Reviewerly/exHarmony huggingface dataset:
The Part A1 Moratorium Through a Signalling and Information-Processing Lens

Using insights from complex systems theory, it is argued in this article that financially distressed large corporates will only seek moratorium protection when the benefits such protection bring outweigh the signalling and information-processing problems associated with it – likely to be in the later stages of distress. With this insight in hand, the article predicts a somewhat gloomy future for the new Part A1 moratorium introduced in the UK by the Corporate Insolvency and Governance Act, 2020. It is suggested that the UK administration moratorium is in fact more fit for purpose, but that serious signalling and information processing concerns remain. After touching on two possible adaptations of the tools, the article concedes that the decision to restrict the usefulness of both tools may have been deliberate. But if this is so, it ends by questioning whether that decision is sustainable in a rapidly changing economic environment.
Entanglement Transfer Via Chiral and Continuous-Time Quantum Walks on a Triangular Chain

We investigate the chiral quantum walk (CQW) as a mechanism for an entanglement transfer on a triangular chain structure. We specifically consider two-site spatially entangled cases in short-time and long-time regimes. Using the concurrence as an entanglement measure; fidelity, and the Bures distance as the measure of the quality of the state transfer, we evaluate the success of the entanglement transfer. We compare the entangled state transfer time and quality in CQW against a continuous-time quantum random walk. We also observe the effect of mixed states on the entanglement transfer quality.
Graph Embeddings for Non-IID Data Feature Representation Learning

Most machine learning models like Random Forest (RF) and Support Vector Machine (SVM) assume that features in the datasets are independent and identically distributed (IID). However, many datasets in the real world contain structural dependencies so neither the data observations nor the features satisfy this IID assumption. In this paper, we propose to incorporate the latent structural information in the data and learn the best embeddings for the downstream classification tasks. Specifically, we build traffic knowledge graphs for a traffic-related dataset and apply node2vec and TransE to learn the graph embeddings, which are then fed into three machine learning algorithms, namely SVM, RF, and kNN to evaluate their performance on various classification tasks. We compare the performance of these three classification models under two different representations of the same dataset: the first representation is based on traffic speed, volume, and speed limit; the second representation is the graph embeddings learned from the traffic knowledge graph. Our experimental results show that the road network information captured in the knowledge graphs is crucial for predicting traffic risk levels. Through our empirical analysis, we demonstrate knowledge graphs can be effectively used to capture the structural information in no-IID datasets.
An approach to the developing analytical platform based on knowledge and metamodeling

The purpose of the study is to develop an approach to creating knowledge-based analytical platforms that inte- grate language toolkits allowing to create new domain-specific languages, customizable to the specifics of the tasks solved by users, to their domains and used solution methods. The basis of the solution is a knowledge base, a multifaceted ontology that describes data and data sources, domain objects, tasks and solving methods and functional modules that implement them, as well as domain-specific languages created to solve user’s tasks. The ontology structure, mathematical model, and metalanguage, on which the implementation of language toolkits is based, are described.
Depth-Based vs. Color-Based Pose Estimation in Human Action Recognition

Recent advances in deep learning resulted in the emergence of accurate models for human pose estimation in color videos. Distance between automatically estimated and manually annotated joint positions is commonly used for the evaluation of such methods. However, from a practical point of view, pose estimation is not a goal by itself. Therefore, in this work, we study how useful are state-of-the-art deep learning pose estimation approaches in a practical scenario of human action recognition. We compare different variants of pose estimation models with the baseline provided by the Kinect skeleton tracking, which, until recently, was the most widely used solution in such applications. We present a comprehensive framework for pose-based action recognition evaluation, which consists of both classical machine learning approaches, including feature extraction, selection, and classification steps, as well as more recent end-to-end methods. Extensive evaluation on four publicly available datasets shows, that by using state-of-the-art neural network models for pose tracking, color-based action recognition matches, or even outperforms, that of the depth-based one.
Approximate Representations

In this chapter, we consider methods for approximating value functions, policies, or transition kernel. This is in particular useful when the state or policy space are large, so that one has to use some parametrization that may not include the true value function, policy, or transition kernel.
Pengembangan Buku Ajar Bahasa Inggris 3 dengan Materi English For Specific Purposes (ESP) untuk Teknik Informatika Semester III Universitas Pamulang

The purpose of developing English language materials 3 is to achieve learning targets in accordance with KKNI standards for teaching English outside the English department, namely English for specific purposes. The development of textbooks for English courses 3 with English content for specific purposes will include information technology that will help students learn independently with the support of mobile assisted language learning. These materials will help students develop 4 skills in English, namely, reading, speaking, listening and writing. This study uses research and development (R&amp;D) method, where the final product is an ISBN textbook for English courses 3. The steps of this research go through 6 stages, namely ; first, collect initial data, then plan the product, then carry out initial product development, the next stage is to conduct initial trials, then make several revisions to the book content, and conduct field tests. The 3rd semester students of the Informatics Engineering Study Program at Pamulang University in 2020/2021 are the subjects of this research.Keywords: Development; teaching materials; English for Specific Purposes; technology
Network-centric Empirical Analysis of Bitcoins cryptocurrency organization

Bitcoins framework (also known as Bitcoins cryptocurrency) is a distributed and decentralized cryptocurrency installment framework that utilizes cryptographic money called bitcoins (BTCs) and was delivered as free and open-source as well as free to use programming in the year 2009 [1]. Bitcoins stage has drawn in both several users which can be categorized as social and against social (anti-social or illegal) components. To see and study how the social and against social inclinations in the client community of Bitcoins influence its development, there is an urgent need to break down the Bitcoins framework as an organization. The current research paper plans to investigate the neighborhood geography and math of the Bitcoins cryptocurrency network as it completes its first decade of presence and achieves nearly a trillion dollar brand value. Bitcoins exchange information was handled for this reason to fabricate a Bitcoins client chart. The qualities, neighborhood and worldwide organization properties of the client’s chart were investigated at ten spans. Little measurement, slanted circulation of exchanges, power-law dispersed in and out degrees, detached chart, and availability of enormous associated parts were the perceptions from network or graph examination.
Critical Infrastructure Protection and Supply Chain Risk Management

Critical infrastructure is a key area in cybersecurity. In the U.S., it was front and center in 1997 with the report from the President’s Commission on Critical Infrastructure Protection (PCCIP), and now affects countries worldwide. Critical Infrastructure Protection must address all types of cybersecurity threats - insider threat, ransomware, supply chain risk management issues, and so on. Unsurprisingly, in the past 25 years, the risks and incidents have increased rather than decreased and appear in the news daily. As an important component of critical infrastructure protection, secure supply chain risk management must be integrated into development projects. Both areas have important implications for security requirements engineering.
Implementasi Metode Convolutional Neural Network Untuk Pengenalan Pola Motif Kain Tenun Rote Ndao Berbasis Android

Rote ndao Ikat Weaving has interesting characteristics in each fabric motif because it has different motifs which indicate the ethnic differences contained in each of the resulting motifs. Rote Ndao weaving has a variety of motifs that are still unknown to many people, so in this study a classification of motifs of rote ndao woven fabrics was carried out using the Convolutional Neural Network method. Weaving motif classification uses 3 motifs with a total of 1050 data including 70 data for Ai Bunak, Dula Kakaik and Lafa Langgak motifs each. Data for 3 fabric motifs is divided into 80% training data and 20% testing data. The classification of the Rote Ndao Weaving motif is carried out by building an architectural model of MobileNetV2 plus Dropout and using a Learning Rate of 0.0003 which is trained and evaluated using K-Fold Cross Validation with a value of K=5, obtaining an accuracy of 93%; The precision is 94% for the Ai Bunak motif, 88% for the Dula Kakaik motif, and 100% for the Lafa Langgak motif. Recall of 87% for the Ai Bunak motif, 94% for the Dula Kakaik motif and 100% for the Lafa Langgak motif. Then the F-Score value obtained is 90% for the Ai Bunak motif, 91% for the Dula Kakaik motif and 100% for the Lafa Langgak motif.
Usability Testing Pada Software Line Messenger

This study aims to perform Usability Testing on software or freeware applications, namely LINE Messenger. Usability Testing itself is a method of evaluating the usability of software (Software) which aims to increase the usability of an application / product by analyzing, identifying problems, measure efficiency, measure convenience and determine user satisfaction. Usability testing for the LINE Messenger application is carried out to determine the level of ease of use of the Line application, such as ease of understanding features, memory location of features, and also assessing the User Interface (UI).&#x0D; to the application, preparing test scenarios, looking for respondents or testing subjects, making questionnaires with the System Usability Scale (SUS) standard, and conducting usability analysis on the results of respondents and questionnaires. Then the final output is in the form of reports and conclusions regarding the results of the analysis. LINE Messenger itself is a popular social media application, an application that has many features such as LINE Today, Share screen and also has a LINE Shop. LINE itself is an easy-to-use application, with the results of the questionnaire showing positive Usability Testing results for LINE Messenger.
On the effect of the number of photons on the generation and transfer of entangled states between toroidal cavities via artificial atoms

We present an efficient scheme for the generation of entangled states of two spatially separated whispering-gallery-mode (WGM) micro-resonators which are coupled via 2 two-level atoms. Using an atom chain as bridges, we explore the possibility of generation, transfer as well as distributing quantum entanglement between the two cavities. We show that, for an initial preparation with the system having only one photon, the atoms can become periodically (and maximally) entangled while the intra-cavity modes in each cavity become periodically (partially) entangled. Interestingly, if the cavities are initially prepared with two photons, the dynamics can be tuned in such a way that the intra-cavity modes in each cavity become periodically entangled, reaching maximum entanglement, while the atoms remain unentangled during all time.
Comparison of Acquisition Results on iPhone 7 Plus (iOS 14.8.1) between Jailbreaking vs Non-Jailbreaking Device

Apple products have been increasingly popular in individual families and businesses over the last 20 years. It was out of a greater desire to learn how to obtain an apple device in a forensic manner for law enforcement. Our research focuses on finding answers to whether the use of jailbreaking techniques can be forensically used to equip data acquisition process on iOS 14.8.1. The methodology of National Institute of standards and technology (NIST) is referred to guide the digital investigation process on mobile device and the MOBILedit Forensic Express tool is used to acquire the potential data from the jailed and jailbreak iDevice. The result shows that more data can be acquired from the jailbreak phone and their data integrity is well preserved.
Recognition of Graphological Wartegg Hand-Drawings

Wartegg Test is a drawing completion task designed to reflect the personal characteristics of the testers. A complete Wartegg Test has eight 4 cm $$\times $$ 4 cm boxes with a printed hint in each of them. The tester will be required to use pencil to draw eight pictures in the boxes after they saw these printed hints. In recent years the trend of utilizing high-speed hardware and deep learning based model for object detection makes it possible to recognize hand-drawn objects from images. However, recognizing them is not an easy task, like other hand-drawn images, the Wartegg images are abstract and diverse. Also, Wartegg Test images are multi-object images, the number of objects in one image, their distribution and size are all unpredictable. These factors make the recognition task on Wartegg Test images more difficult. In this paper, we present a complete framework including PCC (Pearson’s Correlation Coefficient) to extract lines and curves, SLIC for the selection of feature key points, DBSCAN for object cluster, and finally YoloV3-SPP model for detecting shapes and objects. Our system produced an accuracy of 87.9 $$\%$$ for one object detection and 75 $$\%$$ for multi-object detection which surpass the previous results by a wide margin.
The Quadrature of the Governance Triangle: on the Heritage of Idealism and Prometheus’ myth

In this paper, the historical, philosophical and political roots of binary thinking are analyzed. The influence of a religious or ideological hegemony of symbolic nature, on patterns of thinking in philosophy, science and in other aspects of human interest are critically examined. Starting from the Foucauldian merger of biopolitics and state sovereignity – after a major world pandemic crisis – and a post-deconstructivist analysis of the role of written language and academic literacy, a closer look at contemporary developments is offered. In particular, the heritage of Idealism is investigated in the present notions of universal mathematics and loopholes claiming the unification of physics and mathematics and the digitalization and algorithmic quantification of all aspects of human life and culture. In contrast to these developments, we propose a renewed approach of reading and experiencing symbols in patterns of interpersonal communication, with special reference to the phenomenon of music.
Explainability in a Time of Socially Responsible Software

[Context & Motivation] Satisficing Explainability, as a Non-Functional Requirement, is posed to be an increasing social demand. [Question/Problem] Exploring how this quality should be amalgamated into software production is a new avenue of research. [Principal ideas/Results] Using the perspective of intentional modeling, we performed a first probe of challenges for the design of a futuristic kitchen. [Contribution] This paper targets challenges for building socially responsible software by exploring the modeling of ffituristic systems from the point of view of Non-Functional Requirements, in particular of Explainability.
Constructing New Representative Collective Signature Using the GOST R34.10-2012

A representative collective signature is a signature created by a collective of multiple signing groups. The basic requirement for this signature is that it must include information about all participants involved in the signing process of a given document. The U component in the 3-component collective signature (including U, E, S) is used to satisfy this requirement. In this paper, we propose a new form of representative collective signature consisting of only two components (e, s), then, the information of all signers is contained in the pseudo-random parameter R. The purpose of this is both to reduce the size of the signature, as well as ensure that the manager of the signing group has enough information to identify the signer and to prevent "disclaimer" during a dispute. In the proposed collective signature scheme, we use the GOST R34.10-2012 digital signature standard to develop a consensus group signature scheme based on the discrete logarithm problem on the Elliptic curve. This scheme allows the generation of a representative collective signature: i) Only 512 bits in length, but still achieves security level 2512 and ii) Significantly reduced computational performance (in comparison to the representative collective signature that represents the three components).
LFM-C: A Friend Recommendation Algorithm for Campus Mutual Aid System

At present, the campus mutual aid system in colleges and universities is increasingly prevalent, but generally, such systems lack the function of customized friend recommendations. Based on the LFM algorithm and the cosine similarity algorithm, a friend recommendation algorithm, LFM-C, is proposed in this paper. Taking the current students and alumni as data sets, this algorithm establishes connections between current students and alumni and effectively recommends the alumni who graduated from the majors at the universities that are of interest to the current students. The algorithm gives full play to the role of alumni as a mentor and helps students who are preparing to pursue postgraduate studies. Experiments show that the LFM-C algorithm is more accurate and efficient than User-CF.
SHARING INNOVATION – THE KEY TO SUCCESSFUL EDUCATION

The present work is dedicated to the presentation of good educational practices, including methods and means of implementing innovations in the educational process. Exemplary school projects are presented, which are based on the principles of the STEM approach, combined with the use of digital tools from various fields. These project activities are suitable for implementation in the learning process both in face-to-face and distance learning. The innovative practices presented are in line with a large part of the recommendations set out in the framework for the learning skills needed in the 21st century (Learning &amp; Innovation Skills – 4Cs). They enable the development of communication and collaboration skills, the creation of digital content, the development of critical thinking and problem solving, as well as the development of creativity and innovation. The described methods and tools are used in the preparation of teachers in various qualification courses conducted by the Department for Qualification and Professional Development of Pedagogical Specialists at Paisiy Hilendarski Polytechnic, Plovdiv. The teaching practices presented are based on the results of a three-year study of already trained teachers, who try them daily in the learning process and notice their positive impact on students.
Modifikasi Algoritma Ant Colony Optimization Dalam Menentukan Rute Pengisian Mesin ATM

The TSP problem is known as a non-deterministic polynomial-hard (NP-Hard) problem. In its solution, TSP can be solved using swarm intelligence algorithms such as Artificial Bee Colony (ABC), Partical Swarm Optimization (PSO), dan Ant Colony Optimization (ACO). In this study, TSP settlement was carried out using the ACO algorithm because the amount of data was less than 80 data. In addition, modifications were made to the ACO algorithm with the aim of optimizing the probability in node selection by put in Fuzzy C-Means algorithm into the ACO algorithm. &#x0D; Based on the result application of the Modified Ant Colony Optimization algorithm, the distance covered is 101.712 Km when the parameter optimization has been carried out, with parameter values alpha = 5, beta = 0, rho = 0.3, number of ants = 31, dan maximum iteration = 100. Where each parameter has its own role, such as the Intensity Controlling Constant (alpha) which makes the ants only care about the pheromone intensity value without caring about the distance value between points so that the diversity of the paths found gets smaller when the value alpha gets bigger, Visibility Controlling Constant (beta) which affects the diversity of routes produced by each ant where when beta = 0 then the route chosen by each ant varies and when beta &gt; 0 has the possibility for the route that has been selected to be re-elected by other ants so that the diversity of routes found getting smaller, while for the Ant Track Control Constant (rho) it has an influence in determining the next destination point when the value of gets bigger. In addition, the Modified Ant Colony Optimization algorithm has the advantage of accelerating convergence in finding the shortest route.
Three Dimensional Route Planning of UAVs based on Velocity Potential Field Method

With the continuous expansion of the application field of UAV, high-speed 3D(three-dimensional) obstacle avoidance is one of the important problems that must be considered. In this paper, a new artificial potential field(APF) function is specially designed for dynamic path planning for high-speed obstacles whose speed is greater than the UAV. The theory of velocity potential field method is proposed to change the direction of resultant force, that is, add a repulsion force in the repulsion field that is perpendicular to the speed of obstacles and the speed of UAV itself. The improved velocity potential field method is simulated and compared with the original potential field method. The results show that the velocity potential field method can avoid high-speed obstacles with different speeds faster and better, and only the velocity potential field method can make the UAV avoid obstacles whose speed is greater than itself. It proves the advantage of the velocity potential field method in avoiding high-speed obstacles.
ICT Literacy for Indonesian Workers in Singapore

Information and communication technology (ICT) has become an essential aspect of modern life. Everybody has to deal with ICT, especially for work. In Asia, ICT skills involve five main aspects: software development, ICT project management, enterprise architecture design, network and system administration, and information system and network security. Every year Indonesia sends workers to Singapore. In contrast, most of those workers are skilled workers for the household which their job responsibilities are taking care of the house, babysitting, taking care of the elderly and drivers. However, some of them have ICT skills, and some others do not have them. Therefore, Universitas Negeri Jakarta conducted a webinar on "the success key of digital technology utilization" to enhance the Indonesia Worker's comprehension of ICT literacy, which was participated by 210 Indonesian workers in Singapore. The webinar was divided into three parts, pre-test, speaker presentation, and post-test. The results showed that there was an increment of participant comprehension on ICT literacy after the webinar.