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Articles 481 - 510 of 790
Full-Text Articles in Artificial Intelligence and Robotics
Machine Learning Models For Deciphering Regulatory Mechanisms And Morphological Variations In Cancer, Saman Farahmand
Machine Learning Models For Deciphering Regulatory Mechanisms And Morphological Variations In Cancer, Saman Farahmand
Graduate Doctoral Dissertations
The exponential growth of multi-omics biological datasets is resulting in an emerging paradigm shift in fundamental biological research. In recent years, imaging and transcriptomics datasets are increasingly incorporated into biological studies, pushing biology further into the domain of data-intensive-sciences. New approaches and tools from statistics, computer science, and data engineering are profoundly influencing biological research. Harnessing this ever-growing deluge of multi-omics biological data requires the development of novel and creative computational approaches. In parallel, fundamental research in data sciences and Artificial Intelligence (AI) has advanced tremendously, allowing the scientific community to generate a massive amount of knowledge from data. Advances …
Using Deep Learning To Automate The Diagnosis Of Skin Melanoma, Akhil Reddy Alasandagutti
Using Deep Learning To Automate The Diagnosis Of Skin Melanoma, Akhil Reddy Alasandagutti
Honors Theses
Machine learning and image processing techniques have been widely implemented in the field of medicine to help accurately diagnose a multitude of medical conditions. The automated diagnosis of skin melanoma is one such instance. However, a majority of the successful machine learning models that have been implemented in the past have used deep learning approaches where only raw image data has been utilized to train machine learning models, such as neural networks. While they have been quite effective at predicting the condition of these lesions, they lack key information about the images, such as clinical data, and features that medical …
Low-Power And Reconfigurable Asynchronous Asic Design Implementing Recurrent Neural Networks, Spencer Nelson
Low-Power And Reconfigurable Asynchronous Asic Design Implementing Recurrent Neural Networks, Spencer Nelson
Graduate Theses and Dissertations
Artificial intelligence (AI) has experienced a tremendous surge in recent years, resulting in high demand for a wide array of implementations of algorithms in the field. With the rise of Internet-of-Things devices, the need for artificial intelligence algorithms implemented in hardware with tight design restrictions has become even more prevalent. In terms of low power and area, ASIC implementations have the best case. However, these implementations suffer from high non-recurring engineering costs, long time-to-market, and a complete lack of flexibility, which significantly hurts their appeal in an environment where time-to-market is so critical. The time-to-market gap can be shortened through …
Guest Editorial: Non-Iid Outlier Detection In Complex Contexts, Guansong Pang, Fabrizio Angiulli, Mihai Cucuringu, Huan Liu
Guest Editorial: Non-Iid Outlier Detection In Complex Contexts, Guansong Pang, Fabrizio Angiulli, Mihai Cucuringu, Huan Liu
Research Collection School Of Computing and Information Systems
Outlier detection, also known as anomaly detection, aims at identifying data instances that are rare or significantly different from the majority of instances. Due to its significance in many critical domains like cybersecurity, fintech, healthcare, public security, and AI safety, outlier detection has been one of the most active research areas in various communities, such as machine learning, data mining, computer vision, and statistics. Traditional outlier-detection techniques generally assume that data are independent and identically distributed (IID), which are significantly challenged in complex contexts where data are actually non-IID. These contexts are ubiquitous in not only graph data, sequence data, …
Adaptive Operating Hours For Improved Performance Of Taxi Fleets, Rajiv Ranjan Kumar, Pradeep Varakantham, Shih-Fen Cheng
Adaptive Operating Hours For Improved Performance Of Taxi Fleets, Rajiv Ranjan Kumar, Pradeep Varakantham, Shih-Fen Cheng
Research Collection School Of Computing and Information Systems
Taxi fleets and car aggregation systems are an important component of the urban public transportation system. Taxis and cars in taxi fleets and car aggregation systems (e.g., Uber) are dependent on a large number of self-controlled and profit-driven taxi drivers, which introduces inefficiencies in the system. There are two ways in which taxi fleet performance can be optimized: (i) Operational decision making: improve assignment of taxis/cars to customers, while accounting for future demand; (ii) strategic decision making: optimize operating hours of (taxi and car) drivers. Existing research has primarily focused on the operational decisions in (i) and we focus on …
Analog Spiking Neural Network Implementing Spike Timing-Dependent Plasticity On 65 Nm Cmos, Luke Vincent
Analog Spiking Neural Network Implementing Spike Timing-Dependent Plasticity On 65 Nm Cmos, Luke Vincent
Graduate Theses and Dissertations
Machine learning is a rapidly accelerating tool and technology used for countless applications in the modern world. There are many digital algorithms to deploy a machine learning program, but the most advanced and well-known algorithm is the artificial neural network (ANN). While ANNs demonstrate impressive reinforcement learning behaviors, they require large power consumption to operate. Therefore, an analog spiking neural network (SNN) implementing spike timing-dependent plasticity is proposed, developed, and tested to demonstrate equivalent learning abilities with fractional power consumption compared to its digital adversary.
Exploring Ai And Multiplayer In Java, Ronni Kurtzhals
Exploring Ai And Multiplayer In Java, Ronni Kurtzhals
Student Academic Conference
I conducted research into three topics: artificial intelligence, package deployment, and multiplayer servers in Java. This research came together to form my project presentation on the implementation of these topics, which I felt accurately demonstrated the various things I have learned from my courses at Moorhead State University. Several resources were consulted throughout the project, including the work of W3Schools and StackOverflow as well as relevant assignments and textbooks from previous classes. I found this project relevant to computer science and information systems for several reasons, such as the AI component and use of SQL data tables; but it was …
Exploring Complementary Strengths Of Invariant And Equivariant Representations For Few-Shot Learning, Mamshad Nayeem Rizve, Salman Khan, Fahad Shahbaz Khan, Mubarak Shah
Exploring Complementary Strengths Of Invariant And Equivariant Representations For Few-Shot Learning, Mamshad Nayeem Rizve, Salman Khan, Fahad Shahbaz Khan, Mubarak Shah
Computer Vision Faculty Publications
In many real-world problems, collecting a large number of labeled samples is infeasible. Few-shot learning (FSL) is the dominant approach to address this issue, where the objective is to quickly adapt to novel categories in presence of a limited number of samples. FSL tasks have been predominantly solved by leveraging the ideas from gradient-based meta-learning and metric learning approaches. However, recent works have demonstrated the significance of powerful feature representations with a simple embedding network that can outperform existing sophisticated FSL algorithms. In this work, we build on this insight and propose a novel training mechanism that simultaneously enforces equivariance …
Mesoscopic Traffic Simulation Model And Calibration Considering Stretching-Segment Design, Zhaocheng He, Xuanhua Lin, Peilin Nie, Ronghui Zhang
Mesoscopic Traffic Simulation Model And Calibration Considering Stretching-Segment Design, Zhaocheng He, Xuanhua Lin, Peilin Nie, Ronghui Zhang
Journal of System Simulation
Abstract: In order to make the simulation model fit the characteristics of urban traffic, both high accuracy and high performance, a lightweight mesoscopic traffic simulation system and the process of calibration are established. The speed-density model and vertical queue model are equivalent to the vehicle movement processes, the simulation accuracy and calibration efficiency are improved by the stretching-segment design at urban intersections of vertical queuing model, and the real individual vehicle information is used as the calibration data source. The application of the model in Xuancheng urban road network shows that, compared with the vertical queuing model, it can …
Modeling And Simulation Of Electric Vehicle Industry Development Based On System Dynamics, Yueqiang Fu, Tiantian Xia
Modeling And Simulation Of Electric Vehicle Industry Development Based On System Dynamics, Yueqiang Fu, Tiantian Xia
Journal of System Simulation
Abstract: New energy electric vehicle are the main trend of automobile industry upgrading. It plays an important role in ensuring the energy security and improving the ecological environment. It is of theoretical and practical significance to carry out research on the development of new energy electric vehicles. The affecting factors are systematically analyzed, the causal relationship model and stock flow model are established, and the dynamic equation of the model are determined and the parameter assignments are made. The model is verified and the system simulation and analysis are performed. The development trend and main influencing factors of …
Small Fault Detection Based On Cumulative Sum Of Neighbor Statistic, Xiaoping Guo, Jiajun Gao, Jianbin Guo, Li Yuan
Small Fault Detection Based On Cumulative Sum Of Neighbor Statistic, Xiaoping Guo, Jiajun Gao, Jianbin Guo, Li Yuan
Journal of System Simulation
Abstract: Aiming at the small faults and the common data non-linear problems of industrial process, a fault detection method based oncumulative sum of neighbor statistic (CUSUM-NS) is proposed. Mutual information principal component analysis (MIPCA) is used to reduce the dimension of training data, and the principal components based on mutual information are extracted to construct a new sample space. For the new sample space after dimensionality reduction, the nonlinear features of the process data can be fully extracted through the distance square sum statistics of k nearest neighbors. Cumulative summation(CUSUM) method is used to accumulate the sum of squares of …
Visual Simulation Platform For Visible Light Reconnaissance Load Of Unmanned Aerial Vehicle, Yuzhou Chen, Li Yuan, Qinglin Wang, Zhang Qing, Jinyuan Zhang
Visual Simulation Platform For Visible Light Reconnaissance Load Of Unmanned Aerial Vehicle, Yuzhou Chen, Li Yuan, Qinglin Wang, Zhang Qing, Jinyuan Zhang
Journal of System Simulation
Abstract: In view of the simulation and evaluation requirement of the visual system parameters on the performance of video imaging during the operation and reconnaissance of unmanned aerial vehicle, a visual simulation platform for the reconnaissance load is designed and constructed. The collected video is processed according to the visual system parameters and the flight parameters, and the support for the evaluation and the index design of the unmanned aerial vehicle reconnaissance load system is provided, and the guidance is provided for the flight parameters and the flight track setting when the unmanned aerial vehicle reconnaissance and operation …
Research On Some Questions Of Simulation Body Of Knowledge, Xiaogang Qiu, Duan Hong, Xie Xu, Bin Chen
Research On Some Questions Of Simulation Body Of Knowledge, Xiaogang Qiu, Duan Hong, Xie Xu, Bin Chen
Journal of System Simulation
Abstract: Simulation body of knowledge (BOK) is the knowledge required to conduct Modeling and Simulation (M&S) activities, which is a logic system consisting of concepts, propositions, and inferences that are tightly related to each other. The simulation BOK organizes the M&S knowledge in a hierarchical way, reflects the composition and structure of the knowledge in the M&S domain. The establishment of the simulation BOK is crucial to advance the M&S research and education. The requirements for establishing the simulation BOK are summarized, three basic features of the simulation knowledge, practical, systematical, and epochal are discussed, the challenges of establishing the …
Study On Composition Of Simulation Discipline Knowledge Areas, Duan Hong, Xiaogang Qiu, Xie Xu, Rusheng Ju
Study On Composition Of Simulation Discipline Knowledge Areas, Duan Hong, Xiaogang Qiu, Xie Xu, Rusheng Ju
Journal of System Simulation
Abstract: Many disciplines, such as Software Engineering, Automation, have sorted out and formed their own knowledge areas and constructed their Body of Knowledge to steer teaching and study efforts. Describing the composition of Modeling and Simulation body of knowledge from the perspective of knowledge area plays an important role in the simulation engineering education and the development of simulation technology. According to the needs of simulation teaching, the body of knowledge of simulation discipline is divided into three levels, knowledge area, knowledge unit and knowledge topic. On the basis of reviewing the current status of the research and the role …
Research On Combat Simulation Body Of Knowledge, Xie Xu, Xiaogang Qiu, Duan Hong, Kedi Huang
Research On Combat Simulation Body Of Knowledge, Xie Xu, Xiaogang Qiu, Duan Hong, Kedi Huang
Journal of System Simulation
Abstract: Combat simulation is an important research method in modern military domain, since it provides a virtual battlespace for entities of various types that are involved in a battle to interact with each other. Over last several decades, combat simulation has been widely applied in different applications, and as a result the body of knowledge of combat simulation has been extended a lot. The relevant articles and textbooks in combat simulation are extensively investigated, and a three-layer structure to organize the body of knowledge of combat simulation is proposed. Eleven knowledge areas that should be included in the combat simulation …
Personalized Game Recommendation Method Based On Implicit Feedback, Sha Jing, Gongli Zeng, Yang Yang, Wei Yao
Personalized Game Recommendation Method Based On Implicit Feedback, Sha Jing, Gongli Zeng, Yang Yang, Wei Yao
Journal of System Simulation
Abstract: Traditional recommendation systems often use explicit feedback for personalized recommendations. But the explicit feedback data is not easy to obtain, and the quality is poor, and the recommendation results unable to meet the requitrment of the user. Implicit feedback data is easier to obtain and can provide users with the better content. A personalized game recommendation method based on implicit feedback data is proposed. The method builds an implicit feedback recommendation model for game user data based on implicit feedback data such as the game duration and game numbers. A personalized recommendation of the game is implemented through an …
Mesh Solid Construction Algorithm Of Spiral Bevel Gear Based On Virtual Collision Body, Cheng'en Li, Xiangjun Zou, Zeqin Zeng, Jianhua He, Li Hui, Zhaofeng Huang
Mesh Solid Construction Algorithm Of Spiral Bevel Gear Based On Virtual Collision Body, Cheng'en Li, Xiangjun Zou, Zeqin Zeng, Jianhua He, Li Hui, Zhaofeng Huang
Journal of System Simulation
Abstract: In order to improve the production automation, intelligence level and production efficiency of the tractor rear axle, the spiral bevel gear mesh entity based on the virtual collision body is constructed to carry out the human-machine interaction virtual simulation experiment of the tractor rear axle. The spiral bevel gear made by Gleason as is taken an example, the processing technology of arc spur gear is analyzed, the kinematics is used to establish a mathematical model of the spiral bevel gear forming process. The differential and interpolation methods are used to fit the gear curve and surface, the contour point …
Gas-Liquid Two-Phase Flow Pattern Recognition Method Based On Convolutional Neural Network, Weiguo Tong, Xuechun Pang, Genghong Zhu
Gas-Liquid Two-Phase Flow Pattern Recognition Method Based On Convolutional Neural Network, Weiguo Tong, Xuechun Pang, Genghong Zhu
Journal of System Simulation
Abstract: Aiming at the low recognition rate and subjectivity in two-phase flow pattern recognition, a method based on Landweber iterative image reconstruction algorithm and convolutional neural network is proposed. Landweber iterative image reconstruction algorithm is used to obtain the flow pattern images and build the flow pattern image database. By means of the flow pattern identification on, different convolution layers in VGG16 network and different size and resolution of the data set samples, the parameters of network frozen convolutional layer and input image are determined.The experimental results show that the combined method of resistance tomography and convolutional neural network …
Operation Resilience Optimization Of Power System Considering Generalized Energy Storage, Weiqing Sun, Zhang Jie, Ye Lei, Han Dong
Operation Resilience Optimization Of Power System Considering Generalized Energy Storage, Weiqing Sun, Zhang Jie, Ye Lei, Han Dong
Journal of System Simulation
Abstract: Based on the definition and principle of power system resilience, combining the traditional energy storage equipment with the demand response, an optimization method of power system operation resilience considering generalized energy storage is proposed. Five attack schemes based on topology are evaluated according to four indexes, and the most disadvantageous attack strategy is selected to simulate the damage of power system. Taking the minimum operating cost of the system as the objective, a combined scheduling model involving wind power station and energy storage unit is carried out. A generalized energy storage scheduling method is proposed to improve the …
Study On Relay Selection Algorithm Based On Swipt Wireless Cooperative Network, Qun Fang, Xukai Chen, He Xin, Yujun Zhu, Yiyang Liu, Yangyang Fang, Heju Li
Study On Relay Selection Algorithm Based On Swipt Wireless Cooperative Network, Qun Fang, Xukai Chen, He Xin, Yujun Zhu, Yiyang Liu, Yangyang Fang, Heju Li
Journal of System Simulation
Abstract: Although the wireless cooperative networks (WCN) significantly improve the communication quality and network throughput of wireless communications. However, it still faces the challenge of the network lifetime and the energy replenishment due to the energy limitation of relay nodes. In order to tackle this challenge, A multi-relay wireless cooperative network combined with the simultaneous wireless information and power transfer (SWIPT) is proposed and the theoretical performance under the Nakagami-m assumption is analyzed. The selection of the optimal relay node for wireless cooperative networks in the framework of the proposed system is studied. The outage probability of the system …
Compensation Sliding Cross Coupling Control Research Of Cartesian Coordinate Robot, Wang Wei, Zhimei Chen, Zhenyan Wang
Compensation Sliding Cross Coupling Control Research Of Cartesian Coordinate Robot, Wang Wei, Zhimei Chen, Zhenyan Wang
Journal of System Simulation
Abstract: For a typical Cartesian coordinate robot controls precision is low, based on a single-axis mathematical model, a contour error model for a typical robot whose axes are orthogonal to each other is established. An improved double-power approach law is used to design a terminal sliding mode controller to improve the robot. The integral compensation terms are added to stably compensate the position accuracy of each axis to improve the overall trajectory tracking accuracy, and the cross-coupling control between the axes is used to eliminate the contour error between the axes. It not only weakens the chattering of traditional sliding …
Design And Implementation Of Multi Level Terrain Editing Tool, Xiang Bing, Yang Gang, Xiaohong Dong
Design And Implementation Of Multi Level Terrain Editing Tool, Xiang Bing, Yang Gang, Xiaohong Dong
Journal of System Simulation
Abstract: 3D terrain is an indispensable scene element in computer games, virtual simulation, geographic information and other applications. Realistic digital terrain plays an important role in enhancing the reality of virtual scene and the immersion of users. Based on the in-depth analysis of terrain features and user modeling requirements, a multi-level terrain editing mode is constructed. In the mode, the terrain editing behavior can be expanded from three levels of point, line and face. Each level has a specific operation target and corresponding editing tools. A multi-level and comprehensive terrain editing tool set composed of point tool, curve tool and …
Simulation And Optimization Of Support Resource Allocation For Multi-Aircraft Large Fleet Re Dispatch, Xu Gang, Zhang Lei, Yonggang Yun, Du Li
Simulation And Optimization Of Support Resource Allocation For Multi-Aircraft Large Fleet Re Dispatch, Xu Gang, Zhang Lei, Yonggang Yun, Du Li
Journal of System Simulation
Abstract: In view of the complex combination of support resources of multi-aircraft large fleet re dispatch, based on the new complex factors of different models, different support expectation time and different main resource types, the simulation model of multi-aircraft support process based on queuing network is established and a simulation algorithm for the optimal allocation of support resources is proposed. The algorithm takes the total time of fleet support, the average time of aircraft support, the average intensity of fleet support, the cost of resources, the balance of free and busy support, the balance of resource supply and demand as …
Research On Fingerprint Location Algorithm Based On Dynamic Fingerprint Update, Lizhen Cui, Qiaoli Wang, Qianqian Guo, Yang Yong
Research On Fingerprint Location Algorithm Based On Dynamic Fingerprint Update, Lizhen Cui, Qiaoli Wang, Qianqian Guo, Yang Yong
Journal of System Simulation
Abstract: According to the characteristics of underground environment, a fingerprint location algorithm based on dynamic fingerprint updating is proposed. FCM(Fuzzy C-Means Clustering) is used to divide the location area according to the signal distribution characteristics, and the training and learning model is established in each sub area. On the basis of FCM algorithm, a HMM(Hidden Markov Model) motion information sequence model based on the location of mobile users is proposed. The dynamic update of fingerprint database is realized by users unconsciously participating in the collection of RSSI(Received Signal Strength Indication) sequence. ANFIS(Adaptive Network-based Fuzzy Inference System) algorithm …
Load System Modeling Of Ultra-Supercritical Coal-Fired Power Unit Based On Improved Particle Swarm Optimization, Yuzhen Sun, Yiwei Tang, Li Shuai
Load System Modeling Of Ultra-Supercritical Coal-Fired Power Unit Based On Improved Particle Swarm Optimization, Yuzhen Sun, Yiwei Tang, Li Shuai
Journal of System Simulation
Abstract: Aiming at the difficulties in modeling due to variables coupling of ultra-supercritical coal-fired power unit and defects in basic particle swarm optimization, an improved particle swarm optimization algorithm for modeling of load system is proposed. The algorithm introduces the idea of adaptive, Cauchy mutation and gradient guidance crossover, which improves the problems of particle swarm optimization algorithm being prone to premature convergence and has the poor local searching ability. By collecting the actual operation data of the power plant, using the adaptive Cauchy mutation and gradient guidance cross particle swarm optimization (GMGPSO) algorithm, the model established and validated …
Solving Engineering Optimization Design Problems Based On Improved Salp Swarm Algorithm, Jingsen Liu, Mengmeng Yuan, Li Yu
Solving Engineering Optimization Design Problems Based On Improved Salp Swarm Algorithm, Jingsen Liu, Mengmeng Yuan, Li Yu
Journal of System Simulation
Abstract: In order to better solve the engineering optimization design problem and improve the optimization performance of salp swarm algorithm, an adaptive dynamic role salp swarm algorithm with effective scaling and random crossover strategy is proposed. A pareto distribution and chaotic map are introduced into the leader position updating formula to make global search more efficient. In the selection of global and local search, a leader-follower adaptive adjustment strategy is introduced to improve the convergence accuracy. A random crossover strategy is introduced in local search to increase population diversity. The improved algorithm is applied to engineering optimization problems with different …
Combined Gearbox Transmission Ratio Optimization Research Based On Hybrid Particle Swarm, Runhong Wang, Hongjun Wang, Xiangjun Zou, Zeqin Zeng, Li Hui, Zhaofeng Huang, Weiliang Liu
Combined Gearbox Transmission Ratio Optimization Research Based On Hybrid Particle Swarm, Runhong Wang, Hongjun Wang, Xiangjun Zou, Zeqin Zeng, Li Hui, Zhaofeng Huang, Weiliang Liu
Journal of System Simulation
Abstract: Aiming at the difficulty to obtain the optimal solution for the transmission ratio distribution of combined transmission, an optimization method for the transmission ratio of the combined multi-speed transmission based on the hybrid particle swarm optimization algorithm is proposed. Based on the multi-objective particle swarm algorithm, a leader population with a self-renewal mechanism is introduced to form a hybrid particle swarm algorithm. A multi-objective optimization model is established by taking the transmission ratio of each stage of single-speed transmission as a variable, combining the transmission chain layout, taking the driving power loss rate, specific fuel consumption loss …
Research On Fjsp Of Improved Particle Swarm Optimization Algorithm Considering Transportation Time, Chen Kui, Bi Li
Research On Fjsp Of Improved Particle Swarm Optimization Algorithm Considering Transportation Time, Chen Kui, Bi Li
Journal of System Simulation
Abstract: In the actual FJSP(Flexible Job-shop Scheduling Problem) production environment, there is not only the processing time of the workpiece, but also the transport time of the workpiece between the machines, so the flexible job shop scheduling considering the transport time is more practically significant. A hybrid discrete particle swarm optimization algorithm is proposed to solve the flexible job-shop scheduling problem considering transport time. Aiming at the instability and precocity of particle swarm optimization algorithm, the neighborhood search algorithm is applied to improve its stability, and the combination of competitive learning mechanism and random restart algorithm are introduced to avoid …
Simulation Of Anti-Ship Missile Automatic Control Section Trajectory Based On Pso-Lssvm, Shao Cheng, Hongyuan Sun, Zhang Lin
Simulation Of Anti-Ship Missile Automatic Control Section Trajectory Based On Pso-Lssvm, Shao Cheng, Hongyuan Sun, Zhang Lin
Journal of System Simulation
Abstract: The anti-ship missile trajectory simulation model cannot meet requirements of the “red and blue” confrontation simulation deduction. Trajectory modeling of anti-ship missiles based on field data will be a new method. Taking a typical anti-ship missile as an example, a trajectory modeling and simulation method of the missile self-control section based on field data is proposed. The field data is analyzed and the least square polynomial method is used to fit the missile velocity-time curve. Particle Swarm Optimization Least Square Support Vector Machine (PSO-LSSVM) is used to model. The verified and validated show the model has high credibility and …
Modeling And Simulation Of Urination Assist System Based On Working Medium Saturated Vapor Pressure, Li Xiao, Li Shu, Weihong Peng, Ting Guan
Modeling And Simulation Of Urination Assist System Based On Working Medium Saturated Vapor Pressure, Li Xiao, Li Shu, Weihong Peng, Ting Guan
Journal of System Simulation
Abstract: To design and analyze the urination assist system driven by ultrasonic-vaporized steam, a simulation model of the driving capsule and three mathematical models of working medium saturated vapor pressure, bladder pressure and urine flow are established. The simulation experiment system is built to verify the model. The effects of radiation time and sound intensity on the working medium temperature and driving pressure are simulated and analyzed. The results show that the working medium temperature and driving pressure are related to the radiation time and sound intensity. Prolonging radiation time and increasing sound intensity can increase the working medium …