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Inclusion of essential oils in a calf milk replacer and their effects on growth performance and the immune and oxidative systems

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Comparative Clinical Pathology 2024年第2期33卷 327-335页

作者： Nora, Luisa Giacomelli, Charles Marcon Deolindo, Guilherme Luiz Molosse, Vitor Luiz Copetti, Priscila M. Bissacotti, Bianca F. Morsch, Vera M. da Silva, Aleksandro Schafer Postgraduate Program in Animal Science State University of Santa Catarina Chapecó Brazil Graduate Program in Toxicological Biochemistry Federal University of Santa Maria Santa Maria Brazil

The use of essential oils in animal feed is increasing, but it needs to be applicable. This study determined whether a reformulated milk replacer containing a blend of essential oils composed of cinnamon, oregano, and eucalyptus improves suckling calves’ immune and oxidative systems, consequently improving productive performance. Sixteen Holstein calves (ten days old) suckled for 60 days. The animals were divided into a control group (n = 8), which received the commercial milk replacer, and a treatment group (n = 8), which received a milk replacer containing oils. The animals were fed twice daily with 0.25 kg of milk replacer diluted in two liters of water at each feeding. The milk replacer in the treatment group contained 5 g of additive per kg. The milk replacer containing essential oils had a strong aroma and odor and consequently was rejected by two calves in the treatment group. These animals were withdrawn from the experiment after five days of attempting to adapt them. The calves also received pelleted concentrate from the beginning of the experiment and chopped hay from 28 days onwards (both ad libitum). The treatment group showed more weight gain and feed efficiency than control animals. Lower lymphocyte counts were observed in calves fed milk replacers containing essential oils. Total serum protein was higher due to increased globulins in calves in the treatment group than in the control group. Serum immunoglobulin A and heavy-chain immunoglobulins were higher in the treatment group. Lower levels of lipid peroxidation and higher total antioxidants were observed in the serum of calves in the treatment group. We conclude that some animals may not adapt to the milk replacer containing essential oils due to the odor;however, the calves that consumed the milk containing the essential oils showed stimulated humoral immune responses that minimized the physiological oxidative stress of the rearing phase and consequently favored growth and weight gain. © 2024, The

关键词： 1,8-Cyneol Antioxidants Carvacrol Cinnamaldehyde Thymol

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UFCity: A Software Architecture to Create Data Ecosystem in Smart Cities

UFCity: A Software Architecture to Create Data Ecosystem in ...

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2023 Symposium on Internet of Things, SIoT 2023

作者： Pereira, Danne Brayner, Angelo Federal University of Ceara Doctoral Program in Computer Science Fortaleza Brazil Federal University of Ceara Dept. Computer Science Fortaleza Brazil

ISBN: (纸本)9798350329438

Smart city platforms manage resources and information to offer services to citizens. Developing technological solutions for this scenario is not trivial, given data and resource heterogeneity and the need for platform flexibility and adaptability. This work presents UFCity, a software architecture for smart city data ecosystems using microservices, artificial intelligence, and a three-layer networking structure. As a proof of concept, we developed a prototype and tested it in usage scenarios with real data. These use cases explored how our solution solves identified problems, showing meeting essential requirements for smart city platforms. In this way, UFCity is an alternative for data management in a smart city, presenting advantages over other solutions listed in this work in meeting the platform requirements. © 2023 IEEE.

关键词： Smart city

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Boosting Engagement and Academic Performance Through Gamification: Leveraging Student Profiles and Game Personas for Enhanced Learning 17

Boosting Engagement and Academic Performance Through Gamific...

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17th International Conference on computer Supported Education, CSEDU 2025

作者： Moura, Waldir Siqueira Delbem, Edgar França, Juliana Baptista dos Santos Dias, Angélica Fonseca da Silva Computer Science Graduate Program PPGI Federal University of Rio de Janeiro Térreo Bloco E CCMN/NCE University City Rio de Janeiro68.530 Brazil

ISBN: (纸本)9789897587467

This study examines the integration of personalized gamification as a strategy to increase student engagement and academic performance, based on the analysis of behavioral profiles and game user personas. Using Detroit: Become Human as a tool to identify collaborative and competitive tendencies, the research aims to address the limitations of traditional methods, which often fail to engage students. The application of Game Theory, combined with the personalization of pedagogical interventions according to each student's profile, enabled the creation of more adapted and motivating approaches. The final results indicate a significant improvement in grades and student engagement levels, with 38.6% of students who were initially below average reaching or exceeding expected performance, along with a marked increase in interest in classroom participation. These findings reinforce the potential of gamified and personalized methodologies to transform the educational experience, adapting it to the individual traits and needs of students. Copyright © 2025 by SCITEPRESS - science and Technology Publications, Lda.

关键词： Students

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Improving learning material repositories using student profiles

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Soft Computing 2025年第5期29卷 2417-2431页

作者： Silva Bravo, Natalie Ferraz Martins, André Ferreira de Souza Fonseca Rodrigues, Thales Brito Machado, Marcelo Bernardino, Heder Soares Vieira, Alex Borges Barbosa, Hélio José Corrêa de Souza, Jairo Francisco LApIC Research Group Federal University of Juiz de Fora Minas Gerais Juiz de Fora36036-900 Brazil Postgraduate Program in Computer Science Federal University of Juiz de Fora Minas Gerais Juiz de Fora36036-900 Brazil Postgraduate Program in Informatics Federal University of the State of Rio de Janeiro Rio de Janeiro22290-255 Brazil Department of Computer Science Federal University of Juiz de Fora Minas Gerais Juiz de Fora36036-900 Brazil

aaaa The adaptive learning community seeks to provide solutions to customize and enhance students’ learning experiences when accessing web-based learning systems. The adaptation usually occurs from the use of learning materials and user information data, which turns the adaptation process highly dependent on the quality of the repositories. Then, the best adaptation a system may offer might still not satisfy the users’ needs. In this work, we propose an approach to assist teachers and stakeholders in understanding repositories’ characteristics and their gaps according to students’ needs. Our approach, first, selects the best sequence of learning materials for each student, which is a well-known problem called Adaptive Curriculum Sequencing. Then, based on the selected sequences, we use optimization approaches, such as GRASP and Simulated Annealing, to generate new learning materials possibilities that can improve ACS recommendations. This way, our new approach assists teachers in assembling their learning materials. We have evaluated our approach by comparing it to a traditional approach using a real dataset, and the results are promising. In fact, it is possible to design customized materials using a combination of GRASP and brute force algorithms on the characteristics of the learning materials. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2025.

关键词： Federated learning

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Comparison of Spelling Error Correction Algorithms for the Indonesian Language 11

Comparison of Spelling Error Correction Algorithms for the I...

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11th International Conference on Information and Education Technology, ICIET 2023

作者： Yanfi, Yanfi Setiawan, Reina Soeparno, Haryono Budiharto, Widodo Bina Nusantara University BINUS Graduate Program Computer Science Jakarta Indonesia Bina Nusantara University BINUS Graduate Program Computer Science School of Computer Science Computer Science Department Jakarta Indonesia Bina Nusantara University School of Computer Science Computer Science Department Jakarta Indonesia

ISBN: (纸本)9781665465489

Edit distance as a string measurement metric is often used to help detect misspellings in languages. This paper aims to compare two string spelling error correction algorithms for the Indonesian language. The N-gram, Jaro-Winkler distance, and Levenshtein distance algorithms are used to determine whether they can accurately correct typological errors in the Indonesian language. Moreover, this study utilized KNIME tools to process the data from beginning to end. The data was retrieved from news in Indonesia. After the experiment on N from 1 to 12, the results obtained for the comparative analysis proved that Jaro-Winkler distance performed better than Levenshtein distance for comparing smaller strings like words and names. However, Levenshtein distance performs as well as Jaro-Winkler distance started from four strings. Finally, both Jaro-Winkler distance and Levenshtein distance algorithm got the best performance accuracy for eight strings with an accuracy of 99.52 percent. The result of this study is also presented that both algorithms can support word error correction for the Indonesian language. © 2023 IEEE.

关键词： Error correction

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A Multi-Step Multivariate Fuzzy-based Time Series Forecasting on Internet of Things Data

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IEEE Internet of Things Journal 2025年第12期12卷 21679-21690页

作者： Bitencourt, Hugo Vinicius Lucas, Patri-Cia de Oliveira Orang, Omid Silva, Petronio C. L. Guimaraes, Frederico Gadelha Universidade Federal de Minas Gerais -UFMG Graduate Program in Electrical Engineering MG Belo Horizonte31270-901 Brazil Federal Institute of Northern Minas Gerais IFNMG MG Salinas Brazil Universidade Federal de Minas Gerais -UFMG Computer Science MG Belo Horizonte31270-901 Brazil Federal Institute of Northern Minas Gerais IFNMG MG Januaria Brazil Universidade Federal de Minas Gerais -UFMG Department of Computer Science MG Belo Horizonte Brazil

Multi-step ahead time series forecasting is essential in Internet of Things (IoT) applications in smart cities and smart homes to make accurate future predictions and precise decision-making. Thus, this study introduces a novel multiple-input single-output (MISO) forecasting method called Multi-Step Embedding-based Fuzzy Time Series (MS-EFTS), designed to predict high-dimensional non-stationary time series data. As a first-order approach, it employs a direct strategy that integrates an embedding transformation with a weighted multivariate FTS (WMVFTS) model. This combination allows for effective predictions over long-term horizons within low-dimensional, learned continuous representations. The effectiveness of the proposed MS-EFTS is assessed using three high-dimensional IoT time series in this investigation. The obtained results showcase the superior performance of the proposed method compared to some deep learning forecasting methods, including LSTM, BiLSTM, TCN, and CNN-LSTM, in terms of accuracy, parsimony, and efficiency. © 2014 IEEE.

关键词： Smart homes

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Detection of Employee Fatigue Based on Image Processing Using Deep Learning Model 4

Detection of Employee Fatigue Based on Image Processing Usin...

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4th International Conference on Intelligent Cybernetics Technology and Applications, ICICyTA 2024

作者： Ethan, Michael Kusuma, I. Gede Putra Bina Nusantara University Computer Science Department Binus Graduate Program Jakarta11480 Indonesia

ISBN: (纸本)9798331506490

Fatigue in workplace is a common thing shared by all employees. Continuous exposure of fatigue could lead to negative productivity for companies. Current research on fatigue detection mostly focused to detect fatigues from a single 2D image data, meanwhile research on fatigue detection using each frames from video data is needed for better detection for fatigue process. The main advantage of using each timesteps of frames from video data which makes the model is able to predict long term dependency of fatigue person. To solve this problem, a deep learning model is proposed that could detect employee fatigue based on image processing using video data. Three models are used to train data using Convolutional Neural Network (CNN), which are Time Distributed CNN LSTM, 3D CNN, and 3D CNN LSTM. Out of those three models, the best model to detect fatigue person from video data is Time Distributed CNN Model with F-1 Score value of 0.77 and Accuracy Score of 0.76 for testing data. The model that gives best inference time is also Time Distributed CNN Model with the average value of 382 miliseconds to detect fatigues from 58 testing data with each of the data has duration of 3 seconds and 12 frames. © 2024 IEEE.

关键词： Video analysis

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Efficiency of Multi-Language Data Serialization for Hybrid Cloud-Edge HRIS 9th

Efficiency of Multi-Language Data Serialization for Hybrid C...

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9th International Conference on computer science and Computational Intelligence, ICCSCI 2024

作者： Winata, Andreas Soeparno, Haryono Gaol, Ford Lumban Arifin, Yulyani Computer Science Department BINUS Graduate Program Bina Nusantara University Jakarta11480 Indonesia

In hybrid cloud-edge systems, data processing is distributed between cloud servers and edge servers, this makes data serialization critical for efficient data transfer between servers. This study evaluates the efficiency of multi-language data serialization of Human Resources Information System (HRIS) in a hybrid cloud-edge environment. Because lack of existing studies that specifically evaluate multi-language data serialization for hybrid cloud-edge HRIS, this study conducted a Systematic Literature Review (SLR) to get the list of current state of the art of data serialization methods and then used this result to evaluate the methods. By focusing on HRIS employee data from the employee management module, this study measures both data serialization and deserialization using performance metrics of time, data size, and CPU usage. The results indicate that no methods excel in all metrics, but FlatBuffers, Protocol Buffer, and Apache Avro can provide balanced effectivity across the metrics. The study gives valuable insight for selecting data serialization methods, architecture, and systems requirements in hybrid cloud-edge HRIS to ensure the performance efficiency of the system. © 2024 The Authors.

关键词： Cloud platforms

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A model of service-oriented architecture of e-certification system to support boat registration and site visit inspection to support maritime safety and crew health inspection

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Marine Systems and Ocean Technology 2023年第1-2期18卷 45-63页

作者： Saputra, Diaz Gaol, Ford Lumban Abdurachman, Edi Sensuse, Dana Indra Matsuo, Tokuro Department of Computer Science BINUS Graduate Program - Doctor of Computer Science Bina Nusantara University Jakarta11480 Indonesia Department of Computer Science Binus Graduate Program - Master in Information System Bina Nusantara University Jakarta11480 Indonesia Department of Research in Management Bina Nusantara University Jakarta Indonesia Faculty of Computer Science University of Indonesia Jakarta Indonesia Advanced Institute of Industrial Technology Tokyo Japan City University of Macau China Asia University Taichung Taiwan

This article describes the architecture of software services that provide registration of small boat data to build maritime safety. The proposed system architecture which so-called SIMKAPEL aims to support small boat registration for maritime safety. It is developed from a conventional service-oriented architecture (SOA) with an open standard for data interoperability between elements. The goal of this research is to implement and evaluate the proposed architecture to support small boat registration and e-certification. Several parts of the architecture have been implemented as a platform that provides core services and data sources to be used by Ministry of Transportation, Directorate General of Sea Transportation, and other government agencies. Finally, the proposed SIMKAPEL platform with the SOA architecture is evaluated for its benefits to users through the expert opinion survey to measure its efficiency. The analysis results showed that SOA-based SIMKAPEL is feasible to use as a boat e-certification system. Furthermore, experiment results provide three parameters (e.g., maritime safety, namely, cargo/passengers, boat safety facilities, and maritime safety systems) with efficiency values of 42%, 46%, and 42%, respectively. The parameter with the highest efficiency shows a big effect on the level of safety of the boat and passengers. Thus, the parameters that need to be prioritized and need boat owners’ attention are cargo/passenger, boat safety equipment, and maritime safety system. © 2023, The Author(s).

关键词： Boat e-certification Boat online certification Cloud-based service Integrated system SOA architecture

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Object-Driven Fuzzy Decision Model for Assessing the Employees' Work from Home Eligibility 4

Object-Driven Fuzzy Decision Model for Assessing the Employe...

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4th International Conference on Intelligent Cybernetics Technology and Applications, ICICyTA 2024

作者： Utama, Ditdit Nugeraha Immanuel, Christiawan Bina Nusantara University Binus Graduate Program Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9798331506490

Work from Home (WFH), especially in the post-pandemic era, has emerged as an alternative work system adopted by many companies. Efficiency and effectiveness are the two main reasons why WFH is favored. In addition, the implementation of the WFH system in conducting business processes within the company allows for greater flexibility in work methods. For certain types of jobs or specific industry domains, this WFH system can be quite reliable. Workers can perform their tasks from anywhere and at any time. Also, monitoring systems enable employees to be remotely tracked by the company. However, the question remains: is an employee's work environment suitable enough to ensure the successful implementation of WFH? To answer this, a standardized model is needed to assess the level of eligibility for WFH implementation. This study aims to develop a fuzzy-based decision model to evaluate the eligibility of an employee's work environment for implementing WFH. An object-oriented approach is used to describe the design of the decision model, while fuzzy logic serves as the primary method for building the model. The model successfully simulated 24 raw employee data points, yielding a highest eligibility score of 88.61 with a similarity index of 0.78 when compared to the model proposed in previous research. © 2024 IEEE.

关键词： Personnel

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