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A Novel Multiobjective Fireworks Algorithm and Its Applications to Imbalanced Distance Minimization Problems

IEEE/CAA Journal of Automatica Sinica 2022年第8期9卷 1476-1489页

作者： Shoufei Han Kun Zhu MengChu Zhou Xiaojing Liu Haoyue Liu Yusuf Al-Turki Abdullah Abusorrah College of Computer Science and Technology Nanjing University of Aeronautics and Astronauticsand also with the Collaborative Innovation Center of Novel Software Technology and IndustrializationNanjing 211106China Department of Electrical and Computer Engineering New Jersey Institute of TechnologyNewark NJ 07102 USA Center of Research Excellence in Renewable Energy and Power Systems Department of Electrical and Computer EngineeringFaculty of Engineeringand also with the K.A.CARE Energy Research and Innovation CenterKing Abdulaziz UniversityJeddah 21589Saudi Arabia

Recently,multimodal multiobjective optimization problems(MMOPs)have received increasing *** goal is to find a Pareto front and as many equivalent Pareto optimal solutions as *** some evolutionary algorithms for them have been proposed,they mainly focus on the convergence rate in the decision space while ignoring solutions *** this paper,we propose a new multiobjective fireworks algorithm for them,which is able to balance exploitation and exploration in the decision *** first extend a latest single-objective fireworks algorithm to handle *** we make improvements by incorporating an adaptive strategy and special archive guidance into it,where special archives are established for each firework,and two strategies(i.e.,explosion and random strategies)are adaptively selected to update the positions of sparks generated by fireworks with the guidance of special ***,we compare the proposed algorithm with eight state-of-the-art multimodal multiobjective algorithms on all 22 MMOPs from CEC2019 and several imbalanced distance minimization *** results show that the proposed algorithm is superior to compared algorithms in solving ***,its runtime is less than its peers'.

关键词： Adaptive strategy fireworks algorithm multimodal multiobjective optimization problems(MMOP)

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Enhanced Loan Approval Prediction System using Ensemble Machine Learning Techniques 3

Enhanced Loan Approval Prediction System using Ensemble Mach...

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3rd International Conference on Automation, Computing and Renewable systems, ICACRS 2024

作者： Gothai, E. Rajalaxmi, R.R. Thamilselvan, R. Sridhar, K. Department of Computer Technology Kongu Engineering College Tamilnadu Perundurai India Department of Computer Science and Engineering Kongu Engineering College Tamilnadu Perundurai India MSc Software Systems Kongu Engineering College Erode India

ISBN: (纸本)9798331532420

Banks play a pivotal role in generating significant profits through loan operations. However, the challenge lies in accurately identifying genuine loan applicants who are likely to repay their loans. Manual processes are prone to misconceptions, prompting the development of a loan prediction system using deep learning. This system aims to automate the selection of eligible candidates, benefiting both bank staff and applicants by drastically reducing the loan approval timeframe. Two key machine learning algorithms such as Artificial Neural Network (ANN) and Support Vector Machine (SVM) are employed in this work for applicant selection. SVM, a popular supervised learning algorithm, creates a decision boundary or hyperplane to segregate classes in n-dimensional space. Conversely, ANN is inspired by biological neural networks, which mimic the organization of neurons in the input layer, hidden and output layers of the human brain. The integration of ANN and SVM in an ensemble model enhances accuracy compared to traditional methods. This collaborative approach ensures precise predictions of loan repayment likelihood based on applicant data and past loan eligibility records. The model's performance is measured using accuracy. The outcomes of the research were promising and the loan prediction system defines the minimum and maximum loan amounts that can be sanctioned to an applicant. By leveraging the strengths of both ANN and SVM, the ensemble model serves as a robust tool for accurately identifying worthy loan applicants, streamlining the loan approval process, and minimizing the risk of default. The accuracy of the algorithm is improved by this method to 91%. © 2024 IEEE.

关键词： Support vector machines

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Forecasting Price Prediction for Vegetables and Fruits Using Recurrent Neural Network 5

Forecasting Price Prediction for Vegetables and Fruits Using...

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5th International Conference on Electronics and Sustainable Communication systems, ICESC 2024

作者： Gothai, E. Rajalaxmi, R.R. Thamilselvan, R. Harshath, S.M. Kongu Engineering College Department of Computer Technology Tamilnadu Perundurai India Kongu Engineering College Department of Computer Science and Engineering Tamilnadu Perundurai India Kongu Engineering College MSc Software Systems Erode India

ISBN: (纸本)9798350379945

Unpredictable fruit and vegetable prices create significant challenges for farmer livelihoods. This research proposes an innovative approach using recurrent neural networks (RNNs) to predict both minimum and maximum prices. By analyzing historical market data, these models can forecast potential price ranges, empowering farmers to make informed decisions about planting, harvesting, and sales strategies. This enhanced foresight helps farmers navigate market volatility and improve income stability. © 2024 IEEE.

关键词： Vegetables

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Ontology of moodle e-learning system for social network analysis

Ontology of moodle e-learning system for social network anal...

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2nd IEEE International Conference on Open systems, ICOS 2011

作者： Yusof, Norazah Mansur, Andi Besse Firdausiah Othman, Mohd Shahizan Department of Software Engineering Faculty of Computer Science and Information Systems Universiti Teknologi Malaysia 81310 Johor Malaysia Department of Information Systems Faculty of Computer Science and Information Systems Universiti Teknologi Malaysia 81310 Johor Malaysia

ISBN: (纸本)9781612849317

The analysis using Social Network Analysis (SNA) is focusing more on the number or the frequency of social interactions based on adjacency matrix. This method cannot be used to observe the semantic relationship among e-Learning components. Therefore, this paper aims to propose a new paradigm of Social Network Analysis (SNA) using ontology structure of Moodle e-Learning. By considering the relationship of ontology, we can understand the meaning of semantic relationship more deeply. The ontology of Moodle e-learning system for social network analysis will become great advantage to make measurement not only based on the matrix or number of interactions but also based on the semantic meaning of the relationships among users. © 2011 IEEE.

关键词： Ontology

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WIP: An Engaging Undergraduate Intro to Model Checking in software engineering Using TLA+ 54

WIP: An Engaging Undergraduate Intro to Model Checking in So...

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54th IEEE Frontiers in Education Conference, FIE 2024

作者： Läufer, Konstantin Mertin, Gunda Thiruvathukal, George K. Loyola University Software and Systems Laboratory Department of Computer Science Chicago United States Institute for Software Engineering and Programming Languages University of Lübeck Germany

ISBN: (纸本)9798350351507

Background: In this Innovative Practice Work in Progress, we present our initial efforts to integrate formal methods, with a focus on model-checking specifications written in Temporal Logic of Actions (TLA+), into computer science education, targeting undergraduate juniors/seniors and graduate students. Many safety-critical systems and services crucially depend on correct and reliable behavior. Formal methods can play a key role in ensuring correct and safe system behavior, yet remain underutilized in educational and industry contexts. Aims: We aim to (1) qualitatively assess the state of formal methods in computer science programs, (2) construct level-appropriate examples that could be included midway into one's undergraduate studies, (3) demonstrate how to address successive 'failuresy' through progressively stringent safety and liveness requirements, and (4) establish an ongoing framework for assessing interest and relevance among students. Methods: We detail our pedagogical strategy for embedding TLA+ into an intermediate course on formal methods at our institution. After starting with a refresher on mathematical logic, students specify the rules of simple puzzles in TLA+ and use its included model checker (known as TLC) to find a solution. We gradually escalate to more complex, dynamic, event-driven systems, such as the control logic of a microwave oven, where students will study safety and liveness requirements. We subsequently discuss explicit concurrency, along with thread safety and deadlock avoidance, by modeling bounded counters and buffers. Results: Our initial findings suggest that through careful curricular design and choice of examples and tools, it is possible to inspire and cultivate a new generation of software engineers proficient in formal methods. Conclusions: Our initial efforts suggest that 84% of our students had a positive experience in our formal methods course. Our future plans include a longitudinal analysis within our own institution and

关键词： Students

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Enabling collaborative adaptation across legacy components

Enabling collaborative adaptation across legacy components

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3rd Workshop on Adaptive and Reflective Middleware, ARM '04

作者： Yang, Z. Zhou, Z. Cheng, B.H.C. McKinley, P.K. Software Engineering and Network Systems Laboratory Department of Computer Science and Engineering Michigan State University East Lansing MI 48824 United States

ISBN: (纸本)1581139497

software frequently needs to adapt its behavior at run time to respond to changes in its execution environment. Different software components may use different approaches to adaptation. Composing a single adaptive system from existing adaptive components requires an "adaptation infrastructure" to integrate and arbitrate adaptive behaviors. This paper proposes a model for such an infrastructure and describes the design and operation of M2, a prototype implementation. M2 uses a technique called transparent shaping to modify existing components so that they can report events of interest to the M2 core and implement appropriate responses. The architecture and communication infrastructure of M2 are described, followed by a case study in which M2 is used to construct an adaptive multimedia conferencing application from otherwise incompatible components. Copyright 2004 ACM.

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Product Recommendation System using Deep Learning based Recurrent Neural Network

Product Recommendation System using Deep Learning based Recu...

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2023 International Conference on computer Communication and Informatics, ICCCI 2023

作者： Shanthi, S. Nirmaladevi, K. Mathiarasi, N. Tharani, As. Krithika Monisha, A. Kuppuchamy, R. Krishnamoorthy, N. Kongu Engineering College Department of Computer Science & Engineering Perundurai India PSNA College of Engineering and Technology Department of Computer Applications Tamilnadu Dindigul India Vellore Institute of Technology Department of Software Systems and Engineering Vellore Campus India

ISBN: (纸本)9798350348217

Today's marketing strategies place a high priority on comprehending customer sentiments. It will not only give businesses a better understanding of how their clients view their goods and/or services, but it will also give them suggestions on how to enhance their offerings. We make an effort to comprehend the relationship between various factors in customer reviews on an online store for women's clothing. The proposed system also classifies each review, according to, whether it recommends the product in question or not, and whether it has a positive, negative, or neutral sentiment. With the exception of review titles and review texts, we used univariate and multivariate analyses on datasets features to accomplish these goals. Additionally, we have implemented a bidirectional recurrent neural network (RNN) with a long-short term memory unit (LSTM) for sentiment and recommendation. © 2023 IEEE.

关键词： Long short-term memory

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Authentication in reprogramming of sensor networks for mote class adversaries

Authentication in reprogramming of sensor networks for mote ...

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21st International Parallel and Distributed Processing Symposium, IPDPS 2007

作者： Limin, Wang Kulkarni, Sandeep S. Software Engineering and Network Systems Laboratory Department of Computer Science and Engineering Michigan State University East Lansing MI 48824 United States

ISBN: (纸本)1424409101

Reprogramming is an essential service for wireless sensor networks. Authenticating reprogramming process is important as sensors need to verify that the code image is truly from a trusted source. There are two ways to achieve authentication: public key based and symmetric key based. Although previous work has shown that public key authentication is feasible on sensor nodes if used sparingly, it is still quite expensive compared to symmetric key based approach. In this paper, we propose a symmetric key based protocol for authenticating reprogramming process. Our protocol is based on the secret instantiation algorithm from [5, 11], which requires only O(log n) keys to be maintained at each sensor. We integrate this algorithm with the existing reprogramming protocol. Through simulation, we show that it is able to authenticate reprogramming process at very low communication cost, and has very short delay. ©2007 IEEE.

关键词： Sensor networks

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Visualizing requirements in UML models

Visualizing requirements in UML models

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First International Workshop on Visualization in Requirements engineering, REV 2006, at the 14th IEEE Requirements engineering Conference, RE 2006

作者： Konrad, Sascha Goldsby, Heather Lopez, Karli Cheng, Betty H.C. Software Engineering and Network Systems Laboratory Department of Computer Science and Engineering Michigan State University East Lansing MI 48824 United States

ISBN: (纸本)0769527116

As the Unified Modeling Language (UML) and model-driven development (MDD) become increasingly common in industry, many developers are faced with the difficult task of understanding how an existing UML model realizes system requirements. Essentially, developers are required to understand the structure and behavior of UML models that they may have not created. Understanding these relationships is non-trivial, because the interactions in the model are not readily apparent. Commonly, the only means to elicit these relationships is visual inspection and guided simulation. This paper describes an alternative approach termed REVU (Requirements Visualization of UML), a process for visualizing functional requirements in terms of behavioral interactions in a UML model. We illustrate the use of this process with the visualization of scenarios for an adaptive light control system. © 2006 IEEE.

关键词： Requirements engineering

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CAC 2.0: A Corrupt and Correct Logic Locking Technique Resilient to Structural Analysis Attacks 25

CAC 2.0: A Corrupt and Correct Logic Locking Technique Resil...

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25th IEEE Latin American Test Symposium, LATS 2024

作者： Aksoy, Levent Yasin, Muhammad Pagliarini, Samuel National University Of Sciences And Technology Department Of Computer And Software Engineering Islamabad Pakistan Tallinn University Of Technology Department Of Computer Systems Tallinn Estonia Carnegie Mellon University Department Of Electrical And Computer Engineering Pittsburgh United States

ISBN: (纸本)9798350365559

Logic locking proposed to protect integrated circuits from serious hardware threats has been studied extensively over a decade. In these years, many logic locking techniques have been proven to be broken. The state-of-the-art logic locking techniques, including the prominent corrupt and correct (CAC) technique, are resilient to satisfiability (SAT)-based and removal attacks, but vulnerable to structural analysis attacks. To overcome this drawback, this paper introduces an improved version of CAC, called CAC 2.0, which increases the search space of structural analysis attacks using obfuscation. To do so, CAC 2.0 locks the original circuit twice, one after another, on different nodes with different number of protected primary inputs using CAC, while hiding original protected primary inputs among decoy primary inputs. This paper also introduces an open source logic locking tool, called HIID, equipped with well-known techniques including CAC 2.0. Our experiments show that CAC 2.0 is resilient to existing SAT-based, removal, and structural analysis attacks. To achieve this, it increases the number of key inputs at most 4× and the gate-level area between 30.2% and 0.8% on circuits with low and high complexity with respect to CAC. © 2024 IEEE.

关键词： Structural analysis

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