictionary condition means something essential to the appearance or occurrence of something else
Quantum-Safe Asymmetric Cryptosystems

The boom of quantum computing has brought both benefits and threats to cyber-physical systems. The primary purpose of the paper is to highlight the possible threats by quantum computers, and to provide a comparative study of the on-going quantum-resistant post-quantum cryptography suitable for current network infrastructure. Asymmetric key cryptography, mainly the widely adopted RSA and ECC algorithms, has been compromised by quantum algorithms such as the Shor’s algorithm. Moreover, symmetric algorithms such as AES are weakened by brute force attacks using Grover’s algorithm. Thus, researchers are developing public key algorithms based on hard mathematical models that provide resistance against quantum attacks and can be deployed in classical hardware. We categorize the well-known post-quantum schemes based on (1) their security goals: confidentiality and integrity, and (2) their mathematical problems: code-based, lattice-based, super-singular elliptic curve isogeny based, multivariate and hash-based algorithm. Hash-based post- quantum cryptography is further categorized into two: stateless and stateful signature scheme. Furthermore, the chapter compares the algorithms based on the key sizes, ciphertext sizes, signature sizes, computation, and time cost. The paper also presents the challenges faced by the post-quantum algorithms, and it outlines directions for further research to improve the algorithms. Moreover, various cyber-physical fields, including industrial control systems, mainly nuclear power plants, water management plants, and even space stations and their infrastructure, rely on classical cryptography. Thus, the paper presents a generic hybrid cryptosystem based on classical and post-quantum cryptography to enhance resistance against classical and quantum attacks.
EFFECTIVE SEMANTIC FEATURES TO IMPROVE RETRIEVAL OF LUNG NODULES IN CT SCAN IMAGES

Successful treatment of a patient depends on the accurate determination of the disease type. The advent of big data facilitates the retrieving of medical images and helps physicians in reliable diagnoses using content-based medical image retrieval systems (CBMIR). They consist of a feature extraction module and a distance metric. The extracted textural or deep-based features identify different types of diseases. In the proposed retrieval algorithm, we use the gray level cooccurrence matrix as the common textural characteristics and integrate them with semantic attributes. The semantic features are the geometric characteristics of the tumor that a radiologist employ to distinguish between benign and malignant tumors. These high-level attributes include the Euler number, margin smoothness, and the aspect ratio of the lesion’s size. We used the Minkowski distance measure for computing the similarity of images and applied the proposed algorithm to 200 CT-scan data containing lung lesions obtained from the LIDC database. The types of lesions were benign and malignant. Employing an ablation study, we proved the effectiveness of the semantic feature. The precision of the retrieval results is 93% which is promising compared to recent studies. In the future, we plan to define other kinds of semantic attributes to distinguish stages 1–5 of lung tumors as well.
Renewables booming

Chemistry & IndustryVolume 86, Issue 6 p. 4-4 Leader Renewables booming First published: 14 June 2022 https://doi.org/10.1002/cind.866_2.xAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinkedInRedditWechat No abstract is available for this article. Volume86, Issue6June 2022Pages 4-4 RelatedInformation