Open Access. Powered by Scholars. Published by Universities.®
- Institution
-
- University of Nebraska - Lincoln (4187)
- China Simulation Federation (3880)
- TÜBİTAK (3106)
- Chinese Chemical Society | Xiamen University (2029)
- Wright State University (2027)
-
- Old Dominion University (1913)
- China Coal Technology and Engineering Group (CCTEG) (1799)
- University of Kentucky (1290)
- Air Force Institute of Technology (1166)
- Missouri University of Science and Technology (1104)
- Utah State University (903)
- Singapore Management University (888)
- Embry-Riddle Aeronautical University (866)
- University of Nevada, Las Vegas (866)
- Washington University in St. Louis (825)
- University of Arkansas, Fayetteville (620)
- University of Central Florida (581)
- Changsha University of Science and Technology (570)
- Chulalongkorn University (462)
- Montana Tech Library (447)
- Purdue University (406)
- Portland State University (395)
- University of Colorado Law School (384)
- University of South Florida (380)
- Neutrosophic Systems with Applications (375)
- National Taiwan Ocean University (328)
- University of Texas at El Paso (321)
- University of Dayton (288)
- Technological University Dublin (257)
- Santa Clara University (255)
- Keyword
-
- Machine learning (476)
- Engineering (407)
- Computer Science (370)
- Deep learning (357)
- Montana (299)
-
- Department of Computer Science and Engineering (285)
- Simulation (262)
- Gas (260)
- And Energy; Structural Materials; Sustainability (248)
- Energy Systems; Environmental Indicators and Impact Assessment; Environmental Monitoring; Mining Engineering; Oil (248)
- Machine Learning (228)
- Optimization (227)
- Applied sciences (223)
- Sustainability (199)
- Numerical simulation (182)
- Artificial intelligence (181)
- Technical writing (159)
- College of Engineering and Computer Science (157)
- Newsletters (157)
- Science news (157)
- Classification (144)
- Genetic algorithm (133)
- Climate change (130)
- Modeling (126)
- Cybersecurity (120)
- Deep Learning (120)
- Butte (118)
- Water quality (118)
- Colorado (117)
- Security (117)
- Publication Year
- Publication
-
- Journal of System Simulation (3880)
- Nebraska Tractor Tests (3397)
- Turkish Journal of Electrical Engineering and Computer Sciences (3106)
- Journal of Electrochemistry (2029)
- Coal Geology & Exploration (1799)
-
- Computer Science & Engineering Syllabi (1312)
- Theses and Dissertations (1119)
- Research Collection School Of Computing and Information Systems (858)
- All Computer Science and Engineering Research (683)
- Electronic Theses and Dissertations (634)
- World of Coal Ash Proceedings (580)
- Journal of China & Foreign Highway (570)
- Reports (548)
- Faculty Publications (424)
- Bachelors Theses and Reports, 1928 - 1970 (419)
- Neutrosophic Systems with Applications (375)
- Browse all Theses and Dissertations (342)
- USF Tampa Graduate Theses and Dissertations (340)
- Electrical & Computer Engineering Faculty Publications (331)
- Journal of Marine Science and Technology–Taiwan (328)
- Electrical & Computer Engineering Theses & Dissertations (319)
- Electrical and Computer Engineering Faculty Research & Creative Works (303)
- Journal of Digital Forensics, Security and Law (300)
- Open Access Theses & Dissertations (300)
- Graduate Theses and Dissertations (295)
- Dissertations (247)
- Chulalongkorn University Theses and Dissertations (Chula ETD) (246)
- UNLV Theses, Dissertations, Professional Papers, and Capstones (240)
- Applied Environmental Research (216)
- Journal of Sustainable Mining (211)
- Publication Type
Articles 4531 - 4560 of 40906
Full-Text Articles in Engineering
A Computational Investigation Of Wood Selection For Acoustic Guitar, Jonah Osterhus
A Computational Investigation Of Wood Selection For Acoustic Guitar, Jonah Osterhus
Senior Honors Theses
The acoustic guitar is a stringed instrument, often made of wood, that transduces vibrational energy of steel strings into coupled vibrations of the wood and acoustic pressure waves in the air. Variations in wood selection and instrument geometry have been shown to affect the timbre of the acoustic guitar. Computational methods were utilized to investigate the impact of material properties on acoustic performance. Sitka spruce was deemed the most suitable wood for guitar soundboards due to its acoustic characteristics, strength, and uniform aesthetic. Mahogany was deemed to be the best wood for the back and sides of the guitar body …
Pet And Polyolefin Plastics Supply Chains In Michigan: Present And Future Systems Analysis Of Environmental And Socio-Economic Impacts, Utkarsh S. Chaudhari, Kamand Sedaghatnia, Barbara K. Reck, Kate Maguire, Anne T. Johnson, David Watkins, Robert M. Handler, Tasmin Hossain, Damon S. Hartley, Vicki S. Thompson, Alejandra Peralta, Jenny L. Apriesnig, David Shonnard
Pet And Polyolefin Plastics Supply Chains In Michigan: Present And Future Systems Analysis Of Environmental And Socio-Economic Impacts, Utkarsh S. Chaudhari, Kamand Sedaghatnia, Barbara K. Reck, Kate Maguire, Anne T. Johnson, David Watkins, Robert M. Handler, Tasmin Hossain, Damon S. Hartley, Vicki S. Thompson, Alejandra Peralta, Jenny L. Apriesnig, David Shonnard
Michigan Tech Publications
Many actions are underway at global, national, and local levels to increase plastics circularity. However, studies evaluating the environmental and socio-economic impacts of such a transition are lacking at regional levels in the United States. In this work, the existing polyethylene terephthalate and polyolefin plastics supply chains in Michigan were compared to a potential future (‘NextCycle’) scenario that looks at increasing Michigan’s overall recycling rate to 45%. Material flow analysis data was combined with environmental and socio-economic metrics to evaluate the sustainability of these supply chains for the modeled scenarios. Overall, the NextCycle scenario for these supply chains achieved a …
A Deep Learning Framework For Blockage Mitigation In Mmwave Wireless, Ahmed Hazaa Almutairi
A Deep Learning Framework For Blockage Mitigation In Mmwave Wireless, Ahmed Hazaa Almutairi
Dissertations and Theses
Millimeter-Wave (mmWave) communication is a key technology to enable next generation wireless systems. However, mmWave systems are highly susceptible to blockages, which can lead to a substantial decrease in signal strength at the receiver. Identifying blockages and mitigating them is thus a key challenge to achieve next generation wireless technology goals, such as enhanced mobile broadband (eMBB) and Ultra-Reliable and Low-Latency Communication (URLLC). This thesis proposes several deep learning (DL) frameworks for mmWave wireless blockage detection, mitigation, and duration prediction. First, we propose a DL framework to address the problem of identifying whether the mmWave wireless channel between two devices …
Unveiling Anomalies: A Survey On Xai-Based Anomaly Detection For Iot, Esin Eren, Feyza Yildirim Okay, Suat Özdemi̇r
Unveiling Anomalies: A Survey On Xai-Based Anomaly Detection For Iot, Esin Eren, Feyza Yildirim Okay, Suat Özdemi̇r
Turkish Journal of Electrical Engineering and Computer Sciences
In recent years, the rapid growth of the Internet of Things (IoT) has raised concerns about the security and reliability of IoT systems. Anomaly detection is vital for recognizing potential risks and ensuring the optimal functionality of IoT networks. However, traditional anomaly detection methods often lack transparency and interpretability, hindering the understanding of their decisions. As a solution, Explainable Artificial Intelligence (XAI) techniques have emerged to provide human-understandable explanations for the decisions made by anomaly detection models. In this study, we present a comprehensive survey of XAI-based anomaly detection methods for IoT. We review and analyze various XAI techniques, including …
Text-To-Sql: A Methodical Review Of Challenges And Models, Ali Buğra Kanburoğlu, Faik Boray Tek
Text-To-Sql: A Methodical Review Of Challenges And Models, Ali Buğra Kanburoğlu, Faik Boray Tek
Turkish Journal of Electrical Engineering and Computer Sciences
This survey focuses on Text-to-SQL, automated translation of natural language queries into SQL queries. Initially, we describe the problem and its main challenges. Then, by following the PRISMA systematic review methodology, we survey the existing Text-to-SQL review papers in the literature. We apply the same method to extract proposed Text-to-SQL models and classify them with respect to used evaluation metrics and benchmarks. We highlight the accuracies achieved by various models on Text-to-SQL datasets and discuss execution-guided evaluation strategies. We present insights into model training times and implementations of different models. We also explore the availability of Text-to-SQL datasets in non-English …
Security Fusion Method Of Physical Fitness Training Data Based On The Internet Of Things, Bin Zhou
Security Fusion Method Of Physical Fitness Training Data Based On The Internet Of Things, Bin Zhou
Turkish Journal of Electrical Engineering and Computer Sciences
Physical fitness training, an important way to improve physical fitness, is the basic guarantee for forming combat effectiveness. At present, the evaluation types of physical fitness training are mostly conducted manually. It has problems such as low efficiency, high consumption of human and material resources, and subjective factors affecting the evaluation results. ”Internet+” has greatly expanded the traditional network from the perspective of technological convergence and network coverage objects. It has expedited and promoted the rapid development of Internet of Things (IoT) technology and its applications. The IoT with many sensor nodes shows the characteristics of acquisition information redundancy, node …
Dpafy-Gcaps: Denoising Patch-And-Amplify Gabor Capsule Network For The Recognition Of Gastrointestinal Diseases, Henrietta Adjei Pokuaa, Adeboya Felix Adekoya, Benjamin Asubam Weyori, Owusu Nyarko-Boateng
Dpafy-Gcaps: Denoising Patch-And-Amplify Gabor Capsule Network For The Recognition Of Gastrointestinal Diseases, Henrietta Adjei Pokuaa, Adeboya Felix Adekoya, Benjamin Asubam Weyori, Owusu Nyarko-Boateng
Turkish Journal of Electrical Engineering and Computer Sciences
Deep learning (DL) models have performed tremendously well in image classification. This good performance can be attributed to the availability of massive data in most domains. However, some domains are known to have few datasets, especially the health sector. This makes it difficult to develop domain-specific high-performing DL algorithms for these fields. The field of health is critical and requires accurate detection of diseases. In the United States Gastrointestinal diseases are prevalent and affect 60 to 70 million people. Ulcerative colitis, polyps, and esophagitis are some gastrointestinal diseases. Colorectal polyps is the third most diagnosed malignancy in the world. This …
Joint Control Of A Flying Robot And A Ground Vehicle Using Leader-Follower Paradigm, Ayşen Süheyla Bağbaşi, Ali Emre Turgut, Kutluk Bilge Arikan
Joint Control Of A Flying Robot And A Ground Vehicle Using Leader-Follower Paradigm, Ayşen Süheyla Bağbaşi, Ali Emre Turgut, Kutluk Bilge Arikan
Turkish Journal of Electrical Engineering and Computer Sciences
In this study, a novel control framework for the collaboration of an aerial robot and a ground vehicle that is connected via a taut tether is proposed. The framework is based on a leader-follower paradigm. The leader follows a desired trajectory while the motion of the follower is controlled by an admittance controller using an extended state observer to estimate the tether force. Additionally, a velocity estimator is also incorporated to accurately assess the leader’s velocity. An essential feature of our system is its adaptability, enabling role switching between the robots when needed. Furthermore, the synchronization performance of the robots …
Stereo-Image-Based Ground-Line Prediction And Obstacle Detection, Emre Güngör, Ahmet Özmen
Stereo-Image-Based Ground-Line Prediction And Obstacle Detection, Emre Güngör, Ahmet Özmen
Turkish Journal of Electrical Engineering and Computer Sciences
In recent years, vision systems have become essential in the development of advanced driver assistance systems or autonomous vehicles. Although deep learning methods have been the center of focus in recent years to develop fast and reliable obstacle detection solutions, they face difficulties in complex and unknown environments where objects of varying types and shapes are present. In this study, a novel non-AI approach is presented for finding the ground-line and detecting the obstacles in roads using v-disparity data. The main motivation behind the study is that the ground-line estimation errors cause greater deviations at the output. Hence, a novel …
Deep Learning-Based Breast Cancer Diagnosis With Multiview Of Mammography Screening To Reduce False Positive Recall Rate, Meryem Altın Karagöz, Özkan Ufuk Nalbantoğlu, Derviş Karaboğa, Bahriye Akay, Alper Baştürk, Halil Ulutabanca, Serap Doğan, Damla Coşkun, Osman Demi̇r
Deep Learning-Based Breast Cancer Diagnosis With Multiview Of Mammography Screening To Reduce False Positive Recall Rate, Meryem Altın Karagöz, Özkan Ufuk Nalbantoğlu, Derviş Karaboğa, Bahriye Akay, Alper Baştürk, Halil Ulutabanca, Serap Doğan, Damla Coşkun, Osman Demi̇r
Turkish Journal of Electrical Engineering and Computer Sciences
Breast cancer is the most prevalent and crucial cancer type that should be diagnosed early to reduce mortality. Therefore, mammography is essential for early diagnosis owing to high-resolution imaging and appropriate visualization. However, the major problem of mammography screening is the high false positive recall rate for breast cancer diagnosis. High false positive recall rates psychologically affect patients, leading to anxiety, depression, and stress. Moreover, false positive recalls increase costs and create an unnecessary expert workload. Thus, this study proposes a deep learning based breast cancer diagnosis model to reduce false positive and false negative rates. The proposed model has …
05.20.2024 Orsp Connect, Liz Williamson
05.20.2024 Orsp Connect, Liz Williamson
ORED Newsletter
NIH RPPR Update (Research Performance Progress Report)
Signer-Independent Sign Language Recognition With Feature Disentanglement, İnci̇ Meli̇ha Baytaş, İpek Erdoğan
Signer-Independent Sign Language Recognition With Feature Disentanglement, İnci̇ Meli̇ha Baytaş, İpek Erdoğan
Turkish Journal of Electrical Engineering and Computer Sciences
Learning a robust and invariant representation of various unwanted factors in sign language recognition (SLR) applications is essential. One of the factors that might degrade the sign recognition performance is the lack of signer diversity in the training datasets, causing a dependence on the singer’s identity during representation learning. Consequently, capturing signer-specific features hinders the generalizability of SLR systems. This study proposes a feature disentanglement framework comprising a convolutional neural network (CNN) and a long short-term memory (LSTM) network based on adversarial training to learn a signer-independent sign language representation that might enhance the recognition of signs. We aim to …
New Frontier In Race For Deep Space Exploration: Lunar Water Resources, Yong Wei, Honglei Lin, Fei He, Hui Zhang
New Frontier In Race For Deep Space Exploration: Lunar Water Resources, Yong Wei, Honglei Lin, Fei He, Hui Zhang
Bulletin of Chinese Academy of Sciences (Chinese Version)
Deep space exploration has become the commanding heights of science and technology competition. Since the beginning of the 21st century, China has successfully completed the lunar exploration missions of “orbiting, landing, and returning” in just twenty years, and upgraded to a new roadmap of “survey, construction, and utilization”. Meanwhile, lunar exploration worldwide has shown a trend towards normalization and commercialization. The research on lunar water resources has sparked widespread interest and intense competition among countries and space agencies, marking a new focus in human’s deep space exploration. The exploration of lunar water can help reveal crucial processes in the formation …
Winning Battle For Key And Core Technologies In Emerging Fields—Inspiration Based On 863 Program Related Projects, Guangzu Bai, Li Li, Hongfei Meng, Qiang Wang, Xiaoyang Cao, Anrong Liu, Bo Cheng, Mimi Zhan, Jing Li, Leiei Cui, Xiangwan Du
Winning Battle For Key And Core Technologies In Emerging Fields—Inspiration Based On 863 Program Related Projects, Guangzu Bai, Li Li, Hongfei Meng, Qiang Wang, Xiaoyang Cao, Anrong Liu, Bo Cheng, Mimi Zhan, Jing Li, Leiei Cui, Xiangwan Du
Bulletin of Chinese Academy of Sciences (Chinese Version)
Emerging technology fields have become the main battleground for strategic competition among major powers today, with key and core technologies serving as crucial approach in shaping a nation’s international competitive advantage. This study, from the perspective of national strategy, profoundly understands the significant importance of winning the key and core technology battle in emerging fields. Based on this understanding, it starts with a comparison between the implementation background of the 863 Program and the current reality. It systematically summarizes valuable experiences from projects aimed at advancing key and core technologies in emerging fields, and puts forward reflections and suggestions for …
Modeling Synergistic Effects Of Integrin And Tgf-Beta Signaling In Epithelial Mesenchymal Transition, Prerak Thakkar
Modeling Synergistic Effects Of Integrin And Tgf-Beta Signaling In Epithelial Mesenchymal Transition, Prerak Thakkar
Biology and Medicine Through Mathematics Conference
No abstract provided.
A Robust Decision-Making Model For Medical Supplies Via Selecting Appropriate Unmanned Aerial Vehicle, Amira Salam, Mai Mohamed, Rui Yong, Jun Ye
A Robust Decision-Making Model For Medical Supplies Via Selecting Appropriate Unmanned Aerial Vehicle, Amira Salam, Mai Mohamed, Rui Yong, Jun Ye
Neutrosophic Systems with Applications
Recently, Unmanned Aerial Vehicles (UAVs) have been used in many fields, including the field of health care, especially in delivering the necessary medical equipment and supplies, due to the many advantages they have compared to other traditional methods and the presence of different types of UAVs, to improve healthcare and provide it with the medical supplies and equipment necessary to save the lives of patients. Choosing the appropriate UAV for a specific situation represents a problem facing decision-makers, which is considered a multi-criteria decision-making problem. Since the decision-making process is cumbersome and complex, and deals with uncertainty and ambiguity. In …
An Innovative Approach On Yao’S Three-Way Decision Model Using Intuitionistic Fuzzy Sets For Medical Diagnosis, Wajid Ali, Tanzeela Shaheen, Iftikhar Ul Haq, Florentin Smarandache, Hamza Ghazanfar Toor, Faiza Asif
An Innovative Approach On Yao’S Three-Way Decision Model Using Intuitionistic Fuzzy Sets For Medical Diagnosis, Wajid Ali, Tanzeela Shaheen, Iftikhar Ul Haq, Florentin Smarandache, Hamza Ghazanfar Toor, Faiza Asif
Neutrosophic Systems with Applications
In the realm of medical diagnosis, intuitionistic fuzzy data serves as a valuable tool for representing information that is uncertain and imprecise. Nevertheless, decision-making based on this kind of knowledge can be quite challenging due to the inherent vagueness of the data. To address this issue, we employ power aggregation operators, which prove effective in combining several sources of data, such as expert thoughts and patient information. This allows for a more correct diagnosis; a particularly crucial aspect of medical practice where precise and timely diagnoses can significantly impact medication policy and patient results. In our research, we introduce a …
Dense Video Description Method Based On Multi-Modal Fusion In Transformer Network, Xiang Li, Haifeng Sang
Dense Video Description Method Based On Multi-Modal Fusion In Transformer Network, Xiang Li, Haifeng Sang
Journal of System Simulation
Abstract: In order to solve the problems that most of the current dense video description models use twostage methods, which have low efficiency, ignore audio and semantic information, and have incomplete description results, a multi-modal and semantic information fusion dense video description method was proposed. An adaptive R(2+1)D network was proposed to extract visual features, a semantic detector was designed to generate semantic information, audio features were added to supplement it, a multi-scale deformable attention module was established, and a parallel prediction head was applied to accelerate the convergence rate and improve the accuracy of the model. The experimental results …
Research On Simulation Model Of Double-Layer Expansion Design Of Expressway, Jiandong Qiu, Yi Tang, Yuxiong Ji, Heng Liu, Junsha Luo
Research On Simulation Model Of Double-Layer Expansion Design Of Expressway, Jiandong Qiu, Yi Tang, Yuxiong Ji, Heng Liu, Junsha Luo
Journal of System Simulation
Abstract: Aiming at the problems that the traditional traffic simulation technology has insufficient evaluation accuracy and little application effect in the three-dimensional composite expansion scenario of expressway, a simulation model construction method for double-layer expansion design of expressway was proposed. The reconstruction and expansion project of Shenzhen Jihe Expressway is selected as the research object, the three simulation model modeling elements, including road network facilities, traffic demand data, and driving behavior model parameters, are sorted out, and the technical process of simulation modeling is proposed. The whole road network including key infrastructure such as interchange, toll station, ramp up and …
A Graph Neural Network Visual Slam Algorithm For Large-Angle View Motion, Jinhui Liu, Mengyuan Chen, Pengpeng Han, Hebao Chen, Yukun Zhang
A Graph Neural Network Visual Slam Algorithm For Large-Angle View Motion, Jinhui Liu, Mengyuan Chen, Pengpeng Han, Hebao Chen, Yukun Zhang
Journal of System Simulation
Abstract: Aimed at the difficulty of feature point extraction in mobile robots with drastic changes in illumination or sparse texture scenes under large-angle view motion, difficulty in matching features at extreme angles leads to large errors in Epipolar Geometry calculations, a fusion of an improved graph neural network based visual SLAM algorithm (GNN-SLAM) is proposed. The priori location estimation feature extraction network is proposed to achieve fast and uniform detection and description of image feature points by a priori location estimation and to construct real and accurate feature point information. The graph attention mechanism feature matching network is proposed to …
Implementation And Numerical Simulation On Object-Oriented Elastic-Plastic Finite Element Method Based On Python, Henghui Li, Yingxiong Xiao
Implementation And Numerical Simulation On Object-Oriented Elastic-Plastic Finite Element Method Based On Python, Henghui Li, Yingxiong Xiao
Journal of System Simulation
Abstract: With the continuous expansion of the application fields of finite element methods, higher requirements are put forward for the scalability of finite element methods. In order to overcome the defects of the traditional finite element methods, a simple and easily extensible object-oriented elasticplastic finite element program framework is proposed based on Python. Combined with the characteristics of Python, we design some finite element classes such as the pre-processing class, the post-processing class, the linear solution class, the stress integration class and the analysis class. By applying the resulting framework to several typical elastic-plastic mechanical problems and comparing the results …
Optimization Of Highway Emergency Lane Control Based On Kriging Genetic Algorithm, Jinjun Tang, Lipeng Hu, Mingyang Li, Xuan Zhang
Optimization Of Highway Emergency Lane Control Based On Kriging Genetic Algorithm, Jinjun Tang, Lipeng Hu, Mingyang Li, Xuan Zhang
Journal of System Simulation
Abstract: To address the issue of how to effectively improve the highway operational efficiency and reduce the safety risks under different traffic flow conditions, this study proposed a genetic algorithm based on Kriging agent model is proposed to optimize the emergency lane control strategy. A mathematical optimization model is designed by combining the spatial and temporal characteristics of the emergency lane opening strategy. By introducing Kriging agent model, combining the genetic algorithm to build the optimization framework, and using simulation software to obtain data to train the agent model, the problem of minimizing the total travel time and the total …
Research On Forest Fire Spread Simulation System Based On Osg, Lei Shao, Xiaotian Yan, Jian Liu, Yuming Liu
Research On Forest Fire Spread Simulation System Based On Osg, Lei Shao, Xiaotian Yan, Jian Liu, Yuming Liu
Journal of System Simulation
Abstract: A novel expended lattice structure of DEM-Cell model incorporating DEM elevation information is proposed, in response to the requirements of extrapolation of trends and hazards of forest fire spread, as well as the need of route selection and real-time path optimization for rescuers. Combining vegetation attributes of meta cells with geographic elevation information, we develop a simulation and fire fighting exercise system that computing the resultant data in real time and converting it into renderable resource, which is directly used by the OSG engines. With the help of the same data structure and the corresponding key algorithms and technologies, …
Hierarchical Guided Enhanced Multi-Objective Firefly Algorithm, Jia Zhao, Zhizhen Lai, Runxiu Wu, Zhihua Cui, Hui Wang
Hierarchical Guided Enhanced Multi-Objective Firefly Algorithm, Jia Zhao, Zhizhen Lai, Runxiu Wu, Zhihua Cui, Hui Wang
Journal of System Simulation
Abstract: The multi-objective firefly algorithm is easy to produce oscillation and aggregation phenomenon in the solution process, which leads to weak development ability and poor solution accuracy. This paper proposes a hierarchical guided enhanced multi-objective firefly algorithm (HGEMOFA). HGEMOFA builds a hierarchical guidance model, uses non-dominated sorting to obtain different levels of individuals. The individuals in the dominant layer are used to guide the evolution of the individuals in the inferior layer, the guidance direction is clear, the oscillation in the evolution process is solved, the aggregation phenomenon is reduced, and the convergence of the algorithm is enhanced. The Lévy …
Advancing Simultaneous Extraction And Sequential Single-Particle Icp-Ms Analysis For Metallic Nanoparticle Mixtures In Plant Tissues, Lei Xu, Xingmao Ma, John Yang, Joel G. Burken, Paul Ki-Souk Nam, Honglan Shi, Hu Yang
Advancing Simultaneous Extraction And Sequential Single-Particle Icp-Ms Analysis For Metallic Nanoparticle Mixtures In Plant Tissues, Lei Xu, Xingmao Ma, John Yang, Joel G. Burken, Paul Ki-Souk Nam, Honglan Shi, Hu Yang
Civil, Architectural and Environmental Engineering Faculty Research & Creative Works
Engineered Nanoparticles (ENPs) Have Been Increasingly Used in Agricultural Operations, leading to an Urgent Need for Robust Methods to Analyze Co-Occurring ENPs in Plant Tissues. in Response, This Study Advanced the Simultaneous Extraction of Coexisting Silver, Cerium Oxide, and Copper Oxide ENPs in Lettuce Shoots and Roots using Macerozyme R-10 and Analyzed Them by Single-Particle Inductively Coupled Plasma-Mass Spectrometry (ICP-MS). Additionally, the Standard Stock Suspensions of the ENPs Were Stabilized with Citrate, and the Long-Term Stability (Up to 5 Months) Was Examined for the First Time. the Method Performance Results Displayed Satisfactory Accuracies and Precisions and Achieved Low Particle Concentration …
Engineering And Geological Zoning Of The Distribution Areas Of The Eocene Clays Of Northern Tamdytau, Mirabbas Mirsaatovich Zakirov, Inobat Abduvaxidovna Agzamova, Dilshod Kalandarovich Begimkulov, Golibjon Ernazar Ogli Ochilov, Temur Makhmarajabovich Khudoyberdiyev, Dastan Jamal Uli Madiyarov
Engineering And Geological Zoning Of The Distribution Areas Of The Eocene Clays Of Northern Tamdytau, Mirabbas Mirsaatovich Zakirov, Inobat Abduvaxidovna Agzamova, Dilshod Kalandarovich Begimkulov, Golibjon Ernazar Ogli Ochilov, Temur Makhmarajabovich Khudoyberdiyev, Dastan Jamal Uli Madiyarov
Technical science and innovation
The article discusses scientific research on the integrated assessment of the problem of ensuring the sustainability of buildings and structures for industrial and civil purposes. The relevance is due to the development of various zoning methods to establish territories with reliable results on the spread of special soils. Especially in cases where swelling clays are common in the territory, characterized by high sensitivity to weather and climatic conditions. Based on the above, the purpose of engineering and geological zoning of the areas of distribution of Eocene clays of Northern Tamdytau was to identify areas of new construction, to ensure the …
Research On Path Planning Of Warehouse Robot With Improved Harris Hawks Algorithm, Xu Lei, Jingyi Chen, Xiaoyang Chen
Research On Path Planning Of Warehouse Robot With Improved Harris Hawks Algorithm, Xu Lei, Jingyi Chen, Xiaoyang Chen
Journal of System Simulation
Abstract: To improve the path planning efficiency of warehouse mobile robots in static environments, and to solve the problems of slow convergence and local optimum of traditional Harris Hawk (HHO) algorithm in path planning, a Harris Hawk optimization algorithm based on Tent chaotic mapping fused with Cauchy's back-learning variant (TCLHHO) is proposed. The population diversity is increased by Tent Chaotic mapping to speed up convergence. An exponential prey escape energy updating strategy is proposed to balance the global search and local exploitation capabilities of the algorithm. The optimal individual is disturbed by Cauchy mutation operator and inverse learning strategy to …
Image Self-Enhancement De-Hazing Algorithm Combined With Generative Adversarial Network, Wanjun Liu, Yuqian Cheng, Haicheng Qu
Image Self-Enhancement De-Hazing Algorithm Combined With Generative Adversarial Network, Wanjun Liu, Yuqian Cheng, Haicheng Qu
Journal of System Simulation
Abstract: To solve the problem that existing dehazing models are prone to over fitting after training with synthetic hazy image data sets, an image self-enhancement dehazing algorithm is proposed in combination with generative adversarial network. The depth information of an image is estimated while combining two Generative Adversarial Networks. The first GAN uses a clear image to learn the process of image hazing, and then adopts the hazed image generated by it as the input of the second GAN to guide the second GAN to correct dehazing. In order to reduce the difference before and after image processing, the consistency …
Cooperative And Optimal Control Of Multiple Mimo Objects Under Information Sharing, Jiong Shao, Xinchun Jie, Meng Wu
Cooperative And Optimal Control Of Multiple Mimo Objects Under Information Sharing, Jiong Shao, Xinchun Jie, Meng Wu
Journal of System Simulation
Abstract: Aiming at the problems of low cooperative efficiency and slow convergence of control algorithm for multiple MIMO objects in cyber-physical system (CPS), a cooperative optimization control strategy for multiple MIMO objects under the condition of information sharing is proposed. A new network control system structure with only physical layer and information layer is used to realize real-time sharing of state variables, control and detection information of multiple MIMO objects. Under the condition of information sharing, based on the performance indexes assigned by CPS and the physical constraints between each object, the cooperative controller designed by minimum principle realizes the …
Research On Collaborative Optimization Method Of Multi-Uav Task Allocation And Path Planning, Peng Xiao, Feng Xie, Haihong Ni, Min Zhang, Zhili Tang, Ni Li
Research On Collaborative Optimization Method Of Multi-Uav Task Allocation And Path Planning, Peng Xiao, Feng Xie, Haihong Ni, Min Zhang, Zhili Tang, Ni Li
Journal of System Simulation
Abstract: Aiming at the task requirements of multi-UAV to perform multi-target collaborative reconnaissance, a collaborative optimization method of multi-machine and multi-objective task allocation and path planning is proposed. Based on the partheno genetic algorithms (PGA), a cost function combined with the actual path cost is constructed through the Dubins curve. To further reduce the calculation cost, a clustering algorithm based on UAV detection distance is proposed, and the generated clustering point is used as a new waypoint of UAV. The simulation results show that considering the dangerous area and the large number of reconnaissance points, the algorithm can effectively complete …