Reviewerly/exHarmony huggingface dataset:
CigTrak: Smartwatch-Based Accurate Online Smoking Puff &amp; Episode Detection with Gesture-Focused Windowing for CNN

Wearable-based motion sensing solutions are capable of automatically detecting and tracking individual smoking puffs and/or episodes to aid the users in their journey of smoking cessation. But they are either obtrusive to use, perform with a low accuracy, or have questionable ability of running fully on a low-power device like a smartwatch, all affecting their widespread adoption. We propose ‘CigTrak’, a novel pipeline for an accurate smoking puff and episode detection using 6-DoF motion sensor on a smartwatch. A multi-stage method for puff detection is devised, comprising a novel kinematic analysis of puffing motion enabling temporal localization of puff. A Convolutional Neural Network (CNN)-backed model uses this candidate puff as an input instance by re-sampling it to required input size for the final decision. Clusters of detected puffs are further used to detect episodes. Data from 13 subjects was used for evaluating puff detection, and 9 subjects for evaluating episode detection. CigTrak achieved a high subject-independent performance for puff detection (F1-score 0.94) and free-living episode detection (F1-score 0.89), surpassing state of the art performance. CigTrak was also implemented fully online on two different smartwatches for testing a real-time puff detection.Clinical Relevance— Cigarette smoking affects physical & mental well-being of a person, and is the leading cause of preventable diseases, adversely affecting cardiac and respiratory systems. With many adults wanting to quit smoking [1], a reliable way of auto-journaling of smoking activities can greatly aid in cessation efforts through self-help, and reduce burden on healthcare industry. CigTrak, with its high accuracy in detecting smoking puffs and episodes, and capability of running fully on a smartwatch, can be readily used for this purpose.
Network Security and Trustworthiness

In 6G, a range of new technologies will emerge based on intelligent network structures. The connection between 6G technology and AI-based intelligent networks will make communication more convenient for humans, but may also rise to new security threats. As a result, network security and trustworthiness will become a key challenges in 6G. This chapter categorizes security threats in 6G into four areas; openness, post quantum cryptography, privacy preserving, and auction threats. We will also introduce security solutions that can mitigate these security threats in 6G.
The difficulties of elementary teacher education students’ speaking performance: a comprehensive analysis

Speaking English plays a fundamental role in personal development of students. However, many students struggle when speaking, which limits their capacity to communicate effectively and self-assuredly in a foreign language. The goal of this study is to investigate the elements influencing these difficulties in students' speaking abilities. To effectively design measures to improve kids' speaking abilities, educators and policymakers must have a thorough understanding of these challenges. This research also offers techniques to improve students' speaking abilities. This research used the qualitative research methodology. The data was gathered through observation, documentation, and interviews. The findings demonstrate that the factors that influence the students’ difficulties are anxiety, low self-confidence, limited vocabulary, poor pronunciation, and grammar challenges. The strategies to enhancing the students’ speaking performance are building a supportive learning environment, improving vocabulary, using technology, and giving feedback to the students’ speaking performance. Thus, students and lecturers can contribute to create the strategies to enhance students’ speaking performance.
Source localization in signed networks with effective distance

Abstract While progress has been made in information source localization, it has overlooked the prevalent friend and adversarial relationships in social networks. This paper addresses this gap by focusing on source localization in signed network models. Leveraging the topological characteristics of signed networks and transforming the propagation probability into effective distance, we propose an optimization method for observer selection. Additionally, by using the reverse propagation algorithm we present a method for information source localization in signed networks. Extensive experimental results demonstrate that a higher proportion of positive edges within signed networks contributes to more favorable source localization, and the higher the ratio of propagation rates between positive and negative edges, the more accurate the source localization becomes. Interestingly, this aligns with our observation that, in reality, the number of friends tends to be greater than the number of adversaries, and the likelihood of information propagation among friends is often higher than among adversaries. In addition, the source located at the periphery of the network is not easy to identify. Furthermore, our proposed observer selection method based on effective distance achieves higher operational effciency and exhibits higher accuracy in information source localization, compared with three strategies for observer selection based on the classical Full-order neighbor coverage.
Analysis of Real Time Twitter Sentiments using Deep Learning Models

Understanding attitudes regarding distinct topics and public opinions on the sentimental analysis of social media data is important. This research analyses the real-time twitter sentiments using deep learning. The major objective of the study is to create an efficient sentiment analysis algorithm to accurately ensure the sentiment polarity (positive, neutral or negative) of tweets. This study proposed a deep learning approach to capture the contextual information and complex patterns in social media data which leverages the power of neutral networks. To assess the performance of the algorithm the study relies on the evaluation of F1 score, accuracy, precision, and recall through rigorous evaluation metrics. The efficiency of the proposed approach is demonstrated by the numerical outcomes of the study. A novel contribution is provided with a specific emphasis on real-time Twitter sentiments by the study to enhance the sentiment analysis techniques for social media data. The significant implication from accurate and timely analysis of Twitter sentiments for several applications includes public opinion tracking, brand management, customer feedback analysis, and reputation monitoring. The potential to provide significant insights to researchers, organisations and business can be made from promptly addressing the sentiments expressed on real time data of twitter.
Long short-term memory-based chatbot for vocational registration information services

The development of chatbots can communicate fluently like humans thanks to the Natural Language Processing (NLP) technology. Using this technology, chatbots can provide more accurate and natural responses, providing an almost the same experience as human interaction. Therefore, chatbot technology is in great demand by companies and government agencies as a cost-effective solution for information and administrative services that require little human effort and can operate 24/7. The registration information service at BLK Surabaya still uses an operator who serves prospective trainees and answers questions via social media or chat. However, these operators have limitations in terms of time and effort. The purpose of this study is to examine how to use chatbots to answer questions about registration information training at BLK Surabaya using the Long Short Term Memory (LSTM) algorithm with a dataset of questions collected in the form of Frequently Asked Questions (FAQ) in Indonesian. The dataset consists of 2,636 labeled samples of questions, which were divided into three sets: 60% for training (1,581 pieces), 20% for validation (527 samples), and 20% for testing (528 samples) to evaluate the model's performance. Several steps were taken in implementing this research, including changing the list of questions and answers into the JSON data format, preprocessing, creating LSTM modeling, data training, and data testing. The test results show that Chatbot can provide accurate solutions related to training registration questions with Precision of 88.4%, Accuracy of 87.6%, and Recall of 87.3%.
Comparing Kahoot, Quizizz, And Wordwall In EFL Reading Class

The purpose of this study was to compare Kahoot, Quizizz, and Wordwall on student learning outcomes in reading classes. The urgency of this research was to provide references for educators in choosing gamification platforms that are effective for improving learning outcomes and efficient for use as assessment media. This research was comparative quantitative research with a true experimental design. The data analysis technique used was one-way ANOVA with a sample of 57 students. The results stated that there were differences in student learning outcomes that were gamified via Kahoot, Quizizz, and Wordwall. This hypothesis was taken because the analysis results in the ANOVA table show a significance value of 0.013 &lt;0.05, meaning that there are differences in student learning outcomes, so the H1 hypothesis was accepted and the H0 hypothesis was rejected. Furthermore, the results of the post hoc test analysis state that Quizizz was more effective in improving student learning outcomes compared to groups that are gamified via Kahoot and Wordwall. This was evidenced by the average learning outcomes in the Quizizz group of 9.00, which were the highest compared to the Kahoot and Wordwall groups.
Perancangan Sistem Informasi Akuntansi Penggajian Pegawai Instansi Pemerintah di BKPSDM Kab. Cianjur

The process of employee payroll system at BKPSDM Kab. Cianjur Agency already uses a computer but it is not optimal because it still uses Microsoft Excel in data collection and calculation salaries. The purpose of this research is to create a computerized payroll information system that make it easier for agency in the payroll process for employees and minimize the problems that often occur. This information system designed using PHP Myadmin programming language and MySQL as a database. The approach to developing this system uses the waterfall method and the tools involved include Flowmap, Context Diagram, Data Flow Diagrams (DFD), and Entity Relationship Diagrams (ERD). The results of this employee payroll application can make it easier to collect employee data and calculation of employee salaries accurately and can streamline time in making reports so as to reduce errors in the employee payroll system.&#x0D; Keywords: accounting information system; payroll; waterfall
Minat Penggunaan Aplikasi Flip ditinjau dari Kemudahaan, Manfaat, Fitur layanan, dan Kepercayaan pada Reseller Beteng Trade Center

This study aims to analyze the effect of Perceived Ease of Use, Perceived Usefulness , service features and trust on interest in using the Flip Application. The population in this study were 105 Beteng Trade Center resellers who had used Flip. The results show that Perceived Ease of Use, Perceived Usefulness, have no effect on interest in using the Flip Application, while service features and trust have a positive and significant influence on interest in using the Flip Application.&#x0D; Keywords: Perceived Ease of Use, Perceived Usefulness, service features, trust, interest in use.&#x0D;
Pengaruh Sertifikasi Halal dan Izin Edar BPOM terhadap Minat Beli Kosmetik pada Mahasiswi

Whether we realize it or not, in everyday life, women's needs can’t be separated from cosmetics and other beauty products to support their appearance. The increasing public interest in beauty trends encourages the cosmetic industry to develop rapidly. The desire of women to always look beautiful invites actors who are not responsible for creating or trading cosmetics that do not meet the circulation regulations. Basically, this research was conducted with the aim of knowing the effect of halal certification and BPOM distribution permit on the buying interest of female students. This study uses descriptive analysis techniques with a quantitative approach. The population in this study were students of the Faculty of Economics and Islamic Business, Alauddin State Islamic University, Makassar. In determining the sample using the formula from Krijie and Morgan with a total sample of 336 respondents. IBM Statistics SPSS 25 was used as the data analysis method in this study. From the research process, it was found that halal certification had an effect on student cosmetic buying interest. Meanwhile, the distribution permit of BPOM also influences the cosmetic buying interest of female student.&#x0D; Keywords: Halal certification; BPOM Circulation Permit; Buying Interest; Cosmetics
Web-Based Weekly Cash Accounting Information System Design at XYZ Institution

This study aims to create a web-based accounting information system to assist user needs, especially the finance department in processing weekly cash financial data at XYZ company, as well as to produce reports needed by users more effectively and efficiently. This research method uses qualitative research methods. With the results of this system design it can be a solution for the future, especially for the finance section because it is able to help check data, because this system is made to be able to search data based on day, date, year or transaction number so that the process can be more time efficient.
Pemanfaatan Gamelan Digital sebagai Upaya Peningkatkan Kreativitas Mahasiswa PGMI

Purpose: This study aims to see the increase in student creativity in SBDP courses on music art material. Involving 45 PGMI FITK UIN Sunan Kalijaga students consisting of 2 rombel, and grouped in 1 experimental class and 1 control class. Method: The method used is quantitative discretive t test to see the comparison of experimental and control classes. Result and Discussion: Based on the results of the analysis and research hypothesis, it shows that learning SBDP digital music material has been proven to increase student creativity. Observation data obtained that before the action was taken there were 45% of students who had not increased their creativity and there were 55% of children who began to develop their creativity abilities. After taking action in cycles I, II and III, it was obtained that the increase in creativity ability in the experimental class was 67.45% and 22.12% in the control class. The results of this study can see the differences and creativity abilities of students in using smartphone technology in SBDP courses on the theme of digital gamelan music.
Effectiveness of feeding Maggot (Hermetia illucens) and Biomassa Microalga Aurantiochytrium for The Improvement of Joper Chicken (Gallus dometicus) Productivity

Maggots and microalgae Aurantiochytrium sp. are known to improve the growth performance of chickens. However, the provision of these two components of chicken feed is still not widely reported. Maggot contains protein, while Aurantiochytium microalgaeÂ contain omega 3 DHA, both of which are good for growth. This study aims to determine the effectiveness of feeding joper chickens (Gallus dometicus) with maggot (Hermetia illucens) and Aurantiochytrium. The location of the research will be carried out at the Green House of Muhammadiyah University Prof. DR. Hamka. The study was conducted experiments using Complete Randomized Design (RAL) with 6 treatments and 4 repeats. TreatmentÂ P0 (bran and corn 100%), P1 (maggot 10%, microalgae Aurantiochytrium 1.5%, bran &amp; corn 88.5%), P2 (maggot 20%, microalgae Aurantiochytrium 2%, bran &amp; corn 78%), P3 (maggot 30%, microalgae Aurantiochytrium 2.5%, bran &amp; corn 67.5%), P4 (maggot 40%, microalgae Aurantiochytrium Â 3%, bran &amp; corn 57%), P5 (maggot Â 50%, microalgae Aurantiochytrium Â Â Â 3.5%, bran &amp; corn 46.5%) The variables observed were body weight and growth in the daily weight rate of joper chickens. The results showed thatÂ the effect of variations in the concentration of maggot and Aurantiochytrium microalgae onÂ feed had a significant effect on body weight (P&lt;0.05) and a real effect also (P&lt;0.05) on the daily weight growth rate of joper chickens
Implementasi Absensi SIAP (Sistem Informasi Absensi Pegawai) pada Dinas Perindustrian dan Perdagangan Kabupaten Karawang

Along with the development of science and technology in the era of globalization, various applications on smartphones aim to make it easier for users, especially during the COVID-19 pandemic, where many companies implemented work-from-home (WFH) policies, fieldwork and official employees leaving the city. So there is a problem with employee attendance because usually attendance is only done in the office. This research aims to: determine the implementation of SIAP Attendance (Employee Attendance Information System) at the Karawang Regency Industry and Trade Service. The method used in this research is descriptive qualitative using the Triangulation Technique. The sample used was 5 people, using observation and interviews. The research results show that SIAP Attendance can improve an employee's attendance discipline, because this attendance system uses GPS technology, so superiors can know the employee's location when taking attendance.
Sumber Belajar dan Alat Permainan Edukatif untuk Anak Usia Dini

As a result of studying various materials, learning is a process or endeavor that each individual undertakes to bring about behavioral changes, whether in the form of knowledge, skills, attitudes, or positive values. To make the learning process enjoyable for children, a variety of learning resources and engaging educational activities are required. In early childhood, the goal of learning resources and educational game tools is to facilitate the implementation of engaging, focused, and high-quality learning activities for children. The availability of learning resources and educational game tools is crucial because it encourages children's enthusiasm, motivation, and interest in learning and exploring diverse information sources freely and in accordance with their interests. The method employed is a library research method or strategy, and data collection is conducted by studying and exploring a number of periodicals, books, and documents (both print and electronic), as well as other data and/or information sources regarded relevant to the research. Study. Parents and educators must utilize developmentally appropriate learning resources and educational play tools to leverage the potential of early childhood (AUD), according to the findings of this study.
ViT-SigNet: Combining Deep CNN and Vision Transformer for Enhanced Signature Verification

In the digital era, digital signatures are crucial for online processes and transactions. Their blend of security and ease has spurred various verification methods, including machine and deep learning models. Vision Transformers (ViT) have recently gained traction for image tasks due to their effectiveness. This study presents a signature verification method combining a custom ResNet-50 Convolutional Neural Network (CNN) and Transformers. This combined model leverages ResNet-50’s image extraction capabilities and the Transformer’s attention mechanism. We optimized the model with learning rate adjustments, enhancing its performance. Our data included 534 personal signatures from students, split into 128 for training and 406 for testing. We used machine learning for feature extraction and classification, assessing genuineity with cosine similarity. We tested various CNNs, ViT, and our combined model. Paired with XGBoost, our model achieved a 97.7% precision, 98.45% recall, and 97.5% F1 score. It also performed well in signature verification metrics like FNMR 0.090, FMR 0.059, and EER 0.075. Our method shows promise for advancing signature verification, suggesting potential future research directions.
Building an Efficient Retriever System with Limited Resources

Despite significant advancements in Question-Answering (QA) systems based on Large Languge Models (LLMs), the issue of generating imprecise answers leading to less informative responses persists. To develop effective QA systems for open-domain datasets, particularly content-specific datasets, dense passage retrieval and the two-stage retriever-reader model remain a rational choice. However, when being applied in real-world systems, these approaches encounter challenges posed by the limitation of computational resources and training data. To address the scarcity of training data, we propose fine-tuning the pretrained BERT-based encoder using masked language modeling before employing a dual-encoder architecture—an established and efficient technique. Additionally, we introduce a modified loss function for dual-encoder training that reduces memory usage during training without compromising system performance. The new loss function is employed in a multi-stage training strategy, yielding enhanced retriever performance at each training stage. To further augment the system's capabilities, we train a cross-encoder to construct a robust retriever for domain-specific datasets. The effectiveness of these proposed techniques is validated by experiments with significant increases in performance compared to the baseline models, underscoring their potential to advance the state-of-the-art in open-domain question-answering systems.
Research on the Role of Career Planning in Promoting Grassroots Employment of College Students under the Background of Rural Revitalization

With the advancement of China's rural revitalization strategy, the development of rural areas is facing new opportunities and challenges. At the same time, the employment problem of college students has always been a concern of society, especially in the grassroots employment field, there are certain difficulties and challenges. Therefore, studying the role of career planning in promoting grassroots employment for college students is of great significance for adapting to the needs of rural revitalization and solving the employment problem of college students. The purpose of this study is to explore the role of career planning in promoting grassroots employment of college students in the context of rural revitalization in China, and to analyze in depth the impact of career planning on grassroots employment of college students. In addition, this article proposes suggestions to enhance students' awareness of grassroots employment and strengthen career planning education and practice, aiming to provide theoretical and practical guidance for promoting grassroots employment of college students and supporting rural revitalization.