Reviewerly/exHarmony huggingface dataset:
Private Boosted Decision Trees via Smooth Re-Weighting

Protecting the privacy of people whose data is used by machine learning algorithms is important. Differential Privacy is the appropriate mathematical framework for formal guarantees of privacy, and boosted decision trees are a popular machine learning technique. So we propose and test a practical algorithm for boosting decision trees that guarantees differential privacy. Privacy is enforced because our booster never puts too much weight on any one example; this ensures that each individual's data never influences a single tree "too much." Experiments show that this boosting algorithm can produce better model sparsity and accuracy than other differentially private ensemble classifiers.
Smart CCTV Detection Using Local Binary Pattern Histogram (LBPH)

Smart CCTV Detection Using Local Binary Pattern Histogram (LBPH) is a computer vision technique used to improve the accuracy of object detection in video surveillance. This approach uses the LBPH algorithm with the accuracy of 97.56% to extract features from image frames captured by CCTV cameras. The LBPH algorithm is a texture-based feature extraction method that is robust to illumination changes and is capable of detecting local patterns within an image.The proposed system consists of three main stages: preprocessing, fea- ture extraction, and classification. In the preprocessing stage, the input image is preprocessed to enhance its quality and reduce noise. In the feature extrac- tion stage, the LBPH algorithm is applied to the preprocessed image to extract texture features. Finally, in this study, the structural similarity index and the LBPH algorithm are proposed as Smart CCTV with intrusion detection [1]. CCTV cameras record real-time video and analyses it as it is recorded, using intrusion detection to locate illegal individuals entering our monitoring area. Experimental findings demonstrate that the suggested system achieves 97.56% high accuracy in object detection compared to existing methods. This tech- nique has potential applications in various fields such as surveillance, security, and traffic monitoring.
Innovation in Content Design and Construction Path of University Physical Education Teaching Based on Mathematical Model Evaluation

Physical education is an indispensable educational content for cultivating qualified talents. Implementing the educational concept of "cultivating morality and cultivating talents" in college physical education classrooms, combining skill teaching with physical exercise, improving students' cognitive level of sports and health, integrating ideological and political teaching content into public physical education courses, emphasizing student process evaluation, using new technological means, and increasing the assessment of students' extracurricular physical exercise. Relying on student sports club activities, Sunshine Sports Alliance, sports team training and competition activities, strengthen the construction of the "second classroom", investigate students' learning attitude and moral quality, pay attention to path innovation, use research and mathematical evaluation analysis methods, calculate the elements and weights of the cultivation of teaching ability of college physical education, and try to establish the teaching content structure and evaluation system of public physical education.
Uji Coba Gim Edukasi dalam Meningkatkan Hasil Belajar Bahasa Inggris

ABSTRACT&#x0D; This study aims to test the effectiveness of educational game-based digital learning media in improving grade IV elementary school English learning outcomes. The pre-experimental design and One Group Pretest-Posttest were used in this study with a sample of 20 students in a school in Makassar. Pretests and posttests are given to learners to obtain data on improving learning outcomes, which are then analyzed using t-tests and N-Gain. The results showed that there was a significant difference in test results between pretest and posttest seen from the sig.2-tailed value of 0.000, where this result was smaller than 0.05. In addition, an N-Gain of 0.49 indicates a moderate category and indicates that the trial of educational game-based digital learning media can improve student learning outcomes. Educational games can be used as an effective learning medium in the learning process and need to be developed in a better direction.&#x0D; &#x0D; Keywords: Learning Media, Educational Games, Learning Outcomes.
Pengembangan Modul Mata Kuliah Media dan Bahan Ajar Bahasa Indonesia Berbasis Literasi Kritis di Universitas PGRI Silampari

This study aims to determine the development of modules, valid, practical and efficient for Critical Literacy-based Indonesian Media and Teaching Materials courses at PGRI Silampari University. This study uses the R&amp;D (research and development) development model as a guideline for developing critical literacy-based modules for Media Courses and Indonesian Teaching Materials. The sample in this study were VA semester students of the Indonesian Language and Literature Education Study Program at PGRI Silampari University for the 2022/2023 academic year. Data collection techniques carried out included interviews, questionnaires and tests. There are analysis techniques in the form of interview data analysis, questionnaire data analysis and test data analysis. Furthermore, the Indonesian Language Media and Teaching Materials module is valid in the "very good" category with a result of 0.812. From the results of the one to one prototype test, small group test and large group test it is concluded that the Indonesian Language Media and Teaching Material module is practical to use. Data from formative test results show that the average student score is 81.14 in the very good category so it is concluded that the Indonesian Language Media and Teaching Materials module is effectively used in lectures.&#x0D; &#x0D; Keywords: Development, Modules, Indonesian Language.
Use of Android-Based Media Benime Whiteboard Animation in Learning to Write Procedure Text in Vocational High School Students

In the era of the Industrial Revolution 4.0, students are a generation that is very close to the touch of technology. Therefore, teachers can not only rely on traditional-based media, but can also take advantage of technology-based media that are packaged attractively, creatively, and innovatively in order to achieve learning competencies. The purpose of this research is to develop teaching materials in the form of Â the Benime White Board Animation android application Â that can be accessed through student devices. This study also aims to determine the influence of android-based learning media on students' ability to determine the structure and linguistic characteristics of procedural texts. This study uses the R&amp;D (Research and Development) methodÂ which describes data on the Â influence of Benime White Board Animation's android-based learning media Â on students' ability to write procedure texts. The subjects in this study were 36 grade XI students of SMKN 1 Soreang. Data collection was carried out by observation, interviews, and questionnaires. After research, The Benime White Board Animation android applicationÂ was successfully developed so that it can be accessed flexibly. In addition, the quality of this application is rated very decent / very good based on the average score carried out by validators, which is 85.59%. Each assessment was a media expert 83.77%, a material expert 85.00%, and a teacher Indonesian 88.00%. Then, students responded to the application during the trial by giving an excellent rating of 87.24%. Therefore, the Benime White Board Animation Â application has implications for learning that can be used as teaching materials so that it can improve writing skills, especially procedure texts.
THE INFLUENCE OF EDUCATIONAL ONLINE GAMES ON STUDENT LEARNING MOTIVATION

Online games use multimedia that is made as attractive as possible so that players get batik satisfaction and use internet access. So online games can have an impact on student learning motivation. This study aims to determine and analyze online games' influence on student learning motivation at SD Muhammadiyah 1 Waru, Sidoarjo Regency. The type of research used is quantitative. Data collection techniques use questionnaires and documentation of students. The results of research that has been conducted show 1) Online games affect learning motivation in students; 2) The application of a comprehensive technology learning process is one alternative strategy to deal with students who have online game addiction; 3) Based on the results of research on children, it can be seen that a) children spend 15% of the time playing the Internet for 30 minutes, then increase by 25% for 2 to 3 hours in one day; b) 60% of children play the Internet for 5 hours per day or more than 5 hours during school holidays. Based on the findings of a simple linear regression test, it was found that the r-count has a significance level of 5%, which is 0.703 &gt; 0.444, and the r-count &gt; the r-table. Thus, Ha believes that online games influence grade students' motivation to learn at SD Muhammadiyah 1 Waru Kabupateln Sidolarjol is acceptable. Hypothesis tests show a significant effect of educational online games on learning motivation in grade 3, 4, and 5 students of SD Muhammadiyah 1 Waru.
Counterfactual and alternative histories as design practice

The version of design that was shaped and perfected during the 20th Century played a huge role in the making of the modern (global northern) world. Whilst design’s potential as a contributor to the making of worlds is clear, its methods, metrics and purposes have led to a world that is increasingly revealed as fragile, broken and unsustainable. In other words, design today is complicit in the breaking of the world – this essay describes a practice-based design research approach to the making of other worlds. Borrowing from the literary approaches of counterfactual and alternative histories and imaginative fiction, it aims to facilitate the development of new approaches to design, informed through alternative ideologies, methods and motivations. &#x0D; The counterfactual approach allows us to imagine other ways to be, in this case through the application of alternative value systems, a non-additive approach to technology and a removal of the constraints imposed by history. The approach can be summed up as follows: &#x0D; &#x0D; Definition of the theme followed by a broad mapping of its related systems.&#x0D; The creation of a counterfactual timeline based on a different outcome of one or more of the events identified on the real timeline.&#x0D; The design of things along the new timeline: hypothetical products, advertising campaigns, images, texts – evidence of the new value system in action.&#x0D; &#x0D; The most vital use of counterfactuals in design is to allow different voices to emerge that were silenced by the dominant, hegemonic or “standard” narrative(s). As we argue in this essay, illustrated with examples from past and current student projects, alternative histories can open up valuable future paths and create space for rich new imaginaries to flourish.
The Impact of the Window Shopping Learning Model on Learning Outcomes of Junior High School Students

This study aims to analyze the effect of window shopping learning model on the learning outcomes of seventh-grade students in social studies subjects. This research is quasi-experiment research with a randomized pretest-posttest control-group design. Determination of the sample in this study using a simple random sampling technique with the results of the draw obtained class VII B as an experimental class and class VII E as a control class consisting of 30 students each. The results showed that of hypothesis testing which obtained the value of Sig. (2-tailed) &lt;0.05, it is concluded that the window shopping learning model can affect the learning outcomes of junior high school students in Class VII in social studies subjects with the material of the condition of the territory of Indonesia. The results of this study contribute to identifying effective learning approaches for junior high school level, particularly in social studies, and provide valuable guidance for developing better learning strategies in the future.
Designing Learning Monitoring snd Evaluation Management Systems for Lecturer Performance in Informatics Study Program

The main responsibilities of a lecturer is to transform, to develop and to transfer knowledge through teaching and learning process. Assessment by students for their lecturers to provide input for lecturers and study program quality is needed so that the teaching and learning process can be controlled and in accordance with the established quality standards. In carrying out the process of monitoring and evaluating on lecturer performance, the Informatics Study Program, Faculty of Engineering, Universitas Tamansiswa is currently using Google form to distribute questionnaires. This is considered ineffective and produces invalid data. Therefore, the use of technology can be a solution to this problem. The purpose of this research is to design a management information system model for monitoring and evaluating learning that can facilitate the software development stage. The design of this learning monitoring and evaluation processing system uses the Unified Modeling Language (UML) model. While the software development method proposed by the author is Agile Software Development. The result of this research is a design model with UML in the form of use case diagrams, activity diagrams, and class diagrams, where the results of this design model can facilitate the next stage of software development. In addition, PIECES analysis is used to assist in identifying weaknesses in the current system to facilitate the mapping of system requirements. Needs mapping is used to identify the proposed new system, in which this proposed new system has 4 user levels, namely: administrator, GMP (Gugus Mutu Prodi), lecturers and students. Each user has its own authority in the proposed system.
The Society of Method

For a method, a protocol, thought about and done by you, what’s a “you”? What kinds of smaller entities may cooperate to carry out a procedure?
Enhancing Capability of Surveillance actors in using Evidence Informed Decision Making on COVID-19 Response in Nigeria.

The objective of disease surveillance and response is to improve the flow of information to monitor the spread of Infectious diseases, evaluate the effectiveness of control and preventive measures. This study assessed surveillance actors' knowledge and capacity to access and utilize relevant evidence from COVID-19 response data. The study was carried out in Anambra State. We adopted a pre-test and post-test design for the study. The population included all the surveillance actors in Anambra state, and the sample was 42 surveillance officers drawn via purposive sampling. Demographic data and pre-test were administered before the one-day intensive training. After the training, a post-test was administered. Data collected were analyzed using means and standard deviations, and the Chi-square test was used to determine relationships between categorical variables. The study results revealed that there is an increase in the mean of knowledge and capacity amongst the respondents. The findings of this study suggest that ICT competence relevant to data analysis and translating data into Evidence-Informed Decision making (EIDM) can be enhanced through training workshops. This study recommends a conscious effort to institutionalize training, capacity building, and mentoring for knowledge sharing and sustainability of EIDM.&#x0D; Keywords: Surveillance, data, Infectious diseases, Surveillance actors, COVID-19, EIDM, Nigeria
Pedagogical Mechanisms to Activate the Creative Development of Students of Art and Pedagogical Specialties of Higher Education Institutions by Means of the Latest Art

The importance of the topic of the article lies in the fact that today it is necessary to update the methods and techniques of learning in the educational process, the use of innovations in the choice of pedagogical mechanisms to enhance the creative development of students of art and pedagogical specialties of higher education institutions by means of the latest art techniques. The purpose of the article is the need to study and substantiate the importance of studying the essence of the concepts of "artistic techniques" and "newest technologies of students of art and pedagogical specialties" in the system of psychological and pedagogical categories. The article gives a theoretical basis of psychological and pedagogical aspects of creative artistic and graphic activity of students of art and pedagogical specialties of institutions of higher education by means of the latest art techniques; readiness for creative artistic and pictorial activity as professionally important quality of students of art and pedagogical specialties of institutions of higher education; definition of the role of art pedagogy in developing the creative abilities of modern students. The essence of art pedagogy lies in the synthesis of art and pedagogy capable of providing the combination of theory with practice of pedagogical process of art education through the use of art and art-creative activity. The sphere of art pedagogical forms, means and methods should include education of students of art and pedagogical specialties of higher education institutions by means of the latest art techniques.
A Robust Text Dependent Methodology for Automatic Detection of Product Fake Reviews using TF-IDF

A rise in fake product reviews, which companies employ to attract more customers, has been brought on by the growth of social reviews on the internet. As they only concentrate on linguistic characteristics and miss the semantic meaning of reviews, current models for the detection of fake reviews are limited in their ability to distinguish between fake and genuine reviews. To solve this issue, we provide a brand-new ensemble model that integrates transformer architecture with modelling, TF-IDF models, and false review detection. In addition, our method employs suspicion to spot phone reviewer groups. Our results demonstrate that our suggested method beats state-of-the-art baselines in identifying fraudulent reviewer groups after thorough testing on real-world datasets.
An Overlapping Self-Organizing Sharding Scheme Based on DRL for Large-Scale IIoT Blockchain

Sharding is widely regarded as a highly promising solution to address the scalability limitations of blockchain. However, the scalability and throughput improved by using sharding are limited by the verification of cross-shard transactions. To reduce cross-shard transaction and improve the throughput of the blockchain, the existing sharding schemes are based on factors such as the edge-end structure of IIoT for sharding. But these schemes are centralized, leading to the problems of low sharding efficiency, poor scalability and poor security. Moreover, these schemes adopt a non-overlapping sharding architecture, so the verification cost of cross-shard transactions is significantly higher than that of intra-shard transactions. In order to solve the above problems, this paper proposes an overlapping self-organizing sharding scheme (DRL-OSS) for large-scale IIoT blockchain. Based on local blockchain information such as nodes’ information and transaction interaction frequency, DRL-OSS uses DRL to achieve self-organizing sharding with the aim to maximize the throughput and security of blockchain. In addition, based on the threat model, this paper also designs a block complaint scheme to further improve the security of the blockchain, thereby avoiding the reduction in resistance to 1% attack due to the poor anti-predictability of shards and the dilution of computing power. Through experimental verification and analysis, DRL-OSS improves the throughput by 50% when compared to state-of-the-art sharding schemes and has higher system security.
A General-Purpose Protocol for Multi-agent Based Explanations

Building on prior works on explanation negotiation protocols, this paper proposes a general-purpose protocol for multi-agent systems where recommender agents may need to provide explanations for their recommendations. The protocol specifies the roles and responsibilities of the explainee and the explainer agent and the types of information that should be exchanged between them to ensure a clear and effective explanation. However, it does not prescribe any particular sort of recommendation or explanation, hence remaining agnostic w.r.t. such notions. Novelty lays in the extended support for both ordinary and contrastive explanations, as well as for the situation where no explanation is needed as none is requested by the explainee. Accordingly, we formally present and analyse the protocol, motivating its design and discussing its generality. We also discuss the reification of the protocol into a re-usable software library, namely PyXMas, which is meant to support developers willing to build explainable MAS leveraging our protocol. Finally, we discuss how custom notions of recommendation and explanation can be easily plugged into PyXMas.
Deep Reservoir Computing Based on Frequency Multiplexing

Reservoir Computers (RC) are recurrent neural networks where most connections are fixed at random, and only output weights are trained [1]. Exhibiting memory about past inputs, RCs are perfect candidates for tasks involving signal processing, such as distortion-compensation in telecom channels. Due to their low level of complexity, RCs are easy to implement on unconventional computing platforms. A photonic RC can deliver low-cost non-electronic computation, without conversion to the electronic domain, with applications in scenarios like edge-computing [2].
Taming Optical Computing Architectures: From Extreme Learning Machines to Diffractive Neural Networks

Analog processing has recently gained new traction as a result of developments in alternative computing paradigms to the von Neumann one. In particular, concerning optical computing, neuromorphic inspired frameworks strongly simplified the approach to data processing in the optical domain, now opening interesting perspectives for faster and energy-efficient solutions. Yet, while interesting and versatile architectures such as diffractive neural networks [1] and optical extreme learning machines[2]–[4] have been materializing all of this potential, an extensive comparison between distinct architectures is still missing, mostly due to the lack of effective performance metrics and comparable implementations.
Online Image Recognition with Ultrafast Spiking Microlaser Neurons

Photonic artificial neural networks (ANN) offer a great potential for efficient image recognition, thanks to the possibility of integration, low energy dissipation, ultra-fast response times, and availability of a wealth of nonlinear optical responses [1]. We consider an ANN architecture consisting of photonic nodes implemented with semiconductor-based micropillar lasers with integrated saturable absorber which exhibit fundamental properties of biological neurons, such as excitability, refractory periods and temporal summation [2]. These nodes operate six orders of magnitude faster as compared to biological neurons. This unique property makes them particularly well-suited for applications where speed is a crucial requirement.