检索结果-内蒙古大学图书馆

9th IEEE International Conference on Smart Instrumentation, Measurement and Applications, ICSIMA 2023

作者： Gunawan, Teddy Surya Kartiwi, Mira Mansor, Hasmah Yusoff, Nelidya Md. International Islamic University Malaysia Electrical and Computer Engineering Department Kuala Lumpur53100 Malaysia International Islamic University Malaysia Information Systems Department Kuala Lumpur53100 Malaysia Universiti Teknologi Malaysia Kuala Lumpur Razak Faculty of Technology and Informatics Kuala Lumpur54100 Malaysia

ISBN: (纸本)9798350343380

The significance of palm oil, which contributes 30 % of the world's total vegetable oil production, cannot be overstated. Its numerous applications, ranging from soap to cosmetics, have increased demand, thereby increasing the importance of yield management. Human graders have traditionally been responsible for determining the ripeness of oil palm fresh fruit bunches (FFBs), a task upon which the oil extraction rate (OER) relies heavily. This rate has significant economic implications: a 0.13 % drop in OER due to unripe fruits can result in a staggering RM 340 million loss. Precision is stressed, prompting automated detection research. computer vision and Artificial Intelligence are becoming more effective at assessing oil palm fruit ripeness. However, many methods require complex operations, controlled settings, or manual calibrations. Although innovative, microwave sensors and inductive techniques have drawbacks like sample preparation and equipment dependence. This study investigates the potential of the YOLOv8 framework, particularly its YOLOv8m variant, for ripeness classification and detection. This model's mAP50-95 of 0.927 balances computational efficiency and accuracy, indicating its potential to revolutionize the palm oil industry's fruit assessment procedures. The findings here shed light on the model's efficacy and highlight its potential as an industry-standard solution, bridging gaps in ripeness detection methodologies. © 2023 IEEE.

关键词： Object detection

来源：评论

学校读者我要写书评

暂无评论

Lectures on Parallel Computing

arXiv

引用

arXiv 2024年

作者： Träff, Jesper Larsson TU Wien Faculty of Informatics Institute of Computer Engineering Research Group Parallel Computing 191-4 Treitlstrasse 3 5th Floor Vienna1040 Austria

These lecture notes are designed to accompany an imaginary, virtual, undergraduate, one or two semester course on fundamentals of Parallel Computing as well as to serve as background and reference for graduate courses on High-Performance Computing, parallel algorithms and shared-memory multiprocessor programming. They introduce theoretical concepts and tools for expressing, analyzing and judging parallel algorithms and, in detail, cover the two most widely used concrete frameworks OpenMP and MPI as well as the threading interface pthreads for writing parallel programs for either shared or distributed memory parallel computers with emphasis on general concepts and principles. Code examples are given in a C-like style and many are actual, correct C code. The lecture notes deliberately do not cover GPU architectures and GPU programming, but the general concerns, guidelines and principles (time, work, cost, efficiency, scalability, memory structure and bandwidth) will be just as relevant for efficiently utilizing various GPU architectures. Likewise, the lecture notes focus on deterministic algorithms only and do not use randomization. Slides or blackboard drawings are imagined to be worked out for the actual lectures by the lecturer, so the lecture notes deliberately do not provide such important visual aid: some is available from the author on request. Also the student of this material will find it instructive to take the time to understand concepts and algorithms visually. The exercises can be used for self-study and as inspiration for small implementation projects in OpenMP and MPI that can and should accompany any serious course on Parallel Computing. The student will benefit from actually implementing and carefully benchmarking the suggested algorithms on the parallel computing system that may or should be made available as part of such a Parallel Computing course. In class, the exercises can be used as basis for hand-ins and small programming projects for which su

关键词： Parallel algorithms

来源：评论

学校读者我要写书评

暂无评论

Benchmarking Open-Source Large Language Models for Sentiment and Emotion Classification in Indonesian Tweets

引用

IEEE Access 2025年 13卷 94009-94025页

作者： Nasution, Arbi Haza Onan, Aytug Murakami, Yohei Monika, Winda Hanafiah, Anggi Universitas Islam Riau Department of Informatics Engineering Pekanbaru Riau28284 Indonesia Izmir Katip Celebi University College of Engineering and Architecture Department of Computer Engineering Izmir35620 Turkey Ritsumeikan University Faculty of Information Science and Engineering Shiga Kusatsu525-8577 Japan Universitas Lancang Kuning Department of Library Science Riau28266 Indonesia

We benchmark 22 open-source large language models (LLMs) against ChatGPT-4 and human annotators on two NLP tasks - sentiment analysis and emotion classification - for Indonesian tweets. This study contributes to NLP in a relatively low-resource language (Bahasa Indonesia) by evaluating zero-shot classification performance on a labeled tweet corpus. The dataset includes sentiment labels (Positive, Negative, Neutral) and emotion labels (Love, Happiness, Sadness, Anger, Fear).We compare model predictions to human annotations and report precision, recall, and F1-score, along with inference time analysis. ChatGPT-4 achieves the highest macro F1-score (0.84) on both tasks, slightly outperforming human annotators. The best-performing open-source models - such as LLaMA3.1_70B and Gemma2_27B - achieve over 90% of ChatGPT-4's performance, while smaller models lag behind. Notably, some mid-sized models (e.g., Phi-4 at 14B parameters) perform comparably to much larger models on select categories. However, certain classes - particularly Neutral sentiment and Fear emotion - remain challenging, with lower agreement even among human annotators. Inference time varies significantly: optimized models complete predictions in under an hour, while some large models require several days. Our findings show that state-of-the-art open models can approach closed-source LLMs like ChatGPT-4 on Indonesian classification tasks, though efficiency and consistency in edge cases remain open challenges. Future work should explore fine-tuning multilingual LLMs on Indonesian data and practical deployment strategies in real-world applications. © 2013 IEEE.

关键词： Emotion Recognition

来源：评论

学校读者我要写书评

暂无评论

Optimal, Non-pipelined Reduce-scatter and Allreduce Algorithms

arXiv

引用

arXiv 2024年

作者： Träff, Jesper Larsson TU Wien Faculty of Informatics Institute of Computer Engineering Research Group Parallel Computing 191-4 Treitlstrasse 3 5th Floor Vienna1040 Austria

The reduce-scatter collective operation in which p processors in a network of processors collectively reduce p input vectors into a result vector that is partitioned over the processors is important both in its own right and as building block for other collective operations. We present a surprisingly simple, but non-trivial algorithm for solving this problem optimally in ⌈log2 p⌉ communication rounds with each processor sending, receiving and reducing exactly p−1 blocks of vector elements. We combine this with a similarly simple, well-known allgather algorithm to get a volume optimal algorithm for the allreduce collective operation where the result vector is replicated on all processors. The communication pattern is a simple, ⌈log2 p⌉-regular, circulant graph also used elsewhere. The algorithms assume the binary reduction operator to be commutative and we discuss this assumption. The algorithms can readily be implemented and used for the collective operations MPI_Reduce_scatter_block, MPI_Reduce_scatter and MPI_Allreduce as specified in the MPI standard. We also observe that the reduce-scatter algorithm can be used as a template for round-optimal all-to-all communication and the collective MPI_Alltoall operation. Copyright © 2024, The Authors. All rights reserved.

关键词： Vectors

来源：评论

学校读者我要写书评

暂无评论

One-Shot Verification for Paper Certificates in Public Service System

One-Shot Verification for Paper Certificates in Public Servi...

引用

International Conference on Information Technology Systems and Innovation (ICITSI)

作者： Raditya Aditama Maulvi Ziadinda Maulana M. Rifki Virziadeili Harisman Agus Hariyanto Teguh T. D Susanto Faculty of Computer Science Universitas Indonesia Depok Indonesia School of Electrical Engineering and Informatics Institut Teknologi Bandung Bandung Indonesia Department of Informatics Engineering Universitas Kristen Teknologi Solo Surakarta City Indonesia Department of Educational Management Universitas Negeri Jakarta Jakarta Indonesia

ISBN: (数字)9798331511470

ISBN: (纸本)9798331511487

Even if an explosive number of proposals and prototype systems of blockchain based certificates and verification have been suggested and implemented since 2015, still in the public service areas paper certificates are prevalent. Because of advancement of color duplication and editing tools obtainable at almost no price in the internet, paper certificates are easily forged and modified. For the reason, the verification technology of the paper certificates needs need regressive research and can provide abundant research opportunities. In this research, various research suggestions and technical implementation are reviewed and a new system, called ‘one-shot’ verification is briefly described. The one-shot verification captures the image and QR code of the printed certificates with mobile devices before sending them to block-chained server. The block-chained server decides whether the printed certificates are tampered or not, with the OCR content by comparing hash value with hash value of the original content. The image OCR of the paper was trained with more than 1,700 images using YOLOv8. In the testing with preprocessing, the technology showed 96% accuracy.

关键词： Technological innovation Optical character recognition Prototypes QR codes Mobile handsets Servers Proposals Image preprocessing Information technology Testing

来源：评论

学校读者我要写书评

暂无评论

Artificial Intelligence in Next-Generation Networking: Energy Efficiency Optimization in IoT Networks Using Hybrid LEACH Protocol

引用

SN computer Science 2024年第5期5卷 546页

作者： Khan, Surbhi Bhatia Kumar, Ankit Mashat, Arwa Pruthviraja, Dayananda Imam Rahmani, Mohammad Khalid Mathew, Jimson School of Science Engineering and Environment University of Salford Salford United Kingdom Department of Information Technology Guru Ghasidas Vishwavidyalaya Chhattisgarh Bilaspur India Department of Information Systems Faculty of Computing and Information Technology King Abdulaziz University Rabigh 21911 Saudi Arabia Department of Information Technology Manipal Institute of Technology Bengaluru Manipal Academy of Higher Education Karnataka Manipal 576104 India Department of Computer Science College of Computing and Informatics Saudi Electronic University Riyadh 11673 Saudi Arabia Department of Computer Science and Engineering Indian Institute of Technology Patna Bihar Patna India

The convergence of the Internet of Things (IoT) and Artificial Intelligence (AI) is significantly transforming the landscape of future networking. The Internet of Things (IoT) is a technological paradigm that encompasses embedded systems, wireless sensors, and automation, facilitating the integration of various applications ranging from smart homes to wearable devices. In addition, the advent of artificial intelligence (AI) amplifies this influence by providing data-driven analytics, optimising processes, and presenting novel opportunities for growth. Nevertheless, the widespread adoption of devices within Internet of Things (IoT) networks gives rise to apprehensions regarding increased energy consumption. In order to ensure the longevity of network operations, it is imperative to employ energy-efficient protocols for sensor nodes that possess limited power resources. One example of a protocol that demonstrates this concept is the Low Energy Adaptive Clustering Hierarchy (LEACH) protocol. This protocol effectively divides networks into clusters and dynamically adjusts the cluster heads to optimise the transmission of data to the base stations. Our study enhances the LEACH protocol by incorporating digital twin simulation, thereby enhancing the efficiency of IoT systems. Virtual network models and AI analytics are employed to assess energy consumption and performance. Cache nodes play a crucial role within this framework as they collect data from cluster heads in order to transmit it to the base station. By leveraging artificial intelligence (AI) and simulation techniques, we are able to improve the energy efficiency and reliability of the Internet of Things (IoT) systems. The findings indicate a significant reduction of 83% in non-functioning nodes and a notable increase of 1.66 times in energy levels of nodes compared to conventional approaches. This study highlights a potential direction for energy-efficient, AI-enhanced Internet of Things (IoT) networking through

关键词： Cluster head Clustering Data aggregation Gateway Internet of things LEACH Lifetime

来源：评论

学校读者我要写书评

暂无评论

MobileDNN: Leveraging the Potential of Hybrid MobileNetV2-DNN for Advanced Image Analysis

MobileDNN: Leveraging the Potential of Hybrid MobileNetV2-DN...

引用

Science, engineering and Business for Sustainable Development Goals (SEB-SDG), International Conference on

作者： Roseline Oluwaseun Ogundokun Rytis Maskeliūnas Robertas Damaševičius Marion Olubunmi Adebiyi Department of Computer Science Landmark University Omu Aran Nigeria Department of Multimedia Engineering Kaunas University of Technology Lithuania Faculty of Informatics Kaunas University of Technology Kaunas Lithuania

ISBN: (数字)9798350358155

ISBN: (纸本)9798350358162

computer vision systems designed for posture recognition could offer valuable solutions in the healthcare sector, improving healthy ageing and supporting elderly individuals in their daily routines. One area of interest is the automatic detection of falls, which has garnered attention from computer vision and pattern recognition communities. While many existing methods rely on wearable sensors, which demonstrate high accuracy in fall detection, some individuals may be reluctant to wear such devices. Consequently, alternative approaches, such as vision-based techniques, have been developed. The proposed method utilizes a vision-based system that employs a convolutional neural network (CNN) to recognize and categorize various postures (e.g., sitting, lying, standing) in each frame, if available. This approach begins by detecting the person in the frame, applying background subtraction for human body shape extraction, and associating each daily activity with the extracted shape. The proposed model achieved an accuracy of 93.75%, which shows an outstanding performance over existing models. Subsequently, it estimates bounding boxes encompassing the predicted person's body shape. Overall, the proposed technique shows promising results for indoor monitoring systems.

关键词： computer vision Accuracy Shape computer architecture Feature extraction Convolutional neural networks Sustainable development

来源：评论

学校读者我要写书评

暂无评论

Development and Validation of Customer Intention Factors for Live-Stream Shopping 7

Development and Validation of Customer Intention Factors for...

引用

7th International Conference on New Media Studies, CONMEDIA 2023

作者： Fernando, Erick Hidayat, Desman Pengaribuan, Christian Haposan Prabowo, Yulius Denny Universitas Multimedia Nusantara Faculty of Engineering and Informatics Department of Information System Tangerang Indonesia Bina Nusantara University Binus Entrepreneurship Center Management Department Jakarta11480 Indonesia Sampoerna University Management Study Program Faculty of Business Jakarta12780 Indonesia Bina Nusantara University Binus Online Learning Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9798350307504

Along with technological improvements, online shopping is currently developing quickly. Online shops started by selling electronics, clothing, food, and home appliances and continue to evolve, selling various things. Currently, digital marketing has a novel technique, namely live shopping, where sellers can present, promote and offer their products directly through live streaming on social media and e-commerce platforms. This research will focus on gaining insight into the factors influencing customers to watch and purchase through live streaming. This research is an early-stage study of exploring and searching for research models. The study used a literature review approach by reviewing similar previous research articles. Several variable components were used in this study. The findings of the factors include visibility capacity, meta-vocation capacity, purchase orientation capacity, social presence, price, perceived product quality, perceived enjoyment, purchase orientation, perceived usefulness, and intention to buy. These factors were tested and proved to be valid with Cronbach's Alpha value being more than 0.5 and reliable with the value of the loading factor a greater than 0.6. Criteria The factors of the findings for further analysis of the relationship between factors and other variables. © 2023 IEEE.

关键词： Domestic appliances

来源：评论

学校读者我要写书评

暂无评论

A survey and recent advances in black widow optimization: variants and applications

引用

Neural Computing and Applications 2024年 1-21页

作者： Shehab, Mohammad Shambour, Mohd Khaled Yousef Abu Hashem, Muhannad A. Al Hamad, Husam Ahmad Shannaq, Fatima Mizher, Manar Jaradat, Ghaith Sh. Daoud, Mohammad Abualigah, Laith College of Computer Sciences and Informatics Amman Arab University Amman11953 Jordan The Custodian of the Two Holy Mosques Institute for Hajj and Umrah Research Umm Al-Qura University Makkah Saudi Arabia Department of Geomatics Architecture and Planning Faculty King Abdulaziz University Jeddah Saudi Arabia College of Engineering Al Ain University Abu Dhabi United Arab Emirates Research Center University of Tabuk Tabuk71491 Saudi Arabia Computer Science Department Al al-Bayt University Mafraq25113 Jordan Hourani Center for Applied Scientific Research Al-Ahliyya Amman University Amman19328 Jordan MEU Research Unit Middle East University Amman11831 Jordan Department of Electrical and Computer Engineering Lebanese American University Byblos13-5053 Lebanon School of Computer Sciences Universiti Sains Malaysia Pulau Pinang11800 Malaysia School of Engineering and Technology Sunway University Malaysia Petaling Jaya27500 Malaysia Applied science research center Applied science private university Amman11931 Jordan College of Engineering Yuan Ze University Taoyuan32003 Taiwan

Artificial Intelligence techniques, such as optimization algorithms, have become essential for success in many fields. Therefore, most researchers, especially in computer and engineering sciences, focused their efforts and abilities on adapting the optimization algorithms for solving various problems. This review introduces one of the recent nature-inspired optimization algorithms, called black widow optimization (BWO). This review highlights the main procedures of BWO, its strengths and weaknesses, the growth of BWO, the variants of BWO (i.e., binary, modification, and hybridization), and the efficiency of BWO in different fields and applications (i.e., feature selection, medical, image processing, engineering, IoT, power and energy, and networks). As a result, the review seeks to assist researchers who are interested in using the BWO to address their challenges. For instance, it could help manage large pilgrim crowds, enabling smoother ritual performances and overcoming potential difficulties they encounter. Also, it suggests new possible ways of enhancing the efficiency of the basic BWO. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2024.

关键词： Optimization

来源：评论

学校读者我要写书评

暂无评论

Aspect-Based Subjectivity Analysis Using a BERT-Based Approach

Aspect-Based Subjectivity Analysis Using a BERT-Based Approa...

引用

IEEE International Conference on Industry 4.0, Artificial Intelligence, and Communications Technology (IAICT)

作者： Hu Ng Wing Kin Chong Yu Zhang Chia Timothy Tzen Vun Yap Vik Tor Goh Lai Kuan Wong Ian Kim Teck Tan Dong Theng Cher Faculty of Computing and Informatics Multimedia University Cyberjaya Malaysia School of Mathematical & Computer Sciences Heriot-Watt University Putrajaya Malaysia Faculty of Engineering Multimedia University Cyberjaya Malaysia SIRIM Berhad Shah Alam Malaysia

ISBN: (数字)9798350353464

ISBN: (纸本)9798350353471

Aspect-based subjectivity analysis stands as an important task in natural language processing, seeking to identify the subjectivity of various aspects or features within a text. A new method for aspect-based subjectivity analysis using BERT is introduced in this paper. BERT has demonstrated impressive performance across various NLP tasks, and its capabilities are utilized to accurately ascertain the subjectivity of specific aspects within a given text. The approach involves fine-tuning BERT on a sizable dataset annotated with aspect-level subjectivity labels, enabling the model to grasp the subtleties of aspect-based subjectivity analysis. Extensive experiments on benchmark datasets are conducted to showcase the effectiveness of this approach and compare it with existing methods. The results reveal that this proposed approach surpasses state-of-the-art techniques in aspect-based subjectivity analysis, underscoring the potential of leveraging BERT for such purposes.

关键词： Analytical models Sentiment analysis Accuracy Predictive models Benchmark testing Robustness Communications technology

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：