Reviewerly/exHarmony huggingface dataset:
Research on Distributed Multisensor Spectrum Semantic Sensing and Recognition in Internet of Things Environment

The development of 5G technology has brought about a new era of Internet of Thing (IoT), and at the same time, electromagnetic spectrum monitoring and sensing have also ushered in huge challenges. Digital modulation recognition technology is an important content of electromagnetic spectrum sensing. In the increasingly complex wireless communication transmission environment, especially in noncooperative communication, it becomes more and more difficult to receive target signals and accurately extract effective semantic information from diverse modulation signals of the electromagnetic spectrum. At this stage, with the rapid development of network information and wireless communication technology, within a prescribed distance, the IoT built by many sensors has attracted wide attention from people in related fields. This paper proposes a distributed collaborative sensing spectrum semantic recognition architecture for communication signals based on feature fusion. Perform wireless communication and transmission between multiple sensors to form a self-organizing network to cooperatively sense signal semantic information, and extract the signal features of each sensor in the distributed network structure. Finally, the extracted sensor features are semantically analyzed and modeled, and the effective features are fused to complete the entire perception and recognition process. Even if the channel environment of a small number of receiving nodes deteriorates in a complex transmission environment, the signal quality features can still be accurately extracted, the classification and recognition effect like or higher than the best channel state performance can be achieved, and the fault tolerance of the system can be effectively improved. It can also enhance the performance of spectral semantic information sensing and recognition in the IoT environment.
Using Capsule Networks to Classify Digitally Modulated Signals with Raw I/Q Data

Machine learning has become a powerful tool for solving problems in various engineering and science areas, including the area of communication systems. This paper presents the use of capsule networks for classification of digitally modulated signals using the I/Q signal components. The generalization ability of a trained capsule network to correctly classify the classes of digitally modulated signals that it has been trained to recognize is also studied by using two different datasets that contain similar classes of digitally modulated signals but that have been generated independently. Results indicate that the capsule networks are able to achieve high classification accuracy. However, these networks are susceptible to the datashift problem which will be discussed in this paper.
TELAAH PEMBELAJARAN MAHASISWA TERHADAP PERAN BAHASA INDONESIA DI PERGURUAN TINGGI

The Indonesian language course is one of the general subjects that must be taught at the tertiary level, either at the Diploma or Bachelor level. This rule of course has been stated in Article 35 paragraph 3 of Law number 12 of 2002 which is related to learning in higher education. Based on the article, the Indonesian language courses at the university level have changed their names, namely to become general compulsory subjects (MKWU) which were originally called the General Basic Courses (MKDU). It can be said that a substance in the study of Indonesian general courses will always focus on an emphasis on skills in the use of Indonesian as a language known as the national language. However, in accordance with the existing truth, in doing academic writing which is an effort that can be made in obtaining a national literacy program as has happened at this time which is really not in accordance with the intended expectations. Of course, in reality this will have an impact on students at the high school level who will enter the university level who will of course study Indonesian language courses. Seeing in the problems that will arise in the learning process, of course, it is very necessary, namely learning model that will begin to lead to how the ability of the student in carrying out recovery from an event that is in learning. Of course, the learning model as proposed is a guide from various sources by referring to the main points of a problem that will be faced, of course, by lecturers of the Indonesian General Course.
THE SPOC+ PLATFORM: EVALUATION AND PERSPECTIVES

Mobile artifacts are the objects that increasingly surround us in life.They provide us with the opportunity to engage in activities outside the traditional context and at our own pace.In this article, we present the results of the tests of our mobile application intended for the learning of the French language with the concept of SPOC with a methodology of teaching pedagogy by project founded based on MIRTO by using the NLP tools.
Automated Smart Attendance System Using Face Recognition

In the human body, the face contains many important details, so the face is the most significant factor in identifying a person.There are several main ways to detect the presence of a person.Biometrics for capturing attendance.This is a time consuming process. In this paper, we will use a collection of rules to develop a model that classifies each character's face from the captured images. The HOG algorithm for recording student attendance. HOG (Histogram of Oriented Gradients) is one of the methods used to represent and classify images, is a common and effective method, and was chosen for its robustness against changes in pose and lighting. .. The proposed ASAS (Automated Smart Attendance System) captures images and compares themto the images stored in the databases.The database is updated during student enrollment using an automated process that also includes names and role numbers.
Multi-Level-Model of Dyslexia for the Explanation of Reasons and Intervention Methods

If you want to discriminate reasons and symptoms, and in addition the chronological times than you can use this multi-level-model for the describing of the complex phenomena “Dyslexia”. This model allows the order of assessment and intervention methods.
Performance Evaluation of Naive Bayes Algorithm for Classification of Fertilizer Types

Determining the right fertilizer is very important to get optimal plant growth results. Each plant requires different nutrient requirements. Different soil types cause the soil's nutrient content and PH value to differ from one type to another. Regional conditions in a place will also cause the need for plant absorption of nutrient content to be more varied. By using the classification of the problems that have been mentioned, it can be solved by studying patterns from existing fertilizer use data into knowledge that can be used to determine decisions. In this study, modeling with the Naïve Bayes algorithm has been applied to the existing fertilizer use data where the probability value of each class has been calculated to get the highest probability value of a class. The measurement of the accuracy value of the modeling used is measured using the Split Validation method, where the training data will be divided into training data and testing data so that the accuracy value of the model is obtained. From the applied modeling, an accuracy value of 60% is obtained, which shows the level of accuracy of the model obtained from the classification results in the form of the name of the fertilizer, which is expected to help in determining the name of the fertilizer that needs to be used.
Penerapan Model Pembelajaran Preview, Question, Read, Reflect, Recite And Review (PQ4R) Terhadap Keterampilan Membaca Pemahaman Siswa Kelas IV

The problem in this research is the low learning outcomes of fourth grade students. The problem in this study is how the Preview, Question, Read, Reflect, Recite And Review (PQ4R) learning model improves the learning process for reading comprehension skills in fourth grade students of UPT SD Negeri 22 Pinrang and whether the application of the Preview, Question, Read, Reflect, Recite And Review (PQ4R) can improve the learning outcomes of fourth grade students of UPT SD Negeri 22 Pinrang. This study aims to examine the process and learning outcomes using the Preview, Question, Read, Reflect, Recite And Review (PQ4R) learning model. The approach used is an approach approach and the type of research is Classroom Action Research (CAR). The implementation of this research action was carried out in 2 cycles, starting with pre-action activities then in each cycle consisting of 4 stages which included planning, implementation, observation, and reflection. This research instrument uses observation sheets and final evaluation tests in each cycle. The subjects in this study were teachers and fourth grade students of UPT SD Negeri 22 Pinrang in the 2021/2022 academic year which collected 15 students consisting of 9 boys and 6 students. woman. Data analysis techniques are data condensation, data presentation, and conclusion drawing. In the first cycle the research results on the learning process were in sufficient qualification (C) and the learning test results in sufficient qualification (C) while in the second cycle the research results on the learning process were in good qualification (B) and the test learning results were in good qualification (B). The conclusion of this study is that the application of the Preview, Question, Read, Reflect, Recite And Review (PQ4R) learning model can improve the process and student learning outcomes in reading comprehension skills in grade IV UPT SD Negeri 22 Pinrang.
SpeakLiz by Talov: Toward a Sign Language Recognition mobile application – Supported by Mada Innovation Program

The present article discussion on the Sign language recognition which is part of one of the most challenging tasks for Artificial Intelligence (AI) algorithms: camera-based gesture recognition. Probably, hence its relatively novel practical applications despite its old presence in the general AI field due to the required computing power for a device to be able to track complex gestures (like sign languages) just with a camera along with not-ideal light, focus, and stability conditions or even many of them combined. But, reaching acceptable results on mobile devices with this recognition task is even more elusive than doing it on computers (actually, PC-oriented projects are most of the research out there).
Understanding the challenges in creating Motion capture Sign Language Dataset: A Technical Perspective – Supported by Mada Innovation Program

Sign language (SL) is a visual language with a syntactic system different from spoken language and is used by deaf and hearing-impaired individuals as primary mean of communication. The lack of translated information to sign language, especially in written form, represents a barrier and creates a gap between the deaf and hearing communities, this gap is even wider within deaf community with low literacy skills. To fill this gap, in 2021, as part of Jumla Sign language project Mada Center developed and launched “Bu Hamad”, the first virtual and digital character (Avatar) using the Qatari sign language to serve this community and help translate Arabic texts into sign language.
Sign Language Recognition System

Abstract: A large number of deaf and mute people are present around the world and communicating with them is a bit difficult at times; because not everyone can understand Sign language(a system of communication using visual gestures and signs). In addition, there is a lack of official sign language interpreters. In India, the official number of approved sign language interpreters is only 250[1] . This makes communication with deaf and mute people very difficult. The majority of deaf and dumb teaching methods involve accommodating them to people who do not have disabilities - while discouraging the use of sign language. There is a need to encourage the use of sign language. People communicate with each other in sign language by using hand and finger gestures. The language serves its purpose by bridging the gap between the deaf-mute and speaking communities. With recent technological developments, sign language identification is a hard subject in the field of computer vision that has room for further progress. In this project, we propose an optimal recognition engine whose main objective is to translate static American Sign Language alphabets, numbers, and words into human and machine understandable English script and the other way around. Using Neural Networks, we offer a machine learning-based technique for identifying American Sign Language. Keywords: deep learning; convolutional neural network; recognition; comparison; sign language;
Analysis of sentence structure differences in English Chinese Translation

To learn English Chinese translation well, we must understand the characteristics of English and Chinese. Because English and Chinese belong to different language families, the most effective way to understand their characteristics is to compare the syntactic structures of the two languages. The main differences between the two are that English is a morphological language, the connections within sentences or between sentences adopt syntactic or lexical means, the syntactic structure is rigorous, and the form expresses meaning. While Chinese is a semantic language, it is mostly parataxis, with loose syntactic structure and lexical meaning. English Hypotaxis is mainly used in sentences, parataxis is used in texts, while Chinese parataxis is mainly used in sentences, and hypotaxis appears in texts. Only by understanding and mastering these differences, it can help to avoid the problems that may be encountered in English-Chinese sentence translation, and of course, it can also improve the accuracy of sentence translation between English and Chinese
Jumla Sign Language Annotation Tool: an overview

This paper describes an ongoing project on developing a new web-based tool for annotating Sign languages. This tool is used to annotate the First Qatari Sign Language dataset called Jumla Dataset: The Jumla Qatari Sign Language Corpus” with written Arabic text. The annotation of videos in Qatari Sign Language (QSL) takes input from signers to identify the Arabic glosses components toward representing the QSL in a written way with high accuracy, furthermore to the use of the annotation output in the development of computational Sign Language tools. The QSL annotation is based on an input of 4 videos recorded by deaf persons or Sign Language interpreters from different angles (front, left side, right side, and facial view). The output is a JSON file containing all the interpreted sentences given as an entry record. The glosses are annotated for each period and aligned with the Arabic content. Moreover, the presented tool, available as an open source, provides a management system to classify all records from cameras, motion capture systems, and edited files in addition to the possibility to create components for each gloss annotation terminology depending on the target Sign Language.
A Survival Horror Game RIDE OUT

Abstract: In the Field of Software Engineering, Gaming is the fastest growing field and even more rapidly growing sector of game development the coming years are difficult to predict. Survival horror video games (SHVGs) are among the fastest-growing genres for independent video game developers. With horrific cinematic elements and fear-inducing characteristics, survival horror video games create a terrifying experience for users within a virtual environment. There are various game engines where we are able to create such amazing games such as in Unity3d, Unreal Engine, Game Maker, Godot, and more provide access to the identical technologies and tools available to large game developers. Unity3D Game Engine is an integrated development tool which is used to create interactive contents like video games, architectural visualization and real-time 3D animations. This paper studies about the Horror Survival game ‘RIDE OUT’ which we attempt to build for people to experience the horror and thrill within the virtual environment and hence the way it’s designed with horrific cinematic elements and fear-inducing characteristics. For the survival horror game, the plan goes: everything from building a scene and lighting, ending with battle mechanics and the design of game menus, create graphical effects, control the physical behavior of objects or even implement a custom AI system for characters in the game and much more. Keywords: survival horror video game, game development, AI, fear, game design, gameplay.
Research on the Improvement of Teachers’ Practical Teaching Ability in Local Newly-built Universities

Under the background of the local newly-built universities transforming into application-oriented universities, teachers' practical teaching ability decides the quality of applied innovative talents cultivation, affects the school serving local economic and social development level, and thus improving college teachers' practical teaching ability is the key to the successful transformation and high quality development for the newly-built universities. This paper deeply analyzes the problems existing in the improvement of teachers' practical teaching ability and puts forward corresponding solutions.
Pengaruh Metode Sas (Struktural Analitik Sintetik) Dalam Peningkatan Kemampuan Membaca Permulaan Siswa Kelas II Sekolah Dasar

This study aims to find out the effect of the SAS Method on the ability to read Beginning of second grade students of SD Negeri 221 Pattiro Bajo, Sibulue District, Bone Regency. This type of research is an experimental one group pre-test-posttest design. Of the 19 populations taken as a whole as a sample. Data collection techniques used are tests, journals and observations. The data analysis technique used parametric tests which included descriptive statistical analysis, inferential. The early reading ability of second grade students at SD Negeri 221 Pattiro Bajo, Sibulue District, Bone Regency was still dominantly low (not fluent). This is evidenced by the results of the initial reading ability test before the experiment where only 6 out of 19 students 32 percent of students were declared quite fluent and complete with a score of 75. There was an increase in the initial reading ability of second grade students at SD Negeri 221 Pattiro Bajo, Bone Regency after the application of the SAS method in learning. This is evidenced by the results of the students' initial reading ability test after the treatment where the level of completeness increased to 89 percent from the previous only 32 percent. The SAS (Structural Analysis Synthetic) method has a significant effect on the early reading ability of second grade students at SD Negeri 221 Pattiro Bajo, Sibulue District, Bone Regency.
Early prediction and analysis of mammary glands cancer through deep learning approaches

Cancer is the foremost cause behind the most death pace of people around the world. Cancer of breast is the primary reason for mortality among females. There have been various investigation or experimentation aimed at the discovery and interpretation of facts has been done on early expectation and discovery of breast cancer disease to begin treatment and increment the opportunity of endurance. Utmost research targets x-ray pictures of the breasts. Although, photographs of the breasts made by X-rays occasionally produces a threat of fake recognition which can compromise the medical status of infectious person. It’s crucial and import to locate opportunity techniques that might be simpler to put into effect and work with extraordinary records sets, inexpensive and safer, which could produce an extra dependable prognosis. This research journal recommends an associated prototype of numerous DLA (Deep Learning Algorithms) including ANN (Artificial Neural Network) and CNN (Convolutional Neural Networks) for efficient breast cancer detection and prediction. The research exploration utilizes the x-rays image database (as base research datasets) for prediction, detection, and diagnosis of breast cancer. This anticipated research prototype may be associated with several clinical examination data i.e. text, audio, image, video, blood, urine and many more.
Descriptive Analysis of Passive Voice Sentence Through Levels Of Semantic Analysis in the Story of A Study In Scarlet By Sir Arthur Conan Doyle

Learning English as Foreign Language is not that easy in Indonesia. Mostly learners will face some difficulties in learning it as people speak English as foreign language, and the opportunity to interact with English native speakers is very little. The function of English native teachers is to teach English naturally. Therefore, in this research, the researcher offers one of English grammar features to guide the EFL leaners understand English naturally. In this study, the researcher focusses on the level of semantic analysis which is actually a very basic lesson to learn English. The research methodology used is descriptive qualitative research. The data are passive voice constructions consisting of 42 passive voice sentences from a novel of Sherlock Holmes by the title “A Study in Scarlet”. The data are examined by the researcher herself through a software feature on online application. Afterward, the data are analyzed though levels of semantic analysis. There are three key themes which are analyzed: reference, sense relation and thematic role. In summary, the levels of semantic analysis is successful in analyzing the reference which naturally helps the learners memorize many new words also successful in both knowing the sense relation and thematic role which guide the learners think English word just like first language or second language learners.
Intelligent Teaching of Tennis Based on Human Skeleton Node Model

In order to improve the effect of tennis intelligent teaching, this paper combines the human skeleton node model to construct a tennis intelligent teaching model. Aiming at the fact that there are errors in model identification and positional disturbances such as friction which cannot be avoided in actual tennis teaching, an effective sliding mode control strategy based on disturbance observer is presented. Moreover, this paper builds a simulation model through MATLAB/Simulink to verify the influence of the three parameters of inertia, damping, and stiffness in the admittance model on the control performance. Then, this paper combines the admittance control theory to analyze the difference between the active mode and the passive mode and the main functions of the two control modes and constructs an intelligent simulation system. The experimental study shows that the tennis intelligent teaching model based on the human skeleton node model has good effects in tennis action correction and tennis-teaching effect improvement.