Reviewerly/exHarmony huggingface dataset:
Vision Controlled Motorised Wheelchair

Abstract: Even in this modern day, it is very difficult for physically challenged people to move from one place to other without others help. To give them an independent feel, a smart eye-controlled system is provided. A novel design of an embedded cardiorespiratory monitoring system for wheelchair users is proposed. This system gets the input from eye. An eye-ball controlled wheelchair is a type of assistive technology designed for individuals with paralysis or limited mobility. The wheelchair is controlled through the movement of the user's eyes, allowing them to navigate the chair without the use of their hands or arms. The system consists of a set of sensors that detect eye movements, a microcontroller that interprets the signals, and a motor controller that translates the signals into movement. The user wears a headset with a camera that tracks the movement of their eyes, which is then relayed to the sensors. The wheelchair can be programmed to respond to different eye movements, such as blinking or sustained gaze in a particular direction. The system is designed to be intuitive and easy to use, with minimal training required. One of the primary benefits of the eye-ball controlled wheelchair is increased independence for individuals with limited mobility. It allows them to move around their environment and interact with others without needing assistance. Additionally, the system is non-invasive and does not require surgery or implants. The movement of the wheel chair will be controlled by these inputs. Depending on this input the wheel chair will move forward, left, right or backward. With the help of this system the user can move independently without others help. It also included with obstacle detection system to ensure the safety for the user. If any obstacle is detected then the indication can be given with the help of LCD.The entire system is composed of a sensor node, and a cloud server. The former is used to obtain continuous vitalsign signals, and the latter processes the sampled signals to estimate the temperature level, implemented in an embedded system to achieve a fully integrated radar system. MATLAB image processing is used to sense the movement of the eye ball’s direction using eye ball sensor (Straight Command, Left/Right Command, Stop Command). The system is cost effective and thus can be used by patients spread over a large economy range
Chat Application with Profanity Check

Abstract: The use of chat applications has increased to a large extent because it provides users with the facility to interact with their family and friends instantly. But these chat applications are being used for carrying out some unethical practices like cyber-bullying, online harassment, etc and there is a need to find a way to curb this issue. This paper aims to give a clear insight into solutions currently being employed or suggested to overcome this problem and to identify the drawbacks associated with these solutions on a large scale. It also proposes a working model for chat apps with profanity detection based on the gaps identified which can detect foul language and thus it can significantly reduce these unethical practices prevalent today in the world of social media.
THE USE OF THE GEOGEBRA SOFTWARE AS A TEACHING SUPPORT FOR TEACHING TILE WORKING

With the growing importance of Digital Information and Communication Technologies in the educational context, the use of technological tools to contextualize mathematical contents and for reflective and meaningful learning becomes essential.In this context, this study investigated the use of GeoGebra software as a didactic support to help teach tiling.The research was carried out with a second-year class of the Technical Administration course at the Federal Institute of Education, Science and Technology of Maranhão -Barra do Corda Campus, during the second half of 2022.Four moments were carried out, one theoretical in the classroom and three practical ones in the computer lab and in the school yard, with construction activities, analysis and understanding of the tiling study using the GeoGebra software.The results showed the students' interest and excitement in the proposed activities, which were able to promote a contextualized and reflective study, associating theoretical and practical teaching.In addition, the use of this technological tool can meet the individual needs of each student, making classes more dynamic and interesting.
Human Action Recognition Using Convolutional Neural Network and Depth Sensor Data

&lt;p&gt;The paper proposes a technique for Human Action Recognition (HAR) that uses a Convolutional Neural Network (CNN). Depth data sequences from the motion sensing devices are converted into images and fed into a CNN rather than using any conventional or statistical method. The initial data was obtained from 10 actions performed by six subjects captured by the Kinect v2 sensor as well as 20 actions performed by 7 subjects from the MSR 3D Action data set. A custom CNN architecture consisting of three convolutional and three max pooling layers followed by a fully connected layer was used. Training, validation, and testing was carried out on a total of 39715 images. An accuracy of 97.23% was achieved on the Kinect data set. On the MSR data set the accuracy was 87.1%.&lt;/p&gt; &lt;p&gt; &lt;/p&gt;
Deterministic Local Interpretable Model-Agnostic Explanations for Stable Explainability

&lt;p&gt;Local Interpretable Model-Agnostic Explanations (LIME) is a popular technique used to increase the interpretability and explainability of black box Machine Learning (ML) algorithms. LIME typically creates an explanation for a single prediction by any ML model by learning a simpler interpretable model (e.g., linear classifier) around the prediction through generating simulated data around the instance by random perturbation, and obtaining feature importance through applying some form of feature selection. While LIME and similar local algorithms have gained popularity due to their simplicity, the random perturbation methods result in shifts in data and instability in the generated explanations, where for the same prediction, different explanations can be generated. These are critical issues that can prevent deployment of LIME in sensitive domains. We propose a deterministic version of LIME. Instead of random perturbation, we utilize Agglomerative Hierarchical Clustering (AHC) to group the training data together and K-Nearest Neighbour (KNN) to select the relevant cluster of the new instance that is being explained. After finding the relevant cluster, a simple model (i.e., linear model or decision tree) is trained over the selected cluster to generate the explanations. Experimental results on six public (three binary and three multi-class) and six synthetic datasets show the superiority for Deterministic Local Interpretable Model-Agnostic Explanations (DLIME), where we quantitatively determine the stability and faithfulness of DLIME compared to LIME.&lt;/p&gt;
Sentiment Analysis of Twitter Cases of Riots at Kanjuruhan Stadium Using the Naive Bayes Method

Sentiment analysis is a process carried out to analyze opinions, sentiments, judgments, and emotions from the riot case at the kanjuruhan stadium. The purpose of this research is to find out public opinion about the tragedy that is currently happening at the Kanjuruhan Stadium. the data was obtained from social media Twitter using the Twitter API, then after that, an analysis was carried out. data from the results of the analysis will be classified using the Naive Bayes method. The classification process is divided into 7 (seven) stages, namely Crawling, Cleansing, pre-processing, labeling, classification, data training, and data testing. In the labeling process, data is classified into 2 (two) classes, namely the positive class and the negative class. The data obtained before the preprocessing process was 1963 tweets, after the preprocessing the data obtained was 1001 tweets. The data will be trained and tested using the naive Bayes classification method. classification results obtained precision values of 82% for negative data and 65% for positive data, recall values obtained 74% for negative data and 75% for positive data, F1-score values obtained 78% for negative data and 70% for positive data, while accuracy value obtained 74%.
Text To Speech with Custom Voice

Abstract: The Text to Speech with Custom Voice system described in this work has vast applicability in numerous industries, including entertainment, education, and accessibility. The proposed text-to-speech (TTS) system is capable of generating speech audio in custom voices, even those not included in the training data. The system comprises a speaker encoder, a synthesizer, and a WaveRNN vocoder. Multiple speakers from a dataset of clean speech without transcripts are used to train the speaker encoder for a speaker verification process. The reference speech of the target speaker is used to create a fixed-dimensional embedding vector. Using the speaker embedding, the synthesizer network based on Tacotron2 creates a mel spectrogram from text, and the WaveRNN vocoder transforms the mel spectrogram into time-domain waveform samples. These waveform samples are converted to audio, which is the output of our work. The adaptable modular design enables external users to quickly integrate the Text to Speech with Custom Voice system into their products. Additionally, users can edit specific modules and pipeline phases in this work without changing the source code. To achieve the best performance, the speaker encoder, synthesizer, and vocoder must be trained on a variety of speaker datasets.
Informal Pedagogical Assessment in Inclusive Secondary Education for a Student with Autism

The paper presents school and instructional integration in secondary education with the methodology of observation for special educational needs [SENs] in autism. The hypothesis focuses on the literature teachers' ability to understand the difficulties faced by a junior high school teenager with autism spectrum disorder (ASD), as presented in the movie Ben X. For this purpose, the pedagogical tool [TISIPfSEN] is used, with a focus on the weekly timetable of lessons. The pedagogical approach is defined as a Targeted, Individually Structured, and Inclusive Intervention Program for Students with Special Educational Needs [SENs]. Based on the results, it seems that literacy teachers can understand the SENs of a student with ASD, such as Ben, through heterobservations with the Informal Pedagogical Assessment [IPA]. Furthermore, the philologist can set priorities for targeted instructional interventions, focusing on the time the student spends "sitting in front of" the computer while also looking forward to collaborating with his classmates.
Vesicular thyroid carcinoma with retropharyngeal node metastasis: case report

Searchable abstracts of presentations at key conferences in endocrinology ISSN 1470-3947 (print) | ISSN 1479-6848 (online)
Live Yoga Pose Classification using Image Processing and Machine Learning

An approach to accurately recognize various Yoga Pose Assessment using deep learning algorithms has been presented in this work. In this system, we propose a Yoga pose assessment method using pose detection to help the self-learning of Yoga. The system first detects a yoga pose using multi parts detection only with PC camera. In this system, we also propose an improved algorithm to calculate scores that can be applied to all poses. Our application is evaluated on different Yoga poses under different scenes, and its robustness is also. A hybrid Machine learning model is proposed using linear Regression for Yoga recognition on real-time videos, where Linear regression is used to extract features from key-points of each frame obtained from Open Pose.
Sistem Informasi E-Voting Berbasis Web Menggunakan Metode RSA dan Base64

The current problem being faced by Gampong Cot Girek Kandang North Aceh Village is that the selection of Keuchiek is still done manually. Manual selection has many obstacles, one of which is being vulnerable to fraud in voting results because the results cannot be displayed in real-time. Based on these problems, this research will propose an online voting system with web-based e-voting. The web-based e-voting system in this study was created using the RSA and Base64 cryptographic methods to secure voting results data. The results of the study show that a web-based e-voting system using RSA and Base64 is very good for use in the election of Keuchiek besides saving costs because it does not require too many officers and can increase public interest in conducting elections.
Detection of Violence Behavior using Deep Learning Technique

Deep learning-based violence detection approaches from video streams are a rapidly expanding subject of study, this is due to the necessity to develop appropriate and automated violence detection techniques based on visual data obtained from security cameras mounted in various locations.In this research, a modified pre-trained deep learning technique named Convolutional Neural Network-Visual Geometry Group16 (CNN-VGG16) are employed to implement a low complex and uncomplicated model for the detection of violence.The transfer learning technique is applied to take advantage of the pre-knowledge VGG16 in detecting shapes and edges.The final layers of the default VGG16 structure are replaced to accommodate the purpose of the research.The efficiency of this approach is evaluated using two datasets (Automatic Violence Detection Dataset (AvdDS) and Surveillance fight dataset (SfDS)).The experimental outcomes prove the efficiency of the proposed model against alternative methods.In experiment accuracy results for Dataset 1 94% and 91% after applying Canny filter, as for dataset 2, the accuracy is 99% and 92% using canny filter.Also In this paper, the effect of applying edges detector on classification accuracy results and processing time for training the model is observed.
ERRORS IN USING AFFIXES OF EXPOSITION TEXT AT ELEVENTH-GRADE STUDENTS OF SMA NEGERI 1 TAPUNG HULU

This paper describes and analyzes the errors in the use of affixes in the exposition text for students in class X of SMA Negeri 1 Tapung Hulu. The research is qualitative research using the descriptive-analytical method, which analyzes and explains the data found in the form of words. Data analysis techniques began with data reduction, presentation, conclusion, and data verification. The data collection technique used was the writing skill test and note-taking techniques. The research data source of the exposition text was written by students. Based on the research results, five types of errors in the use of affixes were found. There were errors in the use of prefixes, ber-, ter-, di-, meN-, ke-, and peN-. There was the misuse of infixes –em- and –el-. There was the misuse of suffixes -an, –i, and –kan. There were errors in the use of confixes pen-an, ber-an, ke-an, and per-an. There was incorrect use of join affixes meN-per-kan, ter-per-, di-kan, di-per-i, meN-kan, ke- to meN-per, and -i.
THE IMPLEMENTATION OF THE NUMBERED-HEAD-TOGETHER METHOD TO IMPROVE ELEMENTARY SCHOOL STUDENTS’ LEARNING PROCESS

This paper discusses the improvement of Class IV students’ learning process at SDN Segeran Kidul Indramayu by applying the Numbered-Head-Together cooperative learning model. The method used is classroom action research (CAR) using Kemmis and Mc. Taggart model for three cycles. The research instruments include student and teacher observation sheets, multiple-choice questions, and documentation. Data analysis includes data collection, data reduction, data presentation, and conclusion. The results of the research imply that there was an improved learning process followed by significant learning outcomes. There was an increased percentage of students’ learning process at 51% in the first cycle. The increased percentage of students’ learning process in the second cycle was 69.38% with a significant percentage of 18.38% from the first cycle. In the third cycle, students fulfilled the learning process indicator of 84.5% with a significant percentage of 15.12% from the second cycle. This significant percentage was reinforced by the pre-test average score of 46.73 smaller than the post-test average score of 62.82 with a completeness percentage of 21.73% in the first cycle. The percentage of students’ learning outcomes in the second cycle was 47.82% with an average value of 72.17. The increased percentage was 26.09% based on the student’s learning outcomes in the first cycle. The percentage of students’ learning outcomes in the third cycle was 82.60% with an average value of 82.39. There was a significant percentage of 34.78% based on the student’s learning outcomes in the second cycle. These results have achieved the school’s minimum criteria of mastery learning indicator (KKM) at 75%. Therefore, the Numbered-Head-Together method is effective and able to increase the elementary school students’ learning process, especially at SDN Segeran Kidul Indramayu.
IMPROVING TEACHERS’ ABILITY IN CLASS MANAGEMENT THROUGH DEMONSTRATION METHODS AT SLB PELITA HATI PEKANBARU

This paper is based on the low teacher's ability to manage classes at SLB Pelita Hati Pekanbaru. It is seen from 1) there are some teachers who cannot manage student seats properly, 2) there are a number of classrooms that do not have study schedules, class plans, and so on, and 3) there are some classes whose atmosphere is less orderly, which can be seen from the classes whose are not orderly and noisy during the learning process. Based on the formulation of the problem, the purpose of the research is, therefore, for knowing teachers’ ability in managing classes and to be improved through the demonstration method at SLB Pelita Hati Pekanbaru. The research uses the School Action Research design of the Kurt Lewin model. The main concept of PTS according to Kurt Lewin consists of four components, planning, action, observation, and reflection. Based on the description of data processing and discussion, it can be concluded that the teacher's ability in class management was obtained in the first cycle at 56% in the good category and in the second cycle it increased to 87% in the good category. It means that the application of the demonstration method for increasing teachers’ ability to manage classes at SLB Pelita Hati Pekanbaru works.
Lecturers’ Perception of the Use of Social Media for English Language Teaching

The purpose of this study was to see how English lecturers’ perceptions of the use of social media for English Language teaching. This study is limited to 4 aspects (Activities, Motivation, Enhancing students’ skills, and effectiveness). This research was conducted at the English Department at a university in Surabaya using social media for teaching English by lecturers. This study using a case study design and semi-structured interview, by organizing, interpreting, and representing the data. A total of 8 lecturers have participated to be interviewed to know about their perception on the use of social media for English Language Teaching. The results showed that the social media most primarily used by the English lecturers are WhatsApp and Email. The result of the interviews showed about the four aspects that had been determined. They are; 1). Activities when using social media in teaching English; discussion, communication, sharing subjects’ materials, collecting an assignment, giving assignments. 2). The use of Social media can increase students and lecturers’ motivation; improving learning motivation, active, creative, increasing self-confidence, and interesting. 3). The use of social media can enhance students’ English skills; enhancing speaking skill, writing skill, pronunciation, vocabulary. 4). The effectiveness of social media use in teaching English; easy to access, easy to understand, easy to use, easy to be practiced.
Motion Vector Extrapolation for Video Object Detection

Despite the continued successes of computationally efficient deep neural network architectures for video object detection, performance continually arrives at the great trilemma of speed versus accuracy versus computational resources (pick two). Current attempts to exploit temporal information in video data to overcome this trilemma are bottlenecked by the state-of-the-art in object detection models. We present, a technique which performs video object detection through the use of off-the-shelf object detectors alongside existing optical flow based motion estimation techniques in parallel. Through a set of experiments on the benchmark MOT20 dataset, we demonstrate that our approach significantly reduces the baseline latency of any given object detector without sacrificing any accuracy. Further latency reduction, up to 25x lower than the original latency, can be achieved with minimal accuracy loss. MOVEX enables low latency video object detection on common CPU based systems, thus allowing for high performance video object detection beyond the domain of GPU computing. The code is available at https://github.com/juliantrue/movex.
The Role of Volition in Graduate Students’ Academic Writing

Due to Covid-19 outbreak, students and teachers experience a rapid shift from conventional to online learning which requires students to be more self-regulated learners. The purpose of this study is to discover how graduate students remain focused and keep devoting effort in academic writing task completion. This research employed a qualitative study involving 13 graduate students of the English Education Master Program of a private university in Indonesia. Data were collected by distributing questionnaire and conducting interview. The data obtained from the questionnaire were analysed using descriptive statistics. Further, open coding techniques were utilized to examine the interview data. There are three major findings drawn in this study, namely, volitional strategies used by students in the academic writing task, persistence amid pandemic situation, and the role of volition in maintaining students’ motivation. The themes describe how students show their determination during the goal-achievement process of academic writing assignments. Students frequently encounter hardships in their learning process which might distance themselves from accomplishing the learning demands. This study shed the light on fruitful merits of volition, particularly in driving students to stay focused despite challenges or distracting situation.
External Factors Affect English Learning in Rural Elementary Schools: A Qualitative Study

The aim of this study was to discover some external factors that influence the difficulties of teaching and learning English in rural schools for young learners. To obtain detailed data or information, data was collected in this study through observation and interviews using a qualitative research method and a type of case study. The research was conducted at an Al Fatch elementary school in the Silo sub-district of Jember Regency, East Java. The findings revealed that several external factors influence the difficulty of teaching and learning English for young students in rural schools, including 1) the school's location is far from urban areas, making it difficult for the community to reach it; 2) inadequate school infrastructure; 3) inadequate school facilities cannot support the continuity of the English teaching and learning process; 4) a lack of learning resources for students and teachers; 5) the language barrier, which is influenced by the community surrounding the school, which speaks the local language more frequently, makes it difficult for students to understand Indonesian as a medium of instruction in the teaching process.