Reviewerly/exHarmony huggingface dataset:
Pengujian Black Box pada Aplikasi Perpustakaan Menggunakan Teknik Equivalence Partitions

The library application is used to help manage and document transaction activities in the library which include borrowing and repaying. Library applications must be free of errors, because if they contain errors can cause harm to providers, managers, or members of the library. To provide a guarantee that the library application is free from errors, testing needs to be done. Software testing is an activity aimed at finding and finding errors and bugs in an application, which aims to minimize the losses that occur due to system errors. In this study, the proposed library application testing is Black Box. Black Box Testing is a test based on the appearance (interface) and functions of the software itself and not from the source code of the program. Black Box Testing has several methods, one of which is Equivalence Partitions, the method we use for testing the software. Equivalence Partitions are methods that discuss valid or not entered into the software, and observe the accuracy of the input. So that the side of the error is known. The test results have proven that the library application that has been developed is error free and meets all the requirements set.
Path Planning Optimization of a Mobile Robot based on Intelligence Algorithm

Abstract Motion planning is an important topic for researchers working in the field of autonomous robots, it finds an optimal feasible path from start to target point with avoiding the collision, this paper aims to improve motion planning of mobile robot by particle swarm optimization as a method for finding the collision-free optimal path. The objectives considered in this research for optimization are optimal static navigation path with taking into consideration the affect population size on performance for the algorithm to find the optimal path through various environments with population sizes 100, 80, 40, 20. The simulate and evaluate the proposed algorithm proved no strong affected to population size parameter on the optimal path length and its points, hence we can use a small population size for the minimum time in finding the optimal path between start point to goal point with colliding avoidance.
Unsupervised <i>K</i> -modal styled content generation

The emergence of deep generative models has recently enabled the automatic generation of massive amounts of graphical content, both in 2D and in 3D. Generative Adversarial Networks (GANs) and style control mechanisms, such as Adaptive Instance Normalization (AdaIN), have proved particularly effective in this context, culminating in the state-of-the-art StyleGAN architecture. While such models are able to learn diverse distributions, provided a sufficiently large training set, they are not well-suited for scenarios where the distribution of the training data exhibits a multi-modal behavior. In such cases, reshaping a uniform or normal distribution over the latent space into a complex multi-modal distribution in the data domain is challenging, and the generator might fail to sample the target distribution well. Furthermore, existing unsupervised generative models are not able to control the mode of the generated samples independently of the other visual attributes, despite the fact that they are typically disentangled in the training data. In this paper, we introduce uMM-GAN, a novel architecture designed to better model multi-modal distributions, in an unsupervised fashion. Building upon the StyleGAN architecture, our network learns multiple modes, in a completely unsupervised manner , and combines them using a set of learned weights. We demonstrate that this approach is capable of effectively approximating a complex distribution as a superposition of multiple simple ones. We further show that uMM-GAN effectively disentangles between modes and style, thereby providing an independent degree of control over the generated content.
Artificial Software Complex "Artificial Head". Part 1 Adjusting the Frequency Response of the Path

In this paper, the technology of correction of the frequency response of the measuring path of the hardware-software complex "Artificial head", intended for acoustic examination of the rooms, has been developed. This correction is necessary because the amplitude-frequency response of the loudspeaker and the microphone are not perfectly uniform in the frequency band of analysis. Therefore, instead of the room impulse response, the convolution of the room impulse response with the impulse responses of the loudspeaker (test signal source) and the microphone will actually be evaluated. It is shown that such correction can be made by controlled dividing the frequency response of the loudspeaker-room-microphone system by the previously obtained estimate of the amplitude-frequency response of the loudspeaker-microphone subsystem.The problem with such calculations is the division operation, because the amplitude-frequency response of the loudspeaker-microphone subsystem may contain small numerical values, which will overflow the discharge grid of the computing system and crash the computer. However, it is clear that if proper control over the amplitude-frequency characteristics of the loudspeaker-microphone subsystem is ensured, such a division can be practically implemented.Since the amplitude-frequency response of the subsystem "loudspeaker-microphone" takes the smallest values at the edges of the frequency range, and the variance of the evaluation of the mutual spectrum of the system "loudspeaker-room-microphone" is the largest on the right edge of the frequency range, it is advisable to apply the method of regularization to achieve necessary calculation accuracy. In this case, the role of the regularizing factor can be played by a spectral weighting window whose values are close to one at low and medium frequencies, and with the approaching to the right edge of the frequency range, the values of this window are close to zero. The role of the regularization parameter is thus the width of such a weighting window.The nature and value of such correction effect on the accuracy of the room impulse response estimate are analyzed in this paper. It is shown that the Hann (Hanning) window can be used as a regularizing factor, while the width value of this window was experimentally found, which provides satisfactory properties for evaluating the room impulse response. It has been also shown that the width of the Hann window, which is close to 80% of the total frequency range analyzed, is satisfactory for practical applications.
Pedagogical Conditions for the Development of Self-Educational Competence of Future Specialists in the Study of Professional Subjects

The content of the categories “self-education”, “self-educational competence” is analysed. The need for the development of self-educational competence of future specialists in the process of studying professional subjects is actualized. The pedagogical conditions for the formation of self-educational competence of future specialists in the study of professional subjects are determined. Such factors include: motivational and value attitude of future specialists to independent learning and cognitive activities in the process of professional training; ensuring the relationship of all areas of professional training of future specialists (theoretical, methodological, practical), which involves the formation of self-educational competence; development and implementation of educational and methodological support for the development of self-educational competence of students; the use of interactive technologies in teaching professional subjects to build educational dialogue. An experimental verification of the effectiveness of implementation of certain pedagogical conditions. For this purpose, a pedagogical experiment was organized. The conclusion that students of control and experimental groups have significant differences due not to random factors, but to a certain natural reason - conducting research and experimental work on the implementation of pedagogical conditions for the development of self-educational competence of future specialists in the study of professional subjects. Statistical analysis of indicators of transition of students to a higher level of self-educational competence shows that the process of formation of self-educational competence in students of the experimental group is more effective than in students of the control one.
TWO-STREAM CONVOLUTIONAL NETWORK FOR DYNAMIC HAND GESTURE RECOGNITION USING CONVOLUTIONAL LONG SHORT-TERM MEMORY NETWORKS

Human action and gesture recognition provides important and worth information for interaction between human and device ambient that monitors living, healthcare facilities or entertainment activities in smart homes. Recent years, there were many machine learning model application studies to recognize human action and gesture. In this paper, we propose a dynamic hand gesture recognition system in video based on two stream-convolution network (ConvNet) architecture. Specifically, we research the state-of-the-art approaches using to recognize dynamic hand gesture in video and propose an improvement method to enhance performance of model which is suitable for uses such as indoor environment in this paper. Our contribution is improvement of two stream ConvNet to achieve better performance. The results show that the proposal model improves execution speed and memory resource usage comparing to existing models.
A Multi-Keyword Searchable Encryption Scheme Based on Probability Trapdoor over Encryption Cloud Data

With the rapid development of cloud computing, massive data are transferred to cloud servers for storage and management savings. For privacy concerns, data should be encrypted before being uploaded. In the encrypted-domain (ED), however, many data computing methods working in the plain-domain are no longer applicable. Data retrieval has become a significant obstacle to cloud storage services. To break through this limitation, we propose a multi-keyword searchable encryption scheme by introducing probability trapdoors. Firstly, a keywords probability trapdoor is established to ensure that the scheme can resist indistinguishable attacks. Based on the keywords trapdoor, we present the keywords vector to make the scheme realize multi-keyword search in the process of data retrieval in the ED. Both security and performance analysis confirm the advantages of the proposed scheme in terms of search functionality and complexity.
Optimization of Oral English Teaching System Based on Computer-aided Technology

With the development and progress of society, consumers are more and more inclined to choose personalized and rich products.In order to meet the needs of people's increasingly rich material and cultural products, the designed products must not only have functional practicality and beautiful appearance, but also be able to meet the internal personalized needs of consumers.The introduction of experiential teaching in computer-aided graphic design courses is mainly for students to design products with rich connotation and personalization based on mastering the technology of computer-aided graphic design and combining with practice.In experiential teaching, the starting point and end point of our teaching reform is to closely combine classroom teaching of design performance techniques with professors of design theory knowledge, while focusing on cultivating and enhancing students' practical innovation ability and personalized design level.And then achieve the purpose of training high-quality composite design talents.
Perception and Acceptance of Padlet as a Microblogging Platform for Writing Skills

&lt;p class="Abstract"&gt;This research is intended to answer the question, how are the students' perceptions of internet technology in learning and how is the acceptance of Padlet as a &lt;em&gt;microblogging &lt;/em&gt;platform for writing skills in German language level A2-B1 CEFR standards for the student. In summary, 21 students within the range of 19-22 years participated, which consisted of 2 males and 19 females - data obtained through opened and closed questionnaires. The results of data analysis showed that students had positive perceptions using internet technology in learning. However, students cannot accept Padlet as a microblogging&lt;em&gt; &lt;/em&gt;platform in learning German writing skills due to several factors that influence it. This research has an essential finding: before conducting online learning, lecturers have to consider internet availability and the adequacy of reviews to their smartphones as a learning infrastructure.&lt;/p&gt;
Modifying Method of Constructing Quantum Codes From Highly Entangled States

There is a connection between classical codes, highly entangled pure states (called <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$k$ </tex-math></inline-formula> -uniform or absolutely maximally entangled (AME) states), and quantum error correcting codes (QECCs). This leads to a systematic method to construct stabilizer QECCs by starting from a <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$k$ </tex-math></inline-formula> -uniform state or the corresponding classical code and tracing out one party at each step. We provide explicit constructions for codewords, encoding procedure and stabilizer formalism of the QECCs by describing the changes that partial traces cause on the corresponding generator matrix of the classical codes. We then modify the method to produce another set of stabilizer QECCs that encode a logical qudit into a subspace spanned by AME states. This construction produces quantum codes starting from an AME state without tracing out any party. Therefore, quantum stabilizer codes with larger codespace can be constructed.
A Survey of Cybersecurity Risk Management Frameworks

Organizations are faced with a clear need for increasing the maturity of their cybersecurity capabilities to keep pace with the ever-evolving cyber threats and accelerated institutional digitalization driven by financial reward and competitive edge. In this context, organizations acknowledge the importance of strengthening their cybersecurity programs to protect critical business processes along with the confidentiality, availability, and integrity of information and information systems through people, processes, and technology by preventing, detecting, and responding to cyber attackers resorting to sophisticated cyber tactics, techniques, and procedures (TTPs). Meanwhile, national and international standardization bodies reacted through the development of various cybersecurity risk management frameworks and standards that can be leveraged by organizations while maturing their cybersecurity capabilities. In a nutshell, this paper aims to provide a critical evaluation of several widespread cybersecurity risk management frameworks adopted by organizations to alleviate cyber risks. The paper starts with an introduction about the key drivers for adopting a cybersecurity risk management framework within organizations. Further, the paper gives an overview of several well-renowned cybersecurity risk management frameworks and related standards, methods and methodologies. Furthermore, the paper defines the evaluation criteria used for comparing frameworks and provides a holistic evaluation of selective cybersecurity risk management frameworks aiming to support decision-making with respect to framework selection, facilitate pragmatic implementation of cybersecurity programmes, and help organizations cope with cybersecurity risks. Finally, the paper presents the concluding remarks.
Optimization of Computer-aided Teaching Network Management System for College Physical Education Courses

With the development and progress of society, consumers are more and more inclined to choose personalized and rich products.In order to meet the needs of people's increasingly rich material and cultural products, the designed products must not only have functional practicality and beautiful appearance, but also be able to meet the internal personalized needs of consumers.The introduction of experiential teaching in computer-aided graphic design courses is mainly for students to design products with rich connotation and personalization based on mastering the technology of computer-aided graphic design and combining with practice.In experiential teaching, the starting point and end point of our teaching reform is to closely combine classroom teaching of design performance techniques with professors of design theory knowledge, while focusing on cultivating and enhancing students' practical innovation ability and personalized design level.And then achieve the purpose of training high-quality composite design talents.
Abnormal activity detection in surveillance video scenes

Automated detection of abnormal activity assumes a significant task in surveillance applications. This paper presents an intelligent framework video surveillance to detect abnormal human activity in an academic environment that takes into account the security and emergency aspects by focusing on three abnormal activities (falling, boxing and waving). This framework designed to consist of the two essential processes: the first one is a tracking system that can follow targets with identify sets of features to understand human activity and measure descriptive information of each target. The second one is a decision system that can realize if the activity of the target track is "normal" or "abnormal” then energizing alarm when recognized abnormal activities.
Understanding, Supervision, Strategy and Acceptance Effect into the Blockchain Employment in Malaysia

Throughout history, the food industry has been responsible for several crises and, as the market becomes more global, it is difficult to keep information under control and confidence. As a result of food scandals, asymmetry in information increases customer awareness, as well as initiatives such as evidence to address problems. To increase transparency, the information infrastructure is continuously evolving and, more recently, blockchain technology has paid great attention to possible solutions to issues. Blockchain is an open, distributed and decentralized authentication system for digital transactions, where transaction data is stored securely in the so-called blocks that make up a network. In order to obtain effective food retail, it is necessary to monitor specific product information in the food retail industry.The study concludes that blockchain technology is still immature for food retail, and the biggest challenge is to create a culture that promotes collaboration, exchange of information and easy-to-accept standardization. However, the blockchain technology allows safe and transparent tracking functions, with traceability and a framework that can save costs and the environment when removing a product. In addition, to be willing to cooperate and make time and effort in new implementations, it is essential to find the real value of the application for all interested parties.
Integrity Monitoring of Multimodal Perception System for Vehicle Localization

Autonomous driving systems tightly rely on the quality of the data from sensors for tasks such as localization and navigation. In this work, we present an integrity monitoring framework that can assess the quality of multimodal data from exteroceptive sensors. The proposed multisource coherence-based integrity assessment framework is capable of handling highway as well as complex semi-urban and urban scenarios. To achieve such generalization and scalability, we employ a semantic-grid data representation, which can efficiently represent the surroundings of the vehicle. The proposed method is used to evaluate the integrity of sources in several scenarios, and the integrity markers generated are used for identifying and quantifying unreliable data. A particular focus is given to real-world complex scenarios obtained from publicly available datasets where integrity localization requirements are of high importance. Those scenarios are examined to evaluate the performance of the framework and to provide proof-of-concept. We also establish the importance of the proposed integrity assessment framework in context-based localization applications for autonomous vehicles. The proposed method applies the integrity assessment concepts in the field of aviation to ground vehicles and provides the Protection Level markers (Horizontal, Lateral, Longitudinal) for perception systems used for vehicle localization.
Gradient-based Learning Methods Extended to Smooth Manifolds Applied to Automated Clustering

Grassmann manifold based sparse spectral clustering is a classification technique that consists in learning a latent representation of data, formed by a subspace basis, which is sparse. In order to learn a latent representation, spectral clustering is formulated in terms of a loss minimization problem over a smooth manifold known as Grassmannian. Such minimization problem cannot be tackled by one of traditional gradient-based learning algorithms, which are only suitable to perform optimization in absence of constraints among parameters. It is, therefore, necessary to develop specific optimization/learning algorithms that are able to look for a local minimum of a loss function under smooth constraints in an efficient way. Such need calls for manifold optimization methods. In this paper, we extend classical gradient-based learning algorithms on at parameter spaces (from classical gradient descent to adaptive momentum) to curved spaces (smooth manifolds) by means of tools from manifold calculus. We compare clustering performances of these methods and known methods from the scientific literature. The obtained results confirm that the proposed learning algorithms prove lighter in computational complexity than existing ones without detriment in clustering efficacy.
La comunicación y la interacción como aspectos clave de los entornos personales de aprendizaje: Perspectiva de estudiantes costarricenses de educación

Thanks to the proliferation of new information and communication technologies, and through increasingly global internet access, significant changes are being made in both the way we work in the classroom and in the relationships generated by the educational community; this calls for further development of communicative skills as key components of personal learning environments (PLE). This research aims to analyze the tools that Costa Rican education students know and use; it also examines the activities and mechanisms the students generate with their use to promote the communication processes to different levels. From a quantitative approach, and under a non-experimental design, information from a sample of 421 students is collected through a questionnaire composed of different scales. The main tools used to share information are social networks, email, and mobile apps; other resources are largely unknown. The main activities are linked to sending emails, communicating through chat applications, and using the Learning Management System (LMS). The vast majority of students (41.7%) indicate that they use the tools to share information and learn from others; although, it is worth highlighting that a high percentage (20%) does not use them for any of the options mentioned. It is necessary and urgent to stimulate and enrich students’ PLEs so that they can make the most of the resources available to facilitate their learning and develop their communication skills.