Reviewerly/exHarmony huggingface dataset:
Implementasi Aplikasi Berbasis Teknologi IoT pada Perangkat Tracking dan Kendali Kendaraan Bermotor

The increasing use of vehicles, especially motorbikes, has the potential to increase motor vehicle theft cases. The increase in motorcycle theft cases can occur due to the weakness of the owner in installing a motorcycle security system, so that it has the potential to experience losses due to theft. An indication of the problem is how to develop an application that can be used to carry out tracking that can display the position of the vehicle with integrated maps and vehicle control remotely in the event of a vehicle theft. The development of Internet of Things (IoT) technology as well as information and communication technology can now be used to develop an application for wireless vehicle monitoring and control. So that it can make it easier for vehicle owners to track and control the vehicle to minimize vehicle loss. In this study using MIT App Inventor as an application development platform and using ThingSpeak as an IoT database server. Furthermore, the application will be integrated with the Tracking Device device consisting of a microcontroller, Global Positioning System (GPS) module, and a DC relay installed on the vehicle, utilizing an internet connection as a link between the application and the tracking device. The result is that vehicle position data can be displayed through a mobile application with map visualization integrated with google maps and the user can turn off or turn on the vehicle through the application with the farthest distance that has been successfully tested of 141 km. The time for the tracking device to respond to commands from the application varies from 5 to 20 seconds depending on the strength of the internet connection used.&#x0D; Keywords : Internet of Things (IoT), Tracking Device, Global Positioning System (GPS), mikrokontroler.
Automatic learning of modality exclusivity norms with crosslingual word embeddings

Collecting modality exclusivity norms for lexical items has recently become a common practice in psycholinguistics and cognitive research. However, these norms are available only for a relatively small number of languages and often involve a costly and time-consuming collection of ratings. In this work, we aim at learning a mapping between word embeddings and modality norms. Our experiments focused on crosslingual word embeddings, in order to predict modality association scores by training on a high-resource language and testing on a low-resource one. We ran two experiments, one in a monolingual and the other one in a crosslingual setting. Results show that modality prediction using off-the-shelf crosslingual embeddings indeed has moderate-to-high correlations with human ratings even when regression algorithms are trained on an English resource and tested on a completely unseen language.
Pemanfaatan Pembelajaran ICT Dalam Optimalisasi Proses Belajar Mengajar Guru SMP

The development of information technology and telecommunications greatly affected the world of education. By utilizing technology, education would be more advanced and not be left behind. Not only that, the teaching and learning process would be more effective, efficient, interesting and fun. Unfortunately, not all teachers were able to use technology as a learning medium. SMP N 8 Bekasi is a junior high schools located in Bekasi. Distance from the city of Bekasi to the government center (Jakarta) was about 20 km. With the distance that was not too far, the utilization of technology in the world of education should be very high. But the reality was different. the use of technology to help the teaching and learning process is still very minimal. Especially computers as learning media. This was because the skills in operating a computer were still very minimal. From the results of the situation analysis, what was needed by the teachers in the three schools is ICT (Information Communication Technologies) training. The training was specifically for the operation of some software that could help teachers in the learning process. Some of these software include power point, excel, macromedia flash, and movie maker.
Decoding the underlying cognitive processes and related support strategies utilised by expert instructors during source code comprehension

Many novice programmers fail to comprehend source code and its related concepts in the same way that their instructors do. As emphasised in the Decoding the Disciplines (DtDs) framework, each discipline (including Computer Science) has its own unique set of mental operations. However, instructors often take certain important mental operations for granted and do not explain these 'hidden' steps explicitly when modelling problem solutions. A clear understanding of the underlying cognitive processes and related support strategies employed by experts during source code comprehension (SCC) could ultimately be utilised to help novice programmers to better execute the cognitive processes necessary to efficiently comprehend source code. Positioned within Step 2 of the DtDs framework, this study employed decoding interviews and observations, followed by narrative data analysis, to identify the underlying cognitive processes and related support (though often 'hidden') strategies utilised by a select group of experienced programming instructors during an SCC task. The insights gained were then used to formulate a set of important cognitive-related support strategies for efficient SCC. Programming instructors are encouraged to continuously emphasise strategies like these when modelling their expert ways of thinking regarding efficient SCC more explicitly to their novice students.
Online White Board

This paper focuses on a whiteboard project, which was made using web development which included both frontend basics such as HTML, CSS, JS, etc. and backend fundamentals which included but weren’t limited to Mongo-DB, Node.JS, Express.JS etc. “ONLINE WHITEBOARD” is a real time application that allows user to draw/ write important points during a meeting and can also be used for teaching purposes while it helps the teacher to explain the topic in detail while taking the classes online. It has an intuitive interface that allows user to share ideas in real time. It also allows the user to save the current state of the browser for future purposes, which gets saves in users’ local drive.
Developing a Scanning Assistive Input Device for the Severely Disabled to Operate the Computers and Mobile Devices

The severely disabled such as amyotrophic lateral sclerosis and cerebral palsy often have different states and varying degrees of disease, and then the operation way of the assistive devices for the severely disabled to operate the computers and mobile devices is quite different. Thus, to develop a suitable assistive input device for severely disabled in operating computers and mobile devices is very important. In this study, a scanning assistive input device (SAID) is developed for severely disabled. To meet the user’s physical condition, an assistive input switch with different assistive input interfaces is developed to ease severely disabled in inputting commands. To help severely disabled in operating the computers or mobile devices, the SAID control box is designed to recognize and execute the input commands. To ease the operation of SAID, the function indicator lights prompt is applied as the input interfaces. The experimental results showed that the proposed SAID can effectively help severely disabled in operating computers or mobile devices. Thus, the proposed approach can help severely disabled in daily life.
Repositório institucional da Universidade Federal da Bahia: apontamentos para a construção preliminar de um instrumento de avaliação

This article seeks to identify in the literature approaches that contribute to the construction of the assessment instrument for the Institutional Repository of the Federal University of Bahia, in order to serve the repository and contribute to the institutional assessment of the National Higher Education Assessment System (SINAES). The methodology used was the strategic search for the term “evaluation of repositories” and observation of the Repository. The results show the need for discussion, given the lack of standardized documents that support the repositories evaluation. We verified some initiatives, such as the Federal Universities of Santa Catarina and Ceará. We believe that debates on the theme can be intensified and that individual initiatives tend to build criteria and evaluation standards for repositories, so that they can be used as a resource for the evaluation of other repositories as well as institutional evaluation as a whole.
Optimizing Non-Differentiable Metrics for Hashing

Image hashing embeds the image to binary codes which can boost the efficiency of approximately nearest neighbors search. F-measure is a widely-used metric for evaluating the performance of hashing methods. However, it is non-differentiable and hence it has not been used as an object function for hashing. Heuristic algorithms, e.g. evolutionary computation and particle swarm optimization (PSO), are good at optimizing non-differentiable objectives, while they are inefficient in very high-dimensional variables which are commonly used in hashing models. To address this contradict, we propose a scheme to bridge hashing methods and F-measure objective using PSO. The hashing methods are used to generate real-valued codes for images and then the parameters of quantization procedure are optimized by PSO. Our scheme can incorporate a wide range of hashing methods, heuristic optimization algorithms and non-differentiable metrics. Experimental results demonstrate that our scheme can be used to further improve the performance of existing hashing methods.
The Current State and Perceptions of a Cross-cultural Distance Learning Program for English in Korea

This article critically examines the current state of a cross-cultural distance learning program (CCDLP) for English learning in an English as a Foreign Language (EFL) context, which has been running since 1998 among four universities in Korea, Japan, and Taiwan. The initial purpose of the program was to provide a networked English language learning program to overcome the limitations of Asian EFL contexts where authentic interaction in English is minimal and to enhance intercultural competence. With physical exposure to international students on campuses increasing and further developments in communication and educational technology, the CCDLP has needed to evolve. In this article, how courses offered in the program have changed is analyzed. Data from a survey given to participants in two courses in the program were examined to determine participants’ perceptions towards their contributions and satisfaction with the courses in the program. Results show that courses need to be more customized to maximize interaction through online collaborative learning and that the technology part of such a program no longer needs to be emphasized in the wake of widespread remote learning. Lastly, implications for distance learning programs in general are discussed.
Multilingual neural machine translation: case-study for Catalan, Spanish and Portuguese romance languages

In this paper, we describe the TALP-UPC participation in the WMT Similar Language Translation task between Catalan, Spanish, and Portuguese, all of them, Romance languages. We made use of different techniques to improve the translation between these languages. The multilingual shared encoder/decoder has been used for all of them. Additionally, we applied back-translation to take advantage of the monolingual data. Finally, we have applied fine-tuning to improve the in-domain data. Each of these techniques brings improvements over the previous one. In the official evaluation, our system was ranked 1st in the Portuguese-to-Spanish direction, 2nd in the opposite direction, and 3rd in the Catalan-Spanish pair.
Pedagogical design of academic disciplines and lessons in blended learning

A central issue during the implementation of innovative learning forms is the choice of the perfect ratio between the traditions of the existing educational system, modern pedagogical innovations and the instrumentarium of information and communication technologies. From practice and a number of studies, one can see that there is a clear trend for blended learning as a process that creates a comfortable informational educational environment and the systems of communication that provide all necessary educational information. The article deals with the pedagogical design of academic disciplines and lessons in the context of blended learning. A theoretical analysis is carried out of the pattern of using blended learning in the educational process within higher education. Based on the results of an expert survey, pedagogical design stages are defined in the context of blended learning and lessons that utilize the flipped learning model.
Semantic Consistency: The Key to Improve Traffic Light Detection with Data Augmentation

Traffic light detection by camera is a challenging task for autonomous driving mainly due to the small size of traffic lights in the road scene especially for early detection. The limited resolution in the corresponding area of traffic lights reduces their contrast to the background, as well as the effectiveness of the visual cues from the traffic light itself. We believe understanding the scene semantics between traffic lights and their surroundings can play a vital role in tackling this challenge. Towards this goal, we build a generative adversarial network (GAN) model to predict the existence of traffic lights from the road scene image where existing traffic lights are removed with image inpainting. Using Cityscape dataset [2], we verify that the proposed GAN model indeed captures the desired semantics by showing effective predictions of existence of traffic lights that are consistent with real images. Moreover, we leverage this model to augment the training data where traffic lights are inserted to the road scene images based on the prediction of the GAN model. While the augmented images may not be realistic looking, results show that such data augmentation can improve the traffic light detector performance that is comparable to using additional real data collection, and better than other data augmentation with various randomization schemes. These results verify the importance of semantic consistency for data augmentation to improve the traffic light detection.
Finding Flexibility with HyFlex: Teaching in the Digital Age

Teachers knew in the summer of 2020 that the next school year would be a new venture in education. After experiencing a rapid shift in delivery of their classes in the spring, teachers across the country sought the best ways to engage students meaningfully in a variety of modalities, knowing that shift might continue to happen in the coming year. As summer gave way to fall, teachers returned to their schools with great anticipation and a bit of uncertainty. Some teachers returned to their classrooms in a virtual environment with all of their students online. Others returned with all of their students in person. Still others returned with a blend:some students online and some students in person. For those classes that have a blend of online and in-person students at any given time, a flexible approach is needed, a hybrid-flexible or HyFlex model of teaching is the answer, particularly if the students have choice in how they attend and engage in class and they have access to the necessary technology (Beatty, 2019; Ferrero, 2020; Nave, 2020).
Towards Machine Translation for the Kurdish Language

Machine translation is the task of translating texts from one language to another using computers. It has been one of the major tasks in natural language processing and computational linguistics and has been motivating to facilitate human communication. Kurdish, an Indo-European language, has received little attention in this realm due to the language being less-resourced. Therefore, in this paper, we are addressing the main issues in creating a machine translation system for the Kurdish language, with a focus on the Sorani dialect. We describe the available scarce parallel data suitable for training a neural machine translation model for Sorani Kurdish-English translation. We also discuss some of the major challenges in Kurdish language translation and demonstrate how fundamental text processing tasks, such as tokenization, can improve translation performance.
A Database-Driven Algorithm for Building Top-k Service-Based Systems

The purpose of this work aims is to automatically build top-k (the number of suggested results) light weight service based systems (LitSBSs) on the basis of user-given keywords. Compared with our previous work, we use a s... | Find, read and cite all the research you need on Tech Science Press
ConvSVD++: A Hybrid Deep CF Recommender Model using Convolutional Neural Network

Recommender systems are powerful systems that give added value to business and corporation.They are relatively recent technology and they will only keep improving in the future.The most widely used algorithms for recommender systems are categorized into the traditional recommender and deep-based recommender system.The traditional recommendation algorithm suffers from sparse data that significantly degrades recommendation accuracy.The hybrid approaches are attempts to tackle recommendation challenges.This paper addresses the integration of deep learning into traditional recommendation approaches especially, Collaborative Filtering (CF) algorithms to get a significant accurate prediction.It proposes a hybrid deep CF recommender model called ConvSVD++ that tightly integrates Convolution Neural Network (CNN) and Singular Value Decomposition (SVD++).The proposed model incorporates items' content, implicit user's feedback along with explicit item-user interaction to enhance prediction accuracy and handle sparsity problem.The proposed model is evaluated and all baseline models based on Movielens-1M datasets.The results are evaluated using Root Mean Squared Error (RMSE) metric and it is concluded that the proposed model ConvSVD++ outperforms the baselines models.Accordingly, it is concluded that integrating CNN with SVD++ algorithm improves rating prediction accuracy.
YuQ: A Chinese-Uyghur Medical-Domain Neural Machine Translation Dataset Towards Knowledge-Driven

Recent advances of deep learning have been successful in delivering state-of-the-art performance in medical analysis, However, deep neural networks (DNNs) require a large amount of training data with a high-quality annotation which is not available or expensive in the field of the medical domain. The research of medical domain neural machine translation (NMT) is largely limited due to the lack of parallel sentences that consist of medical domain background knowledge annotations. To this end, we propose a Chinese-Uyghur NMT knowledge-driven dataset, YuQ, which refers to a ground medical domain knowledge graphs. Our corpus 65K parallel sentences from the medical domain 130K utterances. By introduce medical domain glossary knowledge to the training model, we can win the challenge of low translation accuracy in Chinese-Uyghur machine translation professional terms. We provide several benchmark models. Ablation study results show that the models can be enhanced by introducing domain knowledge.
Caveat Venditor, Used USB Drive Owner

USB drives are a great way of transferring and backing up files. The problem is that they are easily lost, and users do not understand how to secure or properly erase them. When used to store private and sensitive information, this constitutes a risk that users may be unaware of. Consider that people sell used USB drives online — presumably either their own or drives others have lost. This raises some interesting questions, such as whether sellers know how to ensure that private data is erased before they relinquish the drive to an unknown buyer, and whether sellers use these drives in an attempt to compromise an unwary buyer’s device. Governments do indeed issue advice about the risks of used mobile media, but we do not yet know whether this advice is reaching, and being heeded by, the general public. To assess the situation, a sample of used USB drives were purchased from eBay sellers to determine, first hand, what was on the drives. This acts as an indicator of actual security-related behaviors to answer the questions posed above. Using forensic analysis, it was found that a great deal of private and sensitive information remained on many of the drives, but there was no trace of malicious software. More effective ways of enlightening the public are needed, so that private data is not unwittingly leaked via sold used media.
Enhancing Barangay Justice System Through the Development of a Web-Based Crime Monitoring Module

A secure and harmless environment is a very much important aspect in promoting investment and economic growth. In a community in particular, peace and order has always been a pressing issue. In order to do the things, they need to survive, everyone should be able to feel safe all the times. Public safety officials are aware that protecting their people, their properties, and the environment as well as solving disputes are among of the utmost important responsibilities they need to perform. To be efficient in performing such functions, this study focused on the development of a Web-based Crime Monitoring Module, which enhances the barangay justice system through record keeping, and management of offenses in the community. The system provides a more effective way of monitoring offenses and blotter cases in the selected barangays that leads to better administration of peace-and-order. A crime-mapping scheme is integrated in the system by embedding a Google Map where the administrator can easily tag the reported crime or blotter case within the barangay. Through this, a crime hotspot can easily be determined. Waterfall Model was used for the design and development of the system. The model was used to emphasize on planning, scheduling of time, accomplishing target dates, budgets and implementation of an entire application. The system performance is proven satisfying and acceptable based on the result of Black Box Testing using Test Case method.
A Case Study on the Assessment of Program Quality through CO-PO Mapping and its Attainment

In recent years, accreditation of National Board of Accreditation has become mandatory for all the Autonomous colleges and Universities.NBA stresses on Outcome Based Education to improve the quality of education.It has formulated twelve graduate attributes to measure the quality of the program that a graduate has to acquire from any college/university during his four years of under graduation.The success of any program depends on the attainment of course outcomes and program outcomes.But there is a lack of understanding among the Engineering faculties in CO-PO attainment calculations.This study explores the significance of proper CO-PO mapping and its attainment calculation.CO-PO mapping and its attainment calculations are an integral part of OBE and it helps in continuous quality improvement, which serves as a feedback for OBE loop.CQI is instrumental in identifying any setbacks in Teaching Learning Process and additional solutions are figured out to improve the delivery of the course.In this study, different approaches are suggested to calculate the attainment of COs of the course and POs, PSOs of the program.Results and discussions are done on the attainment of COs of different courses and suggestions for the courses which fail to attain the target has been discussed.A sample of CO-PO attainment calculation for the course Basic Electrical Engineering offered for BTech I Year students has been discussed.Microsoft Office Excel spreadsheet has been used for computation purpose.