Reviewerly/exHarmony huggingface dataset:
An Hierarchical Latent Variable Model Of Synergistic Transformational Leadership Using Pls-Sem And Its Impact On Knowledge Sharing And Sustainability Organization Performance In Private Universities

Strengthening organizational performance through synergistic transformational leadership and knowledge sharing is needed to trigger the implementation of the duties and functions of lecturers to be more dynamic, innovative, and productive in carrying out the tri-dharma activities of higher education.However, on the other hand, the latent construct of synergistic transformational leadership has never been studied in previous journals and literacy.This study proposes a new concept of synergistic transformational leadership, combining transformational and synergistic leadership.For this reason, this research is expected to provide practical and academic contributions that can broaden the research boundary of leadership literacy.The data in this study were obtained from 380 permanent lecturers with available positions at LLDIKTI region III, Jakarta.The data in this study were analyzed using the Hierarchical Component Models (HCMs) approach in exploring and combining two constructs between synergistic and transformational leadership into a new latent variable, namely, synergistic transformational leadership.The results of this study are expected to be used as a reference for both the academic and practical worlds.
Application of Embedded Voice And Digital Forensics System In Financial Cost Management In Biotech Companies.

Financial cost management is a critical component of business operations in the biotech industry. Embedded voice and digital forensics systems are emerging technologies that can improve the efficiency and effectiveness of financial cost management. This abstract explores the application of embedded voice and digital forensics systems in financial cost management in biotech companies. The study highlights the potential of these technologies to enable real-time monitoring and analysis of financial transactions, enhance fraud detection and prevention, and optimize financial cost management. The study reviews the various applications of embedded voice and digital forensics systems in biotech companies, such as invoice processing, expense tracking, and vendor management. The study examines the benefits of using these technologies in financial cost management, such as improved accuracy and efficiency, reduced costs, and enhanced data security. The study also discusses the challenges of implementing embedded voice and digital forensics systems in biotech companies, such as data integration, system interoperability, and organizational resistance to change. The study concludes that embedded voice and digital forensics systems are valuable tools for financial cost management in biotech companies, enabling real-time monitoring and analysis of financial transactions, enhancing fraud detection and prevention, and optimizing financial cost management. The integration of these technologies in biotech companies can improve operational efficiency, reduce costs, and enhance data security, ultimately contributing to the growth and success of the biotech industry.
Lexical Density in EFL Indonesian Textbooks: A Comparative Analysis

The lexical density is known as the component determining the complexity level of the text. Hence, measurement of lexical density is needed to find out how challenging a particular text is to read. However, it is important to know that the lexical density in English reading materials especially in Indonesian EFL textbooks between the Government Publisher and Non-Government Publisher is still less explored. This research will employ the Quantitative design to investigate how dense the lexical items are found in these two EFL Textbooks. The result showed that the lexical density of the non-government textbook is denser in all of the genres of the text compared to the government textbooks. In brief, by knowing the lexical density in the text, the teacher should have known what the appropriate text level should be taught to the students which is neither too low nor too high.
Vision-based biomechanical markerless motion classification

This study used stick model augmentation on single-camera motion video to create a markerless motion classification model of manual operations. All videos were augmented with a stick model composed of keypoints and lines by using the programming model, which later incorporated the COCO dataset, OpenCV and OpenPose modules to estimate the coordinates and body joints. The stick model data included the initial velocity, cumulative velocity, and acceleration for each body joint. The extracted motion vector data were normalized using three different techniques, and the resulting datasets were subjected to eight classifiers. The experiment involved four distinct motion sequences performed by eight participants. The random forest classifier performed the best in terms of accuracy in recorded data classification in its min-max normalized dataset. This classifier also obtained a score of 81.80% for the dataset before random subsampling and a score of 92.37% for the resampled dataset. Meanwhile, the random subsampling method dramatically improved classification accuracy by removing noise data and replacing them with replicated instances to balance the class. This research advances methodological and applied knowledge on the capture and classification of human motion using a single camera view.
Measuring Knowledge Transfer in Innovation Projects: A Comparative Analysis

Collaboration of organizations with universities and research institutes is a way of decreasing not only the time but also the cost of R&amp;D activities in innovation projects. This paper is a study on knowledge transfer measurement models in order to analyze their metrics and identify the use of techniques for measuring the flow of knowledge between companies, public research institutes, and universities in national innovation surveys. The comparative analysis of these models is part of a study to evaluate the ways to measure the impact of universities on society through innovation projects.
High Dynamic Range Dual-Modal White Light Imaging Improves the Accuracy of Tumor Bed Sampling After Neoadjuvant Therapy for Breast Cancer

Accurate evaluation of residual cancer burden remains challenging because of the lack of appropriate techniques for tumor bed sampling. This study evaluated the application of a white light imaging system to help pathologists differentiate the components and location of tumor bed in specimens.The high dynamic range dual-mode white light imaging (HDR-DWI) system was developed to capture antiglare reflection and multiexposure HDR transmission images. It was tested in 60 specimens of modified radical mastectomy after neoadjuvant therapy. We observed the differential transmittance among tumor tissue, fibrosis tissue, and adipose tissue.The sensitivity and specificity of HDR-DWI were compared with x-ray or visual examination to determine whether HDR-DWI was superior in identifying tumor beds. We found that tumor tissue had lower transmittance (0.12 ± 0.03) than fibers (0.15 ± 0.04) and fats (0.27 ± 0.07) (P < .01).HDR-DWI was more sensitive in identifying fiber and tumor tissues than cabinet x-ray and visual observation (P < .01). In addition, HDR-DWI could identify more fibrosis areas than the currently used whole slide imaging did in 12 samples (12/60). We have determined that HDR-DWI can provide more in-depth tumor bed information than x-ray and visual examination do, which will help prevent diagnostic errors in tumor bed sampling.
Explainable AI for sensor-based sorting systems

Abstract Explainable artificial intelligence (XAI) can make machine learning based systems more transparent. This additional transparency can enable the use of machine learning in many different domains. In our work, we show how XAI methods can be applied to an autoencoder for anomaly detection in a sensor-based sorting system. The setup of the sorting system consists of a vibrating feeder, a conveyor belt, a line-scan camera and an array of fast-switching pneumatic valves. It allows the separation of a material stream into two fractions, realizing a binary sorting task. The autoencoder tries to mimic the normal behavior of the nozzle array and thus can detect abnormal behavior. The XAI methods are used to explain the output of the autoencoder. As XAI methods global and local approaches are used, which means we receive explanations for both a single result and the whole autoencoder. Initial results for both approaches are shown, together with possible interpretations of these results.
MobileNetV3-based Automatic Modulation Recognition for Low-Latency Spectrum Sensing

The cognitive radio senses and tracking the spectrum of frequency and allocate dynamically secondary users in spectral holes. Automatic modulation recognition provides preliminary information to assist in spectrum sensing. This letter proposes a MobileNetV3 for the task of modulation recognition. The MobileNetV3 is a recent network that achieved higher accuracy rates with less computation cost. Experiments showed that the proposed framework achieved higher accuracy than other state-of-art techniques in a comparable latency, which 5G and 6G required.
Our War Game

Capture the flag (CTF) is a competitive game in which players mimic the discovery and exploitation of vulnerabilities in information systems. As a kind of hacker eSport, CTF competitions are a distinct example of what Sonia Fizek and Anne Dipple describe as “laborious play” the rigorous application of knowledge-intensive labour in a game or game-like context, often distinctly serious in the real-world application of knowledge sometimes described as “serious play”. This chapter proves that the laborious play of CTF has a specific function, that the game’s design and play reflect a kind of knowledge transfer, in which hacker practice and knowledge informs the work of information security through participation in such a competition. In support of this argument and observations, it utilizes data collected from observation of three CTF competitions and 56 semi-structured interviews with CTF designers and players about their experiences with these games and its relationship to their work/studies in information security.
Listening to and Playing Along with the Soundscapes of Videogame Environments

This chapter offers a range of perspectives on the function of game sound in gameworld soundscape design and innovative approaches to composing, listening to, connecting with, and playing digital sonic environments in games. It outlines some of the genre conventions of soundscape design of game sound as it pertains to worldbuilding, how sonic environments shape players’ perceptions and engagement, and the ways players listen to sonic environments and sense the gameworlds they are immersed in through gameplay. Players listen to a range of sounds and musics, often simultaneously, that comprise the game sound of a game. When the player listens in games, they are not only listening to the extradiegetic soundtrack that plays in the background of a level, location, or region of a game. The underwater level waltz in Super Mario Bros is more than just a musical trope that establishes location; it is also a representation of Mario’s movements in water made audible.
Photo-Realistic 360$$^{\circ }$$ Head Avatars in the Wild

Delivering immersive, 3D experiences for human communication requires a method to obtain 360 $$^{\circ }$$ photo-realistic avatars of humans. To make these experiences accessible to all, only commodity hardware, like mobile phone cameras, should be necessary to capture the data needed for avatar creation. For avatars to be rendered realistically from any viewpoint, we require training images and camera poses from all angles. However, we cannot rely on there being trackable features in the foreground or background of all images for use in estimating poses, especially from the side or back of the head. To overcome this, we propose a novel landmark detector trained on synthetic data to estimate camera poses from 360 $$^{\circ }$$ mobile phone videos of a human head for use in a multi-stage optimization process which creates a photo-realistic avatar. We perform validation experiments with synthetic data and showcase our method on 360 $$^{\circ }$$ avatars trained from mobile phone videos.
Орчин цагийн солонгос хэлийг монгол, турк хэлтэй харьцуулсан судалгаа

Scientist G.I Ramstedt first suggests that the Korean language add to The Altaic language group in 1928, and proposed to add the Korean language to the Altaic language in 1934. But he began to doubt his first suggestion in 1950. To determine the origin and typology of a language, it is necessary to compare it with other languages. Therefore, in order to clarify the doubts of G.I. Ramstedt, I studied the Korean language from a modern point of view, comparing not only one, but also two languages which are Mongolian and Turkish, and tried to identify their similarities and differences. In addition, transitive verbs are inevitably related to vocative, so the distinction between vocative along transitive verbs is reflected in this research. Therefore, the meaning of my research lies in identifying the similarities and differences between the verbs of the three languages and deciphering their meanings.
Linear Codes from Two Weakly Regular Plateaued Balanced Functions

Linear codes with a few weights have been extensively studied due to their wide applications in secret sharing schemes, strongly regular graphs, association schemes, and authentication codes. In this paper, we choose the defining sets from two distinct weakly regular plateaued balanced functions, based on a generic construction of linear codes. Then we construct a family of linear codes with at most five nonzero weights. Their minimality is also examined and the result shows that our codes are helpful in secret sharing schemes.
Design and Build a Web-Based Service Information System at the Sejahtera Medika Clinic in Rangkasbitung

Clinic is a health service facility that provides individual health services providing basic or specific medical services, organized by more than one type of health and led by medical personnel. The service activities carried out are in the form of public services. So far, the service system at the Sejahtera Medika Clinic starts from patient registration, input patient data, diagnoses and prescribes, payments and reports data that still uses the manual method, namely bookkeeping using a ledger. This causes several obstacles that often hinder the clinical management, especially in obtaining data related to patient service information. For this reason, it is necessary to develop a system that utilizes computer technology with a guaranteed security system, then the data is stored in a database and stored automatically. The development method used in this research is the Waterfall method, where there are 5 stages, namely: Analysis, Design, Implementation, Testing and Maintenance. In the implementation using UML (Unified Modeling Language) tools including Use Case Diagrams, Activity Diagrams, Class Diagrams and Sequence Diagrams
Difficulties and Solutions of the Cultivation of Minor Languages Talents under the Background of "Belt and Road"

In the context of the "Belt and Road" initiative, the demand trend of national economic development for minor language talents is further enhanced.In order to ensure the further development of the "Belt and Road" initiative, national higher education departments need to continuously expand the quality of teaching in large and minor languages to meet the needs of market development.However, in the process of cultivating minor language talents, we still face certain difficulties, and need college education to constantly improve the educational model.This paper analyzes the difficulties of talent training in minor languages and tries to put forward countermeasures to optimize talent training to meet the demand for talent in minor languages in the context of the "Belt and Road" initiative.
A != B

We introduce object identities, equalities, equivalences. We assure correctness by introducing a distinct phase in which errors have to be discovered and rectified. We employ methods which guarantee that no errors will exist after such phase.
Sistem Layanan Sirkulasi Pada Perpustakaan Umum Dinas Perpustakaan dan Kearsipan Kota Payakumbuh

This study aims to describe the existing circulation service system at the Public Library of the Payakumbuh City Library and Archives Service. What will be seen or examined in this study are what circulation services are available, what are the service procedures, and the constraints and efforts to deal with the obstacles encountered in the service. The research method used is a descriptive method by taking data directly to the field. Data collection techniques used observation and documentation that were carried out during an internship at the Public Library of the Payakumbuh City Library and Archives Service. The results obtained are that the circulation services available at the Public Library of the Payakumbuh City Library and Archives Service include membership services, borrowing, returning and imposing sanctions. Service procedures are still carried out manually and the obstacles faced lie in the users and the tools used by librarians to help with their work.
Quantum state protection from finite-temperature thermal noise with application to controlled quantum teleportation

We propose a quantum state protection scheme via quantum feedforward control combined with environment-assisted measurement to protect arbitrary unknown initial states from the finite-temperature thermal noise (FTTN). The main strategy is to transfer the quantum system to a noise-robust state by weak measurement and feedforward control before the noise channel. Then we apply the environment-assisted measurement on the noise channel to select our desired damped states that are invertible to the initial state. After the noise channel, the reversal operations are applied to restore the initial state. We consider the protection of a single-qubit system, derive the analytical expressions of the success probability and the fidelity, and analyze the influence of key parameters on the performance of the proposed scheme. Unlike previous studies, there is no trade-off between the fidelity and the success probability in the proposed scheme; hence one could maximize them separately. Simulation results show that the proposed scheme can greatly improve the fidelity of the quantum state with a certain success probability. Moreover, the proposed scheme is successfully applied to improving the fidelity of controlled quantum teleportation through two independent FTTN channels from the perspective of protecting the shared entanglement.
Argument Mining: A Categorical Review

Argument mining is a complex arena built up on natural language processing as its fundamental engine. We may consider it as a specialized branch of natural language processing. There are various aspects involved in argumentation mining, which involve meaning of the input corpus; sentiment of the input corpus; extraction of evidence present in the input corpus; persuasiveness of the input corpus. Each of the aspect is very challenging and has its own presence. But when all of these are put together, these can solve real-world problems. Thereby, making argument mining a lucrative avenue of research. In this paper, we have studied and analyzed various papers with respect to argument mining and its related mechanisms. We have categorically separated various aspects of argument mining and summarized the usage of these aspects in studied papers.
Hackers and Their Companion Viruses Are An Increasing Problem, Especially on the Internet. What Are the Most Important Measurers for a Firm to Take to Protect Itself from This? Is Full Protection Feasible? Why or Why Not?

This article gives an overview of the many security measures that businesses may implement to protect themselves against hackers and malware. It describes how firewalls, antivirus software, intrusion prevention and detection systems, encryption, frequent software updates and patches, staff education and training, and backup and disaster recovery strategies may aid in the protection of a company's network and data. The article also emphasizes the significance of analyzing a company's risk and demands, as well as adhering to industry standards like HIPAA, SOC2, and PCI-DSS. While these methods can help limit risks, no security system is 100% dependable, thus it is critical to have a robust security strategy in place and collaborate with cybersecurity specialists.
ANALISIS KEMANDIRIAN BELAJAR SISWA KELAS XI SMK-SMAK BOGOR PADA PEMBELAJARAN PRAKTIK MIKROBIOLOGI SECARA E-LEARNING

Distance Learning (PJJ) using E-learning makes students feel bored, lazy and lacks motivation to learn so that their learning outcomes are less than optimal. Distance learning that optimizes information technology, the internet and social media will be able to run effectively and optimally if students have independence in learning. For this reason, it is necessary to analyze the level of student learning independence in the process of learning microbiology practices by E-learning. The purpose of this study was to analyze the learning independence of class XI students of SMK-SMAK Bogor in microbiology practice using E-Learning and to find out changes in learning outcomes for class XI students of SMK-SMAK Bogor in the even semester of 2020/2021. The research design used in this research is descriptive exploratory research. This study uses descriptive data analysis with a quantitative approach. Data collection techniques using questionnaires and analysis techniques using the Excel program. Based on the results of the analysis of the independence of class XI students of SMK-SMAK Bogor in learning microbiology practices by E-learning, it is in the good category and there is an increase in learning outcomes for class XI students of SMK-SMAK Bogor. PTS even semester. ABSTRAKPembelajaran Jarak Jauh (PJJ) dengan menggunakan E-learning membuat siswa merasa bosan, malas dan kurang motivasi belajar sehingga hasil belajarnya kurang maksimal. Pembelajaran jarak jauh yang mengoptimalkan teknologi informasi, internet dan media social akan dapat berjalan efektif dan optimal apabila siswa mempunyai kemandirian dalam belajar. Untuk itu perlu dianalisis tingkat kemandirian belajar siswa dalam proses pembelajaran praktik mikrobiologi secara E-learning. Tujuan penelitian ini adalah untuk menganalisis kemandirian belajar siswa kelas XI SMK-SMAK Bogor pada praktik mikrobiologi secara E-Learning dan untuk mengetahui perubahan hasil belajar siswa kelas XI SMK-SMAK Bogor pada semester genap 2020/2021. Desain penelitian yang dipakai dalam penelitian ini adalah penelitian deskriptif eksploratif. Penelitian ini menggunakan analisis data deskriptif dengan pendekatan kuantitatif. Teknik pengambilan data dengan menggunakan kuesioner dan teknik analisis menggunakan program ecxel. Berdasarkan hasil analisis kemandirian belajar siswa kelas XI SMK-SMAK Bogor dalam pembelajaran praktik mikrobiologi secara E-learning masuk kategori baik dan ada peningkatan hasil belajar siswa kelas XI SMK-SMAK Bogor hasil rata nilai PTS semester Gasal 80,56, menjadi 84,50 pada PTS semester genap.