Reviewerly/exHarmony huggingface dataset:
Reverse Difference Network for Highlighting Small Objects in Aerial Images

The large-scale variation issue in high-resolution aerial images significantly lowers the accuracy of segmenting small objects. For a deep-learning-based semantic segmentation model, the main reason is that the deeper layers generate high-level semantics over considerably large receptive fields, thus improving the accuracy for large objects but ignoring small objects. Although the low-level features extracted by shallow layers contain small-object information, large-object information has predominant effects. When the model, using low-level features, is trained, the large objects push the small objects aside. This observation motivates us to propose a novel reverse difference mechanism (RDM). The RDM eliminates the predominant effects of large objects and highlights small objects from low-level features. Based on the RDM, a novel semantic segmentation method called the reverse difference network (RDNet) is designed. In the RDNet, a detailed stream is proposed to produce small-object semantics by enhancing the output of RDM. A contextual stream for generating high-level semantics is designed by fully accumulating contextual information to ensure the accuracy of the segmentation of large objects. Both high-level and small-object semantics are concatenated when the RDNet performs predictions. Thus, both small- and large-object information is depicted well. Two semantic segmentation benchmarks containing vital small objects are used to fully evaluate the performance of the RDNet. Compared with existing methods that exhibit good performance in segmenting small objects, the RDNet has lower computational complexity and achieves 3.9–18.9% higher accuracy in segmenting small objects.
A Neighborhood Model with Both Distance and Quantity Constraints for Multilabel Data

In this paper, a novel distance-based multilabel classification algorithm is proposed. The proposed algorithm combines k-nearest neighbors (kNN) with neighborhood classifier (NC) to impose double constraints on the quantity and distance of the neighbors. In short, the radius constraint is introduced in the kNN model to improve the classification accuracy, and the quantity constraint <math xmlns="http://www.w3.org/1998/Math/MathML" id="M1"> <mi>k</mi> </math> is added in the NC model to speed up computing. From the neighbors with the double constraints, the probabilities for each label are estimated by the Bayesian rule, and the classification judgment is made according to the probabilities. Experimental results show that the proposed algorithm has slight advantages over similar algorithms in calculation speed and classification accuracy.
Minority Identity in Digital Governance and the Challenges of Online Hate Speech and Content Regulation

The internet constitutes public space where users generate all forms of speech, from neutral and benevolent to vitriolic and harmful. While democratising the production of online speech, content moderation is characterised by less transparency and less public visibility of the practices of the private actors involved in hosting and distributing online content. The constantly evolving regulatory frame of online content moderation is affecting minority groups in manifold ways. It is, in fact, creating an “unstable order” both normatively and in practical terms of policymaking by prompting questions such as: who should be held accountable for harmful speech? How is hate speech connected with hate crime? Why are minorities more affected by certain forms of content regulation? What are the limits of the permissible and legal when expressing oneself online? The purpose of this contribution is to reflect on the ways that legal and governance challenges in the regulation of online speech affect minority groups in times of rapid technological change and intense identity politics. Within this unstable order, it proposes a mapping of the ways that bias against minority groups is embedded in online content regulation, including through hate speech, potentially amplifying pre-existing harm against minority populations beyond the digital ecosystem.
A Study on the Development History of Chinese Grammar Studies in Korea

This study examined the history of Chinese grammar studies in Korea in terms of periods and theoretical schools. Thereby, the scope of Chinese grammar research history has been expanded regionally. Although the development of Chinese grammar studies in Korea was influenced by internal factors such as the development of linguistics itself, it was influenced more by external factors. Historical events, including liberation in 1945 and the establishment of diplomatic ties between the Republic of Korea and the mainland China in 1992, had a great influence on the development of Chinese grammar studies.BR The history of Chinese grammar studies in Korea was divided into four stages. In the imitation period, the ancient Chinese language was analyzed using the concept of modern grammar theories. During the development period, research progress was stagnant, but research resumed in the 1960s. However, there were very few articles on grammar studies in the 1960s and 1970s. Research has been increasing since the 1980s. The number of studies on the ancient Chinese grammar and that of the modern Chinese grammar are similar. The theory of structural linguistics was mainly used. During the revival period, academic exchanges with mainland China were strengthened. The main research subjects were changed to the modern Chinese language. The theory of structural linguistics is still the predominant research theory. The use of functional linguistics theory began. During the prosperous period, the scale of Chinese grammar studies expanded. The theory of functional linguistics became the main research theory. The proportion of applied research has increased.BR This study summarizes the context of Chinese grammar research history in Korea, and will help to explore future development trends. In addition, this study hopes to contribute to the exchange of Chinese grammar studies between Korea and China.
An Analysis of Pronunciation Errors in "Erhua" of Korean Chinese Learners : Establishing a Standard Pronunciation Database and Focusing on Experimental Phonetic Contrast

This study is based on a speech analysis experimental method to analyze the pattern of Korean learners mispronouncing "Erhua" and apply it correctly to Chinese teaching. “Erhua” is a unique principle even within the Chinese phonological system, it makes it difficult for foreign learners to acquire the correct pronunciation. Since this is a unique principle, there are many variations of its pronunciation. This variation causes many deficiencies in the process of teaching this principle. In order for scholars to fully understand this principle, improvements must be made in the teaching methods used in textbooks for understanding “Erhua”. This study firstly analyzes how learners misinterpret and mispronounce “Erhua” while reading the “Pinyin”. Secondly, we analyze the speech data of the learners again, after learners have listened to and grasped a proper understanding of the native pronunciation. The results showed that these learners improved their pronunciation substantially. Through this research, the source of practical difficulties in learning the pronunciation of the “Erhua” speech was explored; the results show a need for a more effective learning method for “Erhua” speech.
A survey on android mobile based application and its security

It is undeniable that the significance of mobile phones in our daily life and activities is endless. The reason for this is because the mobile phone is undergoing a huge transformation and is no longer the normal communication device of the past. It has become a huge concern for entities and industries alike due to the variety of incredible features and openings that mobile phones offer. This study sounds to explore the use of mobile phone services in educational settings, banking systems, irrigation facilities, women's safety, etc., and explore the nature of mobile use in today's society. This review talks about mobile phone applications and their challenges used by mobile internet users and various applications. Today, given the large number of mobile phones and users, the security of mobile applications is very important. Identifying these challenges will assist the industries to be ready for efficient mobile application development and enable them in the successful completion of mobile application development projects. It is recommended that practitioners would contribute more attention to the frequently mentioned challenges identified in academia and industry. In future, more empirical studies are needed to revise the existing studies with more diverse practitioners.
Electroweak Force in the Early Universe

At present we distinguish the electromagnetic force and the weak force. However, in the early universe they were one, the electroweak force. In order to understand these forces we need to start from the beginning. We revisit the U(1) symmetry that plays a part in the electroweak force. Then we introduce a second symmetry, the SU(2) symmetry between waves. We will show why we can consider this symmetry between electrons and neutrinos. The consequence is that electrons can turn into neutrinos (as can muons and tauons). As a result, they can produce three types of boson (W bosons). We show why that is and how it works. We introduce the Higgs field in more detail since it was instrumental in breaking symmetries as the universe cooled down. We also provide an overview of the fields we have introduced and the interaction springs they feel/produce.
Noisy Label Classification Using Label Noise Selection with Test-Time Augmentation Cross-Entropy and NoiseMix Learning

As the size of the dataset used in deep learning tasks increases, the noisy label problem, which is a task of making deep learning robust to the incorrectly labeled data, has become an important task. In this paper, we propose a method of learning noisy label data using the label noise selection with test-time augmentation (TTA) cross-entropy and classifier learning with the NoiseMix method. In the label noise selection, we propose TTA cross-entropy by measuring the cross-entropy to predict the test-time augmented training data. In the classifier learning, we propose the NoiseMix method based on MixUp and BalancedMix methods by mixing the samples from the noisy and the clean label data. In experiments on the ISIC-18 public skin lesion diagnosis dataset, the proposed TTA cross-entropy outperformed the conventional cross-entropy and the TTA uncertainty in detecting label noise data in the label noise selection process. Moreover, the proposed NoiseMix not only outperformed the state-of-the-art methods in the classification performance but also showed the most robustness to the label noise in the classifier learning.
A study of graph analytics for massive datasets

The analysis and research of data which can be altered into a comprehensive graph is referred to as "graph analytics." Graph-based data analytics is a budding field in both data mining and data visualization and is applied for a wide variety of applications such as network protection, banking, and healthcare, both multi-disciplinary and high impact applications [5]. Despite the fact that many methods have been developed in the past to analyze unstructured collections of multidimensional objects, graph analytic technologies are a recent trend that poses several challenges, not only in terms of the output of algorithms that are related to data mining that facilitate algorithmic computational data discovery [3]. Graph analytics primarily aimed to evaluate graph oriented structured data in order to uncover answers to queries (e.g. Identify the person who is the most prominent person in a community? What are the main technology nodes for better practice and decision-making on the internet and urban networks?)Analysis of graphs has always attracted and has always been an important topic for researchers in the history of computing; however, the rise of the uses of advanced analytics for large amounts of semi-structured or unstructured data and the revolution of big data has lately picked up the interest of the information systems community [1]. The qualitative effect of data, as well as the impact of graph analytics technology on organizations, has affected the requirements for business outcomes. Graph analytics for big data can not only recognize but also visualize crucial insights in big data. Furthermore, graph analytics may assist in identifying associations between different types of data and determining their existence and meaning within the context [2].In this chapter, we will present the fundamentals of graph analytics and how graphs are related to big data. The chapter will also show some of the most common graph databases and discuss various big data graph analytics approaches which use the massive datasets, as well as different frameworks for each approach. In the latter part of the chapter, various issues and challenges related to big graph analytics will be addressed. A case study for implementation of graph analytics using python will also be discussed.
Performance analysis of autonomous flight models based on reinforcement learning for military UAV

The reinforcement learning has advantage that the agent copes with the unexpected situations while continuously exploring the surrounding environment. In order for Unmanned Aerial Vehicles (UAVs) to perform their mission successfully without the control of human pilots, they must ecognise the surrounding environment and fly autonomously while controlling the movement of airframe. The Unity 2020.3.9 f1 version and ML-Agents 1.0.7 version were used for creating simulation environment. The UAV model used in our research is a rotorcraft quadcop-ter drone. It can be taken by selecting one of six actions: forward, backward, left, right, up, and down. The UAVs used in national defense conduct the mission to reconnaissance mountains and cities in general. For this reason, we generated three 3-D simulation environments such as mountains environment, cities environment, and mixed environment of mountains and cities. The reward value about action selected by agent should be well defined for reinforcement learning.
Research data management and data literacies (chandos information professional series

"Research data management and data literacies (chandos information professional series." Journal of Electronic Resources Librarianship, 34(3), pp. 301–302
<i>Sudden position guide to cataloging and metadata (ALCTS sudden position series, 1)</i>

" Sudden position guide to cataloging and metadata (ALCTS sudden position series, 1) ." Journal of Electronic Resources Librarianship, 34(3), pp. 303–304
<i>Driving Science Information Discovery in the Digital Age (Chandos Information Professional Series)</i>.

"Driving Science Information Discovery in the Digital Age (Chandos Information Professional Series).." Journal of Electronic Resources Librarianship, 34(3), pp. 299–300
<i>Analyzing use of the serials collection to inform an academic library’s annual subscription renewal/cancelation decisions</i>

Click to increase image sizeClick to decrease image size Disclosure statementNo conflict of interest has been declared by the author.
Organizing Library Collections: Theory and Practice

"Organizing Library Collections: Theory and Practice." Journal of Electronic Resources Librarianship, 34(3), pp. 304–305
Analisis Forensik Rekayasa Dokumen Digital dengan Metode NIST

Digital Forensics is one of the technological fields contained many sub-fields that can assist technically in collecting digital evidence to be presented in a trial in accordance with applicable law. The example of digital forensics sub-field is Image Forensics, which aims to digitally collect and look for evidentiary facts in determining the authenticity of an image or document that contained images. Various criminal and pornographic cases involving image files are still happening nowadays, therefore forensics on images as evidence is an important key to assist the court in making decisions. This research examines the authenticity of documents in the form of digital letters using National Institute of Standard and Technology (NIST) method by applying the forensic ELA (Error Level Analysis). Several previous researches have proven that the forensic ELA is able to detect modifications that have been made to images. Differences with previous researches and this research are the authors also checked the metadata of the images before performing the ELA examination using Fotoforensics. The results of the analysis shows a high level of consistency in the images and writings due to the accumulation of white dots in several places such as in headers, logos, header’s writings, text contents, footnotes, and signatures.
The Method of Conjugation of Rectilinear Trajectories of AUV with Regard to Its Dynamic Properties

The paper describes the method of conjugation of rectilinear tacks taking into account the dynamic properties of AUV and the constrains of their propulsion systems. The conjugation of adjacent tacks is proposed to be carried out using arcs of circles so that there would not be a sharp change of the yaw angle of the AUV when it moves along the arc of this circle. Therewith, the parameters of these circles are calculated taking into account the dynamic properties of the AUV and the constraints of their thrusters. To do this, on the basis of a mathematical model of the movement of the AUV in the horizontal plane, expressions were obtained that allow to estimate the minimum radius of rotation of the AUV moving at a given speed, which leads one of the thrusters into a pre-saturated state. Based on the obtained estimates of the arc radius for the conjugating of tacks, the paper proposes a method for calculating the coordinates of transition points from tacks to the specified arc, and also offers expressions for the formation of program signals of the AUV motion along this arc.
Some Attempts on Characterization and Evaluation of Properties of Fracture/Shear Zones

ABSTRACT: This study is concerned with main causes of fault/shear formation and the utilization of various experimental techniques for their evaluating mechanical properties. In the first part, the results of several experimental studies on the formation of fault/shear zones are presented. Then, some proposals have been done how to characterize the geometry, fracturing, morphology, and internal structure of fault/shear zones and some examples are given using some rock classifications. Then, some direct shear tests were performed on the actual fault gouges and their actual characteristics have been evaluated. The characterization and evaluation of the properties of fault/shear zones using RMQR rock classification method are explored. In addition, the utilization of conventional and modified Needle Penetration Index (NPI) for assessing the characteristics of fault/shear core is investigated. Finally, the presented procedures and techniques are applied to actual fault/shear zones and they are validated. 1. INTRODUCTION Fault/shear zones commonly exist in Earth’s crust and they may be encountered almost in all engineering projects. They may cause very severe engineering problems such as heavy water in-flow, squeezing, instability. They may be pathways for leakage of radio-active wastes to the environment as shown in Figure 1. Many fundamental studies on fracture/shear zones have been done by various researchers (e.g., Cloos, 1930, 1968; Tchalenko, 1970; Roth et al. 1981; Tsuneishi, 1978). Hubbert (1951) and Hafner (1951) were first to give the first theoretical treatise of fracture/shear formations in non-cohesive materials. In engineering applications, some studies were concerned how to locate important structures outside the potential rupture zones (e.g. Cole and Lade, 1984a,b; Bray et al. 1992). Many experimental studies on hydro-mechanical properties of fractures zones and faults in several institutes (e.g. Byerlee 1990, Kutter and Rautenberg, 1979; Lama 1978; Moore et al. 1983; Rutter et al. 1986; Archambault et al. 1990). They tested several types of gouges found in fractured zones and faults under different environmental conditions such a normal pressure, temperature, water content, loading rate.
Business Games with Intelligent E-Learning Systems: A Fundamental Study

The desire to make business games more pedagogically capable opens up the prospect of collaboration with current intelligent tutors or intelligent e-learning systems. Due to the laborious and challenging collaboration caused by the lack of specific standards, this subject has not yet been studied. The paper examines the likelihood of such cooperation, as well as the features of business games and intelligent tutors or e-learning systems that would enable and support such cooperation. The combination of a well-known business game with an existing intelligent e-learning system is specifically discussed, along with the modifications that have to be made in order for this cooperation to work. The efficiency of this collaboration is demonstrated by tests that have been conducted, their objective outcomes, and the opinions of the pupils. The integration of both, the BG and the IELS, is used as a learning aid for several graduate distance courses. Improvements have been introduced to obtain a better cooperation. The new results obtained show their beneficial effects.
Policy Change Analysis on Balanced National Development in Terms of Multiple Streams Framework and Its Implications

This study attempted to explore the factors affecting the change in the national balanced development policy based on Kingdon's MSF model and suggest a plan for effective balanced development policy in the future. Methodologically, big data analysis was used along with literature analysis. The analysis results show that the factors affecting the change in the national balanced development policy were influenced by policy problems and policy alternatives at the time, but the most affected was the flow of politics. It should be noted that during the MB Administration and Moon Jae-in Administration, the policy window opened in accordance with the big political trend of "regime change," and the name, degree of implementation, and content of the national balanced development policy changed accordingly. It also supports that the policy output would be influenced by the president's national philosophy following the launch of the new government.