Reviewerly/exHarmony huggingface dataset:
Numeracy and literacy skill in elementary school students: The utilization of kampus mengajar perintis program

Numeracy and literacy skill is some of the current demands that are expected to be the competencies that students have. The purpose of this research is to find out the numeracy and literacy skills of elementary school students before and after receiving periodic assistance on the Kampus Mengajar Perintis program. Sampling was done by using the saturated sampling technique. The research instrument used was problems derived from the literacy and numeracy modules of the elementary school level. The data analysis technique used the paired t-test because the population research data were normally distributed. The result of this research is that the literacy ability of elementary school students has increased with the acquisition of an average score of 8.47. It is higher than before getting the treatment of the Kampus Mengajar Perintis program which is 7.25. Then, the numeracy ability of elementary school students has increased with the acquisition of an average score of 8.16. It is higher than before getting the treatment of the Kampus Mengajar Perintis program which is 6.
Kesulitan Belajar Matematika Siswa Melalui Pembelajaran Jarak Jauh

Learning difficulties that occur during distance learning affect achievement in learning mathematics. This study was conducted to determine the difficulty of learning mathematics through distance education. This type of research is qualitative research. The research subjects were three grade XI students in Kp. Campaka, Garut. Data collection was carried out using questionnaires and interviews. The findings in this study were some of the learning difficulties experienced by students during distance learning in mathematics. These difficulties are difficulty in understanding the mathematical material presented, unstable internet connection, and a learning environment that is less supportive for distance learning to take place. These difficulties affect the psychological factors of students, especially students' interest in learning. The difficulties that arise in distance learning mathematics should be corrected to increase learning success.
Analisis Kesesuaian Buku Matematika Guru dan Siswa Kelas III dalam Tema 2 Revisi 2018

The purpose of this research is to analyze the suitability of the indicators of competence achievement, the suitability of learning objectives, and the suitability of the mathematics subject matter of the teacher's book and the third-grade student's book theme 2 revision 2018. This research is qualitative research with the method used, namely the descriptive method. Content analysis techniques to describe objectively, systematically, and communicatively. This research uses a set of research instruments to conclude a book or document. The subjects in this study were the teacher's and third grades students’ book theme 2 revision of 2018 entitled loving plants and animals. Based on the result concluded that suitability indicators of competency attainment to teacher’s and student’s books are not appropriate because in the 2018 revised theme 2 of the teacher's books and class 3rd student’s books do not include indicators of competency achievement, the suitability of learning objectives for teacher’s and student’s book are not appropriate, learning objectives are only listed in teacher’s book only while student’s book does not include learning objectives, the suitability of mathematics subject matter in the teacher's and student’s book is categorized accordingly because in every mathematics subject in student’s book is the same as mathematics subject matter in the teacher’s book.
HDPE Recycled Plastic Composite with Cellulose Fiber Filler Based on Oil Palm Empty Fruit Bunches

Composite is an advanced material product that has better mechanical properties than a single material and has high tensile strength; it can be applied to the construction of boat walls, car dashboards, electronic casings, and others. This study examines the composite quality of HDPE recycled plastic using cellulose fiber-based on Empty Palm Oil Bunches (TKKS), which is processed through an extruder and injection melt blending system. The method used is mixing plastic and fiber materials with a roll mill and blending with an extruder. Cellulose fiber was dissolved with compatibilizer maleic anhydrous (MAH) 2.5% as much as 20 mL, stirred until smooth, and HDPE plastic was dissolved with benzoyl peroxide (BPO) 0.5% 10 mL. The composite was molded with hot pores at 160-170 ᴼC. The tensile test shows the strength of HDPE composite (90: 10) is 27.0 Mpa with maximum load reaching 274 N, HDPE composite (80: 20) is 26.0 MPa with full load 258 N, HDPE composite (70: 30) is 320.0 MPa with a maximum load of 316 N. SEM shows the surface structure of the fiber-compatible HDPE composite. Functional group analysis showed that HDPE composites had O-H and C-O-C functional groups derived from lignocellulosic OPEFB material. The appearance of these two peaks indicates a compatible interaction between the HDPE matrix and cellulose. DSC shows that HDPE composites have a degradation temperature of up to 260 ᴼC and a decomposition temperature of 493.45 ᴼC. This temperature indicates that the HDPE-cellulose composite can withstand heat until it decomposes at a temperature of 493 45 oC.
American Sign Language Recognition using YOLOv4 Method

Sign language is one of the ways of communication that is used by people who are unable to speak or hear (deaf and mute), so not all people are able to understand this language.Therefore, to facilitate communication between normal people and deaf and mute people, many systems have been invented that translate gestures and signs within sign language into words to be understandable.The aim behind this research is to train a model to be able to detect and recognize hand gestures and signs and then translate them into letters, numbers and words using You Only Look One (YOLO) method through pictures or videos, even in real time.YOLO is one of the methods used in detecting and recognizing things that depend in their work on convolutional neural networks (CNN), which are characterized by accuracy and speed in work.In this research, we have created a data set consisting of 8000 images divided into 40 classes, for each class, 200 images were taken with different backgrounds and under lighting conditions, which allows the model to be able to differentiate the signal regardless of the intensity of the lighting or the clarity of the image.And after training the model on the dataset many times, in the experiment using image data we got a very good results in terms of MAP = 98.01%as an accuracy and current average loss=1.3and recall=0.96and F1=0.96, and for video results it has the same accuracy and 28.9 frame per second (fps).
An Overview on Quantum Image Watermarking for Security of COVID-19 Patient Record

The basics of Quantum Information Processing (QIP) is summarized below, in addition to a comprehensive survey of quantum image-based data hiding techniques.QIP is more efficient and provides higher security than classical information processing.A comparative analysis of the Flexible Representation of Quantum Images (FRQI) and Novel Enhanced Quantum Representation (NEQR) model is also presented.QIP is used in various potential applications, hence offering an interesting and demanding area for researchers [1].Some of the important applications include medicine, military, environmental monitoring, image processing, communications, computations, and cryptography.This article focusses on the processing of information that can be represented using quantum mechanics [2].Furthermore, coherence, entanglement, and superposition of quantum states makes quantum computing more suitable to its classical counterpart for information storage and processing [1], [3].A. An overview of Quantum Information Processing
Eksperimen Penerapan Sistem Traffic Counting dengan Algoritma YOLO (You Only Look Once) V.4.

Traffic counting is the activity of counting traffic (vehicles) that pass on the road in a certain period. The purpose of traffic counting is to collect traffic data, determine traffic characteristics, determine vehicle composition and measure traffic performance. With the YOLO V.4 algorithm, changes in the position, size and volume of the detected object can be carried out in several tests. Although not all the results of using this algorithm are perfect on all data, the results tend to be good. This is related to the services provided in the form of a convolutional layer on YOLO reducing downsample or reducing image dimensions by using anchor boxes, this algorithm can also increase accuracy. The YOLO V.4 algorithm utilizes an image feature scanning model using the concepts of angles and directions mathematically. From the results of experiments carried out in this study, obtained detection results that have a fairly good accuracy in the results of separating frames from video data. Irregular transformations of position, dimension, composition and direction can still be captured as the same feature. YOLO's ability in feature engineering is an acknowledgment that has been successfully proven in this research.
Pengenalan Wajah dengan Menggunakan Metode Local Binary Patterns Histograms (LBPH)

Rapid technological developments in the world have had a major impact on various fields, i.e. administration and data collection. One of the data collection systems that is often used is attendance. The attendance system initially only used an attendance sheet that was filled out manually, but there were shortcomings i.e. the possibility of forging signatures during attendance. Therefore, other methods are needed to overcome these problems. In this study, we propose to use facial features for attendance. The data used are 750 facial images consisting of 5 people with each person having 150 facial images with various expressions. The data is divided into two, namely 500 images as training data and 250 images as test data. The next stage is to find a facial features, we propose to use the Local Binary Patterns Histograms (LBPH) method. LBPH is a combination of the Local Binary Patterns (LBP) method with Histograms of Oriented Gradients (HOG). After that, we perform face recognition based on the features that have been obtained. Based on the research results obtained an accuracy rate of 86%
A STUDY ON STUDENTS’ DIFFICULTIES IN LEARNING VOCABULARY

The objectives of the research entitled “A Study on Students' Difficulties in Learning Vocabulary” were to find out kinds and factors of students' difficulties in learning vocabulary. The subject of this study was the students of the first semester of Stitek Bontang who took English class. This study employed a qualitative research design, implementing characteristics of a case study. For gaining the data, the researcher used interview and questionnaire. All the data were analyzed descriptively. The findings showed that the students still faced the problems or difficulties in vocabulary learning. Kinds of difficulties faced by students in vocabulary learning were various. Kinds of difficulties faced by the students were (1) almost all of the students have difficulties in pronouncing the words, (2) how to write and spell, (3) the different grammatical form of a word known as inflections was one of causes of students difficulties in learning vocabulary. In addition, (4) the students found difficulties in choosing the appropriate meaning of the words and (5) also still confuse in using the word based on the context. The last, (6) the students were also still confuse when they found words or expression that were idiomatic. There were some factors that caused students' difficulties in learning vocabulary (1) the written form is different from the spoken form in English, (2) The nuber of words that students need to learn is exceedingly large, (3) the limitations of sources of information about words, (4) The complexity of word knowledge. Knowing a words involves much more than knowing its dictionary definition, (5) causes of lack of understanding of grammatical of the words, (6) the incorrect pronunciation is often caused by the lack of sound similarity between English and the students' native language.
Towards Trusted and Intelligent Cyber-Physical Systems: A Security-by-Design Approach

Towards Trusted and Intelligent Cyber-Physical Systems: A Security-by-Design Approach
Challenges for XR in Games

Extended Reality as a consolidated game platform was always a dream for both final consumers and game producers. If for one side this technology had enchanted and called the attention due its possibilities, for other side many challenges and difficulties had delayed its proliferation and massification. This paper intends to rise and discuss aspects and considerations related to these challenges and solutions. We try to bring the most relevant research topics and try to guess how XR games should look in the near future. We divide the challenges into 7 topics, based on extensive literature reviews: Cybersickness, User Experience, Displays, Rendering, Movements, Body Tracking and External World Information.
Studies on the Quality Assessment of PRNG for Q-Trits Quantum Cryptography Protocols

Cybersecurity contains three basic features such as confidentiality, integrity and availability. Data confidentiality ensuring by encryption has faced quantum computing threat, but this problem can be solved by using post-quantum cryptography and / or quantum cryptography (quantum key distribution). For cryptographic applications statistical properties of the generated pseudorandom sequences should not be differ from random sequences. To determine such properties a number of statistical testing methods are used, but they all are focused on the evaluation of binary sequences. In quantum cryptography there are some protocols with Q-trits (qutrits), but these sequences cannot be assessed effectively by binary statistic methods. From this position in the paper quality assessment approach for Q-trits pseudo random number generators and formed sequences was proposed. Also the experimental study of proposed approach (in comparison with NIST STS) was carried out. Given results show that NIST STS technique cannot be used to evaluate the quality of the Q-trit sequences and generators, but developed method is suitable to use in practice for evaluating Q-trit sequences (generators) quality.
Identifying Reply Relationships from Telegram Groups Using Multi-Features Fusion

Telegram has become one of the most successful instant messaging services in recent years. Identifying reply relationships from Telegram groups plays a key role in cybersecurity filed. Different from traditional instant messaging platforms, text messages in Telegram groups have some specific characteristics, which make the problem more difficult. Text messages in Telegram groups are usually short and with limited information. And there are also a lot of meaningless messages. In this paper, we propose a novel method based on multi-features to identity reply relationships from Telegram groups. Specifically, We firstly conceptualize the problem as a sentence pair classification task and employ the BERT model to learn the textual representation of an input pair. Then, we utilize the users&#x0027; contextual features that contain richer information to overcome the limitation of short text messages. Furthermore, from the perspective of that the closer the message is to the target message, the more likely it is to be responded, we also introduce the message position features to our model. To evaluate our proposed method, we construct a real dataset from Telegram groups. Experimental results demonstrate that our proposed model achieves good performance in reply relationships identification.
Emotion Recognition using Facial Expression

In recent years, research has shown an increased development of social networking applications.Social networking applications are recently getting wider interest among people of different ages.But due to irrelevant posts, the mood of a user can get affected.The project "Emotion Recognition Using Facial Expression" is based on a new concept where a person can filter friends' posts by emotions.The emotion would be detected from a facial expression.Using this application, a sad person's mood can be elevated as sad posts will be filtered out (as only happy posts will be seen).To develop the mobile application of this project, Android Studio was used.Python and TensorFlow were used to train the model.For data storage purposes, Firebase was used as it is compatible with any other platform.
A Seq to Seq Machine Translation from Urdu to Chinese

Machine translation (MT) is a subtype of computational linguistics that uses to implement the translation between different natural languages (NL). Simply word to word exchanging on machine translation is not enough to give desire result. Neural machine translation is one of the standard methods of machine learning which make a huge improvement in recent time especially in local and some national languages. However these languages translation are not enough and need to focus on it. In this research we translate Urdu to Chinese language with the help of neural machine translation (NMT) in deep learning methods. First we build a monolingual corpus of Urdu and Chinese languages, after that we train our model using neural machine translation (NMT) and then compare the data-test result to accurate translation with the help of BLEU score method.
Diagnosing Changes in An Ontology Stream: A DL Reasoning Approach

Recently, ontology stream reasoning has been introduced as a multidisciplinary approach, merging synergies from Artificial Intelligence, Database and World-Wide-Web to reason on semantics-augmented data streams, thus a way to answering questions on real time events. However existing approaches do not consider stream change diagnosis i.e., identification of the nature and cause of changes, where explaining the logical connection of knowledge and inferring insight on time changing events are the main challenges. We exploit the Description Logics (DL)-based semantics of streams to tackle these challenges. Based on an analysis of stream behavior through change and inconsistency over DL axioms, we tackled change diagnosis by determining and constructing a comprehensive view on potential causes of inconsistencies. We report a large-scale evaluation of our approach in the context of live stream data from Dublin City Council.
Analysis on the Reconstruction of Primary School Mathematics Class Based on the Theory of “Thinking Visualization”

With the continuous advancement of the new curriculum reform, the cultivation of primary and secondary school students’ thinking ability has gradually become the focus of education, and the strength of thinking ability will have a profound impact on students’ problem analysis and judgment ability. Thinking visualization theory provides important guidance for the cultivation and orderly development of students’ thinking ability. The application of thinking visualization theory in primary school mathematics teaching can realize the effective combination of graphics and text, and then present mathematics knowledge and conceptual content to students concretely and vividly, and help students effectively sort out knowledge, To achieve high quality and efficient learning, reduce the primary school students in the process of mathematics problems and difficulties. This research focuses on the reconstruction of primary school mathematics classroom under the theory of “thinking visualization”，and provides ideas and methods from multiple perspectives.
Exploring implications for designing for sociotechnical transitions: Taking reflexivity as a matter of scale

There is increasing interest of design for paradigmatic and sociotechnical changes, in which the significance of actor is recognized.However, design studies that aim to connect actors at the micro level and sociotechnical systems at the macro level is limited.Based on institutional theory in sociotechnical theory, this paper proposes reflexivity as a useful concept to be associated with matters of scale in Design.Based on literature review, we explore the ways "cultivating reflexivity" has been applied in critical design, norm creative innovation and service ecosystem design.This preliminary work seems to suggest an evolution in the application of reflexivity, from a focus on individuals and their own critical attitudes, to the facilitation of a more reflexive design process to the facilitation of collective feedback loops of reflexivity and reformation of institutions and their socio-material manifestations, pointing toward a very relevant area of study for Design and sociotechnical transitions.
Web Service Recommendation Based on Word Embedding and Node Embedding

Thanks to the rapid development of service-oriented computing (SOC) technologies, the number of Web services, such as Web API, is increasing rapidly. However, this brings some difficulties for mashup (a kind of Web API composition) developers to choose appropriate Web Services to build their projects. Finding required Web APIs from a large number of candidates and recommending them to developers has become a vital issue in mashup development. The traditional collaborative filtering algorithm has the problems of cold start and sparse data. In order to solve the deficiency of the collaborative filtering algorithm, we propose an improved hybrid method that combines the two kinds of information to generate word embedding and node embedding, avoiding the cold start problem and data sparsity problem. Experiments on real-world data sets show that our proposed approach is better than five state-of-the-art approaches, which verifies the effectiveness of our approach.
scikinC: a tool for deploying machine learning as binaries

Machine Learning plays a major role in Computational Physics providing arbitrarily good approximations of arbitrarily complex functions, for example with Artificial Neural Networks and Boosted Decision Trees. Unfortunately, the integration of Machine Learning models trained with Python frameworks in production code, often developed in C, C++, or FORTRAN, is notoriously a complicated task. We present scikinC, a transpiler for scikit-learn and Keras models into plain C functions, intended to be compiled into shared objects and linked to other applications. An example of application to the parametrization of a detector is discussed.
Developing novel visual messages for a video screen hand sanitizer: a co-design study with students

This paper reports on the results of a series of co-design workshops devised to generate new messaging ideas for a novel hand sanitizer unit that features a video screen and feedback system. Students of different nationalities, ages and genders were involved in the process either to prime design sessions, or devise/evaluate new ideas for the screen to display in a university setting. The project aimed not only to produce animated designs for subsequent testing but also to elicit key preferences for hand hygiene message tone, content and visual appearance. Research findings revealed a clear preference in the student community for positive, caring and playful approaches to hand hygiene messaging in contrast to many messaging approaches featured in previous studies. In terms of visual approach, students expressed a preference for colourful illustrations rather than photographs or word-based messages. The paper highlights some particularly rich ideas developed to exploit the novelty of the device, such as specific animated sequences or immediate visual rewards of internet memes as ways to engage the student audience. Co-design proved valuable in devising new insights for the hygiene communication community.