Reviewerly/exHarmony huggingface dataset:
Optimization of 3D Printing While Traveling En Route to Extend Range of UAS for Multi-Location Mission Scenarios

Abstract The nexus of two relatively recent technologies, additive manufacturing and unmanned aircraft systems (UAS), has enabled new and unique capabilities that have only started to be realized in integrated systems. This paper explores and quantifies the impact of 3D printing parts for UAS, or entire UAS systems, on an agent platform while it travels to multiple locations as part of a mission objective. The printed or enhanced UAS can then be released at launch points farther away from the goal locations. This, in turn, can accelerate mission completion times and reduce travel costs. The methodology and optimization problem are developed by making use of Apollonius circles extensively with interesting examples presented of the integration of these two technologies. Results indicate that based on the print capability and agent travel speed, using the sequence provided by a Traveling Salesman’s problem solution is not always optimal. Thousands of scenarios are optimized across the design space with some interesting phenomena discussed in the analysis.
Sentiment Analysis of YouTube Comments Toward Chat GPT

&lt;p&gt;Sentiment analysis is used for analyzing the emotions and attitudes expressed in text data. In this study, sentiment analysis is used to understand people’s enthusiasm toward Chat GPT. The primary objective of this study is to investigate the acceptance of people of new artificial intelligence technology, Chat GPT, that may change the future. To get a deep understanding of it, a large dataset of user comments from YouTube is collected and then data pre-processing is done by removing stop words, punctuations, and irrelevant information. Using Text Blob and VADER approaches, comments are classified into positive, neutral, and negative categories. The result shows that most users have a positive sentiment to receive and use Chat GPT. The contribution of this study is to provide insights into the sentiment of people’s response to Chat GPT, which can inform user acceptance of the language model development and give guide its future applications.&lt;/p&gt;
Pengamanan Citra Digital Terenkripsi Menggunakan Kombinasi Steganografi Bit Matching dan Kriptografi Cipher Feedback (CFB) dengan Pembangkit Bilangan Acak Linear Congruential Generator (LCG).

In this study, the design and manufacture of an encrypted digital image security system was carried out by combining bit matching steganography and cryptographic cipher feedback (CFB) using a linear congruential generator (LCG) as a key generator. The test material used 60 message images measuring 120x120 pixels with 1 cover image measuring 64x64 pixels. The results of the study were obtained: (1) the image can be hidden but there is an increase in the size of the embedding file with an average difference of 459.1167 KB (kilobytes) or an increase of 2135.65%, (2) The image can be reconstructed, the physical image of the extraction result is the same as the original image with an MSE value = 0, but there is a change in size that varies with an average difference of 3.433333 KB (kilobytes) or by 16.20%, (3) Some robust tests such as image rotation testing, brightness manipulation, addition of gaussian noise make the extracted image damaged. The image is resistant to all contrast tests. Salt and pepper noise testing does not damage the image too much, the image is still resistant to salt and pepper noise testing of 0.001 with an average MSE = 0
Evaluating the Popularity of Programming Languages in Indonesia using the MABAC Method

&lt;span lang="EN"&gt;In today's fast-paced digital era, the selection of a programming language plays a crucial role in the success of software development projects. This research aims to create an index of popularity for programming languages using the multi-attributive border approximation area comparison (MABAC) method. The study considers four data sources, including Jobstreet.Com, LinkedIn.Com, Google Trends, and Tiobe.com, to obtain the necessary information for evaluating the popularity of programming languages in Indonesia. The data range for this study is from May 1, 2020, until April 31, 2021. The results of the study indicate that the top ten programming languages in terms of popularity in Indonesia are Java, SQL, php, JavaScript, C, C++, python, C#, Visual Basic, and Assembly. The index can serve as a useful guide for strategic decision-making regarding the selection of programming languages for addressing the needs of the information technology market in Indonesia. The study's findings can be useful for software developers, IT professionals, and decision-makers in organizations who need to select a programming language for their software projects in Indonesia. The MABAC method used in this study can also be applied to other contexts for evaluating the popularity of programming languages.&lt;/span&gt;
Perbandingan LSTM dengan Support Vector Machine dan Multinomial Na ve Bayes pada Klasifikasi Kategori Hoax

Hoax is fake news, now massively spread through social media. The impact of hoaxes is that people's misperceptions in understanding of news are very high. With the existence of hoaxes are spreading through social media, it requires the public to think smart when receiving the news. Currently, many ways to prevent hoaxes, right now we have Fact Checker Directory Platform which is a truth platform sourced from several fact check sites. On the truth check platform, every news detected as hoaxes has been categorized into specific type of hoax, manually by the validator. For this reason, this research attempts to automatically categorize the types of hoaxes using comparation of Deep Learning with Machine Learning classifications. Deep Learning uses Long Short Term Memory Network (LSTM), while Machine Learning uses Support Vector Machine (SVM) and Multinomial Naive Bayes. Through the build model process, SVM produces the best accuracy quality of 0.74, Multinomial Na ve Bayes produces an accuracy quality of 0.62 while LSTM displays 0.49. The results of low accuracy in LSTM need to be evaluated on model architecture and data normalization during preprocessing.
Further research results on confusion coefficient of Boolean functions

Abstract The notion of confusion coefficient (CC) is a property that attempts to characterize the confusion property of cryptographic algorithms against differential power analysis. In this article, we establish a relationship between CC and the transparency order (TO) for any Boolean function and deduce some relationships between the sum-of-squares of CC, signal-to-noise ratio, and TO. We also give a tight upper bound and a tight lower bound on the sum-of-squares of CC for balanced s-plateaued functions. Finally, the results generalized a lower bound on the sum-of-squares of CC of Boolean functions with the Hamming weight k .
Research on the Electric Energy Metering Data Sharing Method in Smart Grid Based on Blockchain

Enabling data sharing among smart grid power suppliers is a pressing challenge due to technical hurdles in verifying, storing, and synchronizing energy metering data. Access and sharing limitations are stringent for users, power companies, and researchers, demanding significant resources and time for permissions and verification. This paper proposes a blockchain-based architecture for secure and efficient sharing of electric energy metering data. Further, we propose a data sharing model based on evolutionary game theory. Based on the Lyapunov stability theory, the model’s evolutionary stable strategy (ESS) is analyzed. Numerical results verify the correctness and practicability of the scheme proposed in this paper, and provide a new method for realizing convenient, safe and fast data sharing.
Analisis Usability SLiMS 9 Bulian Menggunakan Metode Software Usability Measurement Inventory

Introduction. The development of ICT is directly related to the availability of information in the library. In addition to hardware, libraries need software to develop library services as ICT advances. One of the basic software required for all libraries is (Integrated Library System/ILS). There is not much research on studies using SUMI for integrated library systems. Until now, not many studies have analyzed the quality of integrated library system applications, especially using the SUMI method. The purpose of this research is to analyze the usability of the integrated library system application SLiMS 9 Bulian. &#x0D; Data Collection Methods. The method used is the quantitative Usability Method using the Usability Measurement Inventory (SUMI) Software by taking data directly from the SUMI questionnaire distributed to respondents.&#x0D; Data Analysis. Data analysis was carried out in a descriptive quantitative way through scoring and the results of the analysis of the collected questionnaires became the basis for assessing usability results.&#x0D; Results and Discussion. The results of this study indicate that 1) Software Usability Measurement Inventory (SUMI) testing on SLiMS 9 Bulian is very efficient in helping work; 2) Affect (general reaction), Helpfulness (clarity), Control (controlling), and Learnability (ease) are below average and have not been said to be good enough.&#x0D; Conclusion. The test results of the Software Usability Measurement Inventory (SUMI) of the SLiMS system are very efficient in helping work. This is obtained from the value of the efficiency scale which is above the average score and 4 indicators that have a low average score, namely affect, helpfulness, control, and learnability. Suggestions for further research can be carried out on SLiMS 9 Bulian using the original version of SUMI without being translated into Indonesian so that the differences with this study can be seen.
Analisis Tingkat Kepuasan Pengguna Terhadap Layanan Ask a Librarian Di Perpustakaan Universitas YARSI

Introduction. Due to the pandemic, virtual services must be maximized as a support for limited face-to-face services. This paper measures the level of user satisfaction with the Ask a Librarian service at the YARSI University Library from the Affect of Service dimension (Performance of Officers in Service); measuring the level of user satisfaction with the Ask a Librarian service from the Information Control dimension (Quality of Information and Access to Information); and measuring the level of user satisfaction with the Ask a Librarian service from the Library as Place dimension.&#x0D; Data Collection Methods. Using a quantitative descriptive method, the aspects studied are based on LibQUAL+™. Data collection through questionnaires from 104 samples.&#x0D; Data Analysis. Measurement of validity and reliability using SPSS, analyzing data with (Gap Analysis) based on LibQUAL+™ to determine user satisfaction.&#x0D; Results and Discussion. Research shows; User perception gets a score of 7.50; The minimum expectation (HM) of the user gets a score of 5.93; The ideal expectation (HI) of the user gets a score of 6.79, the user's adequacy gap (AG) gets a score of 1.57, the superiority gap (SG) of the user gets a score of 0.71.&#x0D; Conclusion. YARSI University Libraries can maintain and improve the quality of the library where users are "quite satisfied" and "very satisfied" with the service. This study only examines one user group, namely YARSI University students. For this reason, further research can conduct research on different users.
Aplikasi Perpustakaan Berbasis Unified Modelling Language

&lt;p class="BasicParagraph"&gt;Perpustakaan SMA Islam Nahdlotusysyubban Ploso masih menggunakan cara konvensional atau cara manual dalam memanajemen pengolahan data buku-buku perpustakaan. Hal tersebut memunculkan beberapa permasalahan baik dalam lamanya proses pencatatan dan keakurasian data buku perpustakaan. Dari permasalahan tersebut perlu adanya sebuah aplikasi yang mendukung dalam proses kerja pustakawan. Dengan adanya aplikasi setidaknya akan mempercepat proses pelayanan perpustakaan, dikarenakan adanya dorongan perangkat lunak (software), perangkat keras (hardware), infrastruktur, dan Sumber Daya Manusia (SDM) yang terlatih. Aplikasi perpustakaan ini menggunakan bahasa &lt;em&gt;Unified Modelling Language &lt;/em&gt;(UML)&lt;em&gt; &lt;/em&gt; dengan menggunakan permodelan &lt;em&gt;use case&lt;/em&gt; &lt;em&gt;diagram&lt;/em&gt;, &lt;em&gt;activity&lt;/em&gt; &lt;em&gt;diagram&lt;/em&gt;, &lt;em&gt;sequensi diagram&lt;/em&gt; dan &lt;em&gt;class diagram. &lt;/em&gt;Metode &lt;em&gt;Waterfall &lt;/em&gt;dipilih dalam pengembangan aplikasi perpustakaan ini.&lt;/p&gt;&lt;p class="IsiAbstrakIndo"&gt;&lt;em&gt;The Nahdlotusysyubban Ploso Islamic High School library still uses the conventional method or the manual method in managing the data processing of library books. This raises several problems both in the length of the recording process and the accuracy of library book data. From these problems, it is necessary to have an application that supports the librarian's work process. With the application, it will at least speed up the library service process, due to the encouragement of software (software), hardware (hardware), infrastructure, and trained Human Resources (HR). This library application uses the Unified Modeling Language (UML) using use case diagrams, activity diagrams, sequence diagrams, and class diagrams. The Waterfall method was chosen in the development of this library application.&lt;/em&gt;&lt;/p&gt;&lt;p class="BasicParagraph"&gt; &lt;/p&gt;&lt;p class="BasicParagraph" style="line-height: 115%;"&gt;&lt;em&gt;&lt;span style="font-size: 8.0pt; line-height: 115%; mso-bidi-font-family: 'Times New Roman'; mso-ansi-language: IN; mso-bidi-font-weight: bold;"&gt;Data Processing; Information Systems; Library; UML; Waterfall.&lt;/span&gt;&lt;/em&gt;&lt;/p&gt;
THE USE OF AFFIXATION ON STUDENTS’ WRITING TEXT AT THE SECOND GRADE OF SMAN 1 KOTA JAMBI

The aims of this study investigates about two type of affixation focused on derivational affixes use by students of SMAN1 Jambi City in writng text.the data of the study are on students writing text. The method of the research was qualitative research and the approach used in counducting this research was descriotive research. The data obtained through documentation. This study involved twenty five students of XI mipa at SMAN1 Jambi City as sample the result of the research showed that there two type of affixation use by the students on their writing text, it shows there are, verb maker (38), noun maker (123), adjective maker ( 56), and adverb maker (127), the totals affixes use 344 word affixes.The researcher uses the classification of affixes by using Fromkin, et al (2014)’s theory about derivation which change grammatical classes which included noun , verb, adjective, and adverb.The findings of the study reveal that from 344 words which consist of affixes that focuse derivational affixes. that grammatical classes which involve 123 for noun which affixes produced are – ation, -ion, -er, -dis,- extra-ence, -er,, -ment,, -ness. 56 for adjective which affixes produced are –ous, - able, -ful, -y, -in, -ir, -ate, -tic, -ive,-al, -less, 127 for adverb which affix produced are –ly, -less, -un, -a, -im, -eag, and 38 for verb which affixes produced are -be-, and -ize. The intended meanings are about the affixation focuse of derivational affixation words that related to the quotations that are analyzed.
THE EFFECT OF COOPERATIVE INTEGRATED READING COMPOSITION (CIRC) TECHNIQUE TOWARD STUDENT READING COMPREHENSION ON RECOUNT TEXT AT GRADE VIII MTS NURUL IMAN ULU GEDONG

The four basic English skills are speaking, listening, reading, and writing. Receptive skills are reading and listening, productive skills are speaking and writing. Reading establishes textual meaning in language. Reading is a vital ability for English learners. It's important since reading helps pupils learn a lot. The first issue with this study was students' low vocabulary. Second, students lack reading motivation. Third, kids think their reading has no relation to the word. Fourth, the teacher applies old reading strategies without student participation. This study examined how the Cooperative Integrated Reading Composition Technique affected reading comprehension on recount texts in grade VIII at MTS Nurul Iman Ulu Gedong. There were 54 students in this study. In the experiment, 28 class VIII pi were utilized to sample. In this study, the mean pre-test score was 63,21 and the post-test score was 79,10 (79,10&gt;63,21). At 27 degrees of freedom and 5% significance. Table values are 2.052 and t-test values are 0.54 (0,54≥2,052). It showed Hi accepted and Ho declined. Thus, the study advised English teachers to employ Cooperative integrated reading composition (CIRC) to teach reading comprehension, particularly recount text.
Automated Dashboard for AWS Services Monitoring

Abstract: Cloud computing has become an integral part of modern business operations, offering flexibility, scalability, and costefficiency. However, the migration to the cloud brings forth a new set of challenges, with security being a top concern. Organizations need to continuously monitor and audit their cloud environments to identify vulnerabilities, detect threats, and ensure compliance with security standards. In today's digital landscape, cloud computing has become the backbone of many organizations, offering scalability, flexibility, and cost-effectiveness. However, with the increasing reliance on cloud services comes the crucial need for robust security measures to protect sensitive data and ensure compliance with industry regulation. Traditional security audits and monitoring processes are often manual, time-consuming, and prone to human error. They lack the agility and real-time insights required to effectively protect cloud assets. To address these limitations, the Automated Reporting and Dashboards for Cloud Security Audits project leverages Artificial Intelligence (AI) and Machine Learning (ML) technologies to revolutionize cloud security management.
Approximate Bayesian inference of directed acyclic graphs in biology with flexible priors on edge states

Graphical models or networks describe the statistical dependence among multiple variables and are widely used in biology (e.g., gene regulatory networks). Under appropriate assumptions, directed edges may represent causal relationships. A key feature of a biological network is sparsity, defined by how likely an edge is present, of which we often have some knowledge. However, most existing Bayesian methods use priors for the entire graph, making it difficult to specify the level of sparsity. The few methods that use priors on edges estimate the two directions independently; the sum of the two probabilities can exceed 1. Here, we present baycn (BAYesian Causal Network), a novel approximate Bayesian method that represents a graph in terms of three states of edges: the two directions and edge absence, and specifies priors on these edge states. We design a pseudo Bayesian sampling algorithm for efficient inference. We apply baycn to two genomic problems: i) distinguishing direct and indirect target genes of genetic variants, using these variants as instrumental variables, and ii) inferring combinatorial binding of highly-correlated transcription factors in Drosophila. In both cases and in extensive simulations, our method demonstrates much improved accuracy over existing methods for the whole graph and for individual edges.
Examining the Effect of Monetary Policy and Monetary Policy Uncertainty on Cryptocurrencies Market

This study investigates the influence of monetary policy and monetary policy uncertainties on Bitcoin returns, utilizing monthly data of BTC, and MPU from July 2010 to August 2023, and employing the Markov Switching Means VAR (MSM-VAR) method. The findings reveal that Bitcoin returns can be categorized into two distinct regimes: 1) regime 1 with low volatility, and 2) regime 2 with high volatility. In both regimes, an increase in MPU leads to a decline in Bitcoin returns: -0.028 in regime 1 and -0.44 in regime 2. This indicates that monetary policy uncertainty exerts a negative influence on Bitcoin returns during both downturns and upswings. Furthermore, the study explores Bitcoin's sensitivity to Federal Open Market Committee (FOMC) decisions.
UniMOS: A Universal Framework For Multi-Organ Segmentation Over Label-Constrained Datasets

Machine learning models for medical images can help physicians diagnose and manage diseases. However, due to the fact that medical image annotation requires a great deal of manpower and expertise, as well as the fact that clinical departments perform image annotation based on task orientation, there is the problem of having fewer medical image annotation data with more unlabeled data and having many datasets that annotate only a single organ. In this paper, we present UniMOS, the first universal framework for achieving the utilization of fully and partially labeled images as well as unlabeled images. Specifically, we construct a Multi-Organ Segmentation (MOS) module over fully/partially labeled data as the basenet and designed a new target adaptive loss. Furthermore, we incorporate a semi-supervised training module that combines consistent regularization and pseudolabeling techniques on unlabeled data, which significantly improves the segmentation of unlabeled data. Experiments show that the framework exhibits excellent performance in several medical image segmentation tasks compared to other advanced methods, and also significantly improves data utilization and reduces annotation cost. Code and models are available at: https://github.com/lw8807001/UniMOS.
WORKSHOP INTERNET OF THINGS (IOT) BERBASIS TECHNOPRENEURSHIP DI SMA/SMK KABUPATEN JOMBANG SEBAGAI MEDIA PEMBELAJARAN REVOLUSIONER DI ERA SOCIETY 5.0

This community service aims to introduce Internet of Things (IoT) based on technopreneurship at SMK Plus Umar Zahid Jombang as a revolutionary learning medium in the era of Society 5.0. Education today is facing the demand to integrate technology, innovation, and entrepreneurship into the school curriculum to prepare students for the challenges of the digital era. This workshop is designed to provide students with a profound understanding of IoT and technopreneurship, enabling them to develop innovative projects using IoT.&#x0D; The workshop encompasses the comprehension of fundamental IoT concepts, related technologies, and the application of IoT in various contexts. Furthermore, the workshop imparts the principles of technopreneurship, including the development of technology-based business ideas and entrepreneurial skills. Through a practical and collaborative approach, students are encouraged to design and implement their IoT projects.&#x0D; The outcomes of this workshop are expected to enrich students' comprehension of IoT's potential in addressing real-world societal issues, while also equipping them with pertinent technopreneurship skills for the digital era. Consequently, this workshop is anticipated to make a positive contribution to education and prepare students for Society 5.0, which emphasizes human-technology collaboration in achieving sustainable social progress
Automatic Restoration of Diacritics for Speech Data Sets

Automatic text-based diacritic restoration models generally have high diacritic error rates when applied to speech transcripts as a result of domain and style shifts in spoken language. In this work, we explore the possibility of improving the performance of automatic diacritic restoration when applied to speech data by utilizing parallel spoken utterances. In particular, we use the pre-trained Whisper ASR model fine-tuned on relatively small amounts of diacritized Arabic speech data to produce rough diacritized transcripts for the speech utterances, which we then use as an additional input for diacritic restoration models. The proposed framework consistently improves diacritic restoration performance compared to text-only baselines. Our results highlight the inadequacy of current text-based diacritic restoration models for speech data sets and provide a new baseline for speech-based diacritic restoration.