Introduces a estimation based totally on time series evaluation. among ladies, and it's far more critical to stumble on and deal with it in the early ranges. However, due to time consumption within the analysis me...
详细信息
Introduction: Vehicle crashes can be hazardous to public safety and may cause infrastructure damage. Risky driving significantly raises the possibility of the occurrence of a vehicle crash. As per statistics by the Wo...
详细信息
Introduction: Vehicle crashes can be hazardous to public safety and may cause infrastructure damage. Risky driving significantly raises the possibility of the occurrence of a vehicle crash. As per statistics by the World Health Organization (WHO), approximately 1.35 million people are involved in road traffic crashes resulting in loss of life or physical disability. WHO attributes events like over-speeding, drunken driving, distracted driving, dilapidated road infrastructure and unsafe practices such as non-use of helmets and seatbelts to road traffic accidents. As these driving events negatively affect driving quality and enhance the risk of a vehicle crash, they are termed as negative driving attributes. Methods: A multi-level hierarchical fuzzy rules-based computational model has been designed to capture risky driving by a driver as a driving risk index. Data from the onboard telematics device and vehicle controller area network is used for capturing the required information in a naturalistic way during actual driving conditions. Fuzzy rules-based aggregation and inference mechanisms have been designed to alert about the possibility of a crash due to the onset of risky driving. Results: On-board telematics data of 3213 sub-trips of 19 drivers has been utilized to learn long term risky driving attributes. Furthermore, the current trip assessment of these drivers demonstrates the efficacy of the proposed model in correctly modeling the driving risk index of all of them, including 7 drivers who were involved in a crash after the monitored trip. Conclusion: In this work, risky driving behavior has been associated not just with rash driving but also other contextual data like driver’s long-term risk aptitude and environmental context such as type of roads, traffic volume and weather conditions. Trip-wise risky driving behavior of six out of seven drivers, who had met with a crash during that trip, was correctly predicted during evaluation. Similarly, for the other 12
The rapid growth of diverse informationtechnology applications has increased the challenge of securing and efficiently managing large volumes of data. Innovative solutions like blockchain technology and distributed f...
详细信息
Smart farming, also known as precision agriculture or digital farming, is an innovative approach to agriculture that utilizes advanced technologies and data-driven techniques to optimize various aspects of farming ope...
详细信息
Object detection and image restoration pose significant challenges in deep learning and computer vision. These tasks are widely employed in various applications, and there is an increasing demand for specialized envir...
详细信息
For the performance evaluation of the clustering algorithm, evaluation metrics are used. For this purpose, the obtained set of clusters are compared with the actual set of clusters (or gold standard). Various evaluati...
详细信息
CC’s(Cloud Computing)networks are distributed and dynamic as signals appear/disappear or lose ***(Machine learning Techniques)train datasets which sometime are inadequate in terms of sample for inferring information....
详细信息
CC’s(Cloud Computing)networks are distributed and dynamic as signals appear/disappear or lose ***(Machine learning Techniques)train datasets which sometime are inadequate in terms of sample for inferring information.A dynamic strategy,DevMLOps(Development Machine Learning Operations)used in automatic selections and tunings of MLTs result in significant performance ***,the scheme has many disadvantages including continuity in training,more samples and training time in feature selections and increased classification execution ***(Recursive Feature Eliminations)are computationally very expensive in its operations as it traverses through each feature without considering correlations between *** problem can be overcome by the use of Wrappers as they select better features by accounting for test and train *** aim of this paper is to use DevQLMLOps for automated tuning and selections based on orchestrations and messaging between *** proposed AKFA(Adaptive Kernel Firefly Algorithm)is for selecting features for CNM(Cloud Network Monitoring)*** methodology is demonstrated using CNSD(Cloud Network Security Dataset)with satisfactory results in the performance metrics like precision,recall,F-measure and accuracy used.
Thyroid disorders are increasingly prevalent, making early detection crucial for reducing mortality and complications. Accurate prediction of disease progression and understanding the interplay of clinical features ar...
详细信息
Software trustworthiness includes many *** weight allocation of trustworthy at-tributes plays a key role in the software trustworthiness *** practical application,attribute weight usually comes from experts'evalua...
详细信息
Software trustworthiness includes many *** weight allocation of trustworthy at-tributes plays a key role in the software trustworthiness *** practical application,attribute weight usually comes from experts'evaluation to attributes and hidden information derived from ***,when the weight of attributes is researched,it is necessary to consider weight from subjective and objective ***,a novel weight allocation method is proposed by combining the fuzzy analytical hierarchy process(FAHP)method and the criteria importance though intercrieria correlation(CRITIC)***,based on the weight allocation method,the trustworthiness measurement models of component-based software are estab-lished according to the seven combination structures of ***,the model reasonability is verified via proving some metric ***,a case is carried *** to the comparison with other models,the result shows that the model has the advantage of utilizing hidden information fully and analyzing the com-bination of components *** is an important guide for measuring the trustworthiness measurement of component-based software.
Intrusion detection systems(IDS)are one of the most promising ways for securing data and networks;In recent decades,IDS has used a variety of categorization *** classifiers,on the other hand,do not work effectively un...
详细信息
Intrusion detection systems(IDS)are one of the most promising ways for securing data and networks;In recent decades,IDS has used a variety of categorization *** classifiers,on the other hand,do not work effectively unless they are combined with additional algorithms that can alter the classifier’s parameters or select the optimal sub-set of features for the *** are used in tandem with classifiers to increase the stability and with efficiency of the classifiers in detecting *** algorithms,on the other hand,have a number of limitations,particularly when used to detect new types of *** this paper,the NSL KDD dataset and KDD Cup 99 is used to find the performance of the proposed classifier model and compared;These two IDS dataset is preprocessed,then Auto Cryptographic Denoising(ACD)adopted to remove noise in the feature of the IDS dataset;the classifier algorithms,K-Means and Neural network classifies the dataset with adam *** classifier is evaluated by measuring performance measures like f-measure,recall,precision,detection rate and *** neural network obtained the highest classifying accuracy as 91.12%with drop-out function that shows the efficiency of the classifier model with drop-out function for KDD Cup99 *** their power and limitations in the proposed methodology that could be used in future works in the IDS area.
暂无评论