Reviewerly/exHarmony huggingface dataset:
Physical Layer Security Using Scrambled BCH with Adaptive Granular HARQ

A dramatic increase in the number of devices that are connected to the wireless networks has seen many challenging issues.One of them is the security problem.Enhancement in physical layer security has shown promising results to improve these security issues in the existing wireless networks.This paper proposes a transmission technique based on scrambled Bose Chaudhuri Hocquenghem code with feedback to improve the physical layer security in wireless communication system.The security of the transmission system over a wiretap channel is investigated.Scrambling matrix is applied to the code word and a hybrid automatic repeat request (HARQ) protocol is used.In this paper, the security gap is used as a performance metric to measure the difference between the authorized and unauthorized channel.We find that the proposed technique results in smaller security gap compared to the conventional techniques.
Considerations on Digital Teaching in Computer Science Courses in Universities in the Post-pandemic Era - Taking Computer Operating Systems as an Example

As the domestic epidemic in China is gradually and effectively controlled, slowly stepping into the post-pandemic era, this study aims to explore and consider the current performance of the combined online and offline teaching model being experienced for the digital teaching of computer courses Chinese university education in response to the sudden and spot new crown epidemic.The current state of teaching and learning of the course Computer Operating Systems is presented as an example of the practice in the semester teaching in response to the sudden epidemic in Taigu District, Jinzhong City, Shanxi Province, where Jinzhong College of Information Technology is located, during the sudden epidemic on February 20, 2022.Through qualitative analysis of the digital practices in emergency online teaching methods and in-depth reflection and analysis of the feedback from the teaching activities, a glimpse is taken to reflect on the digital teaching experiences of computer courses in the post-epidemic era, providing lessons for future teaching activities.
QR Steganography for Information Hiding of Patient Record

In recent research studies, biosignals are used to study the behaviour of a human body function which are useful for medical diagnosis.Biosignals such as electrocardiogram (ECG) signals are used to determine the irregularities in heartbeat meanwhile electroencephalogram (EEG) signal is used to record the brain activity of a patient.This paper aims to put together a mechanism to hide patient details with image of patient medical biosignals using steganography.Patient details are stored in the QR Code meanwhile biosignals that are in 1 dimensional are converted into two-dimensional image.In this process of hiding the patient details and its biosignal, fine details may be lost.Thus, image enhancement process is needed.In this paper, methods such as Local Laplacian filter, Successive Mean Quantization Transform (SMQT) algorithm, Non-Local Means filtering, Bilateral filtering with Gaussian Kernel and Anisotropic Diffusion are used to evaluate the medical image quality of the biosignal.Quantitative metrics are used to evaluate the quality of implementation.The proposed method has given out results of Peak Signal-to-Noise Ratio (PSNR), Mean-Squared Error (MSE), Normalized Cross-Correlation (NCC) that are comparatively well with other established methods.Findings from this paper indicates improvement in the overall image quality of biosignals after extraction from its cover image using the proposed methods.
Comparison of Support Vector Machine and Random Forest Algorithms in Sentiment Analysis on Covid-19 Vaccination on Twitter Using Vader and Textblob Labelling

Corona Virus Disease 2019 is a world outbreak that was first reported in Wuhan in December 2019.The first case of Covid-19 in Indonesia was confirmed on March 2, 2020.Covid-19 is caused by infection with virus named SARS-Cov-2.Currently, social media is widely used to find out public opinion.Generally, on Twitter social media, issues that are currently hot and much discussed by the public will become Trending Conversations.To find out and filter the opinions on social media, whether they include positive or negative opinions, you can use Sentiment Analysis.In this study, the sentiment analysis about covid-19 vaccination will use the Support Vector Machine (SVM) and Random Forest algorithms.The dataset will be labeled using the VaderSentiment and Textblob libraries found in Python.This comparison results that the SVM algorithm with textblob labeling produces an accuracy of 0.8940.Meanwhile, the sentiment results show that people tend to have negative opinions.Therefore, the best modeling for sentiment analysis is to use the Support Vector Machine with Textblob labeling.
A Lossless Compression Algorithm for Astronomical Sequential Images Based on Hybrid Coder

提出了一种将时间和空间双维度预测与混合熵编码结合的图像无损压缩算法，应用于星体定点成像的天文序列图像.时间与空间双维度预测可以消除天文序列图像的时间相关性和空间相关性.混合熵编码融合了高熵编码与低熵编码算法，充分利用预测误差分布的稀疏性，进一步提升压缩效率.针对星体的天文序列图像，该算法首先在时间维度上进行帧间预测，去除时间相关性，再对帧间预测后的图像在空间维度上进行直方图滤波和上下文预测，去除空间相关性，最后将预测误差送入熵编码器进行编码.实验结果表明，本文所提出算法的压缩效果优于JPEG-LS，平均压缩比提升约15%.该算法结构简单，计算复杂度较低，易于硬件实现，适合星载天文图像的无损压缩.
Progress of the Quantum Experiment Science Satellite (QUESS) Micius Project

The Micius satellite was successfully launched on 16 August 2016, from Jiuquan, China, orbiting at an altitude of about 500 km. The main scientific goals, including satellite-to-ground quantum key distribution, satellite-based quantum entanglement distribution, ground-to-satellite quantum teleportation, and satellite relayed intercontinental quantum network, were achieved in 2017. As a starting point, the Micius satellite has become a platform for quantum science experiments at the space scale. Here, we introduce the latest experimental achievements (in 2018-2020) based on the Micius satellite.
Acrosuit: Promoting Improvisation in Acroyogis With Tactile and Visual Cues

Acroyoga practitioners either follow predefined choreographies or play freely to create compositions of two bodies’ poses and transitions. To support their free play, we created the training technology probe Acrosuit. The Acrosuit gives visual or vibrotactile cues to propose a novel point of contact without instructions how to get there. We invited acroyogis to exploratively play with the suit and gained qualitative insights on whether and how they used the cues. The suit influenced their practice and in some cases also the way of communication between the partners. Experiencing the shifts in communication caused by the Acrosuit made acroyogis more conscious about their interaction without the technology.
Malaria Disease Cell Classification With Highlighting Small Infected Regions

Deep learning-based methods have become an active research area in medical imaging.Malaria is diagnosed by testing red blood cells.Deep learning methods can be used to distinguish malaria infected cell images from non-infected cell images.The small number of malaria dataset may limit the application of deep learning.Moreover, the infected area in the cell images is generally vague and small, requiring more complex models and a larger dataset to train on.Motivated by the tendency of humans to highlight important words when reading, we propose a simple neural network training strategy for highlighting the infected pixel regions that are mainly responsible for malaria cell classification.In our experiments on the NIH(National Institutes of Health) malaria dataset available in public domain, the proposed method significantly improved classification accuracy for our four different sized models, ranging from simple to complex including Resnet and Mobilenet.Our proposed method significantly improved classification accuracy.The result indicate that approach achieves a classification accuracy of 97.2%, compared to 94.49% for a baseline model.In addition, we demonstrate the superiority of the proposed strategy by providing an analysis on the magnitude of weight parameters in terms of regularization.
Sentimental Analysis Using Cloud Dictionary and Machine Learning Approach

As a result of greater digitization, user-generated material on the web has exploded, providing people’s viewpoints on many themes. For deep web mining, service qualities, and client behaviour research, use cloud-based sentiment analysis with scheduling and big data. Sentiment analysis measures people’s views and sentiments about an item. Opinions? What’s your opinion? Computer scientists cooperate in languages, data mining, psychology, and sociology. Sentiment analysis employs machine learning and NLP to analyze text for the writer’s sentiment (positive, negative, neutral, and beyond). Positive, negative, and neutral comments may be readily found using machine learning. Sentiment analysis takes numerous forms. Emotion categorizes text polarity. As the internet grows, so do smartphones. The contemporary Internet allows millions of individuals to connect and express their opinions and views through email, social networking websites, and other means. It is inexpensive and easy to communicate. This social network is text-heavy. Text data may be used to study public opinion and online forum emotions. In this study, we’ll compare the Traditional Dictionary-Based Approach with Machine Learning utilizing a text classifier trained on a dataset of US airlines.
Pactolo Bar: An Approach to Mitigate the Midas Touch Problem in Non-Conventional Interaction

New ways of interacting with computers is driving research, which is motivated mainly by the different types of user profiles. Referred to as non-conventional interactions, these are found with the use of hands, voice, head, mouth, and feet, etc. and these interactions occur in scenarios where the use of mouse and keyboard would be difficult. A constant challenge in the adoption of new forms of interaction, based on the movement of pointers and the selection of interface components, is the Midas Touch (MT) problem, defined as the involuntary action of selection by the user when interacting with the computer system, causing unwanted actions and harming the user experience during the usage process. Thus, this article aims to mitigate the TM problem in interaction with web pages using a solution centered on the Head Tracking (HT) technique. For this purpose, a component in the form of a Bar was developed and inserted on the left side of the web page, called the Pactolo Bar (PB), in order to enable or disable the clicking event during the interaction process. As a way of analyzing the effectiveness of PB in relation to TM, two stages of tests were carried out based on the collaboration of voluntary participants. The first step aims to find the data that would lead to the best configuration of the BP, while the second step aims to carry out a comparative analysis between the PB solution and the eViacam software, whose use is also focused on the HT technique. The results obtained from the use of PB were considered promising, since the analysis of quantitative data points to a significant prevention of involuntary clicks in the iteration interface and the analysis of qualitative data showed the development of a better user experience due to the ease of use, which can be noticed in elements such as the PB size, the triggering mechanism, and its positioning in the graphical interface. This study benefits in the context of the user experience, because, when using non-conventional interactions, basic items such as aspects of the graphic elements, and interaction events raise new studies that seek to mitigate the problem of the Midas Touch.
Mobile Assisted Language Learning in Blended Learning Context: How is it used and Students’ Anxiety

This research was conducted to explore how Mobile-Assisted Language Learning was used throughout the English learning process.Not only that but this research was also conducted to find out what level of anxiety the students of SMK N 1 Singaraja faced in the blended learning context of the post-pandemic situation.This research used a mix-method design specifically embedded sequential mix-method.Furthermore, the data were collected through an observation sheet for how MALL was used and used to determine the student's anxiety level using a questionnaire with Oetting Scale.The results show that the teacher used MALL as a strategy in three teaching procedures and sharing materials or assignments.Concerning the student's level of anxiety, 27% of students are classified as having low-level anxiety, 46% as moderate-level anxiety, and 27% as high-level anxiety.
Human-Vehicle Cooperative Visual Perception for Autonomous Driving Under Complex Traffic Environments

Human-vehicle cooperative driving has become one of the critical stages to achieve a higher level of driving automation. For an autonomous driving system, the complex traffic environments bring great challenges to its visual perception tasks. Based on the gaze points of human drivers and the images detected from a semi-automated vehicle, this work proposes a framework to fuse their visual characteristics based on the Laplacian Pyramid algorithm. By adopting Extended Kalman Filter, we improve the detection accuracy of objects with interaction risk. This work also reveals that the cooperative visual perception framework can predict the trajectory of objects with interaction risk better than simple object detection algorithms. The findings can be applied in improving visual perception ability and making proper decisions and control for autonomous vehicles.
Implementation of Virtual Reality for Teaching in Technical Drawing

Three-dimension spatial vision is one of the main abilities that students develop during the teaching–learning process in subjects related to Graphic Expression and Technical Drawing in Engineering knowledge area at university levels. This skill is related not only to the ability to interpret 2D drawings, sketches, schemes, etc. and generate a mental 3D representation of a piece or/and an assembly and vice versa but also to generate these 2D representations from a physical element and the ability to interpret the interaction of the different elements of an assembly. Traditional teaching has used only 2D representations to teach these subjects and, in some moments, it has used 3D models to compare it with 2D representations. To develop these resources, it has been used open-source UNITY software and HTC Vive Pro virtual reality glasses and hand joysticks as well a CAD model generated using Autodesk Inventor. This CAD model is a three axis, two stages speed gearbox box that is used during the problem and theory sessions of the mentioned subjects. It has been studied possible functionalities that could be implemented and it has been selected some: the possibility to disassembly any component and to move and rotate it, the possibility reassembly all the components after moving them into the initial assembly configuration, the possibility to change the size of any component, the possibility to see the assembly/disassembly process and the possibility to see this machine working. Finally, it has developed a virtual environment imported the 3D CAD model.
Framework for Posture and Face Recognition Using Kinect an Ambient-intelligence Method

This electronic document describes one of the first full open-source frameworks for posture and face detection and classification using Kinect sensors, based entirely on an open-sourced software platform. It has been designed with the possibility of automatic monitoring of either an elderly person who is situated in a closed space (a room with furniture, appliances, and other rigid objects), or a patient who suffers from a physiological disorder. It is also based on an original hardware platform (the AmI-Platform), which includes more Kinect sensors, data acquisition stations, and crunches (data servers). The articles tackle two of the most important issues for ambient intelligence: accurate determination of the person and his or her facial landmarks (to understand emotions) and fast and reliable posture determination (to take appropriate measures in case of an accident).
ON THE REALIZATION OF NOANOA AND PRES, TWO PIECES FOR SOLO INSTRUMENTS AND IRCAM SIGNAL PROCESSING WORKSTATION (Xavier Chabot, Kaija Saariaho, Jean-Baptiste Barrière)

This article is a translation of a musicological work written by the Finnish composer Kaia Saariaho with sound engineers Xavier Chabot and Jean-Baptiste Barrière from the Ircam. The study describes two solo pieces – «NoaNoa» and «Près» – one for flute, the other for cello, realized during 1992 by Kaija Saariaho with the Ircam Signal Processing Workstation (ISPW, based on the Next computer) and with Xavier Chabot from the Ircam Pedagogy department. These works are created in the pedagogical perspective to explore the potentialities of Max on the ISPW, and specially its connexion with Patchwork used to prepare data and patches. In the two pieces, the electronic parts amplify and develop the sonic structure of the solo instrument, exemplify the close relationship between sound material and musical structure, and explore real-time strategies for control over various synthesis and signal processing algorithms.
Towards the development of learning through microlearning

This research is referred to the application of a methodology called microlearning that included the creation of content pills or capsules which provided the student with learning accessible at any time and in any place thanks to its ubiquity and virtual context, for the application of microlearning an instructional design was followed that helped to improve the pedagogical practice. The main objective of this research was to determine how the use of microlearning influences learning in the area of Social Science in secondary school students. This study had a quantitative approach, experimental design, pre-experimental level, where students in the third grade of secondary school in Peru were taken as a sample. For data collection, survey techniques were applied in order to compare academic performance with respect to the pre- and post-test of the application of microlearning. The results of the study revealed that microlearning had a satisfactory influence on learning in the area of social sciences since this learning methodology is easy, accessible, flexible, ubiquitous and didactic, showing that it can be a great didactic resource for the teacher in the teaching of the area.
Facial expression recognition using visual transformer with histogram of oriented gradients

Emotions play an important role in our life as a response to our interactions with others, decisions, and so on. Among various emotional signals, facial expression is one of the most powerful and natural means for humans to convey their emotions and intentions, and it has the advantage of easily obtaining information using only a camera, so facial expression-based emotional research is being actively conducted. Facial expression recognition(FER) have been studied by classifying them into seven basic emotions: anger, disgust, fear, happiness, sadness, surprise, and normal. Before the appearance of deep learning, handcrafted feature extractors and simple classifiers such as SVM, Adaboost was used to extracted Facial emotion. With the advent of deep learning, it is now possible to extract facial expression without using feature extractors. Despite its excellent performance in FER research, it is still challenging task due to external factors such as occlusion, illumination, and pose, and similarity problems between different facial expressions. In this paper, we propose a method of training through a ResNet [1] and Visual Transformer [2] called FViT and using Histogram of Oriented Gradients(HOGs) [3] data to solve the similarity problem between facial expressions.
Improvement of a facial recognition system based on one shot camera

In recent years, one-shot cameras that integrate Multispectral Filter Arrays (MSFA) are used to acquire multispectral images. In a previous paper, we have proposed a multispectral image recognition system based on this type of camera. The images acquired with these cameras are then demosaiced. Multispectral facial images acquired with our MSFA one-shot camera present information redundancy which leads to a strong correlation between bands. A dimensionality reduction is necessary to reduce information redundancy. Dimensionality reduction is a set of techniques that allow to project an initial image of dimension n into a final image of dimension p, while preserving its relevant information. This paper proposes an improvement of facial recognition system using the Multispectral Filter Array one shot camera. A dimensionality reduction module has been added to the system. A comparison of the performance of different dimensionality reduction methods based on the eigenvalues, and VGG19 classification results are conducted. Experimental results on the EXIST database made up with our camera indicate a good decorrelation of the bands leading to the reduction of bands from eight to three with the Karhuen-Love transform an accuracy of 100% with VGG19 and a 15 % gain in processing time.
Comparative Study of the Influence of Student Learning Motivation on Student Learning Outcomes in a View of Gender in Thematic Subject

The objectives to be achieved in this study are, 1) to determine the effect of student motivation on student learning outcomes of the male sex in the Thematic subject in class V SDN 52 Bengkulu City. 2) to determine the effect of student learning motivation on student learning outcomes of the female gender in thematic eyes. 3) to determine the effect of student learning motivation on student learning outcomes in thematic subjects and 4) to determine the comparative test results of student learning motivation and student learning outcomes in terms of gender in thematic subjects. This research is a quantitative research with a quantitative descriptive research design with regression and comparison types, sampling was carried out using a non-probability sampling technique. The results of this study are that there is an influence of student learning motivation on student learning outcomes of male and female gender in thematic subjects in class V SDN 52 Bengkulu City. And there are differences in the learning motivation of male and female students.
Pengembangan Media Roda Putar (Rotar) pada Materi IPA Siswa Kelas V SD

This research was conducted at Tenggulang Baru State Elementary School, Musi Banyuasin district, to find out the Development of Rotating Wheel Media (Rotar) in Science Material for Class V Elementary School Students. The problem in this research is that the media used is still not attractive and innovative. The purpose of this research is to describe the validity and practicality of the results of the development of rotary media in the subject matter of healthy food for class V SD. This type of research includes development research. The method used is the development research method or called Research and Development, and uses the ADDIE development model. The results of this development research have produced a product in the form of Rotar Wheel media in the Natural Sciences subject on the Human Digestive System. The results of the assessment of the questionnaire distributed to experts showed that linguists scored 73% in the practical category, media experts scored 83% in the very practical category, and material experts scored 62% in the practical category. This means that the media can be concluded that the validity of the results of the development of rotary media on Healthy Food Materials for class V SD is very valid. Furthermore, this practicality test is carried out by filling out a practicality questionnaire that has been given to students. Practical value criteria are 61-80 Practical 81-100 Very Practical. Based on the results of the questionnaire given to students was 76%, this shows that the Rotar Wheel media is declared practical.