Reviewerly/exHarmony huggingface dataset:
Proposal of Model Predictive Trajectory Planning Method for Autonomous Parking Considering Obstacle Avoidance Constraint with Coordinate Transformation

This paper proposes a model predictive trajectory planning method with collision avoidance in narrow parking spaces such as the case that parking would not be completed by one motion of cutting the wheel. Rectangle expression is used for all objects, and obstacle avoidance constraint is defined by a concise inequality with a coordinate transformation from rectangle to circle shape for each object. Switching of moving forward and backward is conducted regardless of the position and the number of times by tuning weights of the cost function and mechanical constraints for a vehicle. Verification is conducted for the performance of strict obstacle avoidance in a narrow environment and calculation time for optimization using the proposed method by numerical simulations.
Can artificial intelligence make a meaningful contribution to oral healthcare?

Artificial intelligence provides many possibilities for gaining new insights into the functioning of the oral ecosystem. The success of artificial intelligence is based on a combination of an abundance of available data, greatly increased computing powers and the development of complex machine learning algorithms. These algorithms map biological patterns on the basis of data, without being explicitly programmed, i.e. the computer recognises interactions using data only. Artificial intelligence and machine learning can be used very effectively to make predictions about specific biomarkers or groups of biomarkers that can be associated with specific clinical conditions. Such insights into the complex biological processes cannot be achieved with classical p-value-based statistics.Artificiële intelligentie biedt veel mogelijkheden om nieuwe inzichten te verwerven over het functioneren van het orale ecosysteem. Het succes van artificiële intelligentie is gebaseerd op de combinatie van een overvloed aan beschikbare data, sterk toegenomen rekenkracht van computers en de ontwikkeling van complexe machine learning algoritmen. Deze algoritmen brengen op basis van de data biologische patronen in kaart, zonder expliciet geprogrammeerd te zijn, dat wil zeggen de computer herkent zelf interacties door alleen de gegevens te gebruiken. Artificiële intelligentie en machine learning kunnen zeer doeltreffend worden gebruikt om voorspellingen te doen over bepaalde biomarkers of groepen biomarkers die geassocieerd kunnen worden met een specifiek ziektebeeld. Een dergelijk inzicht in complexe biologische processen kan niet worden verkregen met de klassieke op p-waarden gebaseerde statistiek.
Stage Performance and Musical Analysis of Haacaaluu Hundeessaa Works by using Sentiment Analysis Techniques

This research is initiated to analysis the stage performance and musical analysis of Haacaaluu Hundeessaa works on Afaan oromoo reviews text collected from social Medias by applying the concept of sentiment analysis techniques. The data (reviews) were collected manually from social media on Haacaaluu Hundeessaa musical works. Haacaaluu Hundeessaa is Oromo singer, songwriter, civil rights activist and his being a voice his people. He is the most famous young singer, hero and icon of Oromo musician. From his musical works Sanyii Mootii(Race of the King), Waa'ee Keenyaa(Our Plight), Maalan Jira(What existence is mine), JIRTUU? are the most popular known in Oromo peoples as well as nation and nationality of Ethiopia. From Hacaaluu musical works, the researcher considered reviews (opinions) afaan oromoo text data on his single sang “JIRTUU?” to analysis stage performance of Haacaaluu Hundeessaa’s. The researcher inspires to use this single sang because; reviews (comments) are easier to access, available on you tube channel, extensive in size relatively from other his songs from social media. Additionally this song was broadcast live by Oromia Broadcasting Network and other Medias on different stage. Opinion lexicon approach with contextual valence shifter is used for analyzing opinions (comments) given on stage performance of Haacaaluu Hundeessaa works. Totally 18,687 reviews opinions or sentences were collected for experimentations to analysis stage performance and musical works of Haacaaluu Hundeessaa. Accordingly our result indicates around 99.52 percents peoples likes the stage performance and musical works of Hacaaluu Hundeessaa. From the results researcher observed Haacaaluu Hundeessaa has good performer with sing emotional and physically when he sing on the stages. In future works, further research needs to study others musical works of Hacaaluu Hundeessaa.
An Improved Fireworks Algorithm for Ontology Matching

Ontology, presentation of the domain clearly and accurately, is established by knowledge extraction or hand. However, due to differences in construction methods or understanding of domain knowledge, it leads to ontology heterogeneity. This problem interferes with the flow of information between machines. Ontology matching is designed to address this challenge by using different similarity measures. As a branch of ontology matching, ontology meta-matching has the advantages of high efficiency and accuracy in solving ontology heterogeneity. It aims to acquire the matching pairs with the highest confidence by using the best aggregation weights to integrate the similarity measures. Fireworks algorithm (FA) is proposed to solve complex optimization problems, and the experimental results show that it has good performance in optimization accuracy and search ability. However, using roulette to select gaussian variant sparks has greater uncertainty. In addition, the alignment given by experts is impractical in the process of ontology matching, it not only consumes a lot of resources but also is prone to errors. In order to improve these tasks, two novel strategies (Maximum Confidence Model (MCM) and Elite Solution Priority Mutation Strategy (ESPMS)) are proposed in this paper to increase population diversity and evaluate the validity of matching pairs. In order to verify the validity of the proposed method, the benchmark of OAEI (Ontology Alignment Evaluation Initiative) is used.
SISTEM BERBASIS CLOUD COMPUTING UNTUK IDENTIFIKASI RESEP DOKTER “BARSEP”

A doctor's prescription is a doctor's written request to the pharmacist to prepare and give medicine to the patient. Prescriptions are made according to the needs of the patient after the doctor has examined and diagnosed the patient. However, doctor’s writing on a prescription that considered unclear can cause errors when compounding / preparing the drug and using prescribed drugs. In fact, the cure rate and life expectancy of patients is directly proportional to the administration of the right medicine. This study aims to prevent errors in the process of identification of prescription drugs by pharmacists. The technology used is cloud computing with the PHP 7.1.3 programming language, Laravel framework, and database storage using MySQL. BarSep application works by adding QR Code on recipe paper. The QR Code contains patient examination information including patient data, prescription drugs, and diagnoses, so that when the pharmacist scans the QR Code, the system will display all patient information that has been inputted by the doctor at the time of the examination. The results obtained from the implementation of the BarSep application at the Rapha Farma Pharmacy is BarSep applications effective for tackling errors in reading doctor's prescriptions that can save patients from medication errors. A doctor's prescription is a doctor's written request to the pharmacist to prepare and give medicine to the patient. Prescriptions are made according to the needs of the patient after the doctor has examined and diagnosed the patient. However, doctor’s writing on a prescription that considered unclear can cause errors when compounding / preparing the drug and using prescribed drugs. In fact, the cure rate and life expectancy of patients is directly proportional to the administration of the right medicine. This study aims to prevent errors in the process of identification of prescription drugs by pharmacists. The technology used is cloud computing with the PHP 7.1.3 programming language, Laravel framework, and database storage using MySQL. BarSep application works by adding QR Code on recipe paper. The QR Code contains patient examination information including patient data, prescription drugs, and diagnoses, so that when the pharmacist scans the QR Code, the system will display all patient information that has been inputted by the doctor at the time of the examination. The results obtained from the implementation of the BarSep application at the Rapha Farma Pharmacy is BarSep applications effective for tackling errors in reading doctor's prescriptions that can save patients from medication errors.
Digital Library Partnerships: The Issues and Challenges

This session established a global overview on digital libraries and partnerships. The focus then centered on a corporate research and development initiative and a library/public agency collaboration. In both cases the scope and background of the projects were outlined and such issues as implementation and ongoing support were discussed. The Institute for Scientific Information and Thomas Jefferson University concentrated on ISI’s Electronic Library Project which has been designed to test and validate electronic access to bibliographic data and images of a large corpus of scholarly journal literature. The Cornell Mann Library/USDA collaboration, 222which makes available via the Internet nearly 300 USDA electronic publications, will discuss the goals and challenges of implementing this new service. [Article copies available for a fee from The Haworth Document Delivery Service: 1-800-342-9678. E-mail address: getinfo@haworth.com]
Dissemination of village archive management as a historical source

The community service provided in Karang Indah Village aims to disseminate and assist village officials in preparing archives. This activity involves students of the History Education study program as the implementation of archival and museum science. The preparation of archives, both manually and digitally, is very important for all agencies, especially in the village office. This is done, of course, to make it easier to serve the community. When needed, archives that have been well organized will be easy to find. Archives contain primary data and play an important role in the process of reconstructing history. The archive's position is so critical that it must be managed properly and appropriately. The implementation method consists of three steps: planning, implementation, and evaluation. The service activities have resulted in increased knowledge and skills among village officials in the preparation and management of archives, both manually and digitally.
Pemanfaatan Internet Sebagai Media Masyarakat Pada Layanan Perpustakaan di Masa Pandemi COVID-19

The progress of information and communication technology (ICT) is currently growing rapidly. so that a new media called the Internet was born. The internet has made it easier for people to communicate without knowing the barriers of space and time. Its use is like providing space for people to interact more easily and quickly. This interaction exists both in individuals and groups. This article uses a descriptive qualitative research method with a literature study approach. Based on the results of the study, the use of the internet network can make it easier for libraries to provide services to users or virtual communities which were originally developed face-to-face and then turned into online services during the COVID-19 pandemic. In addition, it provides convenience for users who need information by providing electronic sources of information for users who need access via the internet. As a support unit in the field of education, libraries during the COVID-19 pandemic must continue to provide good service to their users so that the library remains busy and up to date.
Detecting Red Flag of Workplace Crime Using Mobile Data on Abnormal Usage Activities

The purpose of this paper is to investigate how to detect the workplace crime of organizational sales representatives (e.g., sales who work with external customers) through abnormal activities that can be traced by mobile devices and applications.The guardianship capability of organizations is considered as the moderator influencing the monitoring of abnormal usage activities calculated by deep learning.In this study, we conduct event history analysis on the occurrence of workplace crime utilizing a longitudinal panel data set, which comprises 197179 weekly observations in 3 years (2017)(2018)(2019).Our finding provides evidence that the abnormal activity pattern is an effective signal for identifying workplace crimes.Furthermore, we illustrate how to design monitoring modes based on guardianship capability in order to maximize the effectiveness of mobile monitoring in reducing workplace crimes.
COVID-19 Contact Tracing using Blockchain

Contact tracing has widely been adopted to control the spread of Coronavirus-2019 (COVID-19). It enables to identify, assess, and manage people who have been exposed to COVID-19, thereby preventing from its further transmission. Today's most of the contact tracing approaches, tools, and solutions fall short in providing decentralized, transparent, traceable, immutable, auditable, secure, and trustworthy features. In this paper, we propose a decentralized blockchain-based COVID-19 contact tracing solution. Contact tracing can greatly suffice the need for a speedy response to a pandemic. We leverage the immutable and tamper-proof features of blockchain to enforce trust, accountability, and transparency. Trusted and registered oracles are used to bridge the gap between on-chain and off-chain data. With no third parties involved or centralized servers, the users' medical information is not prone to invasion, hacking, or abuse. Each user is registered using their digital medical passports. To respect the privacy of the users, their locations are updated with a time delay of 20 minutes. Using Ethereum smart contracts, transactions are executed on-chain with emitted events and immutable logs. We present details of the implemented algorithms and their testing analysis. We evaluate the proposed approach using security, cost, and privacy parameters to show its effectiveness. The smart contracts code is publicly made available on GitHub.
Application of Geophysical Technology in Engineering Investigation

With the development of science and technology and the progress of society, various high and new technologies have increasingly shown their respective advantages. Among them, geophysical prospecting technology is a typical representative. Because it can greatly improve the speed and efficiency of engineering, and at the same time, it also plays an important role in engineering safety and prevention. Therefore, it is widely promoted and applied, especially in engineering survey work. This article studies the importance of geophysical prospecting in engineering exploration, the methods of geophysical prospecting technology, the application of geophysical prospecting technology, and the development trend of geophysical prospecting technology. How to better understand the application of geophysical prospecting technology and rationally choose working methods and methods, so as to serve the geological exploration work to the utmost extent, is an important topic that needs to be solved and studied urgently.
Perbandingan Algoritma SVM dan KNN dalam Mengklasifikasi Kelulusan Mahasiswa pada Suatu Mata Kuliah

Two different algorithms will use different approaches.Like KNN (K-Nearest Neighbour) and SVM (Support Vector Machine), with the former calculates the closest distance between two instances, while the latter calculates the existence of hyperplane that separates two resulted classes.By using train data consisting of anomaly or noise data and using real measurement normally given by a lecturer to the students in the class to determine the students' pass or fail in one subject, the research finds the difference between the two algorithms.The research is conducted in the University of XYZ on IIT (Introduction to Information Technology) subject.With the use of Orange Data Mining software, the research aims to give information about the suited algorithm for prediction or classification of student's success in a related subject or others.It uses quantitative analysis with KNN dan SVM algorithms methods.Based on an assessment of several parameters, KNN is better than SVM, but SVM is better than KNN in obtaining a passing threshold value.
Netizens’ Reaction to the Garbage Prank Case: Forensic Linguistic Perspective Analysis

The purpose of this study is to analyze the reactions of netizens to prank cases FD from the point of view of forensic linguistics.Research methods used in research "Forensic Linguistic View Regarding Warganet's Reaction To This Garbage Prank Case" is a qualitative descriptive research.Sources of data in this study are layer capture (screenshot) on the writings of netizens on social media Twitter, Instagram, Facebook, and Youtube comments column.Data collection in this study using the listening and note-taking technique.Data analysis was carried out by outlining the writings of the netizens are then analyzed related to the use of the language that associated with applicable laws.The results of this study show that the various comments of the netizens seemed to be cornering and did not give space for FP to be able to realize his mistake.Not everyone has a big heart dared to admit his mistake.FP tried to run away first before finally arrested.
Innovative Strategies of Primary School Calligraphy Education Model Under the Background of Big Data

With the continuous improvement of our country’s science and technology level, Internet technology represented by mobile terminal equipment has been extensively developed, and the world has entered the era of big data. However, with the rapid development of the era of big data, the teaching mode of primary school calligraphy has also undergone tremendous changes. The research purpose of this article is based on the rapid development of the current era of big data, to study the methods and strategies of the innovation model of the primary school calligraphy education model. This article first starts from the key points of the transformation of primary school calligraphy education mode under the background of big data, and proposes relevant suggestions. Secondly, it analyzes the effective methods for the innovation of primary school calligraphy education in the era of big data, through the use of multimedia technology, the development of group cooperative learning, and the combination of three ways of extracurricular life. Finally, the innovation of the primary school calligraphy education model in the era of big data is analyzed through graphs, which will help improve the quality of primary school calligraphy teaching. Experimental research results show that primary school calligraphy teachers should actively introduce big data into classroom teaching, give full play to the value and role of the big data era, design scientific teaching links and teaching content based on the growth characteristics of students, and improve teaching with the help of big data information The evaluation system improves the teaching effect of calligraphy and promotes the development of students’ comprehensive ability.
Determination of the content of rare metals in spent anion-exchange resin SIM202 by methods of neutron-activation and mass-spectrometric analysis

Abstract The work is devoted to the development of methods for determining the elemental and isotopic composition of spent ion-exchange resin, industrial waste and environmental objects using an inductively coupled plasma mass spectrometer and analyzing specific samples to determine the content of noble and rare metals in technological materials, industrial waste and natural objects with application of the developed techniques. This article determines the elemental composition of the spent ion-exchange resin SIM202 with the Inductively coupled plasma mass spectrometry (ICP-MS) method and also shows the comparison of the results with neutron activation analysis (NAA). The distribution coefficient of elements in a chromatographic column in ion-exchange resins TAO and SIM202 is given.
<i>Application of UTAUT2 for Analysis of Use Behavior Management Information System</i> (SIMBMD) <i>in Regional Government XYZ</i>

Regional government financial reports in Indonesia, especially in district XYZ are currently entering a period of quality improvement.This is indicated by the increase in the number of regional government Financial Reports that obtain Unqualified Opinion from Audit Board BPK RI.This success is certainly a challenge for the XYZ regional government continue to maintain it.One of the efforts made by the XYZ regional government is to improve the regional property management system by procuring a regional property management information system (SIMBMD) which will support the optimization of regional financial management and reporting.The application of SIMBMD in XYZ regional government is quite new, so it is necessary to know the suitability of using the system.This encourages the authors to conduct research to find out what factors can affect the suitability of SIMBMD implementation.Data were obtained from a questionnaire with a total of 421 respondents.The data were analyzed using an integrated evaluation model UTAUT2, where the method was modified.The results showed that there were 8 main variables and 1 moderating variable that had an effect, namely the main variables consisted of performance expectancy, effort expectancy, facilitating conditions, habit, trust, behavioral intention, use behavior, and net benefits, and the moderating variable consists of experience.The most influential variable indicator is facilitating conditions on the availability of supporting facilities so that the XYZ regional government must provide the facilities needed for the use of SIMBMD.
Parameterized Convexity Testing

Previous chapter Next chapter Full AccessProceedings Symposium on Simplicity in Algorithms (SOSA)Parameterized Convexity TestingAbhiruk Lahiri, Ilan Newman, and Nithin VarmaAbhiruk Lahiri, Ilan Newman, and Nithin Varmapp.174 - 181Chapter DOI:https://doi.org/10.1137/1.9781611977066.12PDFBibTexSections ToolsAdd to favoritesExport CitationTrack CitationsEmail SectionsAboutAbstract In this work, we develop new insights into the fundamental problem of convexity testing of real-valued functions over the domain [n]. Specifically, we present a nonadaptive algorithm that, given inputs ε ∊ (0,1), s ∊ ℕ, and oracle access to a function, ε-tests convexity in O(log(s)/ε), where s is an upper bound on the number of distinct discrete derivatives of the function. We also show that this bound is tight. Since s ≤ n, our query complexity bound is at least as good as that of the optimal convexity tester (Ben Eliezer; ITCS 2019) with complexity ; our bound is strictly better when s = o(n). The main contribution of our work is to appropriately parameterize the complexity of convexity testing to circumvent the worst-case lower bound (Belovs et al.; SODA 2020) of expressed in terms of the input size and obtain a more efficient algorithm. Previous chapter Next chapter RelatedDetails Published:2022eISBN:978-1-61197-706-6 https://doi.org/10.1137/1.9781611977066Book Series Name:ProceedingsBook Code:SOSA22Book Pages:v + 320