Reviewerly/exHarmony huggingface dataset:
PENGEMBANGAN MEDIA PRAKTIKUM BSD (Basic Solution Dilution) BERBASIS ANDROID MENGGUNAKAN TEKNOLOGI AI (Artificial Intelligence) PADA MATERI PENGENCERAN LARUTAN

The purpose of this research is to develop an Android-Based BSD (Basic Solution Dilution) practicum media using AI (Artificial Intelligence) Technology in solution dilution material. The development in this study was carried out with a 4D (four-D) define, design, develop, and disseminate. At the definition stage, the formulation of the practicum objectives is carried out, the design stage is carried out by designing the practicum media, while at the development stage the practicum media content validation is carried out by media experts and material experts, the dissemination stage is carried out via youtube. The results showed that the BSD practicum media was feasible to use, this was based on the validation results from two validators, namely material experts and media experts. The practicum media validation score by material experts is at number 69 which is in the "Eligible" category, while the validation results by media experts get 53 which is in the "Eligible" category. The results of the feasibility assessment of practicum media by students also showed results that were in the "appropriate" category with a conversion value of 3.94. Student learning outcomes after using the BSD practicum media also increased when viewed based on the comparison between students' pretest and psotest scores. The average pretest score of students before using BSD media was 50.76 while the average post-test score of students after using BSD media was 80.96. The results of the student's pretest and posttest gain test have a score of 0.61 with the "Medium" category.&#x0D;
Investigating performance metrics for container-based HPC environments using x86 and OpenPOWER systems

Abstract Container-based High-Performance Computing (HPC) is changing the way computation is performed and reproduced without sacrificing the raw performance compared to hypervisor-assisted virtualization technologies. It primarily supports continuously evolving data-intensive applications such as computational fluid dynamics, seismic tomography, molecular biology, and Proteomics. OpenPOWER systems, unlike the x86 systems, use the POWER-compliant processor to exploit instruction-level and thread-level parallelism heavily. In our previous work, we designed and developed a Containerized HPC environment (cHPCe) from the scratch using Linux namespaces on OpenPOWER systems. This paper aims to provide an in-depth performance analysis of the Containerized HPC environment using x86 systems and Containerized HPC environment using the OpenPOWER system, on systems’ subcomponents, processor, memory, interconnect, and IO. This sub-component analysis provides an insight on several aspects of the system performance. To the best of our knowledge, no research has been reported yet for such a comparative analysis that designs cHPCe for both x86 and OpenPOWER systems. The performance of the developed cHPCe is compared with BareMetals, and VMs using the benchmarks HPCC, and IOZone. Our experimental results achieve 0.13% less compute performance penalty at its peak performance on cHPCe compared to the BareMetal-based solution for x86 systems. In contrast, a VM-based solution introduces an overhead of 20% and 4.83% in x86 and OpenPOWER cases, respectively. Moreover, the x86 and OpenPOWER systems observe inconsistent behavior for memory performance with a worst-case penalty of 9.68% and 6.64% compared to achieved peak performance, respectively. However, similar behavior is reported for cHPCe with an overhead of less than 3% and 2% in the worst case for the latency and bandwidth, respectively, compared to the BareMetal for network and disk performance. Our experimental results reveal that the containerized OpenPOWER environment represents a viable alternative to the counterpart x86 environment for the HPC solution.
Efficient Method for Video Sentiment Analysis

Nowadays, the acquisition of deep knowledge is carried out in many fields like tracking objects from image/video, measuring position, acquiring textual and image content, visual value detection, and recognizing hand gestures. Various deep learning models are available based on classification and regression like Convolutional Neural Networks (CNN), decision trees, linear regression which comes under supervised and Self Organizing Map (SOM), Boltzmann Machines, and Autoencoders which comes under unsupervised models based on clustering. For image classification, one of the well-performing model is CNN. It provides good performance when compared to other deep learning models. In this paper, we propose an efficient method that will analyze sentiment from video. This is carried out by using Convolutional Neural Networks (CNN). The findings are also compared with various well-known deep learning approaches, and the results obtained by the proposed method are higher when compared to existing ones. The proposed methodology gives an accuracy level of 92%. The proposed methodology can be used in various applications such as audio/video data sentiment analysis, monitoring social media, and customer feedback analysis, in the education field to draw student’s opinions.
PELATIHAN PENGGUNAAN WEBSITE WORDWALL DALAM MENDESAIN MEDIA PEMBELAJARAN

Sindangsari village, Cabang Bungin is one of the areas in Bekasi district where this village is still thick with a rural feel, but as technology develops in the current industrial revolution 4.0 we also pay attention to digital literacy that must be implemented so that village communities are able to follow and adapt to technological sophistication. In the world of education that must be developed through digital utilization, therefore the researchers here refer to the training method. Training on using the wordwall website in designing learning media. This training is expected to be able to provide new innovations for elementary school educators in sindangsari village so that the wordwall website here can be applied during the teaching and learning takes place because of the advantages of this wordwall website, namely providing interesting features that can support teaching and learning process activities. Interesting features are also considered practical in its manufacture, therefore the wordwall website is very suitable as a learning medium in the current industrial revolution 4.0 era. The wordwall website also received a positive response from elementary school educators in sindangsari village because the wordwall website is considered to provide a new color in the world education so that the application of learning in the classroom does not seem monotonous
An Inception in Practice

The previous chapter explained what an inception is; in this chapter, you see why it’s so important. Often, before starting a project, team members don't know each other. Thus, one of the functions of an inception is to increase team rapport. There are several techniques, called ice breakers, to help with this.
A universal variational quantum eigensolver for non-Hermitian systems

Many quantum algorithms are developed to evaluate eigenvalues for Hermitian matrices. However, few practical approach exists for the eigenanalysis of non-Hermintian ones, such as arising from modern power systems. The main difficulty lies in the fact that, as the eigenvector matrix of a general matrix can be non-unitary, solving a general eigenvalue problem is inherently incompatible with existing unitary-gate-based quantum methods. To fill this gap, this paper introduces a Variational Quantum Universal Eigensolver (VQUE), which is deployable on noisy intermediate scale quantum computers. Our new contributions include: (1) The first universal variational quantum algorithm capable of evaluating the eigenvalues of non-Hermitian matrices-Inspired by Schur's triangularization theory, VQUE unitarizes the eigenvalue problem to a procedure of searching unitary transformation matrices via quantum devices; (2) A Quantum Process Snapshot technique is devised to make VQUE maintain the potential quantum advantage inherited from the original variational quantum eigensolver-With additional [Formula: see text] quantum gates, this method efficiently identifies whether a unitary operator is triangular with respect to a given basis; (3) Successful deployment and validation of VQUE on a real noisy quantum computer, which demonstrates the algorithm's feasibility. We also undertake a comprehensive parametric study to validate VQUE's scalability, generality, and performance in realistic applications.
Accurate Wide-Range Scaling Manipulation of the Model with a 6-DOF Tracking Device

In virtual reality applications, translation, orientation, and scaling are the three basic properties of 3D model manipulation. The 6-DOF tracking device can be used to directly manipulate the former two properties. However, the scaling property cannot be directly mapped with a hand-held tracking device because it is physically impossible. In this study, we first compare various schemes for mapping the translation and orientation of a handheld tracking device to the 3D model’s scaling property. Next, we propose a scaling manipulation framework that combines the advantages of different schemes. This enables accurate and natural wide-range scaling with the orthogonal combination design of the translation and orientation data of the tracking device. The efficiency and accuracy of the proposed framework were examined in a user study, which verified that it improved the scaling error of wide-range scaling by over 55% without a significant decrease in time performance. Finally, two scaling scenarios for the application of this framework were presented.
Application of Octapace Model to Improve Faculty Performance in Selected Higher Education Institutions in Bhopal Division

The organizational culture is a crucial factor in determining the degree of dedication and engagement exhibited by faculty members towards their respective academic communities. The objective of the present research was to examine the OCTAPACE model, which has received endorsement from institutions of higher education, and determine the variables that influence faculty members' intention to remain employed in such institutions. The investigation examined the theoretical foundations of the OCTAPACE culture and the structure of academic staff's effectiveness within the setting of tertiary education in Bhopal. This study employed both primary and secondary data. A convenience sampling method was utilized to select a sample size of 800 respondents. The statistical methodologies utilized in this study included descriptive analysis, which involved the computation of measures such as mean, standard deviation, and graphical representations. Moreover, the dataset underwent correlation and regression analyses in order to investigate the inter-relationships between the variables. The analysis results suggest that the null hypothesis is not substantiated. The findings of this study suggest that the cultural variables of OCTAPACE have a noteworthy influence on the performance of employees (P) in the context of this specific research. As a result, the inquiry produced results that led to the determination that the null hypothesis was not dependable.
Awareness of Cryptocurrency among general public: Evidences from South India

Cryptocurrency is an advanced cash which is made with the end goal of exchange as a typical cash. It utilizes Cryptography and Blockchain innovation to get its trades and breaking point the creation of a specific kind of digital currency and monitor every single exchange in entire organization. The Cryptocurrency weighed down with such a lot of new age innovations and an enormous market presence from one side of the planet to the other, yet, even following a time of its reality, it has not accomplished a set up picture as another age cash framework among larger part of the nations on the planet and individuals are yet incredulous with regards to its value. Many of the organization accept the crypto currency for exchange for commodities. But in India several perplexing factors are floating around the crypto currency to regulate in the country. This study focused to measure the awareness, differences, intention to invest, factors influencing the investment in cryptocurrency among the public in the selected major cities in the state of Tamilnadu, India. A structured questionnaire was used to collect data from 400 respondents, the data is analyzed with various statistical tools. Variables were identified through qualitative literature review to prepare the structured questionnaire. The questionnaire framed was tested for reliability. The study revealed that income and age influence the investment behavior greatly. The minimum, average, maximum investment ranges were estimated.
Segmentation of cellular ultrastructures on sparsely labeled 3D electron microscopy images using deep learning

Focused ion beam-scanning electron microscopy (FIB-SEM) images can provide a detailed view of the cellular ultrastructure of tumor cells. A deeper understanding of their organization and interactions can shed light on cancer mechanisms and progression. However, the bottleneck in the analysis is the delineation of the cellular structures to enable quantitative measurements and analysis. We mitigated this limitation using deep learning to segment cells and subcellular ultrastructure in 3D FIB-SEM images of tumor biopsies obtained from patients with metastatic breast and pancreatic cancers. The ultrastructures, such as nuclei, nucleoli, mitochondria, endosomes, and lysosomes, are relatively better defined than their surroundings and can be segmented with high accuracy using a neural network trained with sparse manual labels. Cell segmentation, on the other hand, is much more challenging due to the lack of clear boundaries separating cells in the tissue. We adopted a multi-pronged approach combining detection, boundary propagation, and tracking for cell segmentation. Specifically, a neural network was employed to detect the intracellular space; optical flow was used to propagate cell boundaries across the z-stack from the nearest ground truth image in order to facilitate the separation of individual cells; finally, the filopodium-like protrusions were tracked to the main cells by calculating the intersection over union measure for all regions detected in consecutive images along z-stack and connecting regions with maximum overlap. The proposed cell segmentation methodology resulted in an average Dice score of 0.93. For nuclei, nucleoli, and mitochondria, the segmentation achieved Dice scores of 0.99, 0.98, and 0.86, respectively. The segmentation of FIB-SEM images will enable interpretative rendering and provide quantitative image features to be associated with relevant clinical variables.
Research on Virtual Reality Experience and User Behavior from the Perspective of Psychology

Virtual reality (VR) technology has attracted a lot of attention in many fields, including entertainment, healthcare, education and industrial applications. As technology continues to advance, VR has become a powerful tool for psychological research to delve deeper into human cognition, emotion, and behavior. This thesis aims to study the relationship between virtual reality experience and user behavior from the perspective of psychology. By combining virtual reality technology and psychological theory, we explore how virtual reality affects users' perceptual, emotional, and cognitive processes, as well as users' behavior in virtual environments. We first review the development of virtual reality technology, including its definition, technical composition and application areas. We then propose a theoretical framework of psychology to explain the psychological mechanisms of virtual reality experience. This includes important concepts such as perception, attention, emotion, and cognitive load, which play a key role in understanding user behavior and experience in virtual reality. The experience of virtual reality includes not only visual and auditory perception, but also the emotional experience and physical perception of the user. We'll delve into how virtual reality creates immersion, evokes emotions, and changes the user's physical perception. At the same time, we will focus on the user's behavior in the virtual environment, including their actions, interactions and reactions. The research method is an important part of exploring virtual reality experience and user behavior. We will cover experimental design, data acquisition tools, and analytical methods to help researchers delve deeper into this area. In the empirical research section of this paper, we will present a series of specific studies that demonstrate how virtual reality affects user attention, emotion, cognition, and behavior. These studies will provide insights that will help us better understand the psychological effects of virtual reality. Finally, in the discussion and conclusion section, we will summarize the findings, discuss their connection to psychological theory, and make suggestions for future research. These studies are not only of great significance to the field of psychology, but also provide strong support for the application and improvement of virtual reality technology.
Influence of Reading Strategies on ESL Students’ Reading Comprehension in Secondary Schools in Malé, Maldives

The use of reading strategies plays an integral part in the reading comprehension level of students. However, English as a Second Language (ESL) learners are unaware of the impact of reading strategies on their reading comprehension level. Moreover, teachers also lack a solid foundation for teaching reading strategies to students and are unable to understand the reading strategies preferences of the students. Only a few studies have been conducted highlighting the significance of reading strategies on students’ comprehension levels, especially in the context of Maldivian secondary schools. The main objective of this study is to identify the use of reading strategies to improve the reading comprehension level of ESL learners in secondary school. This research employed an experimental design. A total of 118 students from grades 9 and 10 from a secondary school participated in the study. Two instruments were utilized to collect data: a questionnaire, a pre-test, and a post-test. Statistical analysis revealed a strong positive correlation between reading strategies and comprehension achievement. Moreover, a significant difference in strategy use was found between male and female students. Recommendations include implementing school-wide reading programs, using think-aloud technique to model strategies, and consistent teacher training in Maldives as well as monitoring of students' reading strategies to improve comprehension and learning opportunities.
A Gender Classification And Age Detection Using Face Recognition

This study presents a novel approach to simultaneous gender and age recognition by including emotional context using a mask region-based convolution neural network (Mask R-CNN). The suggested approach makes exact gender and age categorization possible by using deep learning to examine facial traits and emotions. The model captures the complex relationship between emotional states and face characteristics by extending Mask R-CNN to include emotional signals. By enhancing overall system performance, this integration offers a more comprehensive comprehension of human behavior. The suggested method achieves state-of-the-art accuracy in gender and age recognition while capturing emotional nuances in facial expressions, as demonstrated by empirical data. This work advances the development of multimodal human-centric systems and has potential applications in a variety of domains, including surveillance, human-computer interaction, and tailored experience.
Has COVID-19 changed the correlation between cryptocurrencies and stock markets?

The COVID-19 pandemic has challenged the notion that cryptocurrencies are uncorrelated with traditional asset markets. This study uses VAR-OLS techniques to investigate the time-varying correlation between Bitcoin and three major European stock market indices from January 4, 2016, to February 26, 2021. Our results show that cryptocurrencies and stock markets are dependent during crisis periods, but not during non-crisis periods. This confirms the time-varying correlation between cryptocurrencies and stock markets, which depends on the extent and persistence of responses to own and cross shocks. To improve the robustness of our results, we also test the impact of government measures on Bitcoin and stock market indices and find that they are both affected by these measures. Our study adds to the literature by examining the impacts of pandemics on the correlations between Bitcoin returns and the stock market, oil, and gold index returns, which have so far been unaddressed.
A Small Step Taken to Ensure Proper and Systematic Accounting Application Has Ensured Highest Revenue Earning in Tripura: A Critical Accounting Analysis of PIRSA System

Proper accounting application is an important and significant key element for every financial transaction of any organization especially in the public sector organization of the country. A systematic accounting application can ensure proper fund management and transparency in financial transactions which not only provides positive impact on financial management but also decreases the propensity and possibility of leakages in the system. A sound accounting and record keeping process ensures accountability and provides the scope and opportunities to fulfil the objectives of finance. The PIRSA - an accounting system for non-Government and non-Treasury fund management of different departments and wings of the Government of Tripura is fulfilling all the objectives of the government along with maximum revenue earnings from the last eleven (11) years.
Interactive Digital Media Based on Our-Space Website in Geography Learning : ICT, Media Skills, and Learning Styles

This study aims to identify the availability of IT facilities and teacher characteristics towards the application of interactive digital multimedia, identification of media needs for students, and student learning styles in learning. This research was conducted at an alliance of geography teacher groups and two excellent schools in Surakarta City and Karanganyar Regency. The method used was descriptive qualitative with respondents consisting of 17 geography teachers of Surakarta City and 16 geography teachers of Karanganyar Regency, 34 students of grade XI of Surakarta 3 public high school, and 35 students of grade XI of Karanganyar 1 public high school. The data collection technique was carried out using observation techniques and questionnaires. The data analysis technique uses the Interactive Analysis Model, while the questionnaire analysis uses percentages. The results showed that: 1) teachers' experience in making IT-based media innovation and applying it in the classroom as much as 64.71% of geography teachers in Surakarta City and 81.25% of geography teachers in Karangayar Regency responded that they had never done it; 2) The need for digital-based multimedia as much as 94.12% of grade XI students in public high school 3 Surakarta and 100% of grade XI students in public high school 1 Karanganyar were interested in learning geography using integrative websites; 3) The average learning style characteristics of ninth-grade students in public high school 3 Surakarta and public high school 1 Karanganyar were 73% and 66% had a visual learning style. Based on the study's results, it was known that the low ICT skills of geography teachers could result in students' digital learning multimedia needs not being appropriately met, so integrative multimedia innovations such as the Our Space website are needed that can be tailored to student learning needs.