Reviewerly/exHarmony huggingface dataset:
Voting-based efficient cluster ensemble fusion

Voting-based consensus clustering is a subset of consensus techniques that makes clear the cluster label mismatch issue. Finding the best relabeling for a given partition in relation to a reference partition is known as the voting problem. As a weighted bipartite matching problem, it is frequently formulated. We propose a more generic formulation of the voting problem as a regression problem with various and multiple-input variables in this work. We demonstrate how a recently developed cumulative voting system is an exception that corresponds to a linear regression technique. We employ a randomised ensemble creation method in which an excess of clusters are randomly chosen for each ensemble partition. In order to extract the consensus clustering from the combined ensemble representation and to calculate the number of clusters, we use an information-theoretic approach. Together with bipartite matching and cumulative voting, we use it. We provide empirical data demonstrating significant enhancements in clustering stability, estimation of the real number of clusters, and accuracy of clustering based on cumulative voting. The gains are made in comparison to recent consensus algorithms as well as bipartite matching-based consensus algorithms, which struggle with the selected ensemble generation technique.
Small Cell Lung Carcinoma On Contrast enhanced Chest Computer Tomography, Are There Special Characteristics be Found ?

Background: Small Cell Lung Carcinoma is the most common primary pulmonary neuroendocrine malignancy.Usually patients present with metastatic disease at diagnosis and poor prognostic.Early and accurate diagnosis is important for SCLC.A contrast enhanced chest CT scan is needed to show more clearly the abnormalities detected on chest X-ray so that it can help to diagnose and reveal the extent of mediastinal invasion. Method:This study was a descriptive type with a retrospective approach.In 30 patients who underwent contrast enhanced chest CT with histopathologically proven SCLC at Dr. Soetomo Hospital, Surabaya.Assessing feature of SCLC based on age, gender, location, and mediastinal extension (airways and vascular).Results: Total sample were 30 patient, with 23 male subjects (76,6%) and 7 female subjects ( 23,3%), The age range of the study was between 31 years and 80 years, with an average age of 62 years, with incidence rate in males being higher than females.it was found that type I 3,3% (n = 1), type II a 13,3% (n = 4), type II b 30% (n = 9), type III a 3,3% (n = 1), III b 23,3% (n = 7), III c 10% (n = 3), type IV 13,3% (n = 4), and type V 3,3% (n = 1).Involvement airways approximately 60% (n=18), either involving one bronchus or 2 or 3 bronchial segments.About 86,6 % (n=26) prove to involve vascular with involvement pulmonal artery in 73,3% (n=22), superior vena cava in 13,3% (n=4) and combination of pulmonal artery and superior vena cava about 6,6% (n =2). Conclusion:Feature of contras enhanced chest CT scan found in SCLC is hilar mass with ipsilateral mediastinal extension involves the main bronchi with 2 or more segmental bronchi.Vascular involvement particularly the pulmonal artery was found.
Automatic model training under restrictive time constraints

We develop a hyperparameter optimisation algorithm, Automated Budget Constrained Training (AutoBCT), which balances the quality of a model with the computational cost required to tune it. The relationship between hyperparameters, model quality and computational cost must be learnt and this learning is incorporated directly into the optimisation problem. At each training epoch, the algorithm decides whether to terminate or continue training, and, in the latter case, what values of hyperparameters to use. This decision weighs optimally potential improvements in the quality with the additional training time and the uncertainty about the learnt quantities. The performance of our algorithm is verified on a number of machine learning problems encompassing random forests and neural networks. Our approach is rooted in the theory of Markov decision processes with partial information and we develop a numerical method to compute the value function and an optimal strategy.
TREN PENELITIAN TENTANG OTOMASI DAN PUSTAKAWAN PADA PUBLIKASI TERINDEKS SCOPUS TAHUN 1997-2022

Automation technology or machines with artificial intelligence are now doing the work done by workers. The librarian's core tasks should be replaced by automata to empower librarians to do other, more productive jobs. This study aims to observe how much use of machines with AI technology in library services, especially manual work. The study took samples from the Scopus website. Data is collected by entering keywords (TITLE-ABS-KEY (“automation”)) AND (“librarian”) on the Scopus search page. It was found around 940 population of papers and about 923 papers were taken for analysis. Data were analyzed by bibliometrics. The results show that AI is becoming one of the trending topics in research for writers. This is because AI is the brain to run automation itself, so a lot of research is needed to examine the development of the use of AI. The results also show where the keywords that are widely used and have a high level of relevance and development according to the field of study, namely automation, paper, and information. This shows that the keywords about automation have been well developed and are very relevant to the field of study of the paper as a sample.
Research on entity extraction based on subway energy consumption patent

In order to reduce operating costs and fulfill social responsibilities, enterprises and researchers in the field of rail transit need to study more efficient energy-saving technologies. Patent is one of the important ways to obtain information and knowledge related to technological innovation, but most of the existing patent analysis systems are statistical analysis of external patent information, and the results are not intuitive enough, which is not conducive to more in-depth mining of patent information. This paper introduces knowledge mapping related technologies to deconstruct and organize patent information to support scalable patent query and analysis requirements.
Information Experience of People with Visual Impairment on Audiobook Use as Information Sources

Background of the study: Information experience is a complex and multidimensional perpspective that sees the relationship between human and information. Purpose: The aim of the research is to understand the experience of person with visual impairment of Braille’iant Indonesia community when they use audiobook as information sources. Method: The research methods used was qualitative method, data collected using interview and informant were recruited through purposive sampling. Findings: Four themes emerged related to the information experience of people with visual impairment when using audiobook. The first theme is motivation which ilustrate the motivation to use audiobook, the second themes is awareness of people with visual impairment to choose information sources. The third one is access contraints that describe how they find obstacle to find the right information sources, the last theme is determining actions of participants to take actions after obtaining information from audiobook. Conclusion: The fourth theme shows information experience influenced by various factors and by the experience audiobook are not the main information sources used by participants.
Research on image matching methods in computer vision

Today, computer vision has shown a variety of roles in our lives, making people’s life more convenient. Also, a variety of artificial intelligence models and algorithms have emerged for computer vision. Image matching is an important technique in the field of computer vision to find the similarities between two images or multiple images with the help of matching algorithms to achieve scientific and accurate processing of images. Therefore, summarizing the effective approximate solution to this problem as well as the future research is the main part for current research. The paper firstly describes the basic elements of the image matching technique. Then, some representative traditional image matching algorithms proposed in the field of computer vision research in recent years are summarized and reviewed. Finally, the future research directions and research ideas of image matching are discussed, providing reliable guidance and reference for subsequent research.
The Analysis of Incomplete Business Data

Missing values can dramatically reduce the accuracy and availability of missing data, especially when analyzing business data. A common method to deal with the missing data is simply deleting the samples containing missing attributes. However, this will lead to bias and invalid conclusions since some data are too important to be omitted easily. Therefore, we should use certain methods to complete the data set instead of deleting data with missing values. In this paper, we compared several data imputation methods by adopting them to deal with six benchmark business data sets. The result provides us with guidance when dealing with incomplete business data.
Relationship Analysis COVID-19 Pandemic and cryptocurrency market with Machine Learning

The global economy receives a catastrophic blow due to the COVID-19 epidemic, with long-term pessimism shown towards the global market and exponential increasing expectation for looking for a reliable safe-haven asset. Now, it seems the possible alternatives to traditional currencies issued and backed by governments have primarily emerged - in the form of Bitcoin and Ethereum, as well as several other cryptocurrencies. Cryptocurrencies have been on the market for a long time and have been controversial in the international financial markets for their unique properties. Since the outbreak of COVID-19, the price of cryptocurrencies has seen an unprecedented increase. Whether the price increase of cryptocurrencies is linked to the COVID-19 outbreak is a mystery. This paper will focus on exploring this question through a linear regression machine learning model. The data in the U.S.A are used here. Our results show that the price of bitcoin is significantly related to the price of Ethereum. There is some correlation between covid-19 new cases incensement and the price of Bitcoin and Ethereum, indicating the legitimacy of predicting cryptocurrencies’ price using covid-19 new cases incensement as a factor.
Preface: 3rd Asia Conference on Geological Research and Environmental Technology (GRET 2022)

The organizing committees are honored to present the proceedings of the 2022 3rd Asia Conference on Geological Research and Environmental Technology (GRET 2022), held in Kamakura City, Japan during 12-13 November, 2022.&#x0D; GRET 2022 aims to bring together outstanding scholars, researchers, and students to exchange and share their experiences and research results about all aspects of earth science, geological research and environmental technology. We also provide the keynote address and several plenary invited speeches for discuss the most recent innovations, trends, and concerns, practical challenges encountered and the various solutions in these fields.&#x0D; Considering the prevention and control of COVID-19 and travel restrictions worldwide, the organizing committee adjust the format to online meeting to avoid personnel gatherings. In everyone's efforts, GRET 2022 was successfully held as scheduled. The conference model was divided into two parts, including keynote speeches and online discussion. In the first part, keynote presentations were delivered in 30 minutes for each talk. The second part was held lasted nearly an hour in a communication group for experts and scholars to discuss more about the talks and presentations.&#x0D; By submitting a paper to GRET 2022, the authors agreed to the review process and understood that papers would undergo a peer-review process. Manuscripts were reviewed by qualified experts in the field selected by the conference committee. The committees invested great efforts in reviewing the papers submitted to the conference and organizing the sessions to enable the participants to gain maximum benefit.&#x0D; We do believe your great participation will make our conference success and we would appreciate your participation. Hopefully, all participants and other interested readers will benefit or find inspirations from this proceeding.&#x0D; With our best regards,&#x0D; Conference Organizing Chair&#x0D; Kamakura City, Japan
A Continuum of Incident Classifications

The chapter begins with the classification of allegations on a continuum of egregiousness. Intake procedures are presented, with a classification and assessment of allegations listed. Investigative steps common to all cases are presented as part of the initial inquiry. Proactive investigative measures are presented to aggressively root out corruption. How to conduct an integrity test properly is identified as an important proactive measure.
Implementasi Total Quality Management (TQM) dalam Manajemen Perpustakaan di Dinas Perpustakaan dan Kearsipan Musi Banyuasin

This thesis discusses the Implementation of Total Quality Management (TQM) in Library Management at the Musi Banyuasin Library and Archives Service. This study aims to find out what the implementation strategy is, to know the inhibiting and supporting factors, and know the steps of the library in improving the quality of services at the Musi Banyuasin Library and Archives Service. The type of research used is qualitative data, which means that the data is in the form of an explanation of matters relating to the implemetation of Total Quality Management (TQM) in Library management at the Musi Banyuasin Library and Archives Service. Methods of data collection in this study in the form of observation, interviews, and documentation. The informants in this study were the head of the library, the head of the sub-divison for processing materials and library data and reporting, and five library users from Musi Banyuasn. The results of this study indicate the implementation strategy of Total Quality Management (TQM) at the Musi Banyuasin Library and Archives Service by apllying the principles of Hensler and Brunell theory consisting of customer satisfaction (users), respect for everyone, management based on facts, and improvement. Continuous. Meanwhile, efforts to improve service quality are based on the theory of Goetsch and Davis, which consist of a focus on customers, libraries to improve service quality, long-termcommitment, teamwork, education and training, freedom of control. The inhibiting and supporting factors, include funds, goverment support, training and promotion programs.
Homomorphic computing of encrypted data outsourcing in cloud data center

In the era of data explosion, data contains massive information, such as health data, time and place, hydrological waves, etc. In order to process and calculate these data, local Wang networking devices will send data to the cloud data center for outsourcing processing due to their limited storage and computing capabilities. However, our data contains a large amount of private data, so we need to protect the privacy of our outsourced data before outsourcing, so as to protect our personal privacy. At the same time, cloud data centers have strong advantages in data storage and computing capabilities, so cloud data centers are increasingly used.
Using WhatsApp in tourism ESP classes

In this paper, we will analyse the language used by a group of Tourism ESP students on WhatsApp. The data will be analysed from different perspectives: a) the grammatical mistakes made, and b) the students´ degree of adaptation to the most common linguistic features in text messages. The results indicate that these students continue to make some basic grammatical mistakes they should have already overcome. Moreover, many linguistic features of text messages were encountered in their interventions such as punctuation overuse and deletion and overuse of sounds. Finally, they insert many emojis in their messages to express different meanings.
DEVELOPMENT OF FLIPBOOK BASED SMART CARD LEARNING MEDIA IN SCIENCE LEARNING TO IMPROVE STUDENT LEARNING MOTIVATION CLASS III SD

This research is research Research and Development (R&amp;D). This study uses the Four D development model. In this study it was only carried out at the development stage. This research was conducted in class II at SD IT Hamas Stabat. The research was carried out in the even semester of the 2021/2022 school year. The subjects in this study were 20 grade II students at SDIT Hamas, 11 male students and 9 female students. The object in this study is flipbook based smart card learning media. Data collection techniques in this study were observation, interviews, tests, questionnaires and documentation. The stages in the four D development model are define, design, develop, disseminate. The results of the validation test by experts, namely media experts, were 89.00%, while the results of the material validation test were 88.06%. The results of material validation and media validation are categorized as very feasible. The results of student learning motivation on flipbook-based smart card learning media amounted to 79.07%.
PENGARUH BUDAYA LITERASI TERHADAP HASIL BELAJAR MATERI IDE POKOK KELAS V DI SEKOLAH DASAR

The ability of students in reading literacy is still low, this is indicated by the decline in student learning outcomes. This study aims to determine the effect of the implementation of literacy culture on the learning outcomes of fifth grade students in learning Indonesian. The target of this research is the students of SDN 1 Paciran class V which is divided into two classes, totaling 28 students in class VA and 28 students in class VB. Using quantitative research methods using experimental research design, namely pre-experimental design, the research design used was control-group design. Prestest Posttest Control Group Design using non-parametric data analysis techniques. In the experimental class, students were given treatment or treatment for reading literacy culture for 15 minutes before learning began, and for the control class they did not give any treatment. The results of this study indicate that there is an influence on student learning outcomes in learning Indonesian between the experimental class and the control class, which is seen from the difference in the average value of the experimental classwhich is higher than the control class.
PROGRAM LIFELONG LEARNING MERDEKA BELAJAR EDUKASI KOGNITIF MEWUJUDKAN SDGS GOAL 4 GUNA MENINGKATKAN KUALITAS SDM DI SLB MEDAN

Lifelong Learning can be experienced by every learning community. Instilling the values of academic education with the aim of improving the quality of Human Resources can trigger schools to seek to optimize innovative learning. Freedom to learn cognitive education as a reference for lifelong learning programs seeks to realize inclusive and equitable quality education. It is believed that the Sustainable Development Goals (SDGs) that spur Indonesia's human development index need to be carried out at the Markus Medan Special School. This program is conducted for Markus SLB students for 1.5 months. The method used is participatory and experimental. During its implementation, students participate in building learning activities, so that data analysis is carried out qualitatively and quantitatively. The collected data is processed interactively and continuously until the data is saturated. The data are also interpreted descriptively through quantitative data measures. The results show that Markus Special School students can participate in cognitive education learning. Continuously, student learning products always influence their learning motivation, especially the results of drawing and motor skills of students. The experimental results showed a significant difference before and after experiencing cognitive education learning activities. As many as 60% of students get test scores above average.
Recipient’s Text Interpretation Through the Explanatory Reading

Creativity cannot be effective in criticism unless the methods that give it value in literature are achieved. It is the reader who identifies the areas of creativity by drawing the features, shape, and meaning of the text. The creator does not write the text for entertainment or fun except rarely. His writing project continues, and the meaning lives with the reader in different readings, the first of which is often difficult, especially if it carries new meanings and ideas that the poets/creatives did not address previously, so he delves into words and searches for what is silent about in the text with deep interpretations and analyzes, and the second is also difficult, but with doubts. Much less than the previous one, which is an attempt to link the text with lexical allowances, or in other words, to stand on the explanation and the general meaning of the text, while some readers began searching for projections of the cultural, social and historical context, so the (reader) carries the text and drops reality on the text, content with a process of inversion of previous readings. It starts from reality and the cultural context to the text, from here the researcher adopted three readings that studied the text based on Todorov’s divisions of reading, which the researcher decided to be a method in studying this research.
Earthquake Early Warning System: A Solution for Life Rescue in Health Facilities and Risks Mitigation for the population of the Virunga Region

The desire for earthquake hazard mitigation has been the focus of many researchers and governments for decades. This is paramount because an earthquake disaster can quickly cause many injuries, fatalities, and damages. The global database of the 21,000 most devastating disasters (earthquakes included) since 1900 indicates that 50% of them with the most significant number of injuries occurred only during the past 20 years. In human history, the Xaanxi earthquake is ranked third among the disasters that claimed more lives. In addition, earthquakes contributed to six of the most deadly disasters of the past two decades and 21% of the economic losses. In the same period, the earthquakes due to the Virunga volcanic activity were responsible for more than 100 deaths and extensive material and infrastructure damage. The referenced information and statistical data about the earthquake occurrence process, adverse effects, economic losses, and the current technological success in reducing its risks through warning systems are the basis for developing this paper. The authors aim to raise awareness and recommend that the Virunga region countries (Democratic Republic of the Congo, Rwanda, and Uganda) be a good place for an Earthquake Early Warning System and Earthquake Management Plan. An Earthquake Early Warning System even caught the attention of the United Nations, where the endorsed Sendai Framework for Disaster Risk Reduction (UNISDR, 2015) specified that early warning must be a priority and has to be substantially evolved by 2030.
About Segmath, a new Cerebral Vascular Segmentation Software after CTA

Objectives: The new segmentation software Segmath delivers a 3D view of the cerebral vascular structures without superposition of bony or other structures. This will, according to the literature, improve the workflow of stroke patients and increase the occlusion detection rate on the original CTA. Materials and methods: The software written in MATLAB is based on the analysis of the local Hessian matrix with new original functions of the resulting local eigenvalues. No user intervention in the segmentation process is needed. Results: The validation of the new software yields good results both with synthetic data and real CTA’s. Conclusion: This segmentation software is a powerful additional diagnostic tool available to radiologists and neurologists examining and treating stroke patients. This will improve the workflow of suspected stroke patients.