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Multi-party Quantum Communication Complexity on Composite Boolean-Valued Function 1

5th International Conference on Artificial Intelligence and Security, ICAIS 2019

作者： Yu, Wenbin Dong, Zangqiang Liu, Wenjie Qu, Zhiguo Xu, Xiaolong Liu, Alex Xiangyang Jiangsu Engineering Center of Network Monitoring School of Computer and Software Nanjing University of Information Science and Technology NanjingJiangsu Province210044 China The Department of Computer Science and Application Zhengzhou Institute of Aeronautical Industry Management ZhengzhouHenan Province450015 China Department of Computer Science and Engineering Michigan State University East LansingMI48824-1226 United States

ISBN: (数字)9783030242688

ISBN: (纸本)9783030242671

The performance of communication complexity depends on the selected computation model. Even on the specific model the quantum communication complexity is not always better than the classical one. This paper investigates the quantum communication complexity based on a multi-party computation model of the composite Boolean-valued function. On this model we design a quantum distributed algorithm to obtain the upper bound of quantum communication complexity. The result shows that the performance gap between quantum and classical communication complexity depends on the infinity order of function domain’s square root and users’ number. In the best situation the performance of the quantum communication complexity wins the quadratic level of advantage than the classical one. And sometimes the classical way is more efficient than the quantum one. © 2019, Springer Nature Switzerland AG.

关键词： Quantum communication

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Symmetric Learning Data Augmentation Model for Underwater Target Noise Data Expansion

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computers, Materials & Continua 2018年第12期57卷 521-532页

作者： Ming He Hongbin Wang Lianke Zhou Pengming Wang Andrew Ju College of Computer Science and Technology Harbin Engineering UniversityHarbin150001China College of Computer and Information Engineering Heilongjiang University of Science and TechnologyHarbin150022China School of Software and Microelectronics Harbin University of Science and TechnologyHarbin150080China Department of Computer Science and Information Systems University of LimerickLimerickIreland

An important issue for deep learning models is the acquisition of training of *** abundant data from a real production environment for training,deep learning models would not be as widely used as they are ***,the cost of obtaining abundant real-world environment is high,especially for underwater *** is more straightforward to simulate data that is closed to that from real *** this paper,a simple and easy symmetric learning data augmentation model(SLDAM)is proposed for underwater target radiate-noise data expansion and *** SLDAM,taking the optimal classifier of an initial dataset as the discriminator,makes use of the structure of the classifier to construct a symmetric generator based on antagonistic *** generates data similar to the initial dataset that can be used to supplement training data *** model has taken into consideration feature loss and sample loss function in model training,and is able to reduce the dependence of the generation and expansion on the feature *** verified that the SLDAM is able to data expansion with low calculation *** results showed that the SLDAM is able to generate new data without compromising data recognition accuracy,for practical application in a production environment.

关键词： Data augmentation symmetric learning data expansion underwater target noise data

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Implementing real-time RCF-Retinex image enhancement method using CUDA

Implementing real-time RCF-Retinex image enhancement method ...

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作者： Yang, Xiaomin Jian, Lihua Wu, Wei Liu, Kai Yan, Binyu Zhou, Zhili Peng, Jian College of Electronics and Information Engineering Sichuan University No. 24 South Section 1 Yihuan Road Chengdu China College of Computer Science Sichuan University No. 24 South Section 1 Yihuan Road Chengdu China School of Electrical Engineering and Information Sichuan University No. 24 South Section 1 Yihuan Road Chengdu China Jiangsu Engineering Center of Network Monitoring and School of Computer and Software Nanjing University of Information Science and Technology Nanjing China

RCF-Retinex is a novel Retinex-based image enhancement method which can improve contrast, eliminate noise, and enhance details simultaneously. It utilizes region covariance filter (RCF) to estimate the illumination. However, RCF-Retinex encounters time-consuming problem, since the region covariance filter is computationally intensive, which restricts the practical application in real-time systems. Therefore, it is necessary to decrease the computational complexity by parallelization. This paper proposes a GPU-based RCF-Retinex, which can accelerate region covariance filter using CUDA. It is feasible to use CUDA to parallel the region covariance filter due to its consecutive convolution operations, thus we can obtain the illumination image fast. Experiments have proved the improvement of running time and the enhancement results are similar with those using the unaccelerated RCF-Retinex method. © 2018, Springer-Verlag GmbH Germany, part of Springer Nature.

关键词： Image enhancement

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Deep3BPP: Identification of blood-brain barrier penetrating peptides using word embedding feature extraction method and CNN-LSTM

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2025年

作者： Rahman, Md. Ashikur Ali, Md Mamun Ahmed, Kawsar Mahmud, Imran Bui, Francis M. Chen, Li Moni, Mohammad Ali Daffodil International University Daffodil Smart City Department of Software Engineering Birulia Dhaka1216 Bangladesh University of Saskatchewan Division of Biomedical Engineering SaskatoonSKS7N 5A9 Canada University of Saskatchewan Department of Electrical and Computer Engineering SaskatoonSKS7N 5A9 Canada Health Informatics Research Laboratory Department of Computer Science and Engineering Birulia Savar Dhaka1216 Bangladesh Mawlana Bhashani Science and Technology University Group of Bio-photomatiχ Information and Communication Technology Santosh Tangail1902 Bangladesh Charles Sturt University Centre for AI & Digital Health Technology Artificial Intelligence & Cyber Futures Institute BathurstNSW2795 Australia

To prevent different chemicals from entering the brain, the blood-brain barrier penetrating peptide (3BPP) acts as a vital barrier between the bloodstream and the central nervous system (CNS). This barrier significantly hinders the treatment of neurological and CNS disorders. 3BPP can get beyond this barrier, making it easier to enter the brain and essential for treating CNS and neurological diseases and disorders. Computational techniques are being explored because traditional laboratory tests for 3BPP identification are costly and time-consuming. In this work, we introduced a novel technique for 3BPP prediction with a hybrid deep learning model. Our proposed model, Deep3BPP, leverages the LSA, a word embedding method for peptide sequence extraction, and integrates CNN with LSTM (CNN-LSTM) for the final prediction model. Deep3BPP performance metrics show a remarkable accuracy of 97.42%, a Kappa value of 0.9257, and an MCC of 0.9362. These findings indicate a more efficient and cost-effective method of identifying 3BPP, which has important implications for researchers in the pharmaceutical and medical industries. Thus, this work offers insightful information that can advance both scientific research and the well-being of people overall. © 2020 IEEE.

关键词： Convolutional neural networks

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Research on Green Energy Saving ECO Intelligent System engineering Cycle

Research on Green Energy Saving ECO Intelligent System Engin...

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2020 International Conference on Green Energy, Environment and Sustainable Development, GEESD 2020

作者： Chen, Jue-Jia Wu, Shinn-Dar Chen, Dong-Yan Li, Jie Huang, Ta-Wei Software Engineering Department of Computer Science Neusoft Institute Guangdong Guangdong Province Foshan528225 China School of Chemistry and Materials Engineering Huizhou University Huizhou Guangdong516007 China USA Saint Paul's College and DePaul University 115 College Drive LawrencevilleVA23868 United States Royal Global Business Center Legaspi Village Makati City Metro Manila1229 Philippines South China Agricultural University Tianhe District Guangzhou510642 China Department of Information Management and Engineering Neusoft Institute Guangdong Guangdong Province Foshan528225 China

With the improvement of living standards, the national coverage of heaters is also higher. From the original only the northern part of the installation of heating devices, to the south of the central area has also installed heaters, and even some people in the southern area installed heaters. With the increase in sales volume and fierce competition, companies need to reform and innovate products to meet the higher requirements of customers for energy-saving effects, comfort and safety. The design of the heater involves theories of structure, integrated circuit, program algorithm, aerodynamics, heat transfer and so on. Due to the technical level and cost constraints of enterprises, few companies can produce safe, energy-saving, moisturizing and comfortable heaters suitable for the public. In this study, the green energy-saving circulating heater of ECO intelligent system adopts the incremental ECO processing algorithm, with the single-chip STC89C52 as the main control chip system, combined with the peripheral STC89C52 temperature data acquisition, HIH-3010 humidity data collector, A/D Conversion module, keyboard settings, LCD1602 liquid crystal display and other circuit modules. This design realizes the temperature value that the heater provides the user with the optimum indoor temperature value and sets the heating according to the user's needs. When the set temperature value is reached or the temperature is high, the controller will control the heating element to reduce power or automatically power off to achieve safe power saving effect. © Published under licence by IOP Publishing Ltd.

关键词： Intelligent systems

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Intelligent building control systems for thermal comfort and energy-efficiency: A systematic review of artificial intelligence-assisted techniques

arXiv

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arXiv 2021年

作者： Merabet, Ghezlane Halhoul Essaaidi, Mohamed Haddou, Mohamed Ben Qolomany, Basheer Qadir, Junaid Anan, Muhammad Al-Fuqaha, Ala Abid, Mohamed Riduan Benhaddou, Driss ENSIAS Mohammed V University Rabat713 Morocco MENTIS Consulting SA 13 rue de Congrès Brussels1000 Belgium KearneyNE68849 United States Information Technology University Lahore54000 Pakistan Software Engineering Department Alfaisal University- Riyadh Saudi Arabia Hamad Bin Khalifa University Doha Qatar Department of Computer Science Western Michigan University KalamazooMI49008 United States School of Science and Engineering Alakhawayn University Ifrane1005 Morocco Department of Engineering Technology University of Houston TX77204 United States

Building operations represent a significant percentage of the total primary energy consumed in most countries due to the proliferation of Heating, Ventilation and Air-Conditioning (HVAC) installations in response to the growing demand for improved thermal comfort. Reducing the associated energy consumption while maintaining comfortable conditions in buildings are conflicting objectives and represent a typical optimization problem that requires intelligent system design. Over the last decade, different methodologies based on the Artificial Intelligence (AI) techniques have been deployed to find the sweet spot between energy use in HVAC systems and suitable indoor comfort levels to the occupants. This paper performs a comprehensive and an in-depth systematic review of AI-based techniques used for building control systems by assessing the outputs of these techniques, and their implementations in the reviewed works, as well as investigating their abilities to improve the energy-efficiency, while maintaining thermal comfort conditions. This enables a holistic view of (1) the complexities of delivering thermal comfort to users inside buildings in an energy-efficient way, and (2) the associated bibliographic material to assist researchers and experts in the field in tackling such a challenge. Among the 20 AI tools developed for both energy consumption and comfort control, functions such as identification and recognition patterns, optimization, predictive control. Based on the findings of this work, the application of AI technology in building control is a promising area of research and still an ongoing, i.e., the performance of AI-based control is not yet completely satisfactory. This is mainly due in part to the fact that these algorithms usually need a large amount of high-quality real-world data, which is lacking in the building or, more precisely, the energy sector. Based on the current study, from 1993 to 2020, the application of AI techniques and personalized comfort

关键词： Energy efficiency

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Performance of multilabelmachine learning models and risk stratification schemas for predicting stroke and bleeding risk in patients with non-valvular atrial fibrillation

arXiv

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arXiv 2022年

作者： Lu, Juan Hutchens, Rebecca Hung, Joseph Bennamoun, Mohammed McQuillan, Brendan Briffa, Tom Sohel, Ferdous Murray, Kevin Stewart, Jonathon Chow, Benjamin Sanfilippo, Frank Dwivedi, Girish Department of Computer Science and Software Engineering The University of Western Australia Australia Medical School The University of Western Australia Perth Australia Harry Perkins Institute of Medical Research Perth Australia Sir Charles Gairdner Hospital PerthWA Australia School of Population and Global Health The University of Western Australia Australia Discipline of Information Technology Murdoch University Perth Australia Department of Medicine Division of Cardiology University of Ottawa Heart Institute Ottawa Canada Cardiology Department Fiona Stanley Hospital Perth Australia

Objective: Appropriate antithrombotic therapy for patients with atrial fibrillation (AF) requires assessment of ischemic stroke and bleeding risks. However, risk stratification schemas such as CHA2DS2-VASc and HAS-BLED have modest predictive capacity for patients with AF. Machine learning (ML) techniques may improve predictive performance and support decision-making for appropriate antithrombotic therapy. We compared the performance of multilabel ML models with the currently used risk scores for predicting outcomes in AF patients. Materials and Methods: This was a retrospective cohort study of 9670 patients, mean age 76.9 years, 46% women, who were hospitalized with non-valvular AF, and had 1-year follow-up. The primary outcome was ischemic stroke and major bleeding admission. The secondary outcomes were all-cause death and event-free survival. Discriminant power of ML models were compared with clinical risk scores by area under the curve (AUC). Risk stratification was assessed using net reclassification index. Results: Multilabel gradient boosting machine provided the best discriminant power for stroke, major bleeding and death (AUC = 0.685, 0.709, and 0.765 respectively) compared to other ML models. It provided modest performance improvement for stroke compared to CHA2DS2-VASc (AUC = 0.652), but significantly improved major bleeding prediction compared to HAS-BLED (AUC = 0.522). It also had much greater discriminant power for death compared with CHA2DS2-VASc (AUC = 0.606). Also, models identified additional risk features (such as hemoglobin level, renal function etc.) for each outcome. Conclusions: Multilabel ML models can outperform clinical risk stratification scores for predicting the risk of major bleeding and death in non-valvular AF patients. Copyright © 2022, The Authors. All rights reserved.

关键词： Diseases

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Design of Intelligent Mobile Robot Control System Based on Gesture Recognition 6th

Design of Intelligent Mobile Robot Control System Based on G...

引用

6th International Conference on Artificial Intelligence and Security,ICAIS 2020

作者： Dai, Dong Zhuang, Wei Shen, Yixian Li, Lu Wang, Haiyan School of Cyber Science and Engineering Southeast University Nanjing210096 China School of Computer and Software Nanjing University of Information Science and Technology Nanjing210044 China School of Economic and Management Southeast University Nanjing210096 China

ISBN: (纸本)9789811580857

At present, technologies such as smart home and intelligent wearable devices are developing, bringing convenience and enjoyment to our daily lives, while also avoiding a series of potential hidden dangers. This study aims to design an intelligent mobile robot control system based on gesture recognition which allows people to control the forward, backward and steering of the mobile robot through simple gestures. For gesture recognition, this paper uses the MPU6050 accelerometer to detect and recognize human gestures. The system adopts the control chip STM32 MCU to collect the acceleration data. The results of the experiments have shown that the proposed gesture recognition device can control the mobile robot maneuvering well and complete the function of forward and backward and steering. © 2020, Springer Nature Singapore Pte Ltd.

关键词： Mobile robots

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Cache location selected algorithm for information-centric networking

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Guofang Keji Daxue Xuebao/Journal of National University of Defense Technology 2019年第1期41卷 152-160页

作者： Wang, Xingwei Wang, Zijian Li, Fuliang Huang, Min College of Software Northeastern University Shenyang110004 China School of Computer Science and Engineering Northeastern University Shenyang110004 China College of Information Science and Engineering Northeastern University Shenyang110004 China

The cache ubiquity feature in ICN (information-centric networking) causes many problems such as higher data duplication rate, underutilization of cache space, etc. To solve such problems, the benefits of multiple network roles were considered. From the views of user-service provider and network operator, two single-objective optimization models were established respectively, aiming at minimizing the network traffic and the network expense, which were merged into the Pareto model. The proposed cache location selected algorithm was described based on the mathematical programming method of Pareto. Simulation results show that the proposed algorithm outperforms the default cache mechanism of ICN in terms of traffic cost-effective. In terms of network expense, the proposed algorithm is more applicable to ICN when there are a few popular contents. However, when all contents are popular, the default mechanism of "cache everywhere" in ICN is more applicable. © 2019, NUDT Press. All right reserved.

关键词： Mathematical programming

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Noncontact Doppler Radar-based Heart Rate Detection on the SVD and ANC

Noncontact Doppler Radar-based Heart Rate Detection on the S...

引用

IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

作者： Qiuxia Shi Bin Hu Fuze Tian Qinglin Zhao Gansu Provincial Key Laboratory of Wearable Computing School of Information Science and Engineering Lanzhou University School of Computer and Communication Lanzhou University of Technology Ministry of Education Key Laboratory of Special Functional Materials and Structural Design (Lanzhou University) Lanzhou China CAS Center for Excellence in Brain Science and Intelligence Technology Shanghai Institutes for Biological Sciences Chinese Academy of Sciences Joint Research Center for Cognitive Neurosensor Technology of Lanzhou University & Institute of Semiconductors Chinese Academy of Sciences Engineering Research Center of Open Source Software and Real-Time System(Lanzhou University) Ministry of Education Key Laboratory of Special Functional Materials and Structural Design Ministry of Education Lanzhou University Lanzhou China

ISBN: (数字)9781665468190

ISBN: (纸本)9781665468206

In the Doppler biological radar-based applications of noncontact measurement of vital signs, effectively extracting heartbeat information from weak thoracic mechanical motion is an important problem to be solved. This study is aimed at extracting heartbeat signal via the technology combined with Short Time Fourier Transform (STFT), Singular Value Decomposition (SVD) and Adaptive Noise Canceller (ANC) from radar recording. The simulated data and the data collected by Doppler radar biosensor realized in laboratory are employed to validate the proposed method. The results show that the proposed method has the ability of detection for the heart rate and heart rate variability indexes in rest state, it has certain advantages in time-consuming and detection accuracy. Therefore, the current method provides another way to process vital sign signals recorded by Doppler radar.

关键词： Biomedical measurement Noise cancellation Time measurement Doppler radar Recording Doppler effect Biosensors

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