Reviewerly/exHarmony huggingface dataset:
Complete, Decomposition-Free Coverage Path Planning

Coverage Path Planning (CPP) requires planning collision-free paths for a robot that observes all reachable points of interest in an environment. Most popular CPP approaches are hierarchical and decomposition-based, involving three steps: (1) decomposing the environment into sub-regions (rectangles or polygons) that simplify the generation of space-filling paths, (2) determining a visitation order over these sub-regions via graph search or a Traveling Salesman Problem (TSP) solver, and (3) generation of space-filling paths in each sub-region. This approach requires significant processing of the environment and the availability of suitable TSP solvers. Furthermore, step (1) can sometimes fail in non-convex environments or lead to "over-decomposition" in cluttered environments. To the best of our knowledge, existing decomposition-free approaches are heuristic or random, and therefore typically inefficient and probabilistically complete. We present a resolution-complete decomposition-free coverage path planner that effectively folds steps (1) and (2) above into a single online search routine, making it significantly easier to integrate into existing robot architectures and applicable to a larger set of environments. Our approach leverages a precomputed library of space-filling coverage patterns and automatically determines where to apply them. We evaluate our approach on a variety of environments to demonstrate its benefits and provide an open-source implementation at https://github.com/ktushar14/cdf_cpp.
LESSON „AN ANSWER TO THE BIG QUESTION: WHAT WILL HAPPEN TO PEOPLE IF GOOD WORDS DISAPPEAR?“

It is a real challenge to study in the future, not in the past trough Big Questions. Big Questions encourage students to suggest theories, to discuss, to work in a team and think critically. They are linked with big ideas, constantly rethinking, suggestions are made, answers are grounded, backed with evidence. They are aimed at deep reflection, meaningful discussion, long study, new understanding, personal experience, previous education as well as use of significant connections. They are often open and complex. They may not receive an answer while working on them. We, the Team for support of personal development in First Primary School „St. Cyril and St. Methodius“ have been faced in front of many unknowns. How to ask big questions? How to set our goals for a project with a big question? How to create a story to engage students? How to plan and organise group work? How to trace the progress? How to plan work with students?The article is based on a lesson in class 5 and it is only a small example of how we use big questions. With it we would like to promote the little-known pedagogical practice giving us another opportunity for innovative education. Our Big Question lesson was dedicated to kind words that we must not let go because they are vital and necessary in our everyday life. The appearance of this article is inspired by the National Kind Words Day held in Bulgaria on 14th April 2022.
Pengembangan Lembar Kerja Siswa Berbasis Teams Games Tournament Pada Materi Keanekaragaman Hayati Di Indonesia Kelas X Sma Negeri 1 Wewewa Selatan

The purpose of this research is to find out the feasibility of student worksheets (lks) based on team games tournament (tgt so that student worksheet products made can be used in the process of teaching and learning in class, in this study using thiagarajan et al' 4-d method (1974) which consists of 4 stages namely define, design, develop, and disseminate conducted in this study is limited to the stage of develop. the subjects of the study are lecturer validators, teacher validators, and test limitations in class x students. the number of students involved in this study as many as 20 people, this research can be obtained data through several validation techniques. The data obtained is the result of various validations then processed / analyzed with a likert scale with a score criteria of 1: not good 2: less good3: good 4: very good. through validation results from material experts get assessments with an average result of 75% with decent categories, media expert validation gets an assessment with an average result of 65.45% with a decent category, validation biology teachers get an assessment with an average result of 70.65% with a decent category and a student readability test student worksheet (lks) 7 question options get an assessment and an average result of 39.5 with a very decent category. it is known that the torunamen team game (tgt) based student worksheet (lks) is worth developing and using.
Common Routines

Now as we come to the end of our book and we reach our learning target, we have the core skills required to write applications in C#. We will now turn our attention to using the skills we have learned and apply them to search and sort routines that developers may commonly use when programming commercial applications. Firstly, we will look at two common search routines, linear search and binary search, and then we will look at two common sorting algorithms, bubble sort and insertion sort.
Dual-Tone Multi-Frequency Assisted Acoustic Side Channel Attack to Retrieve Dialled Call Log

Acoustic side channel attack (SCA) is a type of SCA which exploits the sounds emitted by computers or other devices to retrieve the sensitive information, without requiring the adversary to perform any mathematical cryptanalysis. Recently, acoustic SCA has been exploited by attackers to breach the security of mobile devices. A malicious application installed in the mobile devices can access and take control of system components such as microphone, gyroscope, camera, etc. As users may not be aware of the security guarantee of the malicious applications, they can blindly trust and download such applications in their mobile phones and grant access to unnecessary permission. This security vulnerability can be exploited by an attacker to retrieve user sensitive information and compromise the user privacy. In this paper, a novel Dual-Tone Multi-Frequency (DTMF) assisted acoustic side channel attack is proposed to retrieve dialled call log from mobile devices. In this attack, an adversary can infer the call log or phone numbers dialed by the victims on their devices by gaining access to the in-built microphone. To the best of our knowledge, the proposed acoustic SCA is the first work in the literature that exploits the standards of DTMF to uniquely identify each key/digit dialed on the dialling keypad. In the proposed acoustic SCA methodology, we infer the keys/digits dialed by the victims by first analyzing the recordings of sounds produced from dialed digits and then finding the frequency distribution for each digit using Fast Fourier Transform (FFT). Further, the characteristic frequencies of the keys/digits are matched against the DTMF specifications to uniquely identify them. Further, we have trained the machine learning (ML) models to facilitate the prediction of the call log or the phone numbers dialed by the victim. The proposed attack is device-independent and is capable of predicting the phone numbers dialed in one device while training the ML models on the other. The prediction accuracy of the proposed approach is achieved to be 100% because of exploiting the standards of DTMF which are common for all the communication devices across the globe.
Penerapan Metode SAW dan TOPSIS dalam Sistem Rekomendasi Lowongan Kerja Bali

Job information is important for humans, because almost every human being needs a job. The more unemployed human resources in an area, the higher the demand for job vacancies. Bali is one of the areas that has increased unemployment since the pandemic, Bali has a workforce of 2.6 million who need work. To help Bali job seekers find jobs that match their criteria. In this study, a Bali job vacancy recommendation system was built based on the preferences of respondents residing in Bali. This system will apply the SAW-TOPSIS method in providing recommendations. For the development method, the Waterfall Model will be used. Job vacancies data will be collected on a secondary basis via the internet. The criteria and weighting in the recommendations are based on the results of the respondent's survey. The results of this study note that the application of the SAW-TOPSIS method in the Bali job vacancy recommendation system is in accordance with manual calculations and for direct testing to users using usability testing with 20 respondents the results are 83.39% which shows the system has a very good usability value.
dMITP-Miner: An Efficient Method for Mining Maximal Inter-transaction Patterns

In this paper, we propose an efficient algorithm, namely dMITP-Miner, for mining frequent maximal inter-transaction patterns (FMITPs). The proposed method uses diffset to store the information of patterns for efficiently mining FMITPs. In addition, we also proposed effective pruning strategies to help in reducing the search space to speed up the runtime and to cut down the memory usage. Experiments have been conducted to compare the effectiveness between the dMITP-Miner and the tMITP-Miner method in terms of runtime and memory usage.
Batched Fully Homomorphic Encryption from TFHE

A surge of interest in fully homomorphic encryption (FHE) has produced various FHE constructions in recent years. One of the main goals of these FHE schemes is to improve the efficiency when using the bootstrapping technique. Particularly, TFHE, a fast FHE scheme over the torus, decreases the running time of the bootstrapping significantly. However, it only supports a single-bit bootstrapping, and thus still has high computation cost. In this paper, we propose a batched FHE from TFHE, which can simultaneously bootstrap n torus-based LWE (TLWE) ciphertexts. In more detail, we employ a binary packing tree to pack several TLWE ciphertexts into one TLWE ciphertext, and further optimize the bootstrapping procedure with the homomorphic number theoretic transform (NTT). As a consequence, the amortized computation cost of our batched FHE scheme is reduced to $$O(\log N)$$ from O(N) in the original TFHE scheme, where N is the dimension of the TLWE assumption. Moreover, we provide an implementation of the proposed FHE scheme with specific parameters, so as to demonstrate its practicability.
Motion planning of tbm disc cutter changing robot based on improved RRT-connect algorithm

To solve the problems of narrow working space and complex obstacle environment of disc cutter changing robot in TBM, a motion planning method for TBM disc cutter changing robot based on an improved RRT-connect algorithm was proposed. Firstly, aiming at the shortcomings of the traditional RRT connect algorithm, such as many redundant nodes, unsmooth paths, and large randomness, the probability offset strategy, adaptive dynamic step strategy, path simplification strategy, and path smoothing strategy were proposed. Then the kinematics model of a new 8-joint TBM disc cutter changing robot was analysed, its motion space was determined, and the obstacle envelope model was completed. Finally, to verify the advantages of the proposed algorithm, a simulation comparison was made with the traditional RRT connect algorithm. The results show that the proposed algorithm reduces the running time by 72.0%, and the path length by 41.7%, which significantly increases the speed of motion planning and improves the smoothness of the planned path.
Universal Path Planning Based on Naive Bayes Classifier and Improved A* Algorithm using CNN

As the basis of robot kinematics, path planning occupies an important position in artificial intelligence and other fields. However, not many researches have focus on the importance of generating waypoints in path planning. In order to accurately find the most efficient moving path, we proposes a path planning method based on Naive Bayes Classifier and CNN to improve A* algorithm, which is a search-based algorithm. It first constructs a cost map of the space where the target object is located, and obtains the starting point, ending point with path contour. Next, we obtain the contours of obstacles to calculate the size, use Naive Bayes to realize the mapping, and update the cost map faster instead of the classifers with network structure that need supervised training. After that, we use CNN to find key waypoints, eliminate redundant waypoints and calculate the robot gait. Finally the path planning of the robot is realized. Experiments were carried out in the simulation environment Gazebo and the real space respectively, and the results showed the effectiveness and feasibility of the method.
Impact of Machine Learning in Different Sectors

In today’s technology, human-machine interaction is becoming more common, and robots must be able to comprehend human actions and reactions. Human behavior can be better understood if technology can recognize person’s emotions, resulting in increased work efficiency. Text, audio, linguistic, and facial expressions can all be used to communicate emotions. Facial expressions are important in judging a person’s emotions. In this work, an approach for classifying human moods using face pictures is presented using deep learning technique. The suggested approach uses Haar-cascade face recognition, Active shape Model (ASM) data retrieval (26 face points collected), and Ada-boost algorithm to categorize five emotional responses: rage, hate, pleased, neutrality, and amazement. The proposed approach is unique in that it does the emotional expression in actual environments on the Raspberry Pi, with a real-time average accuracy of 94%. In social surroundings where sentiment identification is vital, the Raspberry Pi can recognize sentiments flexibly in live time when it has been joined to a robotic system
Working with Text

Real-world applications work with a lot of textual data. Unlike languages like C++ and Java, in Go, strings behave as read-only slices of bytes. Furthermore, Unicode text using UTF-8 encoding is used to represent bytes of strings. Several Go libraries are available for the purpose of string manipulation, for example, packages like strings, unicode, and regexp. Note that, in Go, strings are immutable or read-only, meaning that their value cannot be changed after their creation. Trying to make changes to them will raise errors. This chapter discusses how to work with text in the Go language. Specifically, it covers string formatting, Unicode data handling, and using regular expressions in the Go language.
Kontribusi Motivasi Belajar terhadap Kemampuan Menulis Teks Ekposisi

Based on the background of the problem, the purpose of this study is to the contribution of learning motivation on the ability to write text exposition class X SMA N 2 Padang. Quantitative research by using descriptive and correlation design. The study population was all students of class X are divided into nine classes with the number of students 274 people. The sampling technique is done by random sampling that is taking members of the sample population randomized. The total sample is 74 people. The research instrument was a questionnaire and test performance. Techniques to analyze research data using Pearson Product Moment Correlation test (PPM), correlation test, t test, F test, and determinant coefficient formula. Results of this motivation to learn to contribute to the ability to write text exposition of 25.79%. The conclusions of this motivation to learn to contribute and positive relationship significantly the ability to write text exposition.
Breves considerações sobre os nomes coletivos em Português Europeu

In this article we will address the issue of collective nouns in European Portuguese, focusing our attention on collective nouns that denote organized groups of humans. We will begin by questioning the definition of collective nouns, introducing, for this purpose, a distinction between collective reference and a general sense of group. Then we will explore the variability that characterizes collective nouns through the application of some grammaticality tests. Further on, we will argue that a collective noun can be interpreted not only as a single collective entity, as proposed by Raposo (2013), but also as a plural entity (Ritchie 2018), which grant access to the atoms that constitute it. Finally, we will present two semantic problems involving collective nouns. First, we will discuss the relationship that can be established between collective nouns and certain proper nouns. Second, a comparison between collective nouns and some other plural expressions will be explored. In short, we will defend collective nouns as entities that, in a unique way in relation to other nouns and nominal expressions, introduce a collective reference in discourse.
Software module for setting up system for 3D geometry measurements in aerodynamic stand using phase triangulation methods

The paper presents a software module for flexible configuration of a measuring system implements phase triangulation methods to measure three-dimensional profile of objects in aerodynamic experimental stands. To adjust and optimize a wide range of parameters of the measuring system, a universal solution has been implemented, that aimed to control of the operation of phase triangulation algorithms and binary Gray codes. To estimate the measurement error, an automated algorithm is implemented based on a statistical analysis of the distribution of the coordinates of the points of the measured surface.
Development and usage experience of a lendable educational tool for mechatronics in on-line lectures

The pandemic of the COVID-19 has had a major impact on the field of engineering education. Many lectures became online and ensuring the quality of the lectures became a major issue. To improve this situation, we developed a lendable educational tool for mechatronics in on-line lectures. In this paper, its development process, contents and usage experience are reported.
Efficient Learning Assistance Strategies to Improve Learning Efficiency when Online Learning Video Quality Degradation Occurs

Online learning is gradually becoming a mainstream education method, and instructional video plays an indispensable tool for online learning. In order to improve learning efficiency, more and more studies focus on the design of instructional video content. However, online learning requires video transmission over the network, and instructional videos may become blurred due to bandwidth limitation. In this case, the instructional video content designed to improve learning efficiency will lose its usefulness, and alternative instructional strategies need to be provided to improve learning efficiency when online learning video quality degradation occurs. The experimental results have shown that paper assistant learning materials and audio assistant learning materials with voice cues can solve the impact of video quality degradation and improve learning efficiency.
Presenting START, GOAL, Digital Sarthak, SkillBot and Maker’s Space: Inspiring Innovations for an Empowering, Democratic and Inclusive Technological Society

Digital Empowerment Foundation (DEF) has been making use of many innovative methods and technologies to democratize innovation, upskill, build resilience and foster lifelong learning in rural India with a special focus on marginalized communities. We would like to showcase some of our innovations here. // START: A digital learning and Media &amp; Information Literacy (MIL) toolkit, designed exclusively for first-generation technology users to promote digital inclusion and fight information poverty. It is a 45-hour digital learning curriculum that covers 30 topics ranging from basics of computers, use of applications, MIL and online security and safety, among others. The pedagogy for START focuses on hands-on training and workshops in rural and tribal communities through activities and gamification of topics. // GOAL (Going Online as Leaders): A program to connect urban volunteers with rural women online to provide them guidance and support in digital skills to bridge the information gap. This technology-enabled mentorship program was adopted by the Ministry of Tribal Affairs, Government of India and is now being replicated in several states. The data comparing baseline and endline show that beneficiaries of GOAL show higher interest in pursuing higher education, greater self-confidence, improved communication skills and aspiration to become changemakers. // Digital Sarthak: This program demonstrates how digital literacy through the community network model can be an important strategy to achieve a replicable model of local economic development. 100 rural women were trained to further train 500 women-led Community Development Organizations (CDOs) and 10000 rural women entrepreneurs in the first stage. The program placed women in active roles in the information eco-system that further improved their confidence and capacity. // SkillBot: A self-learning chatbot built on the free and open-source Telegram platform. Telegram provides free backend technical support and chatbot feature. SkillBot was developed by DEF and Commonwealth of Learning to teach digital literacy, financial literacy, citizen services and data management to rural youth and artisans. SkillBot is multilingual and employs tutorial lessons, audio graphics, infographics, flashcards, interactive quizzes and activities for teaching. Skil Bot thus provides an accessible, easy to understand platform for skilling. // Maker's Space is an initiative where physical centres equipped with STEM learning and digital skilling tools are created in DEF’s community information centres at the remotest locations. Maker's Space facilitates an unstructured learning space supported by digital/STEM tools that allow children and youth, especially persons with disabilities, to take ownership of their learning and create innovative solutions for their communities.
Some errors are more harmful than others: the role of type and frequency of orthographic errors in word processing

In the modern world of social media, we constantly read texts that were not subject to professional proof-reading and editing. As a result, we see misspelled words more often than the previous generations. The effects are interesting for several scientific disciplines, including psycholinguistics. Several experiments on different languages have recently demonstrated that the incidence of orthographic errors for a particular word reduces the quality of its lexical representation in the mental lexicon. As a result, it is more difficult to judge whether the word is spelled correctly, and — more surprisingly — it takes more time to read the word even when there are no errors. In the present study, our goal was to find out whether the type of orthographic errors (the orthogram) plays a role in addition to their incidence. We selected six orthograms forming two groups: more and less difficult ones. Two experiments were conducted. In Experiment 1, participants were asked to judge whether stimulus words are spelled correctly. In Experiment 2, all stimulus words were presented in the correct spelling in a lexical decision task, i.e. we measured how fast they are processed. In Experiment 1, the type of the orthogram played a significant role, being more important than any other factor. In Experiment 2, the influence of this factor could be reduced to the incidence of incorrect spellings. In other words, when we consciously decide how to spell, the type of orthogram plays a crucial role. As a result, some errors are more frequent than others (although it is obvious that the incidence of errors can be only partially predicted by the type of orthogram). However, when we simply read words, only the incidence of errors matters, i.e. the type of orthogram affects the reading speed only indirectly.