Rapid advancements in automated vehicles(AVs)technology have transformed the measurability,controllability and unpredictability of transportation *** driving risk and effectively managing driving behaviours is *** sho...
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Rapid advancements in automated vehicles(AVs)technology have transformed the measurability,controllability and unpredictability of transportation *** driving risk and effectively managing driving behaviours is *** should be enabled to identify,analyse,evaluate and devise effective countermeasures for driving risk by autonomously learning from human driving *** learning will enhance the interactive decision-making capabilities and achieve driving behaviours that reflect human-like *** primary challenge lies in integrating human-like logic and driving risk constraints based on behavioural decision-making *** integration is crucial to align the AVs’cognitive levels-movement,comprehension,memory and inference-more closely with human driving necessities,habits and *** alignment holds the potential to improve the prediction and planning of future actions and facilitate the development of motion planning schemes geared towards minimizing driving *** performed a comprehensive review of AVs’behavioural decision-making and intelligent motion-planning research from 2000 to 2023 from four key perspectives-driving risk,human-like logic,behavioural decision making and motion *** on the Web of science and China National Knowledge Internet database,the results of our review indicate that significant progress has been made in AV behavioural decision making and intelligent motion planning over *** AVs and human-driven vehicles coexist,greater incorporation of human-like logic is *** by these findings,we delineate future development directions and propose a research paradigm for human-like logic and a research framework for human-like logic-driven behavioural decision making and intelligent motion planning of AVs.
Cognitive Radio Network provides opportunistic spectrum access to unlicensed users in the absence of licensed users using dynamic spectrum access technology. The key challenge here is to impartially share the existing...
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The successful execution and management of Offshore Software Maintenance Outsourcing(OSMO)can be very beneficial for OSMO vendors and the OSMO *** a lot of research on software outsourcing is going on,most of the exis...
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The successful execution and management of Offshore Software Maintenance Outsourcing(OSMO)can be very beneficial for OSMO vendors and the OSMO *** a lot of research on software outsourcing is going on,most of the existing literature on offshore outsourcing deals with the outsourcing of software development *** frameworks have been developed focusing on guiding software systemmanagers concerning offshore software ***,none of these studies delivered comprehensive guidelines for managing the whole process of *** is a considerable lack of research working on managing OSMO from a vendor’s ***,to find the best practices for managing an OSMO process,it is necessary to further investigate such complex and multifaceted phenomena from the vendor’s *** study validated the preliminary OSMO process model via a case study research *** results showed that the OSMO process model is applicable in an industrial setting with few *** industrial data collected during the case study enabled this paper to extend the preliminary OSMO process *** refined version of the OSMO processmodel has four major phases including(i)Project Assessment,(ii)SLA(iii)Execution,and(iv)Risk.
This paper analyses the development and programming of standardized endurance testing equipment for automotive mechanical components, highlighting the advantages of its use. The test bench was designed to reproduce re...
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The solid–liquid interface energy anisotropy of Zn alloys remains poorly understood. Recently, characteristic 14-arm dendritic growth has been observed using time-resolved X-ray computed tomography at SPring-8 during...
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作者：
Gote, Pradnyawant M.Kumar, PraveenVerma, PrateekYesankar, PrajyotPawar, AdeshSaratkar, Saniya
Faculty of Engineering and Technology Department of Computer Science & Design Maharashtra Wardha442001 India
Faculty of Engineering and Technology Department of Computer Science & Medical Engineering Maharashtra Wardha442001 India
Faculty of Engineering and Technology Department of Artificial Intelligence & Machine Learning Maharashtra Wardha442001 India
Faculty of Engineering and Technology Department of Artificial Intelligence & Data Science Maharashtra Wardha442001 India
The swift progression of wireless communication technologies-specifically from 5G to 6G is an approach that could be the most significant revolutionary leap towards changing connectivity and data transmission forever....
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The Gengma-Lancang-Menghai seismic belt,the southernmost part of the North-South seismic belt,is controlled by four active faults:the Nantinghe fault(NTHF),the Sanjianshan fault(SJSF),the Hanmuba-Lancang fault(HMB-LCF...
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The Gengma-Lancang-Menghai seismic belt,the southernmost part of the North-South seismic belt,is controlled by four active faults:the Nantinghe fault(NTHF),the Sanjianshan fault(SJSF),the Hanmuba-Lancang fault(HMB-LCF),and the Heihe fault(HHF),from northwest to ***,the tectonic activity of the faults in the Gengma-Lancang-Menghai seismic belt has not been fully studied *** the present work,we conducted tectonic geomorphic indices to analyze the relative tectonic activity along the faults in the seismic belt based on the digital elevation *** interpreted asymmetric factor,index of drainage basin shape,hypsometric integral,normalized streamlength gradient,valley floor-to-width to height ratio,and longitudinal profiles to show that the relative tectonic activity is higher in the north and lower in the south,and is strong in the region from Shanjia to Huimin in the center of the seismic belt.
作者：
Yesankar, PrajyotGourshettiwar, PalashGote, PradnyawantJiet, Moses MakueiGadkari, Ayush
Faculty of Engineering and Technology Department of Computer Science & Design Maharashtra Wardha442001 India
Faculty of Engineering and Technology Department of Computer Science & Medical Engineering Maharashtra Wardha442001 India
Faculty of Engineering and Technology Department of Artificial Intelligence & Data Science Maharashtra Wardha442001 India
The design of wireless mobile devices of the next generation 5G promises to address the demands of complex IOT designs in terms of connectivity technologies. This The study illuminates the architecture, benefits, and ...
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Facial expression recognition is a challenging task when neural network is applied to pattern recognition. Most of the current recognition research is based on single source facial data, which generally has the disadv...
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Glaucoma is currently one of the most significant causes of permanent blindness. Fundus imaging is the most popular glaucoma screening method because of the compromises it has to make in terms of portability, size, an...
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Glaucoma is currently one of the most significant causes of permanent blindness. Fundus imaging is the most popular glaucoma screening method because of the compromises it has to make in terms of portability, size, and cost. In recent years, convolution neural networks (CNNs) have revolutionized computer vision. Convolution is a "local" CNN technique that is only applicable to a small region surrounding an image. Vision Transformers (ViT) use self-attention, which is a "global" activity since it collects information from the entire image. As a result, the ViT can successfully gather distant semantic relevance from an image. This study examined several optimizers, including Adamax, SGD, RMSprop, Adadelta, Adafactor, Nadam, and Adagrad. With 1750 Healthy and Glaucoma images in the IEEE fundus image dataset and 4800 healthy and glaucoma images in the LAG fundus image dataset, we trained and tested the ViT model on these datasets. Additionally, the datasets underwent image scaling, auto-rotation, and auto-contrast adjustment via adaptive equalization during preprocessing. The results demonstrated that preparing the provided dataset with various optimizers improved accuracy and other performance metrics. Additionally, according to the results, the Nadam Optimizer improved accuracy in the adaptive equalized preprocessing of the IEEE dataset by up to 97.8% and in the adaptive equalized preprocessing of the LAG dataset by up to 92%, both of which were followed by auto rotation and image resizing processes. In addition to integrating our vision transformer model with the shift tokenization model, we also combined ViT with a hybrid model that consisted of six different models, including SVM, Gaussian NB, Bernoulli NB, Decision Tree, KNN, and Random Forest, based on which optimizer was the most successful for each dataset. Empirical results show that the SVM Model worked well and improved accuracy by up to 93% with precision of up to 94% in the adaptive equalization preprocess
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