Reviewerly/exHarmony huggingface dataset:
Primary School Earth and Space Science Educational Game Application

As Vision 2020 approaches, Malaysians have yet to overcome the challenge of being a progressive society that does not just simply act as consumers of technology, but also be capable of contributing to the scientific and technological civilization of the future. Majority of students choose not to pursue into STEM related studies as they are slowly losing interest and the engagement to learn STEM education due to limited availability of interactive teaching method and tools for a more effective learning in the classroom environment. With respect to the matter, games have been introduced over the years as an exciting approach to retain students’ interest in learning using current software like mobile applications. Hence in this regard, an educational game application is proposed to assist in increasing student’s interest in STEM subjects, mainly focusing on the Earth and Space Science topic. The purpose of this project is to study how educational game application can help to incline students’ interest in Science subject, develop an educational game application and conduct usability evaluation of the educational game application. The research covers the scope to the targeted group of Year 4 and Year 5 primary school students and the subtopic chosen is Earth and space science. The project utilizes Rapid Application Development methodology due to the short amount of time. The application was developed using Ionic Framework, Angular 5, C#.NET and SQLExpress. The findings showed that this project is believed to be helpful to incline students’ interest in learning Science subject.
Achievement Orientation Model

In the Achievement Orientation Model, giftedness involves performance, rather than some measure of potential. According to the Achievement Orientation Model, developing one's talent is a choice individuals make based on a set of self-perceptions in three areas—self-efficacy, goal valuation, and environmental perceptions—which collectively influence individuals' motivation, and subsequently interact with self-regulation to promote engagement and ultimately achievement. Many gifted underachievers have high self-efficacy, but fail to achieve in school because they do not value their schoolwork. In order to develop gifts and talents, students must first develop self-efficacy, goal valuation, and positive environmental perceptions. The environmental perceptions factor captures the importance of the interaction between the person and the environment, as well as the perception of that environment on achievement motivation. As individuals mature through childhood to adolescence, however, achievement and high levels of motivation in the domain become the primary characteristics of their giftedness.
Should Young People Be Allowed to Choose Their Own Religion?

Religion unifies people under a set of beliefs and creates communities in which people pray, celebrate, forgive, and support each other. Kids are usually raised to accept the same religion as their family. Religion reflects people’s deepest values. This means that people who follow different religions might have completely different opinions on moral issues, such as how to be a good person or how to treat other people. Philosopher Michael Hand argued that it is important for a child to experience what religious stories and rituals mean to people within that religion. Hand might worry that Vopat’s idea of religious education is like a superficial musical education, in which a child is encouraged to try different instruments without ever being required to learn one instrument in depth.
ANALISIS TINGKAT KEMATANGAN SISTEM INFORMASI MANAJEMEN AKADEMIK DAN KEMAHASISWAAN IAIN PALANGKA RAYA MENGGUNAKAN COBIT 5

The use of Information Technology (IT) at a university is needed at this time. There are many advantages in using IT and have a good impact on a university. The use of IT in a university has different roles according to their needs. The utilization of IT in Higher Education theoretically provides appropriate and efficient administration systems (Fernandes Andry and Christianto, 2018). IAIN Palangka Raya is one of the universities that has implemented IT, in this case, the academic and student management information system. The information system at IAIN Palangka Raya is one of the IT applications that is often used to carry out IT governance, however, there are several problems that occur in the information system, including features or tools that are not yet functional. For this reason, the researcher will analyze the information system to get the level of maturity and recommendations so that IAIN Palangka Raya can follow up on the results of this analysis and improve it to get the goal of good information system governance. In this study, the COBIT 5 framework is used with a focus on the EDM domain (Evaluate, Direct, and Monitor). The results of the analysis showed that the capability level was 2.86 (established), which means that the process was carried out, achieved goals, and well managed. With a balance value of 0.96, which means that the expected distance with the current distance is not too far so that features or tools that are not yet functioning are functional. So that the academic and student management information system of IAIN Palangka Raya runs according to its goals and is better.
Object Detection Using Deep Learning Algorithm

Object detection is a computer technology related to computer vision and image processing that deals with detecting images of semantic objects of a certain class (for example cars, buildings, etc.) in digital images and videos. To detect objects, there are many algorithms available, in this paper YOLO algorithm is explored for detection of objects on real-time data. You Only Look Once (YOLO) is a state-of-the-art real time object detection system whose architecture is based on Convolutional Neural Networks (CNN) and anchor boxes. In this work, YOLO V3 is considered. When it comes to the implementation, the input image is being divided into grids in which for each cell classification and localization is applied. After the localization, the algorithm draws bounding boxes for the detected objects. As in real time images there might be a probability of having objects present in more than one grid cell hence, we also use Non max suppression to detect the object more accurately. We also import OpenCV, NumPy libraries in PyCharm Environment for the better optimization of the output. In this paper, to detect the objects in an image using this YOLO algorithm is also tested apart from videos.
Multi-Vehicle Speed Estimation Algorithm Based on Real-Time Inter-Frame Tracking Technique

Inappropriate vehicle speeding remains a central factor that causes road accidents claiming millions of lives every year. This challenge has raised concerns for vehicle speed estimation as an attempt to promote speed enforcement methods. Traditionally, radar and lidar systems have widely been used for this purpose, despite their several shortfalls: cosine error effects, need for direct line-of-sight, and inability to simultaneously and accurately measure speed from multiple vehicles. The current work proposes an algorithm and a multi-vehicle speed estimation system in a multi-lane road environment to address multi-vehicle speed estimation shortfalls. The proposed solution exploits image processing and computer vision techniques to flag vehicles with inappropriate speeding patterns. A series of experiments showed that the developed system generates more accurate results than those given by the lidar system. In essence, the proposed system can estimate the speed of up to six vehicles concurrently. It can produce an average percentage error of 2.7% relative to the actual speed measured by a speedometer. This error is 5.4% lower than that demonstrated by the lidar system, emphasizing that the proposed system may be a more suitable approach to traffic laws enforcement.&#x0D; Keywords: Computer vision; image processing; inter-frame differencing; vehicle tracking; road accident
A Robust Cyber Security

For several potential IoT implementations, the paradigm changes to the Internet of Things (IoT) and the advent of edge computing are providing major benefits. It also introduces essential challenges to cyber security. We identified and addressed five cyber security issues and five potential prospects for cyber security relevant to this vision throughout this chapter. The development of some convergence between the “edge computing + IoT” platform and the evolving blockchain and AI technologies could theoretically create many of these opportunities that are beneficial.
Dio Arena Enterprise / Andrew Robert Martin Hughes ... [et al.]

Dio Arena is an indoor sports arena that offers high quality equipment and courts for people in residential areas to enjoy and experience ‘World Class’ playing. Dio Arena Enterprise is located at Greentown Avenue, 31400 Ipoh, Perak.Dio Arena was founded by the general manager, Andrew. Moreover, the office and court will be opening soon in 1 March 2021. Our main activity is to serve high quality sports courts and equipment to ensure high performance and comfort for our customers. We also offer low charge fees in order to meet the demands of our customers as we believe that sports business services should be set in a low price. We offer four sports in one court to make it compatible for the space used in our arena as well as being convenient for our customers to access these sports in just one area. These four sports include futsal, volleyball, netball and basketball. For the market target, we are focusing mainly on the local residents such as children, adults and teenagers. This is based on the population of the area where we are in the heart of Ipoh. We are surrounded by famous malls and banks where our arena will be the eye of the public.The quality of our equipments are from high-end sports brands. Our goal is to be the first customer’s choice in the sports industry in Perak and also around Malaysia. We will always ensure our customers on the reliability and high performance of our sports arena that offers low charge fees in order to gain loyalty and trust. Our business operation hour is from 9 am to 3 am, daily. The business has several main positions which is General Manager, Admin Manager, Marketing Manager, Operation Manager, and Financial Manager.
The Descriptive Analysis of Students’ Writing Ability in Narrative Text at the Eighth Grade of SMP Negeri 1 Gunungsitoli Barat in 2020/2021

Writing is one of the four language skills that should be mastered by students. The syllabus of SMP Negeri 1 Gunungsitoli Barat expects the students to be able to compiling the narrative text in the form of personal experience. The purpose of the research was describing the students’ writing ability in narrative text and the factors affecting it. The method used in the research was descriptive qualitative. The analysis of the data was conducted by following steps. Analyzing the quantitative data by using analytic scoring rubric from Glenceo namely, focus/organization, elaboration/support/style, and grammar and mechanics and analyzing the qualitative data through transcripts of structure interviews. Furthermore, the informant of the research was class VIII-A students of SMP Negeri 1 Gunungsitoli Barat which consisted of 20 students. The data were collected through documentary data of students’ worksheets and interview both students and English teacher. The result showed that the students’ ability in writing narrative text was in Good category (66 score). It is proved by the findings that there were 7 students (35%) included in ‘Excellent’ category, there were 4 students (20%) included ‘Good category, there were 3 students (15%) included ‘Fairy’ category and category included in ‘Poor’ were 6 students (30%). Furthermore, the factors that affect the students’ ability in writing narrative text were: students cognitive it was problem organization, less motivation, lack of grammar, lack of practice and the influence of the first language (L1) on writing in English.
Improving an inkjet printer: saturation enhancement based on segmentation and hue

In one of our previous paper [1] proposed in the last year, we described the color management pipeline that applied to our nail inkjet printer. However, the resulting prints are not as vivid as we would like to have since those prints are not well saturated. In this paper, we propose a saturation enhancement method based on the image segmentation and hue angle. This method will not necessarily give us the closest representation of the colors within the input image but could give us more saturated prints. The main idea that we perform our saturation enhancement method is to keep the lightness and hue constant, while stretching the chroma component.
Learning by Doing Intervention: Addressing Phonological Difficulties of Children through Audiolingual Method and Total Physical Response

Phonological awareness is a critical skill that children must master during the early foundations of literacy. It is considered a highly accurate predictor of a child’s success in learning to read. However, at the expected age, there are cases in which children have not developed phonological awareness that consequently result in poor reading skills. This case study sought to determine the alphabet knowledge of two seven-year-old children and address their difficulties in phonological awareness through the alphabetic code. The researchers conducted ten sessions of phonological interventions to children with identified language learning difficulties in reading. The data analysis and collection process included curriculum document reviews, diagnostic assessments, phonological interventions, and evaluation. Diagnostic results indicated that the children have difficulties in letter recognition of Consonant-Vowel-Consonant (CVC) patterns, blending, and segmentation of phonemes. However, anchoring on the principles of learning-by-doing delivered through oral-situational as a core language approach, the interventions in this case study were found effective for phonics instruction. The audio-lingual method and the total physical response in learning phonics, or letter sounds, activated children’s basic phonological skills. Repetition, drilling, memorisation and performing language or vocabulary concepts using physical movement to react to verbal input can lessen the phonological difficulties of children. In light of the current global situation, no previous studies have applied a case study utilizing both audiolingualism and total physical response to address the phonological issues of non-readers. Hence, this study offers scientific and pedagogical implications.
A Decentralized Threshold Signature Scheme of Blockchain-Based Medical Cyber Physical Systems

Abstract With the rapid development of medical information, the medical cyber system is rapidly transforming, and medical information sharing faces new challenges. Blockchain technology is a revolutionary technology. It has the characteristics of tamper-proof and privacy-preserving, and has natural protection for big data systems, that can be used in medical systems. In this paper,we proposed to store medical cyber physical data in a mixed blockchain with private blockchain and consortium blockchain in order to realize the secure storage of medical cyber physical data by the tamper-resistant and sharing of blockchain technology. In the system, a threshold signature system based on blockhain is also proposed. Aiming at the situation that medical accidents are easy to occur in multidisciplinary joint consultation in the medical process, this paper proposes to use threshold signature for joint consultation. Using the security and threshold of threshold signature, treatment can be carried out when the threshold number is reached, and medical data can be uploaded to the consortium blockchain. The security analysis and performance analysis show that the scheme has advantages in safety and performance and is suitable for the medical environment to a certain extent.
Microring resonators with external optical feedback for time delay reservoir computing.

Microring resonators (MRRs) are a key photonic component in integrated devices, due to their small size, low insertion losses, and passive operation. While the MRRs have been established for optical filtering in wavelength-multiplexed systems, the nonlinear properties that they can exhibit give rise to new perspectives on their use. For instance, they have been recently considered for introducing optical nonlinearity in photonic reservoir computing systems. In this work, we present a detailed numerical investigation of a silicon MRR operation, in the presence of external optical feedback, in a time delay reservoir computing scheme. We demonstrate the versatility of this compact, passive device, by exploiting different operating regimes and solving computing tasks with diverse memory requirements. We show that when large memory is required, as it occurs in the Narma 10 task, the MRR nonlinearity does not play a significant role when the photodetection nonlinearity is involved, while the contribution of the external feedback is significant. On the contrary, for computing tasks such as the Mackey-Glass and the Santa Fe chaotic timeseries prediction, the MRR and the photodetection nonlinearities contribute both to efficient computation. The presence of optical feedback improves the prediction of the Mackey-Glass timeseries while plays a minor role in the Santa Fe timeseries case.
Atelenursing system in the management of heart failure

During the emergency period of the Covid 19 pandemic, the suspension of outpatient activities determined by public health measures and the focus of the health system on emergency management, highlighted the need to implement systems for providing nursing services remotely. In particular, managing patients with chronic cardiovascular disease requires having the ability to verify adherence to the therapy, to provide health education to patients and their caregivers, and to continually monitor clinical conditions in order to maintain a health reference and the constancy of a therapeutic relationship. Objectives: Evaluate the usability and effectiveness of a telehealth system for providing supportive and protective nursing care for patients with chronic heart failure and their caregivers. Case Report: From 10 October to 11 November 2020 we enrolled 15 clinically stable patients followed by our Heart Failure Clinic: 13 M,2 F (avg age 63.2 yr, range 49-74 yr). Protocol Patients were provided with a system of devices measuring and transmitting the following vital parameters: temperature, O2 saturation, HR, ECG. It was agreed with the patients that the data would be transmitted twice a week and/or according to clinical needs. Video calls were made weekly for the first month and biweekly for the next two months, using the IT platform. The presence of signs and symptoms of clinical instability, adherence to the plan of treatment and the need for health education and psychological support were monitored through standardized interviews, and by observing patients during video calls. At the end of the course, a questionnaire was administered to investigate the degree of satisfaction of the therapeutic intervention. Results: Continuous monitoring of health status, strengthening of the patients' adherence to the therapy, support for caregivers, ability to recognize early signs of instability of the heart disease. Video calls provide the ability to analyze non-verbal language as well as the patient's daily life context, allowing to be more effective and empathetic compared to telephone contact. Nursing educational intervention reaches patients and caregivers at their home, finding them more receptive and with a smaller anxiogenic component than in the hospital setting. Results from the final questionnaire reveal full satisfaction with the nursing intervention, which gives value to the service offered, although there are some limitations that can be improved in the future.
Room occupancy classification using multilayer perceptron

A room that should be comfortable for humans can create a sense of absence and appear diseases and other health problems. These rooms can be from boarding rooms, hotels, office rooms, even hospital rooms. Room occupancy prediction is expected to help humans in choosing the right room. Occupancy prediction has been evaluted with various statistical classification models such as Linier Discriminat Analysis LDA, Classification And Regresion Trees (CART), and Random Forest (RF). This study proposed learning approach to classification of room occupancy with multi layer perceptron (MLP). The result shows that a proper MLP tuning paramaters was able estimate the occupancy with 88.2% of accuracy
Disentangling Generative Factors in Natural Language with Discrete Variational Autoencoders

The ability of learning disentangled representations represents a major step for interpretable NLP systems as it allows latent linguistic features to be controlled.Most approaches to disentanglement rely on continuous variables, both for images and text.We argue that despite being suitable for image datasets, continuous variables may not be ideal to model features of textual data, due to the fact that most generative factors in text are discrete.We propose a Variational Autoencoder based method which models language features as discrete variables and encourages independence between variables for learning disentangled representations.The proposed model outperforms continuous and discrete baselines on several qualitative and quantitative benchmarks for disentanglement as well as on a text style transfer downstream application.
Boosting quantum key distribution via the end-to-end physical control

Quantum key distribution (QKD) is a cornerstone of the secure quantum encryption. Building on the quantum irreversibility, we develop a technique reborning the existing QKDs into protocols that are unrestricted in distance and have unprecedented high rates enhanced up to the standard protocols communication speeds. The core of our method is the continuous end-to-end physical control of information leaks in the quantum channel. Contrary to the existing long-distance QKD offerings, our technique does not require any trust nodes.
3D-UCaps: 3D Capsules Unet for Volumetric Image Segmentation

Medical image segmentation has been so far achieving promising results with Convolutional Neural Networks (CNNs). However, it is arguable that in traditional CNNs, its pooling layer tends to discard important information such as positions. Moreover, CNNs are sensitive to rotation and affine transformation. Capsule network is a data-efficient network design proposed to overcome such limitations by replacing pooling layers with dynamic routing and convolutional strides, which aims to preserve the part-whole relationships. Capsule network has shown a great performance in image recognition and natural language processing, but applications for medical image segmentation, particularly volumetric image segmentation, has been limited. In this work, we propose 3D-UCaps, a 3D voxel-based Capsule network for medical volumetric image segmentation. We build the concept of capsules into a CNN by designing a network with two pathways: the first pathway is encoded by 3D Capsule blocks, whereas the second pathway is decoded by 3D CNNs blocks. 3D-UCaps, therefore inherits the merits from both Capsule network to preserve the spatial relationship and CNNs to learn visual representation. We conducted experiments on various datasets to demonstrate the robustness of 3D-UCaps including iSeg-2017, LUNA16, Hippocampus, and Cardiac, where our method outperforms previous Capsule networks and 3D-Unets.