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检索条件"任意字段=7th International Conference on the Art, Science, and Engineering of Programming, Programming 2023"

共 1136 条记录，以下是401-410 订阅

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IRS-assisted MISO system energy-saving communication scheme under security constraints

IRS-assisted MISO system energy-saving communication scheme ...

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IEEE Information Technology and Mechatronics engineering conference (ITOEC)

作者： Xin Zhang Xiangdong Jia Gongziyu Chen Xiayang Niu College of Computer Science and Engineering Northwest Normal University Lanzhou China Wireless Communication Key Lab of Jiangsu Province Nanjing University of Posts and Telecommunications Nanjing China

Aiming at the high security and high energy consumption risks of downlink multiple input single output (MISO) systems assisted by intelligent reflecting surface (IRS), the transmission beamforming of the base station(BS), and the phase shift matrix of IRS are jointly considered for the transmission of the system. A system transmission power minimization problem under the constraint of a legal user secrecy rate was constructed. then a second-order cone programming algorithm based on successive convex approximation(SCA) is proposed to solve the problem. the proposed algorithm simultaneously updates all optimization variables in each iteration and obtains a suboptimal solution to the original problem. the simulation results show that compared with the proposed baseline scheme, the algorithm in this paper achieves lower transmit power while ensuring the confidentiality quality of legitimate users.

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Cross-Lingual Reverse Dictionary Using Multilingual mBart and mT5 Models 7th

Cross-Lingual Reverse Dictionary Using Multilingual mBART an...

引用

7th international conference on Intelligent Technologies, ICIT 2022

作者： Mangal, Akshat Rathore, Santosh Singh Arya, K.V. Department of Computer Science and Engineering ABV-IIITM Gwalior Gwalior India

ISBN: (纸本)9789819919116

the task of a cross-lingual reverse dictionary can be considered a combination of conventional text summarization and language translation. the description needs to be summarized into target words and further translated into different languages. the problem is considered complex because it requires identifying the correct target word from colloquial descriptions. the description of the target word ranges from a dictionary definition to a conversational description. A regular dictionary maps words to their respective definitions, whereas reverse dictionaries attempt to map the descriptions to words. In this work, different models, named auto encoder-decoder and sequence-to-sequence models based on Translation Language Modeling (TLM) are explored for solving the limitations of current models, and presents two state-of-the-art cross-lingual reverse dictionary models using multilingual Bart and T5 transformers. the experiment is performed on the trilingual dataset Wikt3l, and the performance of the proposed models are evaluated in terms of Accuracy @1, Accuracy @10, and Mean Reciprocal Rank is used as the performance measures. the results showed that the proposed models achieved higher accuracy as compared to the existing Masked Language Modeling (MLM) based models. © 2023, the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Modeling languages

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Method for haze removal based on local edge total variance

Method for haze removal based on local edge total variance

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7th international conference on Vision, Image and Signal Processing (ICVISP 2023)

作者： R. Xiang X. Zhu F. Wu Q. Xu L. Zhang J. Lu School of Electrical & Information Engineering Changzhou Institute of Technology Changzhou People's Republic of China

To obtain clear images from images with different haze levels, a new haze-removing method is proposed based on local edge total variance, which effectively reconstructs a reflected image from the hazy image. We first rewrite the classical monochrome atmospheric scattering model (CMASM) using a logarithmic operation to obtain the approximate Retinex model. then we compute the approximate atmospheric transmittance map by decomposing the approximate Retinex model using the constrained local edge total variance theory. the decomposition problem can be viewed as an optimization problem with constrained quadratic programming, and the optimization of the channel containing fine details can be achieved by combining the Bregman theory and the fast Fourier transform method. Finally, the reflected image is estimated by the improved monochrome atmospheric scattering model. Compared to other available methods including methods based on CMASM and methods based on deep learning, experimental results demonstrate that our method is not only effective in removing haze, but also improve image qualities, such as contrast, sharpness and colour.

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Unsupervised Image to Image Translation for Multiple Retinal Pathology Synthesis in Optical Coherence Tomography Scans 7th

Unsupervised Image to Image Translation for Multiple Retinal...

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7th international conference on Computer Vision and Image Processing, CVIP 2022

作者： Pasupuleti, Hemanth Kothari, Abhishek R. Girish, G.N. Computer Science and Engineering Group Indian Institute of Information Technology Sri City India Pink City Eye and Retina Center Jaipur India

ISBN: (纸本)9783031314162

Image to Image Translation (I2I) is a challenging computer vision problem used in numerous domains for multiple tasks. Recently, ophthalmology became one of the major fields where the application of I2I is increasing rapidly. One such application is the generation of synthetic retinal optical coherence tomographic (OCT) scans. Existing I2I methods require training of multiple models to translate images from normal scans to a specific pathology: limiting the use of these models due to their complexity. To address this issue, we propose an unsupervised multi-domain I2I network with pre-trained style encoder that translates retinal OCT images in one domain to multiple domains. We assume that the image splits into domain-invariant content and domain-specific style codes, and pre-train these style codes. the performed experiments show that the proposed model outperforms state-of-the-art models like MUNIT and CycleGAN by synthesizing diverse pathological scans with lower FID scores (108.30-Kermany dataset;60-TaeKeun datset) and higher LPIPS scores (0.146-Kermany dataset;0.171-TaeKeun dataset). © the Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

关键词： Generative adversarial networks

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A Cooperative Truck Platooning Approach on Ramp Merging Area of Highway in Mixed Traffic

A Cooperative Truck Platooning Approach on Ramp Merging Area...

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international conference on Transportation Information and Safety (ICTIS)

作者： Xiao Sang Linhan Bai Tao Zhou Fangfang Zheng School of Transportation and Logistics National Engineering Laboratory of Integrated Transportation Big Data Application Technology National United Engineering Laboratory of Integrated and Intelligent Transportation Southwest Jiaotong University Chengdu China Jiangsu Railway Group Nanjing China

Truck platooning has emerged as a promising solution for improving traffic efficiency on highways. this paper proposes an optimization model for connected automated trucks (CATs) that addresses the trajectory optimization problem for CATs as human-driven trucks (HDTs) merge onto highways from on-ramps in a mixed traffic scenario. To maximize the speed of the mixed traffic system, we propose a mixed integer programming (MIP) model based on a rolling horizon algorithm. the algorithm optimizes CATs’ trajectories iteratively, taking into account real-time updates on their driving state, and guides HDTs to follow the trajectories of CATs. the numerical experiments demonstrate that the increasing number of HDTs on the on-ramp negatively impacts the overall system performance, leading to higher traffic delay and reduced system stability. Furthermore, accounting for the stochastic behavior of HDTs can lead to increased instability in the system. Finally, we show that the objective function that comprehensively considers the system speed and platooning time effectively minimizes the delay of all vehicles.

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Co-optimization of intelligent connected fuel cell vehicle powertrain based on networked scenario*

Co-optimization of intelligent connected fuel cell vehicle p...

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conference on Vehicle Control and Intelligence (CVCI)

作者： Hanzhengnan Yu Liang Chang Yu Liu Baodi Zhang China Automotive Technology and Research Center Co. Ltd. Tianjin China School of Mechanical Electronic and Control Engineering Beijing Jiaotong University Beijing China

With the intelligent and networked vehicles, the control of fused traffic information brings new opportunities for fuel cell vehicle energy optimization. In this paper, we use the vehicle-road cooperative system to collect traffic information, adopt dynamic programming (DP) to select the optimal green light passing time, complete the global optimal planning speed based on the quadratic planning algorithm, and the lower layer adopts dynamic planning to realize the power distribution among energy sources. Simulation results show that by co-optimizing the speed planning and energy management strategies, the hydrogen consumption of the vehicle is reduced by 32.3% compared to the original strategy.

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Emotion Based Carnatic Music Recommendation System

Emotion Based Carnatic Music Recommendation System

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international conference on Computation System and Information Technology for Sustainable Solutions (CSITSS)

作者： Prajwal N J Sameeksha Keshav Rashmi R Information Science and Engineering RV College of Engineering® Bangalore India

the project aims to develop an AI-based music recommendation system focused on Melakarta ragas and emotional themes. In the field, previous work has focused on music recommendation systems based on various techniques, but limited research has been conducted specifically on Melakarta ragas and their emotional impact. therefore, there is a gap to propose a new idea that leverages Melakarta ragas to provide personalized music recommendations aligned with users' emotional states. the objectives include preprocessing the dataset, classifying Melakarta ragas, mapping emotions to ragas, and implementing the recommendation system. the methodology involves identification of Navarasa (nine emotions) from camera input. Computer vision techniques are employed to analyze facial expressions and detect emotions such as Hasya, Karuna, Shringara, etc. these identified Navarasas are then mapped to corresponding emotional tags associated with Melakarta ragas. the recommendation system is developed to map the detected Navarasa from camera input to emotional tags and provide personalized music recommendations based on the Melakarta ragas associated with those emotions. the simulation tools used include programming languages like Python, machine learning libraries like scikit-learn and computer vision frameworks like OpenCV. the paper concentrates on majorly 6 rasas that maps with all the 72 melakarta ragas.

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Short-term power forecasting model of floating photovoltaic - A case study of Huainan floating photovoltaic plant, China 7

Short-term power forecasting model of floating photovoltaic ...

引用

7th IEEE international conference on Power and Renewable Energy, ICPRE 2022

作者： Bei, YaoPing Yuan, BingQing Cheng, DaLi Liu, Shenzhen Ma, Chao Zhang, Zihao Co. Ltd. Beijing China Solar Power Generation Co. Ltd. Three Gorges Renewable Energy Huainan Huainan China State Key Laboratory of Hydraulic Engineering Simulation and Safety Tianjin University Tianjin China

ISBN: (数字)9781665450638

ISBN: (纸本)9781665450638

Although the development of floating photovoltaic (FPV) in China is rapid, there are few reports on the power generation forecasting of FPV. Based on the monitoring data of the 150MW FPV plant in Huainan, a short-term power forecasting model for FPV plant is proposed in this paper. Firstly, the input variables of deep belief network (DBN) are selected based on the open-source R programming software;then, wavelet transform is used to decompose the power time series into several components with different frequencies, and convolutional neural network (CNN) is used to extract the nonlinear features and invariant structures of each component;finally, the back propagation neural network (BPNN) optimized by genetic algorithm (GA) is used to integrate the outputs of CNN and DBN to obtain the final PV power forecasting value. the simulation results show that the method proposed in this paper can obtain superior forecasting accuracy than other models. © 2022 IEEE.

关键词： Wavelet transforms

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Design of a robot to automatically measure human temperature indoors

Design of a robot to automatically measure human temperature...

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international conference on Electrical, Telecommunication and Computer engineering (ELTICOM)

作者： Tigor Hamonangan Nasution Seniman Arza Muhammad Prihandoyo Department of Electrical Engineering Universitas Sumatera Utara Medan Indonesia Department of Computer Science Universitas Sumatera Utara Medan Indonesia

the development of robot technology has led to many robot technologies being used in various fields, one of which is the health sector. In this research, a robot was designed that would be useful in the health sector to prevent COVID-19. this robot moves on four wheels and has two ultrasonic sensors; each used to determine the robot’s distance to the front object, search for human presence, and determine turning direction. When encountering an obstacle, a PIR sensor is used to detect human existence (more precisely, the presence of a living object in front of it), and an MLX 90614 temperature sensor is used to measure the object’s body temperature (and also the surrounding temperature). the robot designed is a human body temperature measuring robot that can move automatically to look for people to measure their body temperature. It has dimensions of 25 cm x 15 cm x 23 cm. Based on the results of the design, the robot can recognize moving human objects based on ultrasonic sensors by making a tilt angle to determine whether the thing is a human. Next, the robot can measure and convey the temperature value via audio and LCD Display. However, if the object is rapidly moving, the robot can misrecognize the thing. the motor speed cannot be adequately synchronised with the sensor reading results. To overcome this, it is necessary to change the programming code to synchronize sensor readings with motor speed.

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Human Disease Prediction based on Symptoms

Human Disease Prediction based on Symptoms

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international conference on Computing Methodologies and Communication (ICCMC)

作者： Uday Kiran Kommineni Dhatri Phani Priya Kowthavarapu Guna Sri Manjunadh Polukonda Kalyan Chakravarti Yelavarti Dept. of Information Technology Velagap udi Ramakrishna Siddhartha Engineering College Vijayawada India

there are new diseases discovered in the 21st century which have identical and additional symptoms to the previous diseases but these new diseases are far more dangerous than the previous ones and have some additional symptoms. So, In this work the new diseases can be identified by taking the input from the user and identifying the disease and displaying it on the users smart screen display. this work aim is to reduce the deaths of people by identifying the disease and cure it in advance. the Random Forest and Naive Bayes algorithms are used for predicting the disease. this prediction is done by considering and comparing the accuracies of both the algorithms and gives the predicted disease as output which has best accuracy. Its implementation is completed via python programming language and tkinter library.

关键词： Machine learning algorithms Forestry Prediction algorithms Libraries Naive Bayes methods Random forests Diseases

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