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6th International Conference on Industry 4.0 and Smart Manufacturing, ISM 2024

作者： Putri Ardyanti, Anak Agung Ayu Xie, Zhiqiang Karnyoto, Andrea Stevens Pardamean, Bens Estiyanti, Ni Made School of Computer Science and Technology Harbin University of Science and Technology Harbin150000 China Faculty of Information Technology and Design Primakara University Bali 80226 Indonesia Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta11480 Indonesia Computer Science Department BINUS Graduate Program Master of Computer Science Bina Nusantara University Jakarta 11480 Indonesia School of Management and Business University of Debrecen Debrecen Hungary

The industry is rapidly transitioning from the 4.0 era to the 5.0 era, prompting renewed interest among scholars in scheduling problems. They allow operations to process and assemble various components simultaneously. This bibliometric analysis provides a comprehensive understanding of the diverse research perspectives on the potential challenges of integrated scheduling within the framework. We identified 357 Scopus articles and analysed co-occurrence keyword (CNK) by VOSViewer tools and Global Citation Score (GCS) by Scopus tools. The research data obtained from 1993 to 2023 mainly in the subject areas of Engineering, Computer Science, Maths, and others. CNK identified six cluster keywords, and nine most cited articles based on normalised GCS. These results contribute to our understanding of the development of scheduling algorithms, shifting from an emphasis on manufacturing transfers to contemporary demand-centric research directions. Furthermore, this research provides a valuable perspective for policymakers, plant personnel, and manufacturing managers to make informed decisions. © 2025 The Authors. Published by Elsevier B.V.

关键词： Job shop scheduling

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Mapping the Scientific Landscape of Integrated Scheduling Towards Industry 5.0 with A Bibliometric Analysis

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Procedia Computer Science 2025年 253卷 84-93页

作者： Anak Agung Ayu Putri Ardyanti Zhiqiang Xie Andrea Stevens Karnyoto Bens Pardamean Ni Made Estiyanti School of Computer Science and Technology Harbin University of Science and Technology Harbin 150000 China Faculty of Information Technology and Design Primakara University Bali 80226 Indonesia Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta Indonesia 11480 Computer Science Department BINUS Graduate Program - Master of Computer Science Bina Nusantara University Jakarta Indonesia 11480 Doctoral School of Management and Business University of Debrecen Debrecen Hungary

关键词： integrated scheduling assembly job shop scheduling heuristic algorithm genetic algorithm bibliometric analysis

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Classification machine learning with chromagram and word embedding feature

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AIP Conference Proceedings 2025年第1期3223卷

作者： Thoyyibah Ines Heidiani Ikasari Perani Rosyani Wasis Haryono Sofa Sofiana Neny Rosmawarni Information Systems Management Department BINUS Graduate Program-Master of Information System Management Bina Nusantara University Jakarta Indonesia 11480 Information Technology University of Pamulang Banten South Tangerang Indonesia Faculty of Information Technology Veterans National Development University Jakarta Jakarta Indonesia

Indonesia is a country that is rich in artistic diversity. This art can be a song. In addition to traditional songs, Indonesia is rich in songs from various genres. Some of the genres used by the author are pop, ballad, dangdut. Song or music has become an interesting area of research in computer science. Music recognition is a computational problem in the field of computer vision. Music introduction aims to classify music into several categories such as genre, mood, or music generation. Although in the last ten years a number of studies have been published, the problem of music recognition is still a difficult problem to solve by computers. In addition, it is necessary to explore several features that represent music, including audio spectrograms, chromagrams, and song lyrics. The author processes the lyrics and audio features in the form of a chromagram using many songs. Music can be a collection of data that can be processed by machine learning. The data used for classification is song data in the form of datasets. The author uses his own dataset or manual methods in collecting and processing datasets. The song is downloaded from YouTube after that it is converted into mp3 and cut. The author processed 1181 songs from the 70’s and 80’s era which only took the chorus part. Lyrics in chorus form are saved in excel. The audio chorus is saved in .wav. The results of the Mood classification used by the author in music consist of 3, namely happy, sad and neutral which are processed using machine learning. Using 2 experiments on Chromagram and word embedding feature has a higher value of 81%.

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An approach to parameter optimizer for music mood classification in machine learning

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AIP Conference Proceedings 2025年第1期3223卷

作者： Nunik Destria Arianti T. Thoyyibah Achmad Udin Zailani Neny Rosmawarni Rinna Rachmatika Achmad Lutfi Fuadi Information System University of Nusaputra Sukabumi Indonesia Information Systems Management Department BINUS Graduate Program-Master of Information System Management Bina Nusantara University Jakarta Indonesia 11480 Information Technology University of Pamulang Banten Indonesia Faculty of Information Technology Veterans National Development University Indonesia

Music is a blend of the human voice and instruments that bring beauty to the listener. Many people like music to create an atmosphere or atmosphere. In the field of computer science, with a lot of data, music is an object that can be studied both through lyrics, audio, biographies and others. This research focuses on the mood of Indonesian music in the 70s and 80s. The data set used consists of text data and audio data. The mood tested consisted of sad, happy and neutral. This area of interest was investigated using the Crisp-DM method derived from business understanding, data understanding, data preparation, modelling, evaluation, deployment. In building the Confusion Matrix, this study uses several parameters, namely epoch, dimensions, set size, learning rate and others. The value generated by the confusion matrix contains a good 85 % value.

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Integrating teaching, research and problem solving: An experience in progress at Mucuri Valley region (Brazil) 21

Integrating teaching, research and problem solving: An exper...

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21st World Multi-Conference on Systemics, Cybernetics and Informatics, WMSCI 2017

作者： Barroso, Leônidas Graduate Program in Information Systems and Knowledge Management Universidade FUMEC Belo Horizonte Brazil

ISBN: (纸本)9781941763599

This short article describes an interdisciplinary project that seeks to integrate teaching, research and real life problem solving. It concerns to the question: how to achieve development respecting the natural resources of the Mucuri Valley region in the states of Minas Gerais and Bahia, Brazil. Using geographic information as a guiding axis, the technological support for interdisciplinary dialogues is provided by Geographic information Systems, integrating data, information, techniques, methods and people from different fields of knowledge. © by the International Institute of Informatics and Systemics.

关键词： Geographic information systems

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Reproducing ATT&CK Techniques and Lifecycles to Train Machine Learning Classifier

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IEEE Network 2025年

作者： Yudha, Fietyata Lin, Ying-Dar Lai, Yuan-Cheng Sudyana, Didik Hwang, Ren-Hung EECS International Graduate Program National Yang Ming Chiao Tung University Hsinchu City300 Taiwan Department of Computer Science National Yang Ming Chiao Tung University Hsinchu City300 Taiwan The Department of Information Management National Taiwan University of Science and Technology Tapei106 Taiwan The Computer and Network Center National Cheng Kung University Tainan701 Taiwan The College of Artificial Intelligence National Yang Ming Chiao Tung University Tainan711 Taiwan

he MITRE ATT&CK framework categorizes threat actor behaviors into a sequence of techniques called the attack lifecycle. Based on this, Our work introduces a dual-labeled dataset that is accurately labeled with distinct techniques and lifecycles defined by ATT&CK. The dataset offered a more thorough perspective than previous datasets that employed binary or attack classification. It encompassed 17 distinct techniques throughout five lifecycles and was generated through an automated method that guarantees reproducibility and learnability. Reproducibility guarantees the dataset’s consistency, whereas learnability signifies its use in training machine learning models. Our analysis produced a positive result. The dataset achieved a Pearson correlation coefficient of 0.7 for reproducibility. Regarding distinguishing classes, it exhibits an average AUC-ROC score of 0.92 for techniques and 0.82 for lifecycles. The model training yielded an average F1 score of 0.95 for technique classification and 0.9 for lifecycle classification, but only for the traffic dataset. © 1986-2012 IEEE.

关键词： Adversarial machine learning

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The second half of my life 9

The second half of my life

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9th International Multi-Conference on Complexity, Informatics and Cybernetics, IMCIC 2018

作者： Barroso, Leônidas Conceição Graduate Program in Information Systems and Knowledge Management FUMEC University Belo Horizonte Minas Gerais Brazil

ISBN: (纸本)9781941763766

It is a brief description of the author's professional trajectory, living the second half of his life. This reflection was motivated by the plenary lecture delivered by Ira Blatstein at the 9th International Conference on Society and information Technologies under the title "Strategic Planning for the Second Half of Your Life". © 2018 International Institute of Informatics and Systemics IIIS. All rights reserved.

关键词： Strategic planning

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A contribution to a multimodal approach to knowledge modeling

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Pattern Recognition and Image Analysis 2014年第3期24卷 395-399页

作者： Guadagnin, R. MS Program in Information Technology and Knowledge Management Catholic University of Brasilia Campus II SGAN 916 Norte Brasilia DF70.790-160 Brazil

At present a steep increase in efforts by human beings in search of information take place. Pattern Recognition extracts information from the real world. It is a tool for modelling and real-world learning. Thus it requires precise knowledge of the objectives to be achieved with the information it produces. Human senses are part of their interface with the environment. Our senses are signal encoders according some representation that is understood by the central nervous system. Multimodality in signal capturing makes the spectrum of activities of intelligent agents wider. This paper aims to stimulate research for providing multimodal information, say, information that can be captured by different senses. This technique can improve decision-making;promote the inclusion of sense disabled individuals, giving higher amplitude for usefulness of Pattern Recognition. It considers multimodal display of knowledge to practical feasibility of knowledge presentation adapted to human sensing and perception towards decision improvement and inclusion of perception-impaired people. © 2014, Pleiades Publishing, Ltd.

关键词： Intelligent agents

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Inference of pressure ulcer stage and texture on an image training set

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Pattern Recognition and Image Analysis 2016年第3期26卷 558-564页

作者： Guadagnin, R.V. Santana, L.A. Neves, R.S. MSc Program on Information Technology and Knowledge Management Catholic University of Brasília Brasília DF Brazil MSc Program on Sciences for Health at School of Health Sciences Brasília DF Brazil Head of Scientific Starting Program–PIBIC Health Sciences Graduate School Brasília DF Brazil

Health assistance depends essentially on effective information providing for professionals. Presently visual information plays an outstanding role concerning patients’ status without necessity of invading procedures. The diagnosis related to stage and texture in pressure ulcers (PU) is considered as a classification procedure, based on the image colors. As a training set this study captured 18 PU images from nine persons. RGB mean values were adopted as features to characterize the images. Classification used an ID3 similar algorithm. It achieved 83.3% accuracy concerning color and stage, as well as 88.9% concerning color and texture. So the technique was effective for automatic determination of PU stage and PU texture based on its color. © 2016, Pleiades Publishing, Ltd.

关键词： Color

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Cultural heritage objects: A model of the patrimonialization process 17

Cultural heritage objects: A model of the patrimonialization...

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17th Seminar on Ontology Research in Brazil, ONTOBRAS 2024 and 8th Doctoral and Masters Consortium on Ontologies, WTDO 2024

作者： Marcondes, Carlos H. Graduate Program of Knowledge Management & Organization School of Information Science Federal University of Minas Gerais MG Belo HorizonteCEP 31270-901 Brazil

Patrimonialization is the process through which an object is integrated within a heritage institution’s collection. More than a simple and bureaucratic process of listing an object, of registering it in the registry book, patrimonialization is the process through which a primary object has its cultural value recognized, is integrated into the scope of a specific discipline, and thus, to culture in general, becoming witnesses and representatives of the original context from which they came from, becoming secondary documents or objects. A conceptual model of the patrimonialization process through which an object became a heritage object is proposed. The model emphasizes the role of the Patrimonialization Justification, a paradata dossier in documenting the decisions, criteria, and justifications of a curator to assign to an object the status of a cultural heritage object and incorporate it in the collection of a heritage institution. The model reuses classes and properties of other ontologies to contextualize the patrimonialization process and the documents involved, including the references that support the curator’s decision to patrimonialize an object and include it in a heritage collection. © 2024 Copyright for this paper by its authors.

关键词： Conceptual model Digital Cultural Heritage Object Documentation Heritage paradata Patrimonialization

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