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Improved Quantum algorithm: A Crucial Stepping Stone in Quantum-Powered Drug Discovery

JOURNAL OF ELECTRONIC MATERIALS 2024年第5期54卷 3434-3443页

作者： Bikku, Thulasi Malligunta, Kiran Kumar Thota, Srinivasarao Surapaneni, Phani Praveen Amrita Vishwa Vidyapeetham Amrita Sch Comp Amaravati Dept Comp Sci & Engn Amaravati 522503 Andhra Pradesh India Koneru Lakshmaiah Educ Fdn Dept Elect & Elect Engn Vaddeswaram 522302 AP India Amrita Vishwa Vidyapeetham Amrita Sch Phys Sci Dept Math Amaravati 522503 Andhra Pradesh India PVP Siddhartha Inst Technol Dept Comp Sci & Engn Vijayawada 520007 Andhra Pradesh India

Quantum algorithms which were derived from quantum mechanics principles are further revolutionizing this process with their potential for detailed simulation of molecular interactions. Highly notable observations can be made by delving into quantum chemistry and molecular dynamics, which facilitates the identification of suitable candidates for drug synthesis. This capability enables the identification of potential drug candidates with greater efficiency and accuracy. The critical challenges that must be addressed to realize the potential of quantum computing in drug discovery are suppression of noise due to the susceptibility of quantum structures, enhancing the scalability of tests, and design optimization for complex algorithms. These requirements necessitate the design and implementation of improved quantum algorithms with guaranteed positive computational consistency. This will empower precise simulations of molecular interactions, establishing the groundwork for more sophisticated, world-class, and selective drug discovery methodologies. The proposed quantum algorithm model was tested with PubChem, BindingDB, Tox21, and Maximum Unbiased Validation (MUV) datasets. The performance was compared to existing machine learning algorithms in terms of accuracy, precision, recall, F1 score, qubit fidelity, quantum volume, measurement time, error rate, success rate, scalability, variational quantum eigensolver convergence, entanglement entropy, resource requirements, chemical accuracy, and parallelism, which improved outcomes in most of the parameters. The experimental study shows the transformative potential of integrating quantum algorithms in the pharmaceutical industry, paving the way for the development of more effective and targeted therapeutic solutions.

关键词： Quantum computing drug discovery noise mitigation scalability algorithm optimization

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Comparison of contrast reduction based MODIS AOT estimates with AERONET measurements

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ATMOSPHERIC RESEARCH 2012年 116卷 33-45页

作者： Grosso, N. Paronis, D. Univ Nova Lisboa CENSE Ctr Environm & Sustainabil Res Dept Ciencias & Engn Ambiente Fac Ciencias & Tecnol P-2829516 Caparica Portugal Natl Observ Athens Inst Space Applicat & Remote Sensing Lofos Koufos 15263 Palaia Penteli Greece

Current satellite aerosol retrieval products could be complemented by contrast reduction methods to overcome limitations regarding highly reflective or heterogeneous surfaces such as urban, desert or snow covered areas. algorithms based on the contrast reduction principle, define contrast loss in an image, inside a pre-determined window size, as an exponential function of the Aerosol Optical Thickness (AOT) difference between two images (a reference and a polluted) acquired under similar observation geometry conditions. This paper presents a contrast reduction algorithm designed for the MODIS sensor, based on the Differential Texture Analysis (DTA) approach. It focuses on algorithm optimization by: a) determining an optimal AOT spatial resolution;b) constraining the relative observation geometry differences between polluted and reference images;and c) assessing the influence of several land cover classes on the accuracy of the retrievals. A comparison of the results obtained for 192 images acquired for the year 2005 with data from five European AERONET stations is performed to assess overall algorithm accuracy as well as the impact of the proposed improvements. Comparative analysis of the results for the various sites showed an optimal algorithm performance for MODIS images using a 39 pixel distance window, composed of only forest and urban pixels. Comparison with AERONET AOT data showed a good agreement with a correlation coefficient of 0.78. A similar correlation is found when comparing AERONET measurements and MODIS aerosol standard product. This research supports the establishment of contrast reduction methods as a potential complement to other aerosol retrieval methodologies. Future work will aim at removing the residual aerosol influence from reference images, including BRDFs to better reproduce surface heterogeneity and observation geometry influences and expanding the scope of this study to other AERONET sites so as to further test the algorithm at a global

关键词： Aerosol remote sensing AOT retrieval MODIS Contrast reduction method algorithm optimization Comparison with AERONET measurements

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Recent advances in convolutional neural network acceleration

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NEUROCOMPUTING 2019年 323卷 37-51页

作者： Zhang, Qianru Zhang, Meng Chen, Tinghuan Sun, Zhifei Ma, Yuzhe Yu, Bei Southeast Univ Natl ASIC Syst Engn Technol Res Ctr Nanjing Jiangsu Peoples R China Chinese Univ Hong Kong Dept Comp Sci & Engn Hong Kong Hong Kong Peoples R China

In recent years, convolutional neural networks (CNNs) have shown great performance in various fields such as image classification, pattern recognition, and multi-media compression. Two of the feature properties, local connectivity and weight sharing, can reduce the number of parameters and increase processing speed during training and inference. However, as the dimension of data becomes higher and the CNN architecture becomes more complicated, the end-to-end approach or the combined manner of CNN is computationally intensive, which becomes limitation to CNN's further implementation. Therefore, it is necessary and urgent to implement CNN in a faster way. In this paper, we first summarize the acceleration methods that contribute to but not limited to CNN by reviewing a broad variety of research papers. We propose a taxonomy in terms of three levels, i.e. structure level, algorithm level, and implementation level, for acceleration methods. We also analyze the acceleration methods in terms of CNN architecture compression, algorithm optimization, and hardware-based improvement. At last, we give a discussion on different perspectives of these acceleration and optimization methods within each level. The discussion shows that the methods in each level still have large exploration space. By incorporating such a wide range of disciplines, we expect to provide a comprehensive reference for researchers who are interested in CNN acceleration. (C) 2018 Elsevier B.V. All rights reserved.

关键词： Convolutional neural network Model compression algorithm optimization Hardware acceleration

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Numerical simulation analysis of the rolling process based on the particle swarm hybrid algorithm

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IRONMAKING & STEELMAKING 2023年第9期50卷 1321-1330页

作者： Yan, Zhu-Wen Bu, He-Nan Li, Hao Hong, Lei Nanjing Inst Technol Ind Technol Res Inst Intelligent Equipment Jiangsu Prov Engn Lab Intelligent Mfg Equipment Nanjing Peoples R China Jiangsu Univ Sci & Technol Sch Mech Engn Zhenjiang Peoples R China Nanjing Inst Technol Ind Technol Res Inst Intelligent Equipment Jiangsu Prov Engn Lab Intelligent Mfg Equipment Nanjing 211167 Peoples R China

It is very complicated to study the three-dimensional deformation of metal during rolling. The conventional finite element numerical analysis method generally adopts a fixed algorithm to calculate the whole rolling process. This method consumes huge computing power and sacrifices some computing accuracy. In this paper, according to the characteristics of different rolling stages, on the basis of considering the degree of metal deformation, a particle swarm hybrid algorithm with adaptive weight-learning factor is *** Zoutendijk algorithm, Rosen algorithm, Wolfe algorithm and particle swarm hybrid algorithm are used to numerically simulate the rolling transverse thickness distribution. The accuracy of the rolling model and the particle swarm hybrid algorithm are verified. The influence of work roll edge contact and asymmetric roll bending on the deformation of rolling metal is analysed based on particle swarm mixing algorithm.

关键词： Rolling process metal deformation numerical simulation algorithm optimization influence law

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Steady-state and dynamic control of hydrocracking tail oil distillation process for high-valued products

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ASIA-PACIFIC JOURNAL OF CHEMICAL ENGINEERING 2024年第4期19卷

作者： Li, Min Liu, Wenzhi Gao, Yan Huang, Zhuocheng Li, Gaoyang Pan, Hui Ling, Hao East China Univ Sci & Technol State Key Lab Chem Engn Sch Chem Engn Shanghai 200237 Peoples R China Shanghai Univ Elect Power Coll Environm & Chem Engn Shanghai Key Lab Mat Protect & Adv Mat Elect Power Shanghai 200090 Peoples R China

The maximum utilization of hydrocracking tail oil becomes increasingly important for petrochemical industry. The aim of this work is to develop optimized distillation processes to achieve various high-valued qualified oil products from hydrocracking tail oil. Six different oil products is produced and the steady-state distillation process, which aims to fractionate six qualified narrow distillates is established. The algorithm method incorporating divided-wall column (DWC) configuration was introduced into the steady-state design. Compared with traditional separation sequences, the DWC configuration leads to an energy-saving potential up to 11.17%. Furthermore, effective dynamic control strategies were proposed, demonstrating precise and efficient control performance. In the presence of a 15% feed disturbance, the dynamic control structure is capable of maintaining the product distillation range near the set value. This comprehensive study provides a thorough investigation into the efficient utilization of hydrocracking tail oil, establishing a robust theoretical foundation for its industrial application.

关键词： algorithm optimization dynamic simulation hydrocracking tail oil steady-state simulation

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A Reconfigurable Metasurface Enhancing Signal Coverage for Wireless Communication Using Reduced Numbers of p-i-n Diodes

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IEEE TRANSACTIONS ON MICROWAVE THEORY AND TECHNIQUES 2024年第3期72卷 1964-1978页

作者： Xue, Hao Lu, Zeqing Ma, Xiangjin Wang, Zhiding Zhu, Lihao Yue, Shuyao Han, Jiaqi Liu, Haixia Li, Long Xidian Univ Sch Elect Engn Key Lab High Speed Circuit Design & EMC Minist Educ Xian 710071 Peoples R China

This article proposes a reflective reconfigurable metasurface design that can reduce the number of p-i-n diodes required by up to 60% for enhancing wireless communication signal coverage. The metasurface is also optimized from two aspects of element and array and can achieve enhanced signal coverage in a variety of regions, which proposes a low-cost general-purpose scheme and device. The reconfigurable element with a relative bandwidth of 8.2% is designed in a "subarray" form to reduce the p-i-n diode loading by half, and the array is sparsely designed, resulting in a further reduction of 20%. The genetic algorithm (GA) optimization method suitable for the digital coding metasurface is proposed to optimize the element's phase discretization scheme and the array's sparse method. The proposed metasurface is loaded in familiar T-shaped corridor models, and the coverage enhancement is verified based on the co-simulation of different software, showing the device can be applied in different scenes. For the first time, systematic measurement in a realistic environment using a reconfigurable metasurface with a reduced number of p-i-n diodes is performed, which proves that it can achieve signal coverage improvement in the corridor and in the actual 5G communication environment. The results indicate that this design greatly reduces system complexity and cost, which can be compatible with existing communication optimization methods, providing a practical, scalable scheme and device for enhancing signal coverage in various scenes.

关键词： & nbsp algorithm optimization low diode loading ratio low-cost general-purpose scheme reflective reconfigurable meta-surface signal coverage wireless propagation measurements

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Security algorithm of Internet of Things based on ZigBee protocol

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CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS 2019年第6期22卷 14759-14766页

作者： Wang, Yongkang Chen, Chunxia Jiang, Qijie Civil Aviat Flight Univ China Sch Aviat Transportat Management Guanghan Peoples R China Chengdu Technol Univ Sch Econ & Management Chengdu Sichuan Peoples R China Univ Nottingham Sch Business Nottingham England

To study the application of ZigBee protocol in the security algorithm of Internet of Things, the relevant development status at home and abroad is firstly summarized and ZigBee technology is introduced in detail. Then, the principle of AES-128 algorithm is analyzed, and the steps of decryption algorithm are adjusted, so that the decryption algorithm is symmetric in structure and encryption algorithm. In addition, the encryption and decryption algorithm of AES-128 is implemented by using C language. Based on the characteristics of simplicity and low cost of ZigBee technology, the two optimization algorithms are designed and implemented from the analysis of simplicity and efficiency based on the performances of security algorithm. The analysis and test results show that the two optimization algorithms are better than the UN optimized algorithm in terms of speed and complexity. To sum up, in the result comparison, it is found that the speed and complexity of the round operation optimization algorithm is better than that of the column obfuscation optimization algorithm.

关键词： ZigBee protocol Security AES-128 algorithm optimization

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Fish sonar image recognition algorithm based on improved YOLOv5

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MATHEMATICAL BIOSCIENCES AND ENGINEERING 2024年第1期21卷 1321-1341页

作者： Xing, Bowen Sun, Min Ding, Minyang Han, Chuang Shanghai Ocean Univ Coll Engn Sci & Technol Shanghai 201306 Peoples R China Marine Design & Res Inst China Shanghai 200011 Peoples R China Harbin Univ Sci & Technol Heilongjiang Prov Key Lab Laser Spect Technol & Ap Harbin 150080 Peoples R China

Fish stock assessment is crucial for sustainable marine fisheries management in rangeland ecosystems. To address the challenges posed by the overfishing of offshore fish species and facili-tate comprehensive deep-sea resource evaluation, this paper introduces an improved fish sonar image detection algorithm based on the you only look once algorithm, version 5 (YOLOv5). Sonar image noise often results in blurred targets and indistinct features, thereby reducing the precision of object detection. Thus, a C3N module is incorporated into the neck component, where depth-separable convo-lution and an inverse bottleneck layer structure are integrated to lessen feature information loss during downsampling and forward propagation. Furthermore, lowercase shallow feature layer is introduced in the network prediction layer to enhance feature extraction for pixels larger than 4 x 4. Additionally, normalized weighted distance based on a Gaussian distribution is combined with Intersection over Union (IoU) during gradient descent to improve small target detection and mitigate the IoU's scale sensitivity. Finally, traditional non-maximum suppression (NMS) is replaced with soft-NMS, reducing missed detections due to occlusion and overlapping fish targets that are common in sonar datasets. Experiments show that the improved model surpasses the original model and YOLOv3 with gains in precision, recall and mean average precision of 2.3%, 4.7% and 2.7%, respectively, and 2.5%, 6.3% and 6.7%, respectively. These findings confirm the method's effectiveness in raising sonar image de-tection accuracy, which is consistent with model comparisons. Given Unmanned Underwater Vehicle advancements, this method holds the potential to support fish culture decision-making and facilitate fish stock resource assessment.

关键词： sonar fish detection YOLOv5 deep learning algorithm optimization

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Application of big data optimized clustering algorithm in cloud computing environment in traffic accident forecast

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PEER-TO-PEER NETWORKING AND APPLICATIONS 2021年第4期14卷 2511-2523页

作者： Tian, Zhun Zhang, Shengrui Changan Univ Coll Transportat Engn Xian 710064 Shaanxi Peoples R China Xian Univ Architecture & Technol Sch Civil Engn Xian 710055 Shaanxi Peoples R China Changan Univ Key Lab Transport Ind Management Control & Cycle Xian 710064 Shaanxi Peoples R China

As the usage rate of cars is getting higher and higher, the injuries and losses caused by traffic accidents are also getting bigger and bigger. If some traffic accidents can be predicted, then such losses can be greatly solved. Although there are abundant research results on intelligent transportation, there are not many research results on how to predict traffic accidents. For this issue, the main aim of this paper is to propose a continuous non-convex optimization of the K-means algorithm in order to solve the model problem in the traffic prediction process. First, this paper uses clustering algorithm for feature analysis and big data for the establishment of simulation model in cloud environment. Through this paper an equivalent model, using matrix optimization theory to analyze and process K-means problem, and design efficient and theoretically guaranteed algorithms for big data. By simulating the traffic situation in Shanghai city within three years, the outcomes display that the model endorsed in the given paper can predict traffic accidents at a rate of 93.88% and the accuracy rate of traffic accident processing time is 78%, which fully illustrates the effectiveness of the model established in this paper.

关键词： Cloud computing Big data Clustering algorithm Traffic accident prediction algorithm optimization

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Optimal implicit single-step time integration methods with equivalence to the second-order-type linear multistep methods for structural dynamics: Accuracy analysis based on an analytical framework

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COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING 2024年 418卷

作者： Zhang, Jie Jinan Univ Sch Mech & Construct Engn MOE Key Lab Disaster Forecast & Control Engn Guangzhou 510632 Peoples R China

This paper presents a comprehensive study of the second-order-type time integration methods family encompassing the linear multistep (LMS) methods, the single-step methods, and the LMS equivalent single-step methods for structural dynamics. An analytical accuracy framework for algorithm design, convergence, and optimization is developed, where the obstacles encountered in algorithms construction, convergence accuracy, algorithms equivalence, accuracy measurement, and accuracy optimization in traditional accuracy frameworks are well addressed. Rigorous accuracy analysis successively to the second-order-type LMS (LMS2) methods, the single-step methods, and the LMS2 equivalent single-step methods aims to reveal optimal algorithms with desirable numerical properties. First, independent implicit algorithms including the velocity type and the acceleration type LMS2 methods except the displacement type ones are newly revealed in the LMS2 methods family with second-order convergence and A-stability, and three error constants that can play essential roles in the accuracy measurement and algorithm optimization are developed. Second, a single-step methods family where the displacement, velocity, and acceleration can achieve the same order of accuracy simultaneously is revealed in a generalized 16 -parameters methods family, which contains numerous conventional single-step single-solve methods as subfamily methods. It is found that the unit consistent and non-consistent represen-tations show a significant difference in the local truncation error, stability, and convergence performances. Third, a family of accuracy-improved single-step methods with algorithmic equivalence, which is stricter than the traditional spectral equivalence, to the LMS2 methods is revealed. It is clarified that the difference between the methods with equivalence can significantly influence their convergence accuracy, and the error constants concept of the LMS2 methods can be extended to the single-step m

关键词： Accuracy analysis algorithm optimization Controllable numerical dissipation Stability Time integration Structural dynamics

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