Reviewerly/exHarmony huggingface dataset:
PARALYSIS PATIENT AND PHYSICALLY DISABLED PERSON MONITORING USING SIGN LANGUAGE AND VOICE PLAY

This paper presents an overview of a monitoring system designed specifically for paralysis patients and physically disabled individuals, leveraging the power of sign language and voice play using Raspberry pi Pico and Arduino UNO.Paralysis patients and physically disabled individuals often face significant challenges in communication and independence.The objective of this system is to enable effective communication, enhance independence, and ensure the safety and well-being of the monitored individuals.The proposed system utilizes a combination of sign language recognition and voice modulation techniques to bridge the communication gap between patients and caregivers.Sign language recognition algorithms analyze hand gestures and movements, converting them into corresponding text or audible prompts.Additionally, voice modulation technology enables patients to convey their emotions and intentions through synthesized speech.By integrating these two technologies, caregivers can better understand and respond to the needs of patients, enabling more effective communication and care.The system can provide real-time feedback, allowing for immediate adjustments and interventions as necessary.Moreover, remote monitoring capabilities can be incorporated to extend the reach of the system, facilitating long-distance caregiving.
Detection of Social Bots in Twitter Network

One of the most well-known and widely utilized social networking sites is Twitter. Social Bots are automated Twitter accounts that mimic human behavior and attempt to interact and communicate with real users in order to further nefarious objectives. For the integrity of online dialogue, Twitter needs to identify and eliminate social bots. Twitter Bot detection is modeled as a binary classification problem. Given a set of user accounts, our goal is to build a classifier that categorizes each account as either Genuine or Bot. In earlier studies, researchers have created ways to identify social bots. The use of supervised approaches has been suggested, in which DNA-based features are obtained from tweets using 3 letters A, C, and T-DNA encoding given as input to the Logistic Regression models. To categorize each account as Bot or Genuine, we proposed a hybrid approach using Extreme Gradient Boosting (XGBoost) [1] as a classifier that uses Sentiment Features from Sentiment Analysis, DNA-based features from the approach of DNA encoding given by Pasricha et al. [2] and profile-based features from Yang et al. [3]. Cresci-17 dataset [4] and the more recent and huge dataset TwiBot-20 [5] are taken into consideration for this study. Our model performs better on both the data sets, and especially on the challenging TwiBot-20 [5] dataset, our proposed model obtains an accuracy of 82.3% over 80.6% obtained by Yang et al. [3].
LANGUAGE LEARNING APP

Android language learning apps have the potential to transform the way languages are learned.This study examined the fifty most popular commercially available language learning applications for android phones and evaluated them according to a wide range of criteria.Three major trends were found: first, apps tend to teach vocabulary in isolated units rather than in relevant contexts; second, apps miniAndroid Development adapt to suit the skill sets of individual learners; and third, apps rarely offer explanatory corrective feedback to learners.Despite a pedagogical shift toward more communicative approaches to language learning, these apps are behaviorist in nature.To better align with Second Language Acquisition (SLA) and L2 pedagogical research, we recommend the incorporation of more contextualized language, adaptive technology, and explanatory feedback in these applications.Now learning a new language has always been an exciting prospect and today more and more people are keen on learning new languages as they're traveling more and more.And while earlier people had to attend physical classes for the same, today learning languages is possible even while sitting in the comfort of homes owing to the technology.There are many language learning android apps out there helping students all around the globe gain expertise in another language they are keen on learning, be it French, Italian, Spanish, Chinese, or Mandarin.
Analysis of Middle School English Teaching Mode Based on Teaching Situational Method under the Background of New Curriculum

With the development of globalization, the society's requirements for English ability are constantly improving.In English teaching, the golden stage of students' ability development is this stage of middle school learning.Therefore, if we can make middle school English teaching more efficient, we can effectively improve middle school students' English learning level.At present, with the deepening of the new curriculum reform aimed at developing students' subject literacy, teaching methods are increasingly diversified.Among many teaching methods, situational teaching method attracts people's attention, which plays a positive role in mobilizing students' enthusiasm and emotion, and can effectively improve teaching quality.Based on the implementation of situational teaching method in middle school English teaching, this paper discusses how to implement situational teaching method in English teaching and promote the cultivation of middle school students' English core literacy.English teaching in middle schools plays an important role in promoting students' comprehensive quality and ability.The application of situational teaching method in middle school English teaching can effectively stimulate students' interest in learning English, improve their enthusiasm for learning English, and let students experience situational teaching personally; It can also help students discover the charm of English and cultivate their love for English learning.
Research on the Construction of Professional Competence of University Librarians in the Era of Artificial Intelligence

Artificial intelligence is an important feature and development trend of today's era, which has had a profound impact and challenge on various industries, including libraries as important institutions of knowledge service.The application of artificial intelligence technology provides new opportunities and possibilities for libraries, and also puts forward new requirements and expectations for the professional competence of librarians.Starting from the challenges and opportunities faced by librarians in the era of artificial intelligence, this article analyzes the connotation and composition of the professional competence of librarians, explores the goals, contents and approaches of professional competence construction for librarians in the era of artificial intelligence, and aims to provide references for improving the professional quality and service level of librarians and promoting the innovative development of library services.
The cultivation of core competencies in disciplines in large unit teaching design

Core literacy refers to the integration and transcendence of thinking, knowledge, abilities, methods, skills, emotional attitudes, values, etc. beyond the original point structure, and its performance in real and complex problem situations.Core literacy has characteristics such as comprehensiveness, integration, and practicality, making it difficult to cultivate through a single knowledge topic or learning method.How to build a bridge, establish a close connection and process channel between knowledge and literacy, classroom and literacy, teaching design and literacy?Large unit teaching has clearly become one of the best methods currently available.This study systematically introduces the design process and key points of large unit teaching to cultivate core competencies in the discipline.It is hoped to form a structured synergy of large unit teaching, open up new ways to implement core competencies in the discipline, and promote traditional courses to make great strides towards integrity and innovation.
The Construction and Practice of the High-Quality Online Open Course "Advanced Mathematics" under the Background of New Engineering

Under the background of new engineering, the goal of talent training has been repositioned, and the new teaching concept has highlighted the important position of Advanced Mathematics in engineering majors, and has played an important role in promoting teaching reform, improving teaching quality, and broadening teaching channels.The measures of curriculum construction and practice include curriculum planning, construction concept, teaching design, development of teaching resources, and establishment of assessment mechanism; Through the establishment of operational mechanisms such as organization and implementation, technical support and optimization evaluation, we can ensure that the best online open courses can bring maximum benefits.
SLA4OAI-Analyzer: Automated Validation of RESTful API Pricing Plans

Nowadays, public web APIs are considered as business assets by many organizations. They provide data and functionality which other developers can integrate within their own services. These APIs are commercialized through pricings, which include a series of plans. Each plan contains features and limitations, coupled with a price. Developers who wish to use the API need to choose which plan better suits their needs. The formal description of pricings is not standardized, which hinders the ability to automate their analysis. The SLA4OAI specification aims to provide an extension for OpenAPI that allows pricings to be described. This specification paves the way for an ecosystem of tools that leverage the information of a pricing. In this paper, we present SLA4OAI-Analyzer, a public API that automatically checks an SLA4OAI specification file for conflicts at different levels. We also provide an online Jupyter notebook to validate the API using different examples.
Breast Cancer Classification using Neural Networks

Abstract: Breast cancer is a significant health issue affecting women worldwide, emphasizing the importance of early detection and accurate tumor classification. This research paper proposes a neural network-based breast cancer classification model. The dataset is collected, preprocessed, and used to train the neural network model. The performance of the model is evaluated, and its potential application in clinical settings is discussed. The results demonstrate the model's effectiveness in accurately classifying breast cancer tumors.
RANCANGAN PLTS ATAP GEDUNG GEREJA METHODIST INDONESIA MANNA HELVETIA

Indonesia have potential sunshine over year, it makes indoensia has a large source of renewable energy. However, renewable energy usage is very low. One of the renewable energy is solar power plants (PLTS). Medan City is one of the highly populated cities and it makes Medan city very limited land to build PLTS, and the solution is to build rooftop PLTS. Therefore, this research discusses the planning of PLTS on the roof of the Manna Helvetai Indonesian Methodist Church Building. The design of this PLTS is simulated using the Helioscope simulator. Solar modules are installed as many as 35 pieces and have 1 inverter with a capacity of 20 kW and produce potential energy of 15.8 kWp. Based on the results of the rooftop solar power plant design and the results of the calculation of electrical energy production, it can be analyzed that the economic development of rooftop solar power plants is considered feasible because it meets the criteria of Net Present Value (NPV) greater than zero, namely Rp 44,638,904 and Benefit-Cost Ratio (B-CR) greater than one, namely 1.19 and Discounted Payback Period (DPP) which is reached at the life of the solar power plant.
Knowledge Management, Right to Access Public Information, Governance, Open Government, E Government, Public Administration

ABSTRACT The study develops a theoretical model to explain the financial behavior of immigrant communities. In the study, two key financial behavior models (Financial Health Model by Huston (2015) and Conceptual Model of Young Adults’ Financial Capability by Serido et al. (2013) are leveraged in developing a ‘New Proposed Conceptual Model of Immigrant Financial Behavior’. This new proposed model, which has been leveraged and validated in the present study, combines key variables of the two above mentioned existing models and introduces cultural factors, which has been non-existent in the earlier models, but which is critical to managing financial behavior, especially for a culture-sharing group. Keywords Financial behavior, remittances, immigrants, and culture
Simulation of motion planning control of Ackerman intelligent vehicle based on ROS

The vehicle kinematics model based on Ackerman principle has a wide range of applications in the field of unmanned driving, and the motion planning control of autonomous mobile intelligent vehicles is of great significance for the research of unmanned driving. In this paper, the robot operating system (ROS) is used as the development platform to establish the simulation model of Ackerman intelligent vehicle, and the three-dimensional physical simulation software Gazebo is used to build the simulation environment. The improved rapid expansion random tree (RRT) algorithm is used as the global path planning algorithm, and the TEB algorithm is used for local path planning to complete the simulation verification of the motion planning and control of the Ackerman smart car. The simulation results show that the improved RRT algorithm can obtain the optimal global path, and its search efficiency and path smoothness are significantly improved. Ackerman intelligent vehicle uses this algorithm to move autonomously in the 3D physical simulation environment, and can avoid obstacles in real time, presenting a good simulation effect.
Intelligent recognition system of converter station operation text based on computer image acquisition

In order to improve the efficiency of text recognition of converter station operation, this paper studies the intelligent text recognition system combined with computer image acquisition technology. Through the visual recognition algorithm developed by VS2010 and OpenCv to extract the font outline, combined with the developed outline edge feature extraction algorithm to identify and locate the font, the intelligent recognition statistics are realized. Because the real-time performance of human body detection using gradient histogram features is poor, the method of feature extraction is improved in this paper. The experimental results show that the improved human detection algorithm has good real-time performance. In the experiment, the success rate is over 95%, and the time spent is less than 28s. There is a huge space for practical application and promotion.
Identifikasi Kekeringan Meteorologi menggunakan SPI 3 Bulanan dan 6 Bulanan di DAS Brantas Hulu

Drought is a state of water availability that is far below the need for water for survival, agriculture, economic activity, and the environment. Drought in the Brantas Hulu watershed has been recorded as hampering the function of the Sutami Reservoir. This study used the Standardized Precipitation Index (SPI) method of 3 monthly and 6 monthly to determine the distribution of drought in the form of duration, severity, and maximum intensity of the Brantas Hulu watershed. This study also analyzed the relationship between the 3-monthly and 6-monthly SPI index to the sutami reservoir inflow discharge in the Brantas Hulu watershed using the Pearson Correlation method including correlations without lag, lag 1, and lag 2. The data used are monthly rainfall data for 30 years for the period 1991 - 2020 from 10 Rain Posts in Malang City, Batu City, and Malang Regency as well as monthly inflow debit data for 10 years for the period 2011 - 2020 from Perum Jasa Tirta 1. In general, the distribution of the maximum drought duration occurs for 15 – 17 months, while the SPI of 6 months occurs for 25 – 29 months. The maximum drought severity occurs for 5 - 6 months, while the 6-month SPI occurs for 9 – 11 months. The maximum drought intensity of SPI is 3 months and 6 months is categorized as Dry. Otherwise, the correlation of 3 monthly SPI and sutami reservoir inflow discharge without lag and lag 1 is worth 0,2 to 0,3, while for lag 2 it is worth 0,1 to 0,2. The correlation value of the 6 -month SPI index and the inflow discharge of Sutami Reservoir without lag is worth 0,3 to 0,4, while the correlation of lag 1 and lag 2 is worth 0,2 to 0,3.
POTENSI RISIKO BANJIR MENGGUNAKAN SISTEM INFORMASI GEOGRAFIS (SIG) PADA DAS MAHAKAM KALIMANTAN TIMUR

East Kalimantan as a candidate for the new capital city of Indonesia is the province with the most populous city in Kalimantan, namely Samarinda City. Rainfall is very influential on the potential for flooding. East Kalimantan province is an area that often experiences flooding. Mahakam watershed which is the main watershed in East Kalimantan Province with the Mahakam River as its center. Based on historical data, major floods have occurred since 1998 with the area of submerged settlements reaching 2,084 hectares with a depth of between 30 cm to 3 m. Monthly rainfall data, DEM 30M, data on soil types, land use, river buffers are used to construct flood potential maps. The disaster risk mapping carried out takes into account potential factors for flooding, vulnerability and capacity which results in five classes of flood risk, namely very low, low, medium, high and very high risk. The results of this study indicate that the Mahakam watershed has five flood risk classes. The “very high risk” class covers an area of 17,8833.25 ha, “high risk” covers an area of 1,345,285.73 ha, “medium risk” covers an area of 4,629,765.80 ha, “low risk” covers an area of 796,524.14 ha and the “very risk” class covers an area of 17,8833.25 ha. low” area of 190,169.92 ha. Areas that have the greatest flood risk are areas around rivers and creeks. Meanwhile, other areas that need to be watched out for are the downstream Mahakam river which is located in Kutai Kartanegara Regency and Samarinda City.
Camera coordinate alignment in multi-camera-projector structured light system

This paper presents a calibration method to align the coordinate system of each camera together in a multi-camera-projector system using a flat surface object. The method identifies the geometric relationship between each camera’s coordinate system with the physical feature points from the 3D model of the calibration target sharing the minimum absolute bi-directional phase difference. Experimental results shows that pixel-level accuracy of 3D model alignment can be achieved.
Absolute phase unwrapping via depth from focus in microscopic fringe projection profilometry

This paper presents a novel phase unwrapping algorithm via depth from focus method in microscopic fringe projection profilometry. The proposed method uses fringe contrast to estimate the rough depth information and determines the fringe orders by geometrical constraint relationships. As a result, it does not require extra patterns or images, enabling a higher 3D imaging speed. Experimental results demonstrate that the proposed method can successfully realize phase unwrapping in microscopic fringe projection profilometry.
Flipbook-Based E-Book Learning Media: Strengthening Literacy in Education Early Childhood

This research is based on the importance of innovative and communicative learning media such as e-books in the use of technology in the future to improve students' literacy skills because instilling the habit of reading fondly from an early age is still minimal.The purpose of this study was to produce a proper and effective e-book for improving student learning outcomes at Medan Methodist 5 Kindergarten.The development procedure used in this study is the development model from Borg and Gall and the instructional design step from Dick and Carey which is divided into 4 stages including the needs analysis stage, the product design stage, the validation and evaluation stage, and the final product stage.To see the effectiveness of the E-book, it can be analyzed through the normality test, homogeneity test, and hypothesis testing.Product validation results show a score percentage of 92.94% for material expert validation, 91.76% for media expert validation, 95.55% for design expert validation, and 98.26% for student response results.The results of the normality and homogeneity tests show that the research data has been declared normal and homogeneous.The results of the hypothesis test show that the value of t count is 2.37 and the value of t table is 1.66, where t count > t table.The results of this study indicate that flipbook-based e-books are feasible and effective in improving literacy skills and student learning outcomes in Medan Methodist 5 Kindergarten.
HR Index and CHR Index: Two new literature measurement composite indexes-Taking the evaluation of academic journals as an example

In academic evaluation, some composite evaluation indexes, for example, quantity, quality and prestige, have the advantages of a large amount of information and unique results.First, in this paper, two composite evaluation indexes are proposed, i.e., the HR index and the CHR index, where the HR index is based on the evaluation of prestige and quality, and the CHR index is based on the evaluation of prestige, quality and quantity.Second, two methods are proposed for testing the HR and CHR indexes.One is to test the principles, i.e., the self-interpretation degree of the results to the principle, by means of partial least squares regression.The other is the analysis of the evaluation results, including the relationships between the composite index and other bibliometric indicators, such as the order of magnitude and distinction and the data distribution of evaluation value, etc. Empirical studies are also conducted.The CSSCI periodicals of the CNKI Library Information and Document Science are employed to test the proposed HR and CHR indexes.Empirical analyses find that the HR index and the CHR index are good evaluation indicators that have broad application and can be used in many aspects, such as scholar, institutional and subject evaluations.
AI finds new way to sort data

Millions of programs could run faster thanks to DeepMind discovery of better code