Reviewerly/exHarmony huggingface dataset:
Analysis of Solar Power Plant Development Potential in Adipala - Cilacap

PT Pertamina (Persero) as the vanguard of the archipelago's energy has committed to finding and developing new and renewable energy sources to support national energy independence and sovereignty. One of the concrete steps taken by PT Pertamina through the Cilacap Processing Unit IV is to build a Solar Power Plant. One of the strategic solar power plant construction sites in an empty land area close to the 500 kV Adipala Sutet Power Network is located in Cilacap regency with an average global horizontal irradiation (GHI) value of 1908 kWh/m2. With this value, the installation of solar rooftops is the right solution to support electricity production using renewable energy. The electricity load consumption from the city in one year is 1785.6 KWh and is currently entirely supplied by PLN. In this study, a Solar Power Plant design was carried out on vacant land around housing that can be produced in one year. The design and calculations were carried out using the help of PVSyst and RETScreen software. From the simulation results, the results obtained are a Solar Power Plant that has been designed to produce 463 kWh per year which can meet 25.9% of electricity needs at the design site with a Solar Power Plant performance ratio of 85.74% where Solar Power Plant can produce electrical energy of 1531 KWh per year.
RefineTAD: Learning Proposal-free Refinement for Temporal Action Detection

Temporal action detection (TAD) aims to localize the start and end frames of actions in untrimmed videos, which is a challenging task due to the similarity of adjacent frames and the ambiguity of action boundaries. Previous methods often generate coarse proposals first and then perform proposal-based refinement, which is coupled with prior action detectors and leads to proposal-oriented offsets. However, this paradigm increases the training difficulty of the TAD model and is heavily influenced by the quantity and quality of the proposals. To address the above issues, we decouple the refinement process from conventional TAD methods and propose a learnable, proposal-free refinement method for fine boundary localization, named RefineTAD. We first propose a multi-level refinement module to generate multi-scale boundary offsets, score offsets and boundary-aware probability at each time point based on the feature pyramid. Then, we propose an offset focusing strategy to progressively refine the predicted results of TAD models in a coarse-to-fine manner with our multi-scale offsets. We perform extensive experiments on three challenging datasets and demonstrate that our RefineTAD significantly improves the state-of-the-art TAD methods with minimal computational overhead.
Ontological Representation of Business Processes in an Educational Institution

Management business processes of educational work in an institution of secondary special education, such as the planning of ideological, educational and information work, organization of curator’s work, organization and formation of culture of safe life activity, everyday life, leisure, physical culture and healthy lifestyle are considered. The business process model “Curator’s work management” in BPMN notation is presented. With the help of set theory, the output data of business process models of educational work are presented. The ontological model of educational work in an institution of secondary specialized education is developed. This model displays classes, instances, and relations between them, which allows structuring and unifying the knowledge base of the subject area under consideration.
Vocational Students’ Perception of The Use Problem-Based Learning in Speaking English

This study was conducted based on the regulations of the Ministry of Education and Culture related to the teaching and learning process for SMK students, SMK PGRI 3 Malang has attempted to apply problem-based learning methods, which are believed to be methods that help students face real problems in the field. world of work because it can help improve students' speaking skills. Meanwhile, studies on students' perceptions of the use of problem-based learning in their speaking skills are still under-explored. Therefore, this study aims to determine the perception of SMK students about the application of problem-based learning in their speaking skills. This study uses a survey design with SMK PGRI 3 Malang student population, while the sample is 102 students. Data were collected by conducting a survey using a questionnaire. This study's findings imply strengths in applying problem-based learning in the classroom. Furthermore, the researcher revealed that students positively perceived using problem-based learning on their speaking skills.
Binary Similarity Few-Shot Object Detection with Modeling of Hard Negative Samples

For few-shot object detection, this work proposes a binary similarity detector (BSDet), which realizes a novel similarity-based multiple binary classification and enhances the feature margin between positive and hard negative samples. First, we revisit the classification paradigm, concluding that multiple binary classification paradigm is more suitable than multi-class classification paradigm for the few-shot task. Hence, we propose a binary similarity head (BSH) by posing the classification task as multiple binary similarity measurements rather than a multi-class prediction. Second, focusing on the hard negative samples, we propose a feature enhancement module (FEM). During training phase, the FEM can push the features of positive and hard negative samples far away from each other, and thus effectively suppresses false positives. Abundant experiments and visualizations indicate that our method achieves state-of-the-art performances on few-shot object detection tasks. The codes are available at <uri xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">https://github.com/yrqs/bsdet</uri> .
An Overview of Video Summarization

Video summarization is an important task in the field of computer vision, with applications in many areas, such as video surveillance, video indexing, and video recommendation. It aims to generate a concise and informative summary of a video by selecting the most important frames or segments.Web-based applications for video summarization offer a number of advantages over traditional desktop-based applications. First, they are more accessible, as they can be used from any device with a web browser. Second, they are more scalable, as they can be deployed on cloud servers to handle large volumes of video data. Third, they are more collaborative, as they can be used to share and discuss video summaries with others. Keywords: Text summarization, model, video.
Hate speech or legitimate satire? Drawing the line in cartoons

Controversial cartoons appearing in contemporary news and social media are periodically denounced by consumers for hate speech, and argued over in blogs, reader comments and news articles. Visual and verbal discourse analysts could contribute useful insights to such debates and to awareness raising programmes for addressing hate speech issues in cartoons, but to date have produced little work on the topic. This paper addresses the difficult question of how we distinguish between legitimate satire and hate speech in controversial cartoons about real events featuring public figures belonging to groups with a history of discrimination. The paper proposes that key considerations in this endeavour are the distinction between conceptual and narrative representations and the relevant participant role(s) assigned to the public figure in question (Kress &amp; Van Leeuwen, 2006). The latter’s construal as being, doing or undergoing in the visual structure constrains the options for their evaluation. The evaluations are analysed using visual analogues of the verbal appraisal framework (Martin &amp; White, 2005; Economou, 2009; Swain 2012; White, 2014). It is argued that negative evaluations based on representations of the public figure’s real-life behaviour may more plausibly pass for legitimate satire, whereas those based on the public figure’s appearance alone may be more susceptible to a hate speech interpretation.
Improving Students’ Pronunciation in Word Stress through TTS (Text To Speech) Feature: On a Google Translate Application

This research aimed to find out the improvement of students’ pronunciation in word stress through text-to-speech software at the 11th-grade students of SMAN 1 Kaledupa, in the academic year of 2021/2022. The samples of this study were 22 students, and purposive sampling was applied for this research. This research used a pre-experimental research design where there were three sessions conducted to reach the result of this research. Pre-test and post-test design consisted of 5 meetings, including the treatments. The pre-test in this research is to obtain students' prior knowledge, and the post-test is to measure students’ improvement after the researcher applies or uses the text-to-speech software in the treatment session. The finding of this research showed a significant improvement in students’ pronunciation after the use of text-to-speech software. This was proven by the mean score before treatment was 32.04, and the mean score after treatment has given was 60. The percentage of the improvement was 87.26%. The t-test value (6.106178) was higher than the t-table value (2.07961). H1 is accepted while H0 is rejected, and it can be concluded that there is a significant improvement in students’ pronunciation in word stress.
The Effect of Expressive Writing Techniques on Reducing Academic Anxiety in Medical Profession Students in Makassar

Medical profession students have a high level of academic anxiety, one of the interventions that can reduce expressive writing. This study aims to determine the effect of expressive writing techniques on reducing academic anxiety in medical profession students in Makassar. This study used a Pretest Post-test Control Group Design. The research participants were medical profession students from several universities in Makassar, totaling 6 experimental groups and 6 control groups. The measuring instrument used in this study was the academic anxiety scale. Data analysis techniques using Wilcoxon and Mann Whitneyy hypothesis tests. The results showed that expressive writing can reduce academic anxiety scores in medical profession students. The results of the Mann Whitney test, namely p = 0.004, show that there are differences in academic anxiety scores in the experimental and control groups. Wilcoxon test results are p=0.028 for the experimental group and p=0.783 for the control group. The results of this study found that the posttest score owned by the experimental group (mean = 90) was lower than the control group (mean = 113). The implication of this study is that expressive writing can be used as one of the media to reduce academic anxiety of medical profession students.&#x0D;
SQUATS: Web-Based Security System for Sta. Philomena Residences Dormitel Using QR Code Technology with Analytics

Efficient log management is crucial for organizations, and Sta. Philomena Residences Dormitel currently relies on a paper-based logbook for recording visitor information. This approach is susceptible to flaws such as logbook and ID misplacement and challenges in legibility and searchability. To overcome these limitations, this study presents “SQUATS,” a web-based security system that digitizes log information through QR code scanning. By implementing SQUATS, a secure environment is established for visitors while enhancing resident protection against potential trespassers. The system incorporates a resident's approval process for visitor registration, ensuring that only authorized visitors are granted access. The analytics encompasses tracking building occupancy, monitoring curfew hours, and performing log analysis. The findings of this study demonstrate the successful development and implementation of a web-based security system for log management at Sta. Philomena Residences Dormitel provides enhanced efficiency and security for visitor registration.
The Archetypal Images in “Coraline” Novel By Neil Gaiman (2002)

The dark fantasy children's book Coraline by Neil Gaiman described Coraline's adventured as she tried to uncover strange and frightening secrets in her new home. The goal of this study was to describe the archetypal images that emerged in the Coraline novel based on Carl Jung's theory of the archetypal image. The issue identified in this study is that many readers are still not aware of what an archetypal description in a novel implies. This research was a qualitative descriptive research proposed by Creswell (2018). In collecting data, researchers used observation (reading) and note-taking techniques. Then, for data analysis methods, the researchers used content analysis and interpretation techniques. The result of this research was the discovery of 15 data of archetypal images in the novel Coraline. The 15 data consisted of four data of terrible mother, two data of demon lover, two data of black color, two data of tree, one data of red color, one data of rising sun, one data of desert, one data of serpent, and one data of circle. Considering the findings of the study, it could be concluded that the novel Coraline used a number of image archetypes to convey hidden meanings through the use of symbols.
An improved SCOT double weighted quadratic correlation time delay estimation algorithm based on infrasound signal

In the pipeline leak location technology by detecting Infrasound signals, time delay estimation algorithm has become a significant method, but the quality of time delay estimation calculation method determines the accuracy of location. This article proposes an improved Smooth Coherent Transform (SCOT) generalized weight function based on the quadratic correlation delay estimation algorithm, defined as SCOT-&gamma; to suppress the false peak of the signal by adding weight to the SCOT weight function , the two cross-correlations in the quadratic cross-correlation algorithm are weighted separately with the improved weight function. In this paper, MATLAB is used for experimental simulation. First, Infrasound signals with Gaussian white noise are constructed,then the influence of the weighting factor on the delay estimation performance is verified through multiple experiments, and the optimal value of the weighting factor &gamma; is determined at the same time. Then perform cross correlation peak detection on the SCOT primary weighting method, SCOT-&gamma; once weighting method, and SCOT-&gamma; double weighting method and compare the noise reduction effect; finally, compare the performance of the three algorithms by calculating the root mean square error of the delay value of the three algorithms. The results show that the improved SCOT double weighted quadratic correlation time delay estimation algorithm has better anti-noise performance and higher precision.
Mo2Hap: Rendering VR Performance Motion Flow to Upper-body Vibrotactile Haptic Feedback

We introduce a unique haptic rendering framework that transforms the performer’s actions into wearable vibrotactile feedback for an immersive virtual reality (VR) performance experience. To capture essential movements from the virtual performer, we propose a method called Motion Salient Triangle. Motion Salient Triangle is a real-time 3D polygon that computes haptic characteristics (intensity, location) based on motion skeletal data. Here, we employ an entire upper-body haptic system that provides vibrotactile feedback on the torso, back, and shoulders. This haptic rendering pipeline enable audiences to experience immersive VR performance by accommodating the performer’s motions on top of motion-to-haptic feedback.
ISSUES OF THE DEVELOPMENT OF THE EDUCATIONAL SYSTEM AND THE MARKET OF EDUCATIONAL SERVICES

The article deals with the socio-economic aspects of the higher education system. Education creates a flow of benefits not only for individuals, but for society as a whole. The state is interested in raising the educational, scientific and cultural level of society and should contribute to the preservation and improvement of the intellectual potential of the country. High-quality education is an integral mechanism in ensuring the progressive growth of the economy of each state. The market of educational services is specific and insufficiently studied, especially in crisis situations. In this regard, the author analyzed the current state of this market, the current problems of the organization and functioning of the educational services market.
The Effect of Implementing Student Pictorial Worksheet on the Vocabulary Skill of Student Wangsaphung School, Thailand

The social and behavioral changes in the field of education have occurred. The students have fallen far behind one and another especially in English education on mastery vocabulary. The researcher conducted in pre-experimental with a one group design pretest-posttest design with quantitative data used. This data uses respondents from 36 students in the Thai Wangshapung School. data in the study were collected using test instruments (pre-test &amp; post-test) with analysis carried out including validity tests, reliability tests, normality tests, T-tests and descriptive data .So this research conduct to find out if there is a change in their vocabulary skills in their learning outcomes when using pictorial worksheets that assist with new technology canva. there is a significant difference in improving student learning outcomes on vocabulary skills. This is shown by the evidence of the t-test analysis value which is p value or Sig. (2-tailed) &lt; .05 or .000 &lt; .05. It means that H0was rejected and Hawas accepted; In other words, there was a significant difference between participants' pretest and post test scores. Which means There is an effect of the implementing student pictorial worksheet for vocabulary skill in learning outcomes. some academic researchers focus on examining the use of worksheets themselves without the use of images in order to attract students, and some of them have used image media but with the level of playground education (PRESCHOOL) or kindergarten. But the research needed is to improve students' English skills (vocabulary) with the help of pictorial worksheets as this researcher conducted research in this study.
Implementation Of The Dude Application As A Network Management System

The development of information technology and especially networks is very rapid. Therefore, there is a demand for a sophisticated computer network system. Where the admin cannot know the condition of each user's computer and whether the existing service system is on or off. Display and sound are technologies for detecting network damage on company computers. Implementation of a computer network client monitoring system using display and sound allows the system to send reports when a client computer or service shuts down automatically to the admin without involving the user. For this reason, researchers are trying to develop The Dudemonitoring network application in the form of display and sound. The results obtained from using this network monitoring application are monitoring the services carried out by each host or IP address. If a network error is correctly detected, a notification will be sent to the network administrator, then the network administrator will be able to repair network damage..
Using MNIST Dataset for De-Pois Attack and Defence

Machine learning (ML) has grown into compelling element of diverse systems and applications. Recent research have revealed that ML algorithms are at the risk of serious security vulnerabilities, notwithstanding the outstanding validity of ML algorithms in various signals and decision-making tasks. ML systems trained on user-provided data are vulnerable to various data poisoning attacks, by which attackers inject the malicious training dataset with the purpose of misconducting the learned model. For instance, in model extraction attacks, an attacker can steal the proprietary and secret data of ML models, and in model inversion attacks, they can obtain the private and sensitive data of the training dataset. The objective of this study is to build defence technique by using De-Pois to tackle attackers where they corrupt the ML models by data poisoning in training dataset. De-Pois is the only popular means of protection for poisoning attacks. It offers defence without information of any ML algorithms, kinds of poisoning attacks, and it may be applied to both classification and regression. Hence, De-Pois is a common defence system which will be able to stop all types of attacks. De-Pois approach is crucial for training mimic models, whose goal is to replicate the activities of the target model. The solution developed a De-Pois-based defence mechanism to combat attackers that damage ML models via data poisoning in the training dataset. De-Pois is the only and most popular means of poison defence. De-Pois is a security solution that can be used to safeguard both classification and regression workloads without the need for specialized understanding of ML methods or poisoning attack types.
Fine-Grained Visual Prompt Learning of Vision-Language Models for Image Recognition

Large-scale pre-trained vision-language (VL) models have shown powerful generic representation capabilities for adapting to downstream tasks with limited training data, which are data-efficient solutions to various applications such as image recognition. In order to enhance the adaption performance, most existing methods attempt to introduce learnable vectors into the text prompt to generate adaptive classification weights for the class in the downstream task. However, they generally focus on the text side while neglecting adaptive visual feature generation on the image side, which is insufficient to fit the downstream task data. In this paper, we propose fine-grained visual prompt learning (FG-VPL) of vision-language models for image recognition with few training samples, and the main contributions are: (1) Fine-grained visual prompt is introduced into the image encoder of the vision-language model for focusing on the target object and conducting information interaction within the object, which facilitates generating discriminative visual features for image recognition. (2) A two-pathway adaptive recognition module is proposed to narrow the domain gap and utilize both the cross-modal knowledge of the vision-language model and the visual information of the few-sample training set for classifying images with the help of feature adapters. We conduct extensive experiments on 11 image recognition benchmark datasets under the few training samples setting, which demonstrate that our proposed approach can achieve state-of-the-art performance. The code is available at https://github.com/PKU-ICST-MIPL/FG-VPL_ACMMM2023.