Reviewerly/exHarmony huggingface dataset:
Gaming on an Immersive Virtual Reality Platform to Ameliorate the Level of Anxiety in Patients Undergoing Congenital Heart Disease

The double outlet right ventricle (DORV) is an unusual cardiovascular abnormality that is present at birth. The pulmonary artery and the aorta, the cardiovascular system's two major arteries, link to the right ventricle in the DORV. The coronary artery links to the right ventricular, while in an ideal heart, the aorta connects to the left ventricle. DORV is an issue as the right ventricle delivers blood that is low in oxygen, subsequently distributed all around the human being. DORV is always connected with a further cardiac ailment known as a ventricular septal defect (VSD). Behavioral issues are quite prevalent in children. Emotional-obsessive-compulsive disorder, sadness, stress, social fear, and developmental problems are among them. Virtual reality (VR) is a stimulating experience that uses position tracking and three-dimensional (3D) near-eye presentation to give the participant a realistic view of a virtual environment. VR applications involve enjoyment (especially video games). A nine-year-old female complained of a tingling sensation over her right palm. She also had right-side weakness and convulsions, which were restricted to the dominant side. After investigation and evaluation of the condition, it is a known case of congenital heart defects and was planned for surgical correction. The study aims to provide information on an instance of DORV, transposition of great arteries, VSD, and pulmonary stenosis with resolved brain abscess by giving VR video games to reduce anxiety in patients undergoing an operation.
Aplikasi Sistem Pakar Berbasis Android dengan Metode Certainty Factor untuk Mendiagnosis Penyakit pada Tanaman Karet

Rubber is an important plantation commodity as a source of income, employment and foreign exchange opportunities, as an engine of economic development in new centers within the rubber plantation environment. Rubber plant diseases generally cause economic losses to rubber plantations. Lack of knowledge of farmers to control rubber plant diseases can result in losses and ultimately reduce farmers' income. Therefore, it is necessary to build a system that can diagnose diseases like an expert or an expert. The method used in this system is the certainty factor method which is used to prove whether a fact is certain or uncertain. This method is very suitable for expert systems that diagnose uncertainty. After that, a system validity test is carried out which aims to test the ability of the expert system to identify diseases. Based on the test results, the highest disease score was tapping groove disease with a disease percentage of 94.96%, while the lowest disease percentage was red root fungus disease with a percentage of 79%, with an average test result above 75% so that it was concluded that the system can diagnose rubber plant diseases well in accordance with the results of the diagnosis obtained.
Sistem Informasi E-Campaign Pemilihan Kepala Desa Berbasis Website

Campaign are activities carried out to gain public support for potential candidates and convince them to vote for the candidate. Lack of information about the campaigns carried out by the candidates, the dissemination of information through online media. E-campaign is defined as the use of technology by prospective candidates in attracting public trust and assisting in the democratic process. The village head election e-campaign information system was built to help the community get correct information about candidates, make it easier for candidates in the campaign process and the process of collecting village head election requirements data, and make it easier for administrators to collect village head election requirements data. The system development uses the PHP programming language and the Laravel framework. The system development methodology uses the waterfall method. The waterfall method has 5 stages, namely communication, planning, modelling, construction, and deployment. System testing is done by black box testing and User Acceptance Testing (UAT). The results of the black box testing that have been carried out on the test class are presented successfully or unsuccessfully. The results of the User Acceptance Testing (UAT) that have been carried out have obtained a percentage of 81.2% which can be concluded that the e-campaign information system from user perceptions is very good.
Analisis Visualisasi Data Prestasi Mahasiswa Universitas Lampung Menggunakan Tableau

This research focuses on visualizing student academic and non-academic achievement data for the years 2018, 2019, 2020, as well as data related to the 2020 MBKM program at the University of Lampung. The data is processed using Tableau software, allowing for the examination of visual patterns in achievement data based on key attributes, including types of achievements, participants categorized by faculties, and achievement levels classified into three categories: international, national, regional, and provincial achievements. Tableau Public Tools is a software application used for analyzing and presenting data sets to support decision-making processes and assist in organizational data analysis. The output produced using Tableau is presented in the form of a visual dashboard, presenting pre-defined attribute data. This dashboard offers valuable insights and graphical representations of achievement attribute data, which can be utilized for evaluating achievement data by BP2M staff and capturing the interest of the University of Lampung community.
Challenges and Strategies of Teachers in Integrating Canva in English Classroom Teaching

Information Communication Technology (ICT) has been applied and integrated into education that enhances teachers to explore various teaching and learning strategies, materials, and media. This study aims to discover the experiences of English teachers in the use of Canva, an ICT application, to create an attractive presentation of teaching English. The researchers employed Generic Qualitative Research to investigate the challenges and strategies in using the application. The researchers interviewed two English teachers responsible for teaching English at the high school, junior high school, and elementary school levels at the SMART Indonesia Pekanbaru. The instruments used in this research were interviews and documentation. To analyze the data, the researchers transcribed the interview and employed thematic analysis by identifying patterns or finding themes in the interview data. The researchers found two challenges the teachers faced in the research findings: low internet connectivity and the limitation of templates availed in the free version Canva application. In the meantime, to cope with the challenges, the teachers used two strategies, providing learning modules and adding pictures for an attractive appearance. In advance, the researchers found that the teachers benefitted from Canva's application in English classroom teaching. In conclusion, though English teachers experience challenges with the Canva application, they can anticipate them and benefit from using the learning application for teaching English.
Data-Driven Modeling of Human Development Index in Eastern Indonesia's Region Using Gaussian Techniques Empowered by Machine Learning

The Human Development Index (HDI) is a statistical measure used to measure and evaluate the progress and quality of human life in a country. For the Government of Indonesia, HDI is important because it is used to create or develop effective policies and programs. In addition, HDI is also used as one of the allocators in determining the General Allocation Fund. The 2022 HDI data released by BPS shows that there has been an increase in the HDI in each district/city over the last 12 years, including in the regions of Eastern Indonesia. High and low HDI values are influenced by several factors, and there are indications that there is spatial diversity where surrounding areas tend to have HDI levels that are not far from the area. The Geographically Weighted Regression method is used in this study because it takes into account spatial aspects. However, the GWR model must be built repeatedly if there is regional expansion. Therefore, a GWR model that applies machine learning methods is needed where the model is built and tested using different datasets, namely training data and test data, so that the model can predict new data better. The results obtained are that the GWR model with test data has a better R-Square value when compared to the GWR model previously trained using training data, which is 0.9946702, based on the linear regression model shows the results that the most influential factor on HDI in Eastern Indonesia is expected years of schooling (X2).
Development of English Learning Media Using Adobe Animate in the Material Pronoun

To interact with others around the world and to learn a foreign language, English is used. In Indonesia, English is taught as a foreign language in schools. So, teachers need a media to teach English. Media and software platforms like Adobe Animate (formerly known as Macromedia Flash and Shockwave Flash) enable the creation of various types of multimedia content including vector graphics and animation. The purpose of research is to know the development of English learning media using adobe animate in the material of pronoun at seventh grade students of junior high school. The research method used Research and Development or commonly known as R&amp;D. This research was tested on the seventh grade students’ as population at MTs Muhammadiyah 02 Pekanbaru. The sample was taken from a class in the seventh grade which total of 36 people. The research was carried out in June 2022, at the MTs Muhammadiyah 02 Pekanbaru. Based on the research result, it can be concluded that the learning media developed has successfully undergone alpha and beta testing to determine its feasibility. It can affirm that the application of English learning media in the material Pronoun using adobe animate android-based software is suitable for use by students in learning. The average pretest result of was 6,2. Then the average post-test result was 7,9. Based on Figure 4, it can be seen that the gain score is 0,70. The value is based on the classification of the gain value is in the high classification.
Promotion of Modern Tourism in Lampung Province with the Scaffolded Reading Method in the New Normal Era

In the midst of the COVID-19 outbreak, learning activities became online, resulting in a change in the teaching system. In English, there are several skills that are usually done face-to-face, but due to the covid-19 outbreak, all learning is done online. Ideally, reading skills should be done face-to-face. Of course this is a concern for lecturers in determining learning methods, so that online-based learning outcomes can represent offline learning in a balanced way. In addition, students can also be well facilitated during the learning process like face-to-face learning. The second concern arose because researchers saw a fairly large impact due to the Covid-19 outbreak, especially in the field of tourism. Lampung Province has a lot of contemporary tourism potential that can be a regional and national asset. Since the outbreak of Covid-19, tourism potential has weakened and is getting worse. The purpose of this study is to improve reading skills, increase understanding of the current tourism potential of Lampung Province, and promote the current tourism potential of Lampung Province in the English Club community of Universitas Muhammadiyah Lampung in the new normal era. This study uses a quantitative approach. The method used is Quasi Experimental design. The steps taken include: 1) giving a pre-test several times; 2) provide treatment; 3) give a pot-test several times.
Penggunaan Metode Simple Additive Weighting dalam Sistem Pendukung Keputusan Evaluasi Potensi Pegawai di SMK Negeri 2 Bandar Lampung

This research was conducted to build a decision support system for employee potential assessment at SMK Negeri 2 Bandar Lampung using the Simple Additive Weighting (SAW) method. Decision support system is made web based with 3 actors namely admin, employees and leaders. The data used comes from the Employee Work Target (SKP) data at SMK Negeri 2 Bandar Lampung. The selection process is done by collecting employee data and employee performance values along with the criteria used. The data received is processed by the system by determining the priority of each criterion and doing the sum of the weights of each criterion value. The results of functional testing in the SPK Employee Potential Assessment is a compatible system on the computer being tested and all menus on the system are running well. The results of testing the system using Black Box Testing using 20 data employees of SMK Negeri 2 Bandar Lampung. The conclusion of this research is that the Employee Potential Assessment Decision Support System can help the Head of SMK Negeri 2 Bandar Lampung to conduct a performance evaluation of employees with 100% accuracy. Thus, the SAW method is appropriately used in the Employee Potential Assessment Decision Support System.
Trends of Academic Publications: A Case Study of Malaysian Research Universities

The Ministry of Higher Education Malaysia granted five universities with Research University (RU) status, which are Universiti Malaya (UM), Universiti Putra Malaysia (UPM), Universiti Kebangsaan Malaysia (UKM), Universiti Sains Malaysia (USM), and Universiti Teknologi Malaysia (UTM). These RUs are expected to focus on research and innovation and become a model of Malaysian universities for research activities aimed at knowledge advancement. Publications are one of the performance indicators for RUs. Thus, this paper confined its scope to the publications produced from 2016 to 2020 by the five RUs. The study aimed to analyse the patterns related to the number of publications, subject areas, type of publications, international joint publications, and the language of the publications. The findings show that the number of publications increased for UPM, UKM, and USM over five years, while UTM champions four subjects: Engineering, Materials Science, Computer Science, and Environmental Science. Journal articles are the most prominent scholarly output for all RUs. All RUs actively collaborate with international scholars and use English as the primary language for publications.
Object-Directory Mapping

Enterprise Java developers employ object-oriented (OO) techniques to create modular, complex applications. In the OO paradigm, objects are central to the system and represent entities in the real world. Each object has an identity, state, and behavior. Objects can be related to other objects through inheritance or composition. On the other hand, LDAP directories represent data and relationships in a hierarchical tree structure. This difference leads to an object-directory paradigm mismatch and can cause problems in communication between OO and directory environments.
Invariance Principle and the Asymptotic Behavior of T-S Fuzzy Systems

In this paper, the asymptotic behavior of nonlinear systems is studied by means of a T-S fuzzy system, which exactly represents the nonlinear system in question, and the extended Invariance Principle. An important feature of the proposed approach is the exhibition of conditions to estimate the attracting invariant set in terms of LMIs.
Investigating the Impact of Business Development Fund Ltd's Credit Guarantee on Small and Medium Enterprises in Rwanda: A Comprehensive Analysis

In Rwanda, the Business Development Fund Ltd aims to support the initiation, growth, and success of Small and Medium Enterprises (SMEs) by providing credit guarantees, facilitating their access to bank financing. This study explores the efficacy of the credit guarantee fund in stimulating SME growth in Rwanda, particularly within Kigali City. It delves into the accessibility of the BDF Ltd credit guarantee fund for SMEs, assesses its correlation with employment generation, evaluates its influence on SMEs' sales turnover, and analyzes its responsiveness to borrower demands from 2011 to 2013. Employing an explanatory research approach, this study employs a mixed-methods approach, combining qualitative and quantitative methodologies for data collection. A sample of 98 units was selected, utilizing interviews for primary data and document analysis for secondary data. Statistical analysis, including SPSS and tools like Kendall's tau correlation and regression analyses, was employed to scrutinize the relationship between various variables. The findings indicate significant hurdles faced by SMEs in Kigali in accessing the fund, with 95.2% of respondents citing challenges such as prolonged application processes, increased collateral requirements, low bank utilization of the fund, additional bank prerequisites, and perceived inequities. The research reveals a noteworthy positive relationship (r = .37, p &lt;.05, one-tailed) between the guaranteed amount for SMEs in Kigali and employment creation, where an estimated 3,333,333 RWF guaranteed amount predicts the creation of an additional job. Moreover, the study underscores that credit guarantees contribute positively to the beneficiaries' sales turnover and notes that the BDF Ltd has effectively met borrower demands during the 2011-2013 period. This research presents a comprehensive analysis of the impact of credit guarantee funds on SME growth in Rwanda, shedding light on challenges faced by SMEs in accessing these funds and highlighting the fund's substantial role in fostering employment and bolstering sales turnover within the SME sector. Keywords: Business Development Fund Ltd, SMEs, Credit guarantee fund, Kendall's tau correlation, Banks.
DFENet: Double Feature Enhanced Class Agnostic Counting Methods

Object counting is a basic computer vision task, which can estimate the number of each object in an image, thus providing valuable information. In dense scenes, there are huge differences in target individual scale, and the different target individual scale leads to low accuracy of target count. In addition, most of the existing target count datasets in the field require a lot of manual creation and annotation, which increases the cost and difficulty of the dataset, lack of ease of use and portability. To solve these problems, this paper proposes a class agnostic counting method Double Feature Enhancement Net based on improved Bilinear Matching Network+ (BMNet+). By introducing the feature enhancement module based on the principle of conditional random field and the adaptively spatial feature fusion module, combined with the feature similarity measurement strategy of bilinear matching network, the method can effectively extract the target features of different scales, enhance the adaptability to the targets with large scale changes, and improve the counting performance of the network. Experiments were carried out on FSC-147 data set, and the experimental results show that the proposed model has been further improved in counting accuracy. The MAE and MSE of the verification set are 15.03 and 54.53 respectively. In the test set, MAE reaches 13.65, MSE reaches 89.54, and the counting performance is at the advanced level in the field.
AENet: attention efficient network for cross-view image geo-localization

&lt;abstract&gt;&lt;p&gt;To address the problem that task-irrelevant objects such as cars, pedestrians and sky, will interfere with the extracted feature descriptors in cross-view image geo-localization, this paper proposes a novel method for cross-view image geo-localization, named as AENet. The method includes two main parts: an attention efficient network fusing channel and spatial attention mechanisms and a triplet loss function based on a multiple hard samples weighting strategy. In the first part, the EfficientNetV2 network is used to extract features from the images and preliminarily filter irrelevant features from the channel dimension, then the Triplet Attention layer is applied to further filter irrelevant features from the spatial dimension. In the second part, a multiple hard samples weighting strategy is proposed to enhance the learning of hard samples. Experimental results show that our proposed method significantly outperforms the state-of-the-art method on two existing benchmark datasets.&lt;/p&gt;&lt;/abstract&gt;
Indistinguishability-assisted two-qubit entanglement distillation

Abstract Production of quantum states exhibiting a high degree of entanglement out of noisy conditions is one of the main goals of quantum information science. Here, we provide a conditional yet efficient entanglement distillation method which functions within the framework of spatially localized operations and classical communication. This method exploits indistinguishability effects due to the spatial overlap between two identical qubits in distinct sites and encompasses particle statistics imprint. We derive the general conditions for the maximum entanglement distillation out of mixed states. As applications, we give a thorough description of distilled entanglement and associated success probability starting from typical noisy states, such as thermal Gibbs states and Werner states. The influence of local temperatures and of noise parameter is discussed, respectively, in these two cases. The proposed scheme paves the way towards quantum repeaters in composite networks made of controllable identical quantum particles.
Hypersonic snake maneuvering target detection algorithm in complex electromagnetic environment

The track before detect technology based on Hough transform is an effective method for hypersonic target detection, but this method requires the target to move as linearly as possible. In practice, hypersonic targets often generate significant maneuvers during flight, such as “snake maneuver” where the accumulated values from the previous time will have a notable impact on the accumulated values at the current time. Aiming at this issue, this paper proposes a recursive accumulation method based on attenuation factor. By setting an attenuation factor with a value less than 1 and using time difference as the power of the attenuation factor, the accumulated value at the previous time is weakened, ensuring that the accumulated value at the previous time can be accumulated while reducing its impact on the current accumulation. At the same time, it avoids the computational burden caused by the continuous deletion and addition of measurement point information in the original recursive method, which has certain application prospects.