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2nd International Symposium on computer Applications and Information Systems, ISCAIS 2023

作者： Gao, Yingning Liu, Weisheng School of Computer and Software Engineering Liaoning University of Science and Technology Liaoning Anshan China

ISBN: (纸本)9781510666665

The label is used to mark the object information or classification of the logo, complex label then contains more layout information than ordinary labels. These include Chinese and English characters, pictures, symbols and barcodes. When text detection is performed in complex labels, the detection capability of the algorithm is reduced and is prone to feature overlap resulting in missed and false detection. In this paper, the original YOLOv5 algorithm is optimized by an improved channel attention mechanism to form the new algorithm SA-YOLOv5. The experimental results show that the SAYOLOv5 model can effectively improve detection efficiency and solve the problem of false and missed detections. The average detection accuracy mAP value is 92.24%, which is 0.68 percentage points higher than the original algorithm, proving the effectiveness of the algorithm. © 2023 SPIE.

关键词： Classification (of information)

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A Double MCDM-GIS Analysis for Solar Power Plant Site Selections in Disaster-Prone Area: A case study of Hawkes Bay

A Double MCDM-GIS Analysis for Solar Power Plant Site Select...

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2023 International Conference on Power and Renewable Energy engineering, PREE 2023

作者： Rahayani, Rizki Dian Nair, Nirmal-Kumar C University of Auckland Computer and Software Engineering Dept. Electrical Auckland New Zealand

ISBN: (纸本)9798350321906

Selecting an appropriate site for solar power plants is a critical long-term investment decision to maximize solar energy generation while minimizing investment and operational costs and ensuring environmental sustainability. While solar irradiance has traditionally been the primary factor in site selection, accounting for disaster risk assessment is becoming increasingly crucial, particularly in countries prone to natural disasters. Hawkes Bay, New Zealand, holds great promise as a region with high solar potential. Yet, it is susceptible to natural disasters like earthquakes, landslides, and floods. This research aims to identify the most suitable solar farm location in Hawkes Bay by integrating estimated solar energy production with disaster risk assessment. The study employs a two-stages multi-criteria decision-making (MCDM) approach, combining data envelopment analysis (DEA) and the analytical hierarchy process (AHP), alongside the utilization of geographical information system (GIS) technology. The finding, among 15 candidate locations, the area in a 5 km radius of Te Haroto weather station has the most potential for solar PV farms. 82 % of the location has low disaster risk, and only 7% of the area is considered high risk. © 2023 IEEE.

关键词： Disasters

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Utilizing Evidential Reasoning (ER) Approach for software Components Selection

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SN computer Science 2025年第3期6卷 1-13页

作者： Ahmad, Nabot Al-Qerem, Ahmad Omar, Firas Jebreen, Issam Department of Software Engineering Al Zaytoonah University of Jordan Amman Jordan Computer Science Department Zarqa University Zarqa Jordan Business Intelligence Department Al Zaytoonah University of Jordan Amman Jordan Software Engineering Department Middle East University Amman Lebanon

software component selection is one of the most challenging problems for software developers to meet customer needs. Despite various methods researchers propose to aid in component selection, a gap exists in addressing the complexities of decision-making under uncertainty. This study utilizes the Evidential Reasoning (ER) approach, which effectively handles multi-criteria decision-making (MCDM) scenarios to evaluate software components for an online bookstore. The methodology involves assessing quality attributes using the ER approach incorporating evaluation grades, weights, and belief degrees to manage information uncertainty. The results demonstrate that the ER approach provides a robust framework for software component selection leading to informed decisions. This approach offers significant advantages in scenarios where traditional MCDM methods are insufficient, thereby enhancing the reliability of component selection in software engineering. © The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. 2025.

关键词： Decision making Evidential reasoning Multi-criteria software component

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Colorectal Cancer Diagnosis with Deep Learning Models 28

Colorectal Cancer Diagnosis with Deep Learning Models

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28th World Multi-Conference on Systemics, Cybernetics and Informatics, WMSCI 2024

作者： Taşci, Merve Esra Elmi, Zahra Albayrak, Ömer Faruk Tokat, Mustafa Software Engineering Department Sabahattin Zaim University Istanbul34303 Turkey Computer Engineering Department Sabahattin Zaim University Istanbul34303 Turkey

ISBN: (纸本)9781950492794

The third most common disease in the world, colorectal cancer, frequently has the highest death rate. Surgery is a viable treatment option, but after five years, thirty to forty percent of patients have recurrence. Many people who have effectively treated their colorectal cancer also develop metastatic illness. Early detection is crucial since colorectal cancer has a high fatality rate. Deep learning techniques make colorectal cancer screening timelier and more cost-effective by enabling early and quicker identification of the disease. A collection of cell pictures was employed in the study to detect colorectal cancer. To demonstrate the capability of deep learning approaches, we used Convolutional Neural Networks (CNN), AlexNet, VGG-16, ResNet models and our proposed model as Hybrid CNN-LSTM. The accuracy and loss rates provided by the propos models were compared. The highest accuracy rate performance was observed with from the Hybrid CNN-LSTM model. The highest loss rate performance was observed with from the CNN model. © 2024 by the International Institute of Informatics and Systemics. All rights reserved.

关键词： Convolutional neural networks

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Research on Obstacle Avoidance Algorithm of UAVs Reinforcement Learning based on Vision 5

Research on Obstacle Avoidance Algorithm of UAVs Reinforceme...

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5th International Conference on Frontiers Technology of Information and computer, ICFTIC 2023

作者： Gao, Yuan Shi, Tianwei Xu, Teng Ding, Jianbang Jing, Rongchen University of Science and Technology Liaoning School of Computer Science and Software Engineering Anshan China

ISBN: (纸本)9798350309034

In recent years, the combination of deep reinforcement learning and unmanned aerial vehicle (UAV) to achieve autonomous flight has been a hot research field. In this paper, an obstacle avoidance navigation algorithm (PA-SAC) based on priority experience buffer pool (PEBP), attention, and Soft-Actor-Critic (SAC) is proposed to solve the continuous space obstacle avoidance navigation problem of UAVs by using a deep reinforcement learning algorithm. In the two simulation experiments, the success rate of the PA-SAC algorithm was 95.6% in the known environment and 73% in the unknown environment. These results demonstrate that the PA-SAC algorithm can achieve autonomous obstacle avoidance for UAVs with deep image input. © 2023 IEEE.

关键词： Attention component Obstacle Avoidance PEBP UAVs

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Russian Language Datasets in the Digital Humanities Domain and Their Evaluation with Word Embeddings 1

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20th International Conference on Computational Linguistics and Intelligent Text Processing, CICLing 2019

作者： Wohlgenannt, Gerhard Babushkin, Artemii Romashov, Denis Ukrainets, Igor Maskaykin, Anton Shutov, Ilya Faculty of Software Engineering and Computer Systems ITMO University St. Petersburg Russia

ISBN: (数字)9783031243370

ISBN: (纸本)9783031243363

In this paper, we present Russian language datasets in the digital humanities domain for the evaluation of word embedding techniques or similar language modeling and feature learning algorithms. The datasets are split into two task types, word intrusion and word analogy, and contain 31362 task units in total. The characteristics of the tasks and datasets are that they build upon small, domain-specific corpora, and that the datasets contain a high number of named entities. The datasets were created manually for two fantasy novel book series ("A Song of Ice and Fire" and "Harry Potter"). We provide baseline evaluations with popular word embedding models trained on the book corpora for the given tasks, both for the Russian and English language versions of the datasets. Finally, we compare and analyze the results and discuss specifics of Russian language with regards to the problem setting. © 2023, Springer Nature Switzerland AG.

关键词： Embeddings

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Supercapacitor-battery hybrid energy storage for portable smart devices using supercapacitor swapping energy harvester 50

Supercapacitor-battery hybrid energy storage for portable sm...

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50th Annual Conference of the IEEE Industrial Electronics Society, IECON 2024

作者： Dissanayake, Kavishka Kularatna-Abeywardana, Dulsha Patel, Nitish Kularatna, Nihal Department of Electrical Computer and Software Engineering University of Auckland New Zealand School of Engineering Teaching Research University of Waikato Hamilton New Zealand

ISBN: (纸本)9781665464543

A novel hybrid energy storage mechanism for portable smart devices that combine supercapacitors and batteries is proposed. Supercapacitors offer rapid charging and high-power delivery, which are ideal for short bursts of power activity, and batteries provide long-term energy storage. The system incorporates a solar energy harvester that efficiently charges the supercapacitor. A unique swapping converter topology allows for quick replacement of depleted supercapacitors with charged ones. This hybrid approach along with the solar harvester aims to extend device operation and reduce reliance on conventional battery charging methods and converters. © 2024 IEEE.

关键词： Charge storage

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Role of Non-functional Requirements in projects' success 2

Role of Non-functional Requirements in projects' success

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2nd International Conference on Digital Futures and Transformative Technologies, ICoDT2 2022

作者： Ali, Arsalan Khalil, Ibrahim Ahmad, Israr Parveen, Iqra Uz Zaman, Uzair Khaleeq Department of Computer & Software Engineering Islamabad Pakistan

ISBN: (纸本)9781665498197

Non-functional Requirements (NFRs) are the vital part of software development. NFRs define the quality attributes of the software product. According to the researchers' nonfunctional requirements are of equal importance as of functional requirements. But among practitioners it is debatable, as most of them do not give significance value to NFRs because of the rapid development nature of the projects. In the literature it is encouraged to provide proper attention to non-functional requirements during the development of the project because it could lead to new functional requirements and hence would tend to change the development approach. It is also believed that the absence of non-functional requirement could cause extra cost or customer's dissatisfaction. Hence, this paper aims to conduct an industrial survey to gather the data about how software practitioners think about the importance of nonfunctional requirements in the project success. Furthermore, we will be applying statistical testing on our data to analyze the results to check the significance role of NFRs in the success of the software project. © 2022 IEEE.

关键词： Surveys

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K Semantics for Security Policy Enforcement on Android Applications with Practical Cases 2nd

K Semantics for Security Policy Enforcement on Android Appli...

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2nd EAI International Conference on Computational Intelligence and Communications, CICom 2021

作者： Ziadia, Marwa Mejri, Mohamed Fattahi, Jaouhar Department of Computer Science and Software Engineering Laval University QuébecQC Canada

ISBN: (纸本)9783031195228

As much as they have positioned Android among the most widely used operating systems, Android applications have helped malware creators to break in and infect its devices. A long list of threats caused by downloaded applications targets the integrity of the system and the privacy of the users. To protect Android users from such applications, we propose a formal environment for security policy enforcement. The main idea is to establish a synergy between the aspect-oriented paradigm and formal methods such as the program rewriting technique. The purpose of our approach is to rewrite the application program by adding control tests at certain carefully selected points to ensure that the security policy is respected. The new version of the program preserves all the good behaviors of the original version that comply with the security policy and acts against the bad ones. The particularity of this approach is that all the steps for security policy enforcement are performed automatically using the K-framework. This semantic engineering framework handles the whole process, from the formal specification of the policy and the program to the enforcement technique. Two practical cases are fully discussed in this paper. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Semantics

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From Faces to Traffic Lights: A Multi-Scale Approach for Emotional State Representation 25

From Faces to Traffic Lights: A Multi-Scale Approach for Emo...

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25th IEEE International Conferences on High Performance Computing and Communications, 9th International Conference on Data Science and Systems, 21st IEEE International Conference on Smart City and 9th IEEE International Conference on Dependability in Sensor, Cloud and Big Data Systems and Applications, HPCC/DSS/SmartCity/DependSys 2023

作者： Nguyen, Minh Yan, Wei Qi Auckland University of Technology Department Computer Science and Software Engineering Auckland New Zealand

ISBN: (纸本)9798350330014

This paper presents an innovative Smart Traffic Light System designed to assess Emotional Expression in enclosed settings such as corporate offices and educational facilities. The system combines artificial intelligence, super-resolution algorithms, and facial recognition to provide both real-time and longitudinal insights into the collective emotional atmosphere. Utilizing a three-tier light indicator, the system visualizes emotional trends in the short-term (immediate), medium-term (daily or weekly), and long-term (semi-annual or annual) contexts, employing a color-coded scheme to denote positive or negative emotional states. This augments situational awareness and contributes to the emotional well-being of individuals in these settings. The underlying technology leverages closed-circuit television (CCTV) footage and introduces a state-of-the-art temporal expression recognition mechanism to capture a broad spectrum of human emotions. A notable innovation is the incorporation of facial super-resolution techniques to enhance the quality of low-resolution facial data, thereby boosting the system's overall accuracy and robustness. This enhancement is accomplished while maintaining adherence to ethical standards for data collection and usage. This system has implications that reach far beyond simple emotional recognition. It serves as a cornerstone for the development of emotionally intelligent smart cities. Providing both immediate feedback and historical data on community emotional states, it enables more informed decision-making, streamlined resource allocation, and ultimately, an improvement in the overall quality of life. This research contributes to the evolving discussion on how smart cities can foster communities that are not just more efficient, but also more emotionally resilient. © 2023 IEEE.

关键词： Smart city

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