Reviewerly/exHarmony huggingface dataset:
Copyright protection of deep image classification models

With the growing number of tasks solved using deep learning methods, the need for protection against unauthorized distribution of the intellectual property such as pre-trained models of deep neural networks is growing. To date, one of the most common ways to protect copyright in the digital space is through embedding digital watermarks. When solving the problem of watermark embedding, an important criterion is the preservation of the model prediction accuracy after introducing the protective information. In this paper, we propose a method for embedding digital watermarks into image classification models based on adding images obtained by superimposing pseudo-holograms on images of the original dataset to the training set. A pseudo-hologram is an image synthesized on the basis of a given binary sequence by arranging pulses for bit encoding in the spectral region. Results of the experimental study show that the proposed method allows one to maintain the classification quality, while also retaining its performance regardless of the architecture of the protected neural network. The conducted series of attacks on protected models show that attempts of an attacker to completely remove the watermark will almost inevitably lead to a significant loss in the model prediction quality. The results of the experiments also include recommendations on the choice of method parameters, such as the size of the trigger and training sets, as well as the length of sequences encoded by pseudo-holograms.
Penggunaan Software 3Dd Slicer pada Pemodelan dan Visualisasi Volumetrik Meningioma

Meningioma is a tumor that is often found in Indonesia. Treatment for meningomenia itself can be through surgery, radiotherapy, or a combination of both. The decision to carry out radiotherapy itself must go through a planning stage using a treatment planning system (TPS) which requires accurate 3D volumetric imaging. On the other hand, 3D slicer itself is 3D imaging software that is commonly used in the field of radiology. Therefore, this study aims to find out how to use 3D slicer software in modeling and volumetric visualization of meningioma disease. This study uses MRI data from meningioma patients which are processed for volumetric segmentation with a 3D slicer. Based on the results obtained, it can be concluded that the 3D slicer software is effective for modeling and visualizing volumetric brain tumor disease. In this case the visualization &amp; volumetrics look clear and relatively accurate, namely a volume of 16,8402 cm3 with an accuracy of 98.5%.
The Innovation Capacity of the Electronic Traffic Law Enforcement (ETLE) of the Indonesian National Police Viewed by the Observatory of Public Sector Innovation (OPSI) Framework

Electronic Traffic Law Enforcement (ETLE) has been inaugurated and is expected to improve the image of the National Police, minimize extortion practices by officers, and increase driving discipline. Apart from that, ETLE is a National Police program to realize good governance with the values of transparency, accountability and responsiveness. This paper aims to analyze problems in the ETLE program using the Observatory of Public Sector Innovation (OPSI) Innovation Framework prepared by the Organization for Economic Co-operation and Development (OECD). The OPSI Framework consists of innovation objectives, potential, capacity, and impact. The analysis uses the OPSI Innovation Framework to identify problems that occur in innovation to carry out improvements and developments to create sustainable innovation. Based on the results of research using the OPSI framework, ETLE has several problems: requiring a lot of infrastructure with significant resources, an organizational culture that is still silo-like, community disobedience to rules and an organizational culture that is still traditional. The solution to this problem is: First, for limited infrastructure that requires a large budget, apart from collaborating with regional governments, the National Police can also request support from the central government to provide infrastructure for the implementation of ETLE throughout Indonesia because this is a priority program for the National Police; Second, the rules were not followed openly, the police had to carry out intensive information activities about ETLE and issue manual fines to deal with violations on the spot. Third, regarding organizational culture, the Police Chief, as the leader of the National Police, can create an innovative and agile corporate culture and implement collaborative governance with various stakeholders.
PassViz: An Interactive Visualisation System for Analysing Leaked Passwords

Passwords remain the most widely used form of user authentication, despite advancements in other methods. However, their limitations, such as susceptibility to attacks, especially weak passwords defined by human users, are well-documented. The existence of weak human-defined passwords has led to repeated password leaks from websites, many of which are of large scale. While such password leaks are unfortunate security incidents, they provide security researchers and practitioners with good opportunities to learn valuable insights from such leaked passwords, in order to identify ways to improve password policies and other security controls on passwords. Researchers have proposed different data visualisation techniques to help analyse leaked passwords. However, many approaches rely solely on frequency analysis, with limited exploration of distance-based graphs. This paper reports PassViz, a novel method that combines the edit distance with the t-SNE (t-distributed stochastic neighbour embedding) dimensionality reduction algorithm [19] for visualising and analysing leaked passwords in a 2-D space. We implemented PassViz as an easy-to-use command-line tool for visualising large-scale password databases, and also as a graphical user interface (GUI) to support interactive visual analytics of small password databases. Using the “000webhost” leaked database as an example, we show how PassViz can be used to visually analyse different aspects of leaked passwords and to facilitate the discovery of previously unknown password patterns. Overall, our approach empowers researchers and practitioners to gain valuable insights and improve password security through effective data visualisation and analysis.
Probabilistic Device Scheduling for Over-the-Air Federated Learning

Federated learning (FL) is an emerging distributed training scheme where edge devices collaboratively train a model by uploading model updates instead of private data. To address the communication bottleneck, over-the-air (OTA) computation has been introduced to FL, which allows multiple edge devices to upload their gradient updates concurrently for aggregation. However, OTA computation is plagued by the communication error, which is critically affected by the device selection policy and impacts the performance of the output model. In this paper, we propose a probabilistic device selection scheme PO-FL, which effectively enhances the convergence performance of over-the-air FL. Specifically, each device is selected for OTA computation according to the predetermined probability, and its local update is scaled by this probability. By analyzing the convergence of PO-FL, we show that its convergence is determined by the device selection via the communication error and the variance of global update. Then, we propose a device selection algorithm that jointly considers the channel condition and gradient update importance of edge devices to optimize their selection probabilities. The experimental results on the MNIST dataset demonstrate that the proposed algorithm converges faster and learns better models than the baselines.
The Realization of Presuppositions in Harry Potter Philosopher’s Stone

This study aimeld at investigating the realization of presupposition in Harry Potter philosopher’s stone and the implication of presupposition on the teaching of English as a foreign language in Indonesia. Thel design of this study focused on pragmatic analysis, and this study employed a qualitative approach. This relselarch useld script and movie of Harry Potter philosophers stone as thel sourcel of thel data. The researcher used an instrument based on the theory proposed by Yule’s (1996). The categories are existential presupposition, structural presupposition, counter factual presupposition, factive presupposition, non-factive presupposition, and lexical presupposition. The finding of this research shows that five among the six types of presupposition were found in the movie. The whole data of the types of presupposition are 58 data, 19 are Existential Presupposition, 14 are Structural Presupposition, 13 are Factive Presupposition, 11 are Counter Factual Presupposition, 1 is Non-Factive Presupposition, and the last 0 Lexical Presupposition found in Harry Potter philosopher’s stone movie. And all the types of presupposition implied on teaching English as a foreign language through various manners. Presupposition is the important thing, thus the writer suggests the readers of this research, the listeners of a speech, the politician and the next researcher that understanding the presupposition and its types will reduce the misunderstanding in a communication and give more information than just stated.
Generation of Communication Interference Waveforms Based on Variational Autoencoders

The generation of interference waveforms is one of the core technologies in communication countermeasures. Existing communication interference methods usually rely on signal information obtained from communication reconnaissance, but these methods are not ideal when facing unknown target signal characteristics or dynamically changing parameters. Therefore, this paper proposes a communication interference waveform generation method based on Variational Autoencoders (VAE). This method uses VAE to directly extract the latent features of the target signal and generate interference signals with similar characteristics. Through comparative experiments on interference effects, the results show that the interference effect of the interference waveform generated by VAE can approach the optimal interference effect, effectively meeting the requirements of communication interference.
Evaluating The Quality of Teacher’s Talk in English Classroom Interaction at SMPIT Cahaya Bangsa Semarang

Teachers talk play an essential role in classroom interaction, the study evaluated the quality of the teacher’s talk in English language class using Flanders (FIAC) system (1989) in Teacher‟s talk interaction. It aimed to evaluate seven of teacher talk quality in English classroom interaction. The study used a descriptive qualitative research design since involves human behavior in natural setting. The data was collected used audio recording and observed two class meetings at eighth grade of SMPIT Cahaya Bangsa Semarang which took approximately 160 minutes. One of English teacher was the subject and 29 students was the object in this study. The result of the study showed that asked questions was the most frequently shown which is 63 times, with percentage 36,2%. Giving direction was the often shown which is 47 times, with percentage 27,01%. Praises and encourages was the quite often shown which is 29 times, with percentage 16,66%. Lecturing was the quite rare shown which is 14 times, with percentage 8,04%. Accept feeling was the rarely shown which is 8 times, with percentage 4,6%. Criticizing or justifying authority was the rarely shown which is 7 times, with percentage 4,02%. Accepts and uses idea of students was the rarest shown which is 6 times, with percentage 3,44%. The evaluated of teacher‟s talk interaction quality that teacher focus on two interactions are asked questions and giving direction.
The Realization of Affect, Judgement, and Appreciation of Discoursal Attitude in Library Ghost Webtoon

This research is aimed to evaluate and interpret the meaning of feelings into the webtoon makers to readers through a written. This research was qualitative since the findings took the form primarily of words. The source is a Webtoon. The researchers chose a Webtoon because interested in examining Appraisals using Webtoon because it can be media in learning and teaching for educators and will also help them improve their reading skills; the author is curious about the realization of Attitudinal in the Webtoon, especially on Library Ghost Webtoon. The reason for choosing this study is because Attitudes are believed to affect the meaning of language directly. Attitude plays an essential role in the expression of interpersonal meanings of language. The instruments applied were Library Ghost, adapted by Webtoon to assess the attitude system and the appraisal resources checklist to determine the distribution of appraising items of attitude in Webtoon and the relationship of the attitude system on Webtoon. This study proves that a text such as a webtoon, especially Library Ghost, has three items of attitude system in each episode. The author of this webtoon is more dominant in using affect than appreciation and judgment in the webtoon. This study shows that writing in a text can express the emotions or feelings contained in the text. Because Webtoon is a conversation-based online comic. Therefore, affect is more dominant than appreciation and judgment. In the ghost webtoon library, the author expresses more emotions and feelings to the characters.
A Technology-Enhanced Multi-Source Feedback Model for L2 Writing Classes

In second language (L2) writing classes, feedback is not only viewed as assessment of learning, but also increasingly as assessment for learning. The incorporation of teacher feedback, peer feedback, self-feedback and automated feedback into second language writing classes with the aid of appropriate educational technologies can scaffold students’ development of not only their linguistic knowledge and skills but also their transferable skills such as critical thinking, autonomous learning and collaboration. This paper proposes a technology-enhanced multi-source feedback model for L2 writing classes. A learning management system named Mosoteach, a smart teaching tool called Rain Classroom and an automated feedback tool called Uwrite are integrated into this feedback model. This paper also evaluates the implementation of this feedback model in an L2 English writing course for Chinese college students.
A Conceptual Design for a Learning Platform Enhancing Children and Youth’s Soft Skills Education

The significance of soft skills in determining an individual’s future success has been increasingly recognized by educators. Although there have been growing calls to bring soft skills education into the school curriculum, only a few soft skills curricula are found in elementary and secondary mainstream education. To address this gap, this study conceptually designs an online platform - Edu-Shine for children and youth’s soft skills education. Edu-Shine is a high-resolution online platform that offers a unique and engaging learning experience. This study presents the learning platform’s detailed design, including the architecture modules such as the Public Area, Learning Area, Course Creator, and API modules, facilitating more interactive and effective learning experiences between teachers and students. As a result, this research project aims to develop Edu-Shine as a conceptual online platform that promotes soft skills education to cater to children and youth development needs in the 21st century.
Virtual Reality Experiment for 5G Service Convergence Course in Communication Engineering

Virtual Reality (VR) technology is a computer simulation system that allows the creation and experience of virtual worlds. Because of its immersive, interactive, and realistic characteristics, VR is increasingly useful in educational contexts. However, due to the limitation of communication technology, problems such as high latency and vertigo of VR gradually appear in the teaching process, greatly affecting the learning experience of learners. 5G's technical advantages with high speed, low latency, and large capacity can provide the possibility for VR to better serve teaching practice activities. Thus, based on the unique advantages of 5G, this paper describes the virtual reality experiment (VRE) of the 5G service convergence course based on 5G+VR. Combined with our school's training plan for the communication major, this paper proposes the VRE teaching model. According to the results of the learning effect and learning process evaluation, the VRE teaching model can effectively improve students' enthusiasm and initiative in learning, thereby promoting the cultivation of communication professionals.
Analysis of Vocabulary Learning Strategies in Vocabulary Learning Software from the Perspective of Psycholinguistics

The present paper selects four mainstream vocabulary learning software in the market, namely, BaiCiZhan, BuBeiDanCi, Maimemo, and Shanbay Words. Based on the psycholinguistic framework, and adopting the classification of vocabulary learning strategies by O’Malley & Chamot, the current study discusses the learning strategies in vocabulary learning software from three aspects: vocabulary understanding, memorizing, and reviewing. The results show that in terms of the number of strategies achieved, Maimemo uses the most vocabulary learning strategies, so the software can better meet the learning needs of most learners based on different learning strategies. BuBeiDanCi uses the least learning strategies and the learning mode is relatively flexible, which is more suitable for learners who use the fragmented time for vocabulary learning. In terms of the implementation form of the strategy, BaiCiZhan is illustrated with pictures and texts, and BuBeiDanCi has diverse audio, these two are more suitable for interest learning. Maimemo pays more attention to the actual use of vocabulary, so it is more suitable for the learning needs of improving skills. Shanbay Word is mainly based on the memory of English and Chinese definitions of words, which is closer to traditional book learning and more suitable for learners who tend to traditional learning mode. It hopes to help learners better understand the learning strategies in various software and help learners choose more suitable vocabulary learning software, to improve learners’ vocabulary learning efficiency.
VR Serious Game for Learning the Computer Organisation and Architecture Course

Computer Organisation and Architecture is a core subject in Computing Science (CS) in Higher Education. Some topics in this subject are thought to be dry by students through traditional teaching, such as computer functions and interrupts, as students are unable to visualize these multiple-step procedures of how the CPU performs. This research aims to utilize the virtual reality (VR) serious game to help students learn better these topics and absorb abstract concepts or comprehend scenarios that would be difficult in a typical classroom setting. It also enables an engaging and motivating platform, achieving successful learning for CS students. The effectiveness of the designed VR serious game is evaluated with two groups of participants: control group and experiment group. The results reveal that the serious game is able to provide students with positive learning efficiency as well as an engaging and self-motivated experience. The research provides an effective way of teaching and learning modality of the Computer Organisation and Architecture subject for CS students.
Benchmarking and Analysis of Quantum Error Correction Codes

Quantum Computing is a computing framework that takes advantage of unique quantum mechanical properties (such as superposition and entanglement) to perform calculations and implement algorithms that could offer exponential speed-ups over classical computing. However, in physical implementations of such quantum computers, qubits – the fundamental components of these systems – can accumulate errors that must be accounted for. In order to mitigate these errors, various quantum error correction (QEC) codes have been developed, including the repetition code and surface codes. In this experiment I implement and evaluate three types of QEC codes on the Qiskit simulator to compare their efficacy and applicability in correcting for different kinds of errors. I hypothesize that surface codes, with their more effective design and range of correction methods, should perform the best with much lower error thresholds and resultant logical error rates. The results support the hypothesis and suggest that surface codes are a viable method of implementing scalable error correction in quantum computers.
AiShifu: AI Karate Pose Trainer Using Human Pose Estimation

One application of the artificial intelligence (AI) technology is self-guided physical activities where a computing device acts as a trainer. One key challenge for these applications is how to measure the performance of such an AI trainer, especially when the AI trainer is run on a generic PC or a mobile device. In the spirit of the Turing test, an AI trainer should mimic the behavior of a human trainer. A good human trainer generally considers the training history and the level of the trainee when providing feedback, which requires more than body position analysis. In this work, we built a Martial Art trainer application called AIShifu that helps users practice martial art poses using Human Pose Estimation (HPE). We chose an open-source neural network called HRNET trained with MS-COCO dataset as the core of the HPE. The joint coordinates and angles were used to identify the pose being practiced by the trainee, whether the active side is left or right, and how close is the key joint angle to that from a “golden” image. We collected data from both a black belt martial artist and a novice trainee and on three Karate poses. Based on the data, it is clear that the blackbelt performed the poses more consistently. A much larger sample size was required to test how well an AI trainer can discern the difference between trainees with different levels of proficiency. This understanding forms the foundation to customize AI trainer softwares for different users.
Scouting Robot with Search-Space Reducing Hybrid Networks for Unknown Environment Path Planning

Autonomous vehicle navigation is becoming an important problem as fully self-driving cars are becoming a possibility in the next few decades and space exploration is gaining more momentum. One of the most important aspects of autonomous vehicle navigation is a solid path planning algorithm. Most path planning algorithms can be categorized into 2 groups, classical and machine learning algorithms. Classical algorithms can find the shortest path and usually have a 100% accuracy, but it can't function when its environment isn’t 100% mapped out. On the other hand, ML algorithms can operate on partial maps or no maps at all, but they have poor success rate and produce long paths. However, a hybrid approach to a path planning algorithm could eliminate the downside of both categories of algorithms. A robot with a hybrid algorithm could have 100% accuracy while maintaining a near optimum route without a map of the environment. This paper proposes a search space reduction hybrid network (SRHN) path planning algorithm that not only combines the advantages of classical methods and machine learning methods, but also reduces the search space and memory usage. SRHN works by dividing up the distance between a start point and an endpoint with landmarks and paths from its current landmark to the next. While calculating an approximate optimal path, it significantly reduces search space. To test the result of SRHN, experimentation was conducted in the real world. Excellent results have been achieved in the real world 2D tests that were conducted.