Reviewerly/exHarmony huggingface dataset:
Impact of Bilingualism on the Process of Learning a Foreign Language

Objective: This paper addresses the impact of being bilingual on the process of learning a particular foreign language. In other words, it seeks to illuminate the positive aspects of bilinguals over monolinguals while learning foreign languages. Based on several studies in the field of language acquisition, it has been revealed that bilinguals tend to be more experienced and capable than monolinguals by virtue of their rich linguistic and cultural repertoire that they possess.&#x0D; Methodology: A group of bilingual and monolingual students at the university were sampled to find out the effect of bilingualism on the process of learning foreign languages. Questionnaires along with some tests were the main instruments employed in the analysis so as to examine the primary discrepancies between bilinguals and monolinguals in the learning outcomes.&#x0D; Findings: The findings highlight and account for the positive impact of being bilingual. Implications: Being exposed to an array of linguistic interactions within society does contribute in the development of a positive capacity, ability, willingness and aptitude in learning a new language.
THAILAND STUDENTS’ DIFFICULTIES AND MOTIVATION IN STUDYING BIPA AT UNIVERSITAS MUHAMMADIYAH SUMATERA UTARA

This study was conducted to identify the difficulties, challenges, and motivations of foreign students studying Bahasa at the Universitas Muhammadiyah Sumatera Utara (UMSU). This research was conducted by taking data from 12 foreign students from Thailand who took part in the Bahasa Indonesia Bagi Penutur Asing (BIPA) program at UMSU as research respondents. Observations, questionnaires, and interviews were used as research materials to obtain data and analyzed using the descriptive qualitative method by looking at the percentage only. The results showed that there were several difficulties faced by BIPA students, including; difficulty pronouncing some phonemes in Bahasa; lack of time both in learning and practicing Bahasa; lack of confidence to speak Bahasa; challenging teaching materials, students’ cultural background; the different languages of the learners; and the lack of additional resources that can be accessed online. It was also found that the respondents had a positive attitude and high motivation when learning Bahasa. Further findings indicate that BIPA teachers’ role also motivates students to learn Bahasa. Overall, foreign students have a positive attitude and high motivation to learn Bahasa if they get encouragement and guidance from the teacher and the surrounding environment.
Tools Expert Choice Dalam Implementasi Metode Analytical Hierarchy Process (AHP) Untuk Penseleksian Kurir Baru

Westbike Messenger Service (WMS) is a company engaged in courier services in delivering packages for individuals and companies that use bicycles, but in the process of accepting candidates and courier selection with file collectors as requirements and direct interviews. To simplify the process, a decision system is needed to support the selection of new couriers using the Analytical Hierarchy Process (AHP) method, so that the results are obtained that the system built can be used by the WMS recruitment department according to the criteria required by several candidate names as an alternative to be calculated and obtained the best courier candidates to be accepted by the WMS company.
Multi-modal Object Tracking: Comparison and Prospective

RGBT tracking has recently attracted attention from researchers. As more and more scientists manage to improve model performance on this tracking field, this paper aims to introduce the advantage of using RGBT for visual object tracking, and summarize the recent accomplishments and milestones on this particular field. The paper covers all frameworks of RGB-T tracking algorithms. Finally, this paper also discusses the advantage and weakness of each paper. We hope the paper can help the beginners to recognize this area and provide a future prospective of multi-modal object tracking task.
Dual-Language Detection using Machine Learning

There are number of languages around the world and knowing all the languages is very difficult for any person. At the same time, unawareness about the language will hinder communication. Language identification is the process where the identifying the language(s) in text form is performed based on the writing style and looking at the unique diacritics of each language. When a multitude of languages are spoken in any circumstances, the first step in communication is the identification of the language. There are several techniques used for language detection like machine learning and deep learning. These are used in detecting languages like German. In India, numerous languages are spoken by the people and thus we propose to develop a model that detects two languages: Kannada and Devanagari/Sanskrit. In this study, Support Vector Machines classifiers were used, for classification and an accuracy of 99% was achieved.
Design and Implementation of a Rolling Hovercraft for Amphibious Locomotions

Environmental sampling and monitoring in the field are essential tasks for research and surveys. Enabled by the advancements of the robotic platform, aquatic and terrestrial tasks can be performed accordingly. For the tasks with both land and water area, multi-modal robots outperform mono-modal robots for their cross-domain locomotion ability between different media, and thus they can improve the exploration and monitoring coverage area. The challenges comprise actuators adaption in different working media, and the cross-domain locomotion efficiency. Therefore, this paper proposes a rolling hovercraft design and implementation to address the issues. For the actuators adaption in different environments, the proposed robot utilizes the same three ducted fans as its actuation system, and the ducted fans spin at high rotational speed in air to generate thrust in both land and aquatic mode. Besides, a cylindrical body hull works as a rolling wheel in land mode and as a floating hovercraft in aquatic mode. For locomotion efficiency, we implement a compact robot design with a proper allocation method of actuation units in land mode, aquatic mode, and the modes transition, which generalizes the actuators utilization efficiency. Specifically, for the land to aquatic mode transition, the center of gravity (COG) imbalance guarantees the actuation units above the water, and the robot works as a hovercraft. The prototype of the robots has been implemented, and the preliminary experiments verify its operations in cross-domain locomotion modes. The test trials ascertain our design objectives, and the results are promising for future field deployment and exploration or monitoring tasks.
Steady Tracker: Tracking a Target Stably Using a Quadrotor

Maneuvering target tracking of Unmanned Aerial Vehicle(UAV) in cluttered environments is a challenging issue owing to the unknown motion intention of the target and the complex moving environments. As the complexity of the environment increases, stable and secure target tracking is increasingly difficult to guarantee. To address the issue, this paper proposes a stable quadrotor tracking solution. The proposed solution contains two parts: target motion prediction and tracking path searching. The target motion prediction method predicts the future target motion based on the obtained target observations while considering observation noise and prediction errors. The tracking path searching method utilizes a sampling-based search method, using the homotopy of paths to ensure that the tracking path and the target position are in the same space. Finally, simulations, real-world experiments and statistical analysis verify the correctness and effectiveness of the proposed approach.
Emission Activity Parts Extraction using custom Named Entity Recognition

Carbon emission reduction is a worldwide priority. Businesses that refuse to change will face problems in the future. Reduced greenhouse gas emissions should be a key priority for every large, medium, or small firm. Governments also enforce many rules to control GHG emissions. Companies, on the other hand, tend to limit their carbon emissions. Collecting and keeping emission factors is a vital responsibility for every firm. A single business analyst (BA) or a small BA team is generally in charge of this. Collecting data about emission activities from various sources is a time-consuming effort for a business analyst, and it can sometimes be inaccurate. They usually capture emission data after the emission process has been finished for a more extended period, and most of these procedures are done manually. Therefore, there will be no real-time data on the organization’s emissions and no real-time data on the organization’s emissions. The solution of text input is implemented in a mobile application that takes the emission details from the employee’s text. From the text emission factors, named entity recognition techniques will be extracted. The extracted factors will be forwarded to the search system to search for emission factors and provide ranked results.
PENGGUNAAN METODE SIMULATED ANNEALING DAN TRILATERATION UNTUK OPTIMASI PENEMPATAN POSISI TITIK AKSES STUDI KASUS: KANTOR KESYAHBANDARAN DAN OTORITAS PELABUHAN (KSOP) KELAS 1 TANJUNG EMAS

Computer network technology is developing rapidly, and wired networks are being replaced by WiFi technology.&#x0D; The limitation of the WiFi coverage area is the main problem with this technology. Therefore, it is necessary to design for optimal placement of access points.&#x0D; This study analyzes the need for access point placement at KSOP Tanjung Mas Port, Semarang, where the need for internet connection via WiFi is very high.&#x0D; Simulation Annealing and Trilateration method is used in this study to determine the position of the access point. With the point blankspot method can be reduced.
Unhackable quantum Internet inches closer

Two groups have demonstrated device-independent quantum key distribution, which represents a major step towards secure quantum communication. Martijn Boerkamp explains
Protons may contain intrinsic charm quarks

A new machine-learning study could help to resolve a 40-year debate about the nature of the proton, but some physicists urge caution. Edwin Cartlidge reports
VLSI Implementation of Ternary Operand Binary Addition Using Parallel Prefix Adder for Area Efficiency

Cryptographic applications and pseudo random generator perform modular arithmetic three operand is the basic fundamental unit used in all these applications. For performing three operand additions, CSA (carry save adder) is one of the most widely used adders[5]. But in CSA in the final stage, carry is propagated which impacts the delay. Prefix parallel adders are therefore employed to get around this. The parallel prefix adders use more space even though performance in terms of latency is improved. Parallel prefix adders can also be used to build three operand adders. A brand-new, high-speed, and hardware-efficient adder technique is used to boost performance in terms of latency and area. This adder approach uses four stages to achieve three operand addition. Since Han Carlson adder is used in third stage, the suggested adder is not area efficient. To overcome this, in this paper we are replacing the Han Carlson parallel prefix adder with sklansky adder.
Method for Calculating the Particle Projection Area in Two-Dimensional Nanoscale Images using the Threshold Algorithms

The growing complexity of studying nanoscale images and meshing the results of experiments processing makes it necessary to automate this process to improve accuracy and reliability of the results obtained. As part of the ongoing research, a method was developed to determine automatically the particles area in the electron microscope images. The threshold algorithm and its modification was considered to identify particles in the nanoscale images. Block matching and 3D filtering algorithm was selected for preprocessing. The optimal sequence of the above algorithms for images application was obtained in order to solve the problem. Several threshold algorithms and methods for calculating the corresponding threshold values were considered forming the base to select the most appropriate algorithms in the context of the problem being solved. The above method resulted in determining dependence of the particles number on their area for each given image. Currently, quite large and constantly growing volumes of nanoscale images were accumulated, which leads to a need to automate the research process. The proposed method is intended to solve practical problems in determining the particles area in the nanoscale images and could be used at various stages of the experiment
Radio Modulation Classification Using Deep Residual Neural Networks

We propose a new deep residual network for Automatic Modulation Classification, OPResNet-18. It achieves state-of-the-art accuracy on the RadioML 2016.10a data set. We train the proposed model and other state-of-the-art networks with augmented data by adding a Carrier Frequency Offset (CFO). We find that the previously proposed IQNet-3 is robust to CFO. We demonstrate that this robustness allows the performance of IQNet-3 to be further improved through data augmentation in contrast to existing neural networks that cannot handle CFO. Finally, we provide evidence that standard data pre-processing techniques for time-domain data that reportedly perform well in many domains do not perform as well as a simple alternative, the outer product, in the IQ domain.
Investigating the Effect of BD-CRAFT to Text Detection Algorithms

With the rise and development of deep learning, computer vision and document analysis has influenced the area of text detection. Despite significant efforts in improving text detection performance, it remains to be challenging, as evident by the series of the Robust Reading Competitions. This study investigates the impact of employing BD-CRAFT – a variant of CRAFT that involves automatic image classification utilizing a Laplacian operator and further preprocess the classified blurry images using blind deconvolution to the top-ranked algorithms, SenseTime and TextFuseNet. Results revealed that the proposed method significantly enhanced the detection performances of the said algorithms. TextFuseNet + BD-CRAFT achieved an outstanding h-mean result of 93.55% and shows an impressive improvement of over 4% increase to its precision yielding 95.71% while SenseTime + BD-CRAFT placed first with a very remarkable 95.22% h-mean and exhibited a huge precision improvement of over 4%.
Substation Project Evaluation Model Based on Coefficient of Variation And Fuzzy Comprehensive Evaluation

Aiming at the problems of single traditional index, fuzzy evaluation result and subjective index weight in evaluating the investment benefit of substation project, a substation project evaluation model based on coefficient of variation and fuzzy comprehensive evaluation is constructed. First of all, this paper constructs a more perfect evaluation substation project investment index system from four dimensions: project maturity, project rationality, project effectiveness and investment construction environment. Furthermore, a combination weighting method based on coefficient of variation is proposed and introduced into the calculation of fuzzy comprehensive score, and the necessity model of power grid project investment is established. Finally, an example analysis is carried out for the 35kv project put into production in a certain province, and it is verified that the weighting method and evaluation model proposed in this paper can reasonably and effectively quantify the investment benefit and necessity of the evaluated substation project, which is practical in promoting the lean investment of the substation project.
Evaluation and Improvement of User Interface for Online Passport Service Application using User Centered Design Approach

The Indonesian Directorate General of Immigration launched an online passport service application in early 2019 to make people queue for passport documents more efficiently and quickly. After being available in Google Play and App Store, several issues appeared on its user interface by distributing an online questionnaire to identify User Interface/User Experience (UI) problems with this application. The preliminary evaluation results indicated that the existing online passport service application designs received below-average results, indicating that the current design should be improved. This research performed the User-Centered Design technique to design and develop the improved UI/UX design by analyzing user needs. The results of the UEQ method evaluation for new designs revealed that the overall average value has increased. This research generated a new UI/UX design where these dimensions' scores were increased: Attractiveness (−0.24 to 1.63), Perspicuity (0.27 to 1.63), Efficiency (−0.18 to 1.75), Dependability (−0.30 to 1.75), Stimulation (0.11 to 1.77), and Novelty (−0.59 to 1.45). Therefore, this research solved the UI/UX issues to enable user satisfaction and meaningful experience by implementing the User-Centered Design approach.
Design of Counterdevice of Computer Intelligent Control Technology for Teaching Athletic Training

Athletics, as a diversified and flexible athletic sports, is also an important basis for all sports. With the continuous development of modern science and technology, in the process of athletic training through the rational application of technological elements, especially computer intelligent control technology, targeted application strategies can be constructed with its advantageous features to ensure the effectiveness of athletic training work, but also to enrich the modern sports training model, so as to promote the long-term development of the sports industry. Therefore, in this paper, according to the characteristics of sports training, and then combined with computer intelligent control technology, the overall design of the sports training control integrated system and the design plan of the countermeasure device were developed, and a hierarchical planning approach was used to propose an optimal way of sports training program.
Structured Multimodal Fusion Network for Referring Image Segmentation

Referring image segmentation aims to segment one particular object referred by a natural language expression in the image. One major challenge of this task is how to understand and align vision and language to distinguish the referent. Another major challenge is how to refine the segmentation mask of the referent. In this paper, we focus on dissecting and enhancing the interaction between modalities to address these challenges. Specifically, we propose a Structured Multimodal Fusion Network (SMFN), which consists of a multimodal tree, a cross-modal transformer, and a mask refinement module. SMFN first exploits multimodal fusion structures to deeply integrate visual and linguistic features so that the referent can be accurately distinguished and then further utilizes a mask refinement module to aggregate multi-scale visual features to clarify boundaries. We conduct extensive experiments on the four benchmark datasets and achieve new state-of-the-art performances under different evaluation metrics.
Search-Efficient NAS: Neural Architecture Search for Classification

Recently, there has been an increasing trend in automating the process of NAS. Most SOTA approaches required higher computational costs and hardware. Among all methods, the Differentiable Architecture Search (DARTS) made the automating process available within a few GPU days. However, the performance of DARTS is observed to struggle with memory issues and often collapsed when used a larger number of epochs while searching architectures. To overcome the issue of memory overhead and longer search time, the paper proposes a method by sampling the selected channels only, which not only reduces the redundant operations but will also minimize the search time. This method has reduced the GPU search hours drastically to 6.3 hours as compared to DARTS.
An Automatic Method of Constructing Readability Corpus for International Medical Chinese Teaching

Since the beginning of the Medical Chinese (MC) course, Medical Chinese textbooks have been compiled since the 1960s, and now it has experienced 60 years of development. As the support of Medical Chinese teaching, the research on the teaching content and teaching difficulty of Medical Chinese textbooks has become an important topic to improve Medical Chinese teaching, help foreign students enter the medical major as soon as possible and smoothly carry out medical practice. Therefore, it is necessary to further intervene the results of Repeated bisection clustering (RBC) clustering in order to improve the scientificity of the construction of Medical Chinese readability corpus. After using RBC to divide the corpus into six categories, our method uses Hanyu Shuiping Kaoshi (HSK) vocabulary and Medical Chinese Test (MCT) vocabulary to measure the proportion of words at all grades in the text. Practice has proved that the method of creating Medical Chinese readable corpus is effective.
Extending Graph Databases With Relational Concepts

Today we have to deal with large amounts of data, and for large amounts of interconnected data, graph databases represent an excellent choice. However, some concepts that are used in relational databases are still not supported in graph databases, and this could hinder their wider use. In this article, how relational database concepts have been successfully transferred into graph databases, including integrity constraint support, inheritance, trigger specification, new visual query languages, etc., is demonstrated.
Cybercrime Insurance Is A Protection Tool Of The Society: An Analytical Study

Despite the increasing awareness of cybercrime, there are many people who are still not sure what it is. Cybercrime is a criminal activity that is committed using computers or the internet. It can include anything from hacking and identity theft to fraud and child pornography. With the rise of technology, cybercrime has become one of the most common forms of crime. According to a report by Norton, a cyber-security company, there were 4.1 billion records breached in the first six months of 2019 alone. And the rate of cybercrime is only increasing. The same report stated that the average cost of a data breach globally was $3.86 million in 2018, which is up 6% from the previous year. During the duration of the Pandemic of Covid-19 most, most of the cyber-crimes increased by around five hundred times is stated by Chief of Defence Staff (CDS) General Bipin Rawat in a discussion with the Hindu Newspaper reporter in Nov. 2021. With the growing rate of cybercrime, many businesses are starting to purchase cybercrime insurance. Cybercrime insurance is a protection tool that businesses can use to financially protect themselves in the event of a data breach or other type of cyber-attack. In this research paper, we will explore the need for cybercrime insurance and how it can help businesses recover from a cyber-attack. We will also look at some of the challenges that businesses face when it comes to purchasing such insurance.