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检索条件"任意字段=Knowledge-Based Software Engineering Conference"

共 17482 条记录，以下是961-970 订阅

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Hybrid Multi-Objective Genetic Programming for Parameterized Quantum Operator Discovery

Hybrid Multi-Objective Genetic Programming for Parameterized...

引用

Genetic and Evolutionary Computation conference (GECCO)

作者： Gemeinhardt, Felix Klikovits, Stefan Wimmer, Manuel Johannes Kepler Univ Linz Inst Business Informat Software Engn CDL MINT Linz Austria

ISBN: (纸本)9798400701207

The processing of quantum information is defined by quantum circuits. For applications on current quantum devices, these are usually parameterized, i.e., they contain operations with variable parameters. The design of such quantum circuits and aggregated higher-level quantum operators is a challenging task which requires significant knowledge in quantum information theory, provided a polynomial-sized solution can be found analytically at all. Moreover, finding an accurate solution with low computational cost represents a significant trade-off, particularly for the current generation of quantum computers. To tackle these challenges, we propose a multi-objective genetic programming approach-hybridized with a numerical parameter optimizer-to automate the synthesis of parameterized quantum operators. To demonstrate the benefits of the proposed approach, it is applied to a quantum circuit of a hybrid quantum-classical algorithm, and then compared to an analytical solution as well as a non-hybrid version. The results show that, compared to the non-hybrid version, our method produces more diverse solutions and more accurate quantum operators which even reach the quality of the analytical baseline.

关键词： Quantum Circuit Synthesis Genetic Programming Hybrid Search Search-based Quantum software engineering

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Debiased Contrastive Loss for Collaborative Filtering 16th

Debiased Contrastive Loss for Collaborative Filtering

引用

16th International conference on knowledge Science, engineering and Management (KSEM)

作者： Liu, Zhuang Ma, Yunpu Li, Haoxuan Hildebrandt, Marcel Ouyang, Yuanxin Xiong, Zhang Beihang Univ State Key Lab Software Dev Environm Beijing Peoples R China Ludwig Maximilians Univ Munchen Lehrstuhl Datenbanksyst & Data Min Munich Germany Beihang Univ Engn Res Ctr Adv Comp Applicat Technol Minist Educ Beijing Peoples R China Univ Munich Munich Germany Siemens AG Munich Germany

ISBN: (纸本)9783031402883;9783031402890

Collaborative filtering (CF) is the most fundamental technique in recommender systems, which reveals user preference by implicit feedback. Generally, binary cross-entropy or bayesian personalized ranking are usually employed as the loss function to optimize model parameters. Recently, the sampled softmax loss has been proposed to enhance the sampling efficiency, which adopts an in-batch sample strategy. However, it suffers from the sample bias issue, which unavoidably introduces false negative instances, resulting inaccurate representations of users' genuine interests. To address this problem, we propose a debiased contrastive loss, incorporating a bias correction probability to alleviate the sample bias. We integrate the proposed method into several matrix factorizations (MF) and graph neural network-based (GNN) recommendation models. Besides, we theoretically analyze the effectiveness of our methods in automatically mining the hard negative instances. Experimental results on three public benchmarks demonstrate that the proposed debiased contrastive loss can augment several existing MF and GNN-based CF models and outperform popular learning objectives in the recommendation. Additionally, we demonstrate that our method substantially enhances training efficiency.

关键词： collaborative filtering debiased contrastive learning sample bias matrix factorization graph neural network

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Computer simulation of the biomorphic neuroprocessor 5

Computer simulation of the biomorphic neuroprocessor

引用

5th International Youth conference on Radio Electronics, Electrical and Power engineering, REEPE 2023

作者： Ebrahim, Abdulla Busygin, Alexander Udovichenko, Sergey Tyumen State University Center for Nature-Inspired Engineering Laboratory of Nanomaterials and Nanoelectronics Tyumen Russia

ISBN: (纸本)9798350399523

In this paper, numerical simulation was carried out and the operability of the input and output devices of a biomorphic neuroprocessor, built using a logic matrix, was shown using the specialized software SPICE (Simulation Program with Integrated Circuit Emphasis) for simulating large electrical circuits with memristor-diode crossbars. The modes of encoding a binary number into frequency and delay of pulses, simultaneously into frequency and delay of pulses by neuron population were investigated. Also, the mode of decoding pulses into a standard binary code for outputting information from the neuroprocessor was investigated. The simulation results of the associative self-learning mechanism in hardware spiking neural networks based on the memory matrix of a neuroprocessor are presented. The learning rules are LTP (Long-Term Potentiation) for a network of four neurons and STDP (Spike-Time Dependent Plasticity) for a hardware spiking perceptron. For the first time, the generation of a new association (new knowledge) in a composite memristor-diode crossbar according to the STDP rule is demonstrated, in opposite to self-learning in existing hardware neural networks with discrete memristors synapses. © 2023 IEEE.

关键词： Memristors

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Data Driven Testing for Context Aware Apps 34

Data Driven Testing for Context Aware Apps

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34th International conference on software engineering and knowledge engineering, SEKE 2022

作者： Michaels, Ryan Piparia, Shraddha Adamo, David Bryce, Renee St Edward's University United States University of North Texas United States Block Inc.

ISBN: (纸本)1891706543

Context driven environments are growing in popularity. Mobile applications, Internet of Things devices, autonomous vehicles, and future technologies respond to context events in their environments. This work uses a set of context events from real users to guide the generation of context driven test cases. Context event sequences are obtained by applying Conditional Random Fields (CRF). Test suites are then constructed by interleaving the context event sequences with GUI events. The choice of context event is made based on transitions obtained from the CRF. Results of the empirical studies show that techniques that incorporate context events provide better code coverage than NoContext for the subject applications. A heuristic technique introduced in this work, ISFreqOne, yields 4x better coverage than NoContext, 0.06x better coverage than Random Start Context, 0.05x better coverage than Iterative Start Context, which are control context generation techniques, and 0.04x better coverage than ISFreqTwo, another heuristic introduced in this work. © 2022 knowledge Systems Institute Graduate School. All rights reserved.

关键词： software testing

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Variable Training of IT Engineers for software Development 27th

Variable Training of IT Engineers for Software Development

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27th International conference on Interactive Collaborative Learning-ICL

作者： Kirilova, Galia I. Khasanova, Gulnara F. Shorina, Tatyana V. Yimin, Chen Yangxingyue, Guo Kazan Volga Reg Fed Univ Kazan Russia Kazan Natl Res Technol Univ Kazan Russia Kazan State Power Engn Univ Kazan Russia

ISBN: (纸本)9783031856518;9783031856525

The paper is devoted to comparing the effectiveness of variable methods for training future IT specialists, based on identifying the initial level of proficiency in SQL and HTML programming languages. An experiment was conducted with the participation of second-year students of the Kazan State Energy University (N = 200). The experiment tested two options for completing tasks, combining experience in web programming and experience working with databases. Students were given the opportunity to begin doing their work in a known way, obtain a positive result sufficient for a positive self-assessment, and then develop their knowledge and experience in accordance with the requirements of the curriculum. The study demonstrated the effectiveness of conducting an entry survey to identify the initial level of programming languages proficiency. Changes made to the content and process of training future IT specialists based on data obtained from surveys made it possible to eliminate gaps in IT competencies.

关键词： Contents of IT specialists training SQL and HTML programming languages proximal development zone of students

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Reverse engineering of Hamiltonian Expressions from D-Wave programs

Reverse Engineering of Hamiltonian Expressions from D-Wave p...

引用

1st IEEE International conference On Quantum software (IEEE QSW) / IEEE World Congress on Services (IEEE SERVICES)

作者： Perez-Castillo, Ricardo Jimenez-Navajas, Luis Piattini, Mario Univ Castilla La Mancha aQuantum Fac Social Sci & IT Talavera De La Reina Spain Univ Castilla La Mancha aQuantum Informat Technol & Syst Inst Ciudad Real Spain

ISBN: (纸本)9781665481342

Quantum annealing software has achieved a certain market penetration since it has demonstrated a good performance for optimization problems. The problem definitions (Hamiltonians functions to be minimized) are usually built in combination with classical software that can evolve over time. Thus, it is difficult to comprehend the underlying Hamiltonian and represent it in an accurate way for maintaining such programs. Although some reverse engineering techniques have been proposed for gate-based software, there are no choices to accomplish reverse engineering in quantum annealing. This research proposes a dynamic analysis technique of D-Wave (python) programs for reversing Hamiltonians, which has been preliminarily evaluated with nine programs. The technique also represents those expressions by using the knowledge Discovery Metamodel (ISO/IEC 19506). Due to the usage of this standard, the outgoing expressions can be represented in combination with other parts of classical-quantum software systems. Thus, the main implication is that this technique contributes to the software modernization of/towards hybrid information systems.

关键词： Quantum software engineering Quantum Computing D-Wave Quantum algorithms Quantum Annealing Reverse engineering KDM

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Man-hour Prediction for Complex Industrial Products 4

Man-hour Prediction for Complex Industrial Products

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4th International Informatics and software engineering conference, IISEC 2023

作者： Unal, Ahmet Emin Boyar, Halit Pak, Burcu Kuleli Cem Yildiz, Mehmet Erten, Ali Erman Cagri Gungor, Vehbi Istanbul Tech. University Dept. of Comp. Engineering Istanbul Turkey Adesso Turkey R&d Department Istanbul Turkey Ermetal Automotive R&d Center Bursa Turkey Erkalip Quotation Department Bursa Turkey Abdullah Gül University Dept. of Comp. Engineering Kayseri Turkey

ISBN: (纸本)9798350318036

Accurately predicting the cost is crucial for the success of complex industrial projects. There can be several sources contributing to the cost. Traditional methods for cost estimation may not provide the required accuracy and speed to ensure the success of the project. Recently, machine learning techniques have shown promising results in improving cost estimation in various industrial products. This study investigates the performance of gradient-boosting machine learning models and feature engineering techniques on a private dataset of metal sheet project man-hour costs. A comparison of distinct models is conducted, key aspects influencing cost are identified, and the implications of incorporating domain-specific knowledge, including its advantages and disadvantages, are assessed based on performance outcomes. Experimental results demonstrate that LightGBM and XGBoost outperform other models, and feature selection and synthetic data generation techniques improve the performance. Overall, this study highlights the potential of machine learning in metal sheet sampling projects and emphasizes the importance of feature engineering and domain expertise for better model performance. © 2023 IEEE.

关键词： Forecasting

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knowledge Management Using Cloud Computing in Higher Educational Institutions

Knowledge Management Using Cloud Computing in Higher Educati...

引用

Advancement in Electronics & Communication engineering (AECE), International conference on

作者： Ruchi Sharma Girish Lakhera Department of Management Studies Graphic Era Deemed to be University Dehradun India

ISBN: (数字)9798350364729

ISBN: (纸本)9798350364736

"knowledge" is a vital resource for organisation that should be gathered, safeguarded, & disseminated. It should be used to inform decisions. "Cloud-based Computing" and “knowledge Management” solutions help organizations manage their information and boost productivity by fusing traditional organizational methods with cutting-edge technology. This study specifically looks at cloud-based software services to explore how organizations use ubiquitous computing to adopt innovative software development and delivery approaches. The study’s findings show that factors like complexity, compatibility, relative advantage, security, privacy, and trust, as well as reputation and KM practices (knowledge accessibility, storage, application, and sharing), have a significant and positive impact on whether cloud-based software services are adopted. “Coordination and communication” problems are the cornerstone of winning remote “development and innovation” practices. The conclusion also lend credence to the idea that the effects of cloud services and knowledge management practices can be attenuated by spatial (cultural) diversity.

关键词： Productivity Cloud computing Technological innovation Privacy Organizations Ubiquitous computing knowledge management software Security software development management

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EHealthcare: IoT & AI Enhance the Scope and Effectiveness of Diagnostics and Treatment Modalities 21

EHealthcare: IoT & AI Enhance the Scope and Effectiveness of...

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21st IEEE International conference on Smart Communities: Improving Quality of Life using AI, Robotics and IoT, HONET 2024

作者： Ahmed, Shaftab Raja, Junaid Y. Raja, M. Yasin Akhtar Bahria University Software Engineering Islamabad Pakistan University of Alabama Vascular and Interventional Radiology O'Neal Comprehensive Cancer Center BirminghamAL United States University of North Carolina Physics and Optical Sc and Engineering Center for Optoelectronics and Optical Communications CharlotteNC United States

ISBN: (纸本)9798350378078

Intelligent hardware deployment for autonomous sensing and data collection, use of various computing technologies, algorthms for response systems form the core of Internet of Things. The devices and systems allow collection of live data backed up by a knowledge base of information. Emergence of Artificial Inteligence (AI) has assumed great importance in Information Technology (IT). e-Healthcare systems benefit using AI tools and IoT applications. Hence the concept of early diagnosis and continous monitoring of patients are beneficial and crucial. Machine learning allows the sytems to collect data in real-Time to be used in intelligent and proactive decision making. This has led to a number of challenges for the developers of software and intelligent hardware for secure operations and management. In the paper, we have discussed the role of AI and ML for medical systems. Those are championed by sofware engineering tools and domain specific architetures for prividing hardware support for fast data-processing. We also have dicussed security and operation concerns in implementation of IoT-based intelligent systems specially to meet the HIPPA standards. IoT in healthcare is generating a huge amount of useful data. That has to be handled with data processing supported by Domain Specific Architecture (DSA). IoT and AI together are poised to play an important role in support of medical professionals, physicians and nurses alike in ICU. Rapidly changing critical parameters and their interpretation by intelligent systems can help saving human lives. We have discussed the ICU situations and two case-studies to support the concept. © 2024 IEEE.

关键词： Diagnosis

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Blockchain based Services in Education: A Bibliometric Analysis 1st

Blockchain Based Services in Education: A Bibliometric Analy...

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1st International conference on Machine Intelligence and Emerging Technologies, MIET 2022

作者： Hossain, Md. Shariar Haque, A. K. M. Bahalul Noakhali Science and Technology University Noakhali3814 Bangladesh Software Engineering LENS LUT University Lappeenranta Finland

ISBN: (纸本)9783031346217

Blockchain technology promotes immutability, transparency, integrity, and enhanced security. Recently blockchain-based applications and associated technologies have been noticeable in various domains such as finance, healthcare, education, transportation, supply chain, and access control. Blockchain in the education sector is a newly explored topic;the nature of research and the trend should provide useful directions for future research. Motivated by this factor, this work presents a bibliometric analysis of the blockchain in the education sector by investigating 512 research articles from the Scopus database. In particular, we had 335 conference Papers, 150 Articles, and 27 Book chapters that were published between the year 2016 to 2022. This study provides a comprehensive visual analysis of research trends in subject areas, author contribution, citation, publication channels and venues, country-based research output, and other bibliometric data. To identify the gaps and expand the current scope of knowledge on blockchain technology in the education system, we have used the bibliometric data extracted from the Scopus database. Finally, the investigation concludes with guidelines for future research directions. © 2023, ICST Institute for Computer Sciences, Social Informatics and Telecommunications engineering.

关键词： Blockchain

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