Reviewerly/exHarmony huggingface dataset:
Conformal Prediction Regions for Time Series using Linear Complementarity Programming

Conformal prediction is a statistical tool for producing prediction regions of machine learning models that are valid with high probability. However, applying conformal prediction to time series data leads to conservative prediction regions. In fact, to obtain prediction regions over $T$ time steps with confidence $1-\delta$, {previous works require that each individual prediction region is valid} with confidence $1-\delta/T$. We propose an optimization-based method for reducing this conservatism to enable long horizon planning and verification when using learning-enabled time series predictors. Instead of considering prediction errors individually at each time step, we consider a parameterized prediction error over multiple time steps. By optimizing the parameters over an additional dataset, we find prediction regions that are not conservative. We show that this problem can be cast as a mixed integer linear complementarity program (MILCP), which we then relax into a linear complementarity program (LCP). Additionally, we prove that the relaxed LP has the same optimal cost as the original MILCP. Finally, we demonstrate the efficacy of our method on case studies using pedestrian trajectory predictors and F16 fighter jet altitude predictors.
Data-Efficient Policy Selection for Navigation in Partial Maps via Subgoal-Based Abstraction

We present a novel approach for fast and reliable policy selection for navigation in partial maps. Leveraging the recent learning-augmented model-based Learning over Subgoals Planning (LSP) abstraction to plan, our robot reuses data collected during navigation to evaluate how well other alternative policies could have performed via a procedure we call offline alt-policy replay. Costs from offline alt-policy replay constrain policy selection among the LSP-based policies during deployment, allowing for improvements in convergence speed, cumulative regret and average navigation cost. With only limited prior knowledge about the nature of unseen environments, we achieve at least 67% and as much as 96% improvements on cumulative regret over the baseline bandit approach in our experiments in simulated maze and office-like environments.
Crossword: A Semantic Approach to Data Compression via Masking

The traditional methods for data compression are typically based on the symbol-level statistics, with the information source modeled as a long sequence of i.i.d. random variables or a stochastic process, thus establishing the fundamental limit as entropy for lossless compression and as mutual information for lossy compression. However, the source (including text, music, and speech) in the real world is often statistically ill-defined because of its close connection to human perception, and thus the model-driven approach can be quite suboptimal. This study places careful emphasis on English text and exploits its semantic aspect to enhance the compression efficiency further. The main idea stems from the puzzle crossword, observing that the hidden words can still be precisely reconstructed so long as some key letters are provided. The proposed masking-based strategy resembles the above game. In a nutshell, the encoder evaluates the semantic importance of each word according to the semantic loss and then masks the minor ones, while the decoder aims to recover the masked words from the semantic context by means of the Transformer. Our experiments show that the proposed semantic approach can achieve much higher compression efficiency than the traditional methods such as Huffman code and UTF-8 code, while preserving the meaning in the target text to a great extent.
Coincidental Generation

Generative A.I. models have emerged as versatile tools across diverse industries, with applications in privacy-preserving data sharing, computational art, personalization of products and services, and immersive entertainment. Here, we introduce a new privacy concern in the adoption and use of generative A.I. models: that of coincidental generation, where a generative model's output is similar enough to an existing entity, beyond those represented in the dataset used to train the model, to be mistaken for it. Consider, for example, synthetic portrait generators, which are today deployed in commercial applications such as virtual modeling agencies and synthetic stock photography. Due to the low intrinsic dimensionality of human face perception, every synthetically generated face will coincidentally resemble an actual person. Such examples of coincidental generation all but guarantee the misappropriation of likeness and expose organizations that use generative A.I. to legal and regulatory risk.
Bringing Telepresence to Every Desk

In this paper, we work to bring telepresence to every desktop. Unlike commercial systems, personal 3D video conferencing systems must render high-quality videos while remaining financially and computationally viable for the average consumer. To this end, we introduce a capturing and rendering system that only requires 4 consumer-grade RGBD cameras and synthesizes high-quality free-viewpoint videos of users as well as their environments. Experimental results show that our system renders high-quality free-viewpoint videos without using object templates or heavy pre-processing. While not real-time, our system is fast and does not require per-video optimizations. Moreover, our system is robust to complex hand gestures and clothing, and it can generalize to new users. This work provides a strong basis for further optimization, and it will help bring telepresence to every desk in the near future. The code and dataset will be made available on our website https://mcmvmc.github.io/PersonalTelepresence/.
WeakTr: Exploring Plain Vision Transformer for Weakly-supervised Semantic Segmentation

This paper explores the properties of the plain Vision Transformer (ViT) for Weakly-supervised Semantic Segmentation (WSSS). The class activation map (CAM) is of critical importance for understanding a classification network and launching WSSS. We observe that different attention heads of ViT focus on different image areas. Thus a novel weight-based method is proposed to end-to-end estimate the importance of attention heads, while the self-attention maps are adaptively fused for high-quality CAM results that tend to have more complete objects. Besides, we propose a ViT-based gradient clipping decoder for online retraining with the CAM results to complete the WSSS task. We name this plain Transformer-based Weakly-supervised learning framework WeakTr. It achieves the state-of-the-art WSSS performance on standard benchmarks, i.e., 78.4% mIoU on the val set of PASCAL VOC 2012 and 50.3% mIoU on the val set of COCO 2014. Code is available at https://github.com/hustvl/WeakTr.
Convergence and Disruption in Digital Society -- Money, Secure  Communication, Digital Objects and Generative AI in Spatial Mixed Reality

In the digital society's evolving landscape, open-source tooling and generative AI are pivotal in transforming global collaboration. These technologies promise to dismantle traditional barriers of accessibility, language, and governance, fostering an inclusive digital ecosystem. However, the journey towards a fully integrated digital society faces significant challenges, including trust, accessibility, and sustainable development. Emerging technologies like global ledgers and blockchain propose novel methods for transferring digital goods and personal data across diverse digital spaces. This development, coupled with augmented intelligence tools, aims to create decentralized and federated environments where creativity and collaboration can flourish. An "open metaverse" concept is gaining traction, promoting an alternative to restrictive proprietary platforms and emphasizing user empowerment and equity. Despite the opportunities, governance and ethical considerations remain paramount. The digital society must navigate the fine balance between innovation and the potential risks associated with new technologies. The drive for an inclusive, innovative, and secure digital society necessitates a commitment to open-source principles and ethical AI application. It also involves overcoming cultural, legislative, and technical barriers that impede global collaboration. The future digital society envisions a collaborative, inclusive, and innovative global community. By focusing on augmented intelligence and supported creativity, it aims to unlock new possibilities for economic empowerment, cultural exchange, and technological advancement. This vision is not without its challenges, but with continued commitment to ethical, open, and inclusive development, a more connected and empowered global community is within reach.
Scene gist and local meaning guide attention and build memory representations: Evidence from mouse-clicks

Global and local semantic information are thought to influence where attention is allocated in real-world scene images. How the two interact to guide attention and what subsequent effects each has on memory for a viewed scene is unknown. We used the BubbleView paradigm (Kim, Bylinskii, et al., 2017) to monitor movements of attention via participants’ clicks during a scene-viewing task. We manipulated access to scene gist by providing a preview of the BubbleView scene on some trials. ‘Click Maps’ were compiled from participants’ click locations. These were compared to fixation density maps for the same scenes and to meaning maps. Click maps were similar to fixation density maps, suggesting that clicks in the BubbleView paradigm approximate the locus of overt attention. In both a between-subjects (Experiment 1) and a within-subjects comparison (Experiments 2 and 3), access to gist guided attention to locally meaningful scene regions. Local meaning also guided attention, even in the absence of gist. These results support theories describing cognitive guidance of attention in natural scene images. Access to gist and attention to meaning were also important for participants’ memory for the scene images: when participants had access to gist and when they had clicked more meaningful scene regions, they were more likely to remember the image at test. Taken together, our results suggest that global (scene gist) and local scene semantics influence both where we attend in a scene and our subsequent memory for it.
Structural Teaching of Basic Practice of Writing a Publication to Young Writers of a Public Elementary School

This study intends to enhance writing skills among young writers in a public elementary school through the structural teaching basic practice of writing a publication. Effective expression of one's own views, opinions, ideas, and values on a certain subject through writing using one's own language is a skill that should be nurtured in school for every student. This study used a descriptive research design, and the participants were 35 students from a public elementary school. Qualitative data were gathered through the use of questionnaires with pretest and post-test to analyze whether the implementation of structural teaching basic practice of writing a publication to young writers of public elementary school was effective in improving the students' writing skills. The study revealed the skills that most of the grade 4, grade 5 and grade 6 students have not yet mastered are the following: writing an explanation, talks, commenting on an issue and an opinion on an issue (97.14%); writing scripts for radio broadcasting and writing short news, editorials, and other parts of the newspaper (100%); writing a report, sports news, letter to the editor, script for radio broadcasting (100%) respectively. Descriptive statistics were used to interpret data gathered. The students got a pretest mean score of 11.63 with a standard deviation of 0.55 and a post-test mean score of 25.66 with a standard deviation of 0.51. It is evident that there is an increase in mean score of +14.03 between pre and post-tests, from 11.63 to 25.66. The participants' pre-test and post-test differences are very significant based on the computed t-value of 29.08 0.05 level of significance. It is important to note that the use of structural teaching basic practice of writing a publication to young writers has improved their skills in writing.
Electronic Commerce Ethics: The Business Ethics Practices applied by Online Sellers in Qatar

Introduction As technologies advance the market takes a step forward and becomes accessible to everyone through the Internet Especially with the past pandemic of COVID plenty of entrepreneurs joined the online business industry This study focuses on the business ethics practices of online sellers in Qatar Methodology Using a quantitative descriptive research design a survey questionnaire was made and validated The researchers chose online sellers in Qatar using purposive and quota sampling and distributed the research instrument Result This study discusses the business ethics used by online sellers which are Security Privacy Non Deception and Reliability Furthermore the study s results show the level at which online sellers execute these business ethics in electronic commerce It was found that Reliability is the highest business ethic applied by online sellers in Qatar overall followed by Privacy Security and then Non Deception Discussion The conclusion drawn from this study states that most businesses in Qatar practice a high level of business ethics However there was also a difference in the online sellers practice of business ethics according to their demographic profile Regarding age the older the respondents the higher they applied business ethics In terms of sex there was a minor to no correlation between gender and online ethical behavior Finally in terms of the length of business operation the longer the business is operated the higher its owner applied business ethics Recommendation It is recommended that online sellers in Qatar maintain or improve the practice of business ethics in electronic commerce to benefit their business and their consumers
Youtube Transcript Summarizer Using Flask

Abstract: Every day, countless videos are being created and shared on YouTube. and Such videos are the primary source of learning for college and school going students, people preparing for competitive exams and many more people use YouTube for productive outcomes. But longer than expected videos can be difficult to watch, and if we don't learn anything useful from them, our efforts might be in vain. Even sometimes while watching video people face lots of obstacles like network issues and all may lead to wastage of time. Automated summarization of video text allows us to quickly spot important trends and efficiently streamline the video's content, thus saving our time and efforts. In this YouTube transcript summarizer web application developed using flask, the transcript of the video is converted into text and thus summarizing that text and in case if there is no transcript available then the model will convert the audio directly into text using speech recognition followed by the summarization. Summary can be downloaded and translate in different language. Summarization of the video is done by using Python libraries and NLP (Natural Language Processing).
Telegram Bot-Based Expert System as A Detection Tool for Early Symptoms of Borderline Personality Disorder

The prolonged COVID-19 pandemic may cause stress that leads to both physical and mental health issues, especially for those who categorized as mentally fragile people, such as the people with Borderline Personality Disorder (BPD) where their fragility is caused by overreaction to stress compared to normal people. This journal explains how AI is applied in form of a Telegram-bot based expert system that aims to be a tool to detect early symptoms of BPD and provide treatment advice to people with BPD (PWBPD) as well as people who can potentially be PWBPD, according to recommendation of the psychologist. This research was conducted with qualitative method. The data collection is done by interview and literature study. Application development is carried out using waterfall method, forward chaining reasoning method, PHP, and MySQL. Application testing is done by interview to psychologist. The study shows an overall result that this tool is useful in providing education, detection, and the right ways to treat early symptoms of BPD. This application is also considered interesting and easy to use. The application testing results have been confirmed to pass the qualitative test using interview method with the psychologist and BPD expert, Dr. Christin Wibhowo, S.Psi, M.Si.
Development of Electronic Documentation System for Final Project with Gamification to Improve the Effectiveness of Final Project Creation

The final project is very important for every student in their educational program. This is a final project that requires in-depth research and thought, helping students put into practice the knowledge they learn and apply it in the form of real work. In several educational programs, the results of the final assignment can also be used as a determining factor for a student's final grade. The process of preparing the final assignment involves several stages, including determining the topic, selecting a supervisor, conducting guidance, conducting a plagiarism test, final assignment exam, and uploading the results of the assignment. end to the existing system. However, in such a long process, if it is not supported by a good system, the process of compiling the Final Project can be a troublesome thing. Therefore, there is a need for a gamification process in the existing system to improve the quality of the system and re-encourage students in doing their final assignments. Gamification uses game design and has several important components such as feature points, badges, levels, leaderboards, challenges and prizes. The gamification process can increase student involvement and the achievements given.
The Utilization Of Cse Mikrobisnis Application Build Via Wordpress In Supporting Small Business

An information system is a set of software components that aid in the process of converting raw data into information that is needed by a related party. In utilizing information systems that facilitate work and decision making, its use cannot be separated from the role of technology and the internet. Therefore, information systems are an essential component of any business, organization, or even individual. Technology of information systems offers numerous benefits in the business sector. Particularly when dealing with the rivals by channeling innovations and different ideas purchased on the internet. The same thing happens to entrepreneurial businesses that benefit from technology for their development, even though they started from scratch. Transactions for purchasing products and meals using the CSE Mikrobisnis application via Wordpress, are the example of a technology in information system use for the student business. Before it can be extensively used, it is essential to evaluate the application’s viability and functionality to ensure that users can conduct transactions with confidence.
Effectiveness of “How to Write a Sentence” as Instructional Material to Improve the Writing Skills of Grade 6 Pupils

As students’ progress in their studies, they must learn a variety of important skills. Among these is writing, which is undeniably one of the most important skills that every student must develop. However, writing has always been a major challenge for students learning English, particularly in elementary schools and for second language learners. This study determined the effectiveness of the instructional material "How to Write a Sentence" as an intervention to improve the writing skills and academic performance in English of Grade 6 students at a public elementary school in the Philippines. The one-group pretest-posttest design of the quasi-experimental research design was used in this study. A 50-item pretest and posttest were used to assess the participants' academic performance before and after the intervention was implemented. The mean, standard deviation, and paired-samples t-test were used to interpret the data. Results revealed that the use of the instructional material "How to Write a Sentence" was found to be an effective intervention in improving the writing skills and academic performance in English of Grade 6 students at a public elementary school in the Philippines. It is recommended that administrators should encourage teachers to collaborate in order to further enhance or improve the intervention material or to create other contextualized and localized learning materials suited to diverse learner types.
Study Habit and Social Media Exposure as Predictors of Grade 10 Students Academic Performance

The purpose of this study was to determine the respondents' study habits and social media exposure during the school year. 2019-2020.The study's participants were 50 grade 10 students of Alabel 4 District. The researcher administered the survey to all of the student respondents. Majority of respondents were 17 years old, and the majority of their parents had a bachelor's degree and were all employed.&#x0D; The researcher administered the survey to all of the student respondents. The majority of respondents were 17 years old, and the majority of their parents had a bachelor's degree and were all employed. It also has a high correlation with respondents' social media exposure. The responses revealed that respondents' use of social media has a direct or indirect positive effect on their academic performance.&#x0D; The study suggests that parents should constantly guide and supervise their children's use of social media, particularly female and younger students who are more interested in social networking. Despite the fact that this study discovered that respondents' socio-demographic characteristics have no bearing on their academic performance. It also suggests that a long-term program be implemented to assist students in constantly improving their study habits.&#x0D; According to the study's findings, teachers must continue to effectively stimulate and sustain students' interests and enthusiasm for learning in order for them to consistently achieve exceptional academic performance. Teachers should receive regular service trainings and workshops to stay current on their knowledge and pedagogical skills, improve the quality of the teacher workforce, and improve students' academic achievement.
PENGARUH PENGGUNAAN MEDIA AUDIO VISUAL DAN MOTIVASI BELAJAR SISWA TERHADAP HASIL BELAJAR MATA PELAJARAN AKIDAH AKHLAK DI KELAS VII SMP MUHAMMADIYAH WATUKELIR SUKOHARJO TAHUN AJARAN 2021/2022

This study aims to determine how the influence of the use of audio visual, learning motivation, student learning outcomes and is there any effect of using audio-visual media and learning motivation on student learning outcomes. This type of research is quantitative research. The subjects in this study were 7th grade students of SMP Muhammadiyah Watukelir Sukoharjo. Data collection techniques used in this study were interviews, questionnaires, observation and documentation. While the data analysis using multiple linear regression. Measuring instrument validity test uses the Product Moment Person correlation, and the reliability test uses Cronbach's Alpha formula. The analysis requirements test consists of a data normality test, a linearity test and multicollinearity test. Hypothesis testing using multiple linear regression analysis. The results of this study show that audio-visual media and learning motivation have an effect on student learning outcomes.