检索结果-内蒙古大学图书馆

2nd International Conference on Machine Learning and Autonomous Systems, ICMLAS 2025

作者： Gonia, Diana Hannah F. Jamodiong, Marjore I. Yadao, Haidee M. Paquiao, Lord Ian M. Pandiin, Jamel D. Cabagay, Daryll A. ACLC College of Butuan Information Technology Program Computer Education Department Butuan City Philippines

ISBN: (纸本)9798331505745

The ScaNana project delves into the innovative use of image recognition technology to realize the full potential of scanned banana varieties, with a special focus on Lakatan, Latundan, and Saba. By combining cutting-edge machine learning techniques and practical applications, the project seeks to address pressing challenges in the banana industry. Its primary objective is to develop a user-friendly tool capable of accurately identifying different banana types while recommending a wide array of products that can be made from them. This approach aims to minimize food waste, foster creativity in recipes, and expand bananas' culinary and commercial possibilities. The system employs Convolutional Neural Networks (CNNs) for image classification, leveraging the capabilities of TensorFlow and Teachable Machine for model training. TensorFlow Lite (TFLite) is integrated to enable efficient processing on mobile devices, ensuring that users can access the platform conveniently without needing high-end hardware. Meanwhile, OpenCV enhances image recognition accuracy, making the system reliable and precise. ScaNana aspires to provide an accessible and intuitive platform that allows users to scan bananas, identify their varieties, and explore their potential uses. The project evaluates its functionality, reliability, usability, and efficiency to ensure high performance and user satisfaction. By bridging the gap between technology and sustainability, ScaNana promotes innovation, productivity, and the sustainable use of bananas in culinary arts, product development, and other commercial applications. This initiative champions a greener, more resource-efficient future for the banana industry. © 2025 IEEE.

关键词： Rapid prototyping

来源：评论

学校读者我要写书评

暂无评论

Predicting Dry Matter Intake in Lactating Crossbred Cows Under Semi-Arid Conditions Using an Error-Based Evolving Takagi-Sugeno Fuzzy Model

引用

IEEE Access 2025年 13卷 71521-71529页

作者： Leal, Dijair B. Soares, Rafael A. Junior, Vicente R. Rocha Moncao, Flavio P. Camargos, Murilo O. D'Angelo, Marcos F. S. V. Miralles-Pechuan, Luis UNIMONTES Graduate Program in Animal Science Montes Claros39401-089 Brazil UNIMONTES Graduate Program in Computer Modeling and Systems Montes Claros39401-089 Brazil UNIMONTES Department of Agricultural Sciences Minas Gerais Montes Claros39401-089 Brazil UNIMONTES Department of Computer Science Minas Gerais Montes Claros39401-089 Brazil Technological University Dublin School of Computer Science Dublin 8 D07 EWV4 Ireland

Accurately predicting dry matter intake (DMI) in lactating crossbred cows under semi-arid conditions is a critical challenge in dairy farming. Precise DMI predictions are essential for optimizing nutrient utilization and enhancing animal performance, particularly in semi-arid environments, where complex and dynamic conditions prevail. This paper introduces a novel Error-Based Evolving Takagi-Sugeno (EBETS) Fuzzy Model designed to address these challenges by dynamically adapting to real-time data and leveraging both current and historical information to enhance prediction accuracy. The EBETS model employs fuzzy set theory and multivariate Gaussian functions to model complex, nonlinear relationships between variables, offering a more robust and flexible approach to DMI prediction. In experiments involving data from 114 crossbred cows under semi-arid conditions, the EBETS model was compared to traditional models and an artificial neural network. It achieved a mean squared error of 0.25, which is more than 90% lower than that of all the other models, while demonstrating a higher correlation coefficient with the expected values, indicating superior predictive performance and reliability. These results underscore the EBETS model’s substantial superiority over existing methods, highlighting its potential to significantly improve dairy farming productivity by providing precise and reliable DMI predictions in challenging environmental conditions. The model’s ability to continuously learn and adapt to changing conditions makes it a promising tool for various applications in agricultural science. © 2013 IEEE.

关键词： Prediction models

来源：评论

学校读者我要写书评

暂无评论

Photovoltaic Fault Detection in Remote Areas Using Fuzzy-Based Multiple Linear Regression (FMLR)

引用

International Journal of Advanced computer Science and Applications 2025年第4期16卷 243-249页

作者： Ardianto, Feby Ermatita, Ermatita Sofijan, Armin Doctoral Program in Engineering Science Universitas Sriwijaya Palembang Indonesia Faculty of Computer Science Universitas Sriwijaya Palembang Indonesia Faculty of Engineering Universitas Sriwijaya Palembang Indonesia

This research focused on developing and implementing a fault detection model for photovoltaic (PV) systems in remote areas, utilizing a Fuzzy-Based Multiple Linear Regression (FMLR) approach. The study aimed to address the challenges of monitoring PV systems in locations with limited access to conventional power grids and technical resources. The fault detection system integrated environmental parameters such as solar radiation, temperature, wind speed, and rainfall, alongside PV system parameters like panel voltage, current, battery voltage, and inverter performance. Data collection and preprocessing were conducted over a specified period to identify operational patterns under both normal and faulty conditions, ensuring data accuracy through cleaning, normalization, and categorization. The research was conducted in Pandan Arang Village, Kandis District, Ogan Ilir Regency, South Sumatera, Indonesia, contributing to the improvement of reliability and sustainability of renewable energy sources in isolated communities. The total number of data points for 276 rows with 6 attributes each was 1656 records. The MLR model was developed to predict the output power of the PV system, while fuzzy logic was employed to handle uncertainties in the data, offering a more flexible and adaptive decision-making process. The system applied fuzzy rules to determine the charging status (P3), categorizing it into Optimal Charging, Adjusted Charging, Charging Delay, or Fault Alert. The model was tested with real-time data, and its performance was validated through comparison with manual inspections. The results showed that the FMLR-based fault detection system effectively identified faults and optimized the performance of the PV system, making it suitable for remote areas in South Sumatera. © (2025), (Science and Information Organization). All Rights Reserved.

关键词： Multiple linear regression

来源：评论

学校读者我要写书评

暂无评论

Perfomance Improvement of mpdCNN as Ensemble Learning Model on Low Resolution Image-Face Recognition System 8

Perfomance Improvement of mpdCNN as Ensemble Learning Model ...

引用

8th International Conference on Electronics, Materials Engineering and Nano-Technology, IEMENTech 2025

作者： Wangean, Daniel Anando Suhartono, Derwin Bina Nusantara University Master of Computer Science Binus Graduate Program Jakarta Indonesia School of Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9798331520762

Low resolution image-face recognition system is one of the challenging aspects of face recognition models' development. From machine learning, deep learning, and into ensemble learning are implemented to develop face recognition models. Including mpdCNN that published by Mishra in a journal article. This mpdCNN already achieved 88.6% accuracy score on SCFace dataset while published. Based on literature review, ensemble learning model can be improved by modifying parallel layers. The purpose of this research is to improve mpdCNN's performance by implementing some modifications include adding parallel layers, alternating the fusion layers, expanding the layers, and adding residual connections. Some modifications were successfully improved mpdCNN's accuracy score. By adding parallel layers and residual connections into mpdCNN's architecture, the modified mpdCNN that proposed in this research achieved 92.33% accuracy score, measured by Rank-k evaluation metric. © 2025 IEEE.

关键词： Face recognition

来源：评论

学校读者我要写书评

暂无评论

Remote Sensing Scene Classification Based on Hybrid Convolutional Neural Network and Attention Module

Remote Sensing Scene Classification Based on Hybrid Convolut...

引用

2025 International Conference on Advancement in Data Science, E-learning and Information System, ICADEIS 2025

作者： Kardawi, Muhammad Yusuf Gunawan, Alexander Agung Santoso Bina Nusantara University Profesional Engineer Program Faculty of Engineering Jakarta11480 Indonesia Faculty of Computer Science University of Indonesia Computer Science Department Jakarta Indonesia School of Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9798331513320

Remote sensing images present classification challenges due to the complexity of their structural and spatial patterns. This research explores a hybrid approach that combines convolutional neural network (CNN) and attention through feature fusion to improve scene classification accuracy in remote sensing images. The proposed architecture utilizes EfficientNet and VGGNet to extract depth features separately. The extracted features are then integrated with Dynamic Selfattention (DSA), which dynamically focuses the model on the most relevant information in the image. DSA allows the model to adaptively assign weights to different parts of the image, thus improving the discriminative ability of the model. Furthermore, a feature fusion technique is applied to combine information from different layers of the CNN and DSA modules. Experiments conducted on the UC Merced dataset showed accuracies of 0.9181 and 0.9167. These results show that the combination of CNN, DSA, and feature fusion is an effective and robust approach for remote sensing image classification. © 2025 IEEE.

关键词： Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

ATMAE to ABET accreditation: An assessment transition in an electronics and computer engineering technology program 123

ATMAE to ABET accreditation: An assessment transition in an ...

引用

123rd ASEE Annual Conference and Exposition

作者： Kolla, Sri R. Border, David Bowling Green State University Electronics and Computer Engineering Technology Program OH United States Bowling Green State University United States

Bowling Green State University currently offers an ETAC-ABET accredited undergraduate Bachelor of Science degree in Electronics and computer Engineering Technology. The program was previously accredited by ATMAE with the name Electronics and computer Technology in the Bachelor of Science in Technology degree. The program faculty has decided to seek ABET accreditation due to the professional engineer registration our students can seek and other reasons. This paper presents the process adopted by the ECET program faculty to use the past ATMAE accreditation practices to present ABET accreditation. A hallmark of our program has been the mandatory two-semester long co-op experiences and an optional third-semester co-op experience, which has served as an important tool along with our in-class course instruction and laboratory experience for the success of our students. Our program educational objectives review and student outcomes assessment of ABET's Engineering Technology Accreditation Commission general 'a to k' criteria and Electrical/Electronic(s) Engineering Technology, and computer Engineering Technology program specific criteria use four direct and indirect quantitative methods and additional qualitative methods. The direct quantitative methods include: course-embedded assessment, course final grades, co-op employer student performance appraisal;and the indirect quantitative method is an end of semester student course evaluation. The qualitative methods include student co-op report feedback, industrial advisory board input, and alumni input in addition to regular input from faculty. This paper describes how the data from these methods are used for assessment and continuous improvement that resulted in a successful maximum ABET accreditation period for our ECET program. © American Society for Engineering Education, 2016.

关键词：

来源：评论

学校读者我要写书评

暂无评论

The development of a summer study abroad program for engineering and computer science students at Baylor University

The development of a summer study abroad program for enginee...

引用

34th Annual Frontiers in Education: Expanding Educational Opportunities Through Partnerships and Distance Learning - Conference Proceedings, FIE

作者： Fry, Cynthia C. Maastricht Summer Study Abroad Program School of Engineering and Computer Science Baylor University One Bear Place #97356 Waco TX 76798

The Baylor In Maastricht (BIM) Summer Study Abroad program is a 41-day study abroad program in the Netherlands. Baylor In Maastricht is a summer program that is sponsored by the School of Engineering and Science of Baylor University in Waco, Texas, in conjunction with the Universiteit Maastricht, in the Netherlands. The program gives engineering and computer science students an opportunity to take two Baylor courses (six hours), while also providing an abroad experience in the heart of Europe. It also answers the charge given four years ago by the Dean of the School of Engineering and computer Science to get our students out of the building! This paper will discuss the goals and objectives of such a program, and will chronicle the design, development, and execution of the resulting study abroad program. We will explore, in depth, the number and type of participants, the details of trip planning and organization, the decision on which courses to offer, planned weekend group trips, the facilities and support of the Universiteit Maastricht, and accommodations. This paper will also discuss the execution of the first two study abroad programs to Maastricht, the Netherlands - what worked, what didn't work, what was good, where we have improved. A summary of the student evaluations from the program is included. © 2004 IEEE.

关键词： Engineering education

来源：评论

学校读者我要写书评

暂无评论

Challenges and Recommendations for Improving Logistic Skills Through Simulation-Based Learning Technology

Challenges and Recommendations for Improving Logistic Skills...

引用

2025 International Conference on Advancement in Data Science, E-learning and Information System, ICADEIS 2025

作者： Sirait, Tamsir Hasudungan Meyliana Arifin, Yulyani Yulianto, Budi Bina Nusantara University Binus Graduate Program Jakarta Indonesia Bina Nusantara University Computer Science Department Jakarta Indonesia

ISBN: (纸本)9798331513320

Simulation-based learning is one of the most powerful tools to support the educational process. This learning offers an opportunity to learn based on experiences that are very similar to real-world environments. In the context of logistics, which can be considered a complex system, significant efforts are required to enhance students' understanding and practical skills. For that reason, simulations are used so that benefits such as skills and knowledge in the field of logistics can be achieved. However, there are currently several challenges in developing simulation-based learning in higher education. These challenges include the need for simulations that are appropriate for the current learning context, where the students are generally from Generation Z, and how to improve their learning quality in the era of Industry 4.0. To address these challenges, more suitable simulations need to be developed, and higher education institutions must carefully examine how to develop them, including identifying the essential components in the development of simulations for logistics learning. In this research, a systematic literature review using the PRISMA method and also creating a conceptual model of simulation that better meets the current needs of logistics education will be proposed. The results of this research can be used as a basis for developing updated simulations to better prepare students for the challenges of Industry 4.0. © 2025 IEEE.

关键词： industry 4.0 logistics simulation development simulation learning simulation learning component

来源：评论

学校读者我要写书评

暂无评论

Rate Distortion Analysis of Wavefield Coding in Wireless Geophone Networks 8th

Rate Distortion Analysis of Wavefield Coding in Wireless G...

引用

8th EAI International Conference on Smart Grid and Innovative Frontiers in Telecommunications, SmartGIFT 2024

作者： Khan, Hamood ur Rehman Khan, Farhan Sir Syed Center for Advanced Studies in Engineering Islamabad Pakistan Electrical and Computer Engineering Program Habib University Karachi Pakistan

ISBN: (纸本)9783031788055

Current and future trends in seismic acquisition point towards higher geophone densities (forecasted to be 1M nodes per survey). The geophones’ high operating precision and a sampling rate of a few milliseconds leads to a huge aggregate data rate in the geophone array. To handle this large data rate a hierarchy of multiplexed lines (including fiber optic cables) are used, resulting in substantial deployment costs. This work considers wireless geophone networks to mitigate these costs. Because of limited bandwidth of the wireless medium, compression of acquired data is needed. We assess lossy source coding (signal compression) performance using a rate-distortion tradeoff based on a physical model of the earth. The distortion criterion used is mean squared error. The earth’s physical model considered here consists of a randomly layered subsurface structure where the acoustic impedance of the earth varies as a homogeneous spatial random process. The rate distortion performance is assessed in terms of the parameters of this physical model e.g., the speed of sound underground and correlation length of acoustic impedance process. In comparison with previous work, this paper derives a closed form expression for the autocorrelation function for the reflection process for the 3D subsurface volume. We also show from the resulting rate-distortion curves that the compression performance improves both as the coding bock length increases and as the correlation length of the medium properties increases. The rate-distortion surface as a function of normalized MSE and sound of speed underground is also computed and validated through extensive simulations. © ICST Institute for computer Sciences, Social Informatics and Telecommunications Engineering 2025.

关键词： Signal distortion

来源：评论

学校读者我要写书评

暂无评论

TaxDiff: taxonomic-guided diffusion model for protein sequence generation

引用

Science China(Information Sciences) 2025年第4期68卷 385-386页

作者： Zongying LIN Hao LI Liuzhenghao LV Yu WANG Bin LIN Junwu ZHANG Zijun CHEN Calvin Yu-Chian CHEN Li YUAN Yonghong TIAN School of Electronic and Computer Engineering Peking University AI for Science (AI4S)-Preferred Program Peking University Shenzhen Graduate School Peng Cheng Laboratory School of Chemical Biology and Biotechnology Peking University

Protein design aims to generate protein variants with targeted biological functions, which is significant in multiple biological areas, including enzyme reaction catalysis, vaccine design, and fluorescence intensity. Protein design contains two paradigms: sequence generation and structure generation. Recently, EvoDiff [1] proposed a universal designing paradigm, combining structure and sequence generation using the diffusion framework, which improves the protein design efficiency.

关键词：

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：