Workforce optimisation for improving customer experience in urban transportation using heuristic mathematical model

Chen, Jie; Wei, Shi; Wang, Xi; Pandian, Sanjeevi; Sathishkumar, V E

doi:10.1504/ijstl.2021.10038102

Cited by 10 publications

(10 citation statements)

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“…The proposed algorithm ESS-BR22-002 "encryption performance compared with ChaCha. ChaCha concept is the all diagonal values move to the 1st column" [18] [19]. The three by three matrix has "24 bytes of fie size; the six by six matrix has 76 bytes of file size; the ten by ten matrix has 312 bytes of file size [20] [21]; the fifteen by fifteen matrix has 812 bytes of file size; the twenty by twenty matrix has 1531 bytes of file size; and the forty by forty matrix has 6580 bytes of file size" as shown in the Table 1 [22] [23].…”

Section: Resultsmentioning

confidence: 99%

The Security Algorithm ESS-BR22-002 for enhancing the security of the data

Rajaprakash

Indirajith

2023

ACE

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The information age data is impressively more critical in open life, since people's prosperity data just finished up whether or not COVID'19 affected, and besides associated with all clinical issues data. These data used to inspected and expect the clinical issues data by Machine Learning Algorithm, and a while later expected data need more prominent security. Along these lines, we applied the ongoing procedure ChaCha method and that system focused in fig-uratively speaking "encryption execution" so security is less. In this paper, to apply the new ES-BR22-001 methodology and this strategy has 8 stages. The 1st stage is finding the K value. The 2nd stage is applying the K value, that is n is the order of matrix and Sk is start from intial values. The 3rd stage is find the Sk values. The 4th stage is to apply the Sk values in the sparse matrix. The 5th stage is sparse matrix values is converted into single line. The 6th stage is pair all the values. The 7th stage is all pair values will be apply in the matrix. The fi-nal stage is apply the Salsa operations in the matrix. The new ESS-BR22-002 method has provide security and performance are good while compared to ChaCha method.

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Section: Resultsmentioning

confidence: 99%

The Security Algorithm ESS-BR22-002 for enhancing the security of the data

Rajaprakash

Indirajith

2023

ACE

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“…Accuracy is a metric for deciding the classification models [18]. Accuracy is the fraction of total number of appropriate values by total number of predictions [19].…”

Section: Performance Metrics Accuracymentioning

confidence: 99%

Identification of Kidney Related Disease Using Deep Learning

Selvaraj¹,

Thangarajan²,

Ramya

et al. 2023

ACE

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Nowadays, kidney stone problems are frequent, as more people are suffering from acute discomfort caused by kidney stones. The main cause of this disease is a high level of unhealthy food consumption and a low level of water consumption. Most health problems can be avoided if we drink enough water, but in this fast-paced world, people often forget to do so. As a result, stone concerns have arisen and been discovered as stone sizes have grown greater. They employ coronal computed tomography (CT) scan results and other study data on the belly and thorax to determine the sizes of stones and detect them in hospitals. This could assist in locating the issues. They currently utilize a back propagation method to assist them spot problems with an accuracy of 85 percent. We suggested deep learning methods and approaches, which process training data and data sets with labels, to find a more accurate level than the previous one. To obtain an accurate result rate, a larger number of photos are compared and analyzed with the scanned images. The accuracy level has been raised to 97.6%. So that we can acquire reliable results and diagnose problems sooner. We can observe how deep learning works and how it handles urological difficulties in this paper.

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“…ResNet50's architecture [18] is divided into four stages, as depicted in Fig 3 . Generally, ResNet50 design uses a 7×7 and a 3×3 kernel (filter) sizes for initial convolution and max pooling, respectively. The ResNet architecture has 4 stages of concolutional and pooling layers.…”

Section: Resnet50 Architecturementioning

confidence: 99%

ResNet50 Architecture Based Dog Breed Identification Using Deep Learning

Selvaraj

Thangarajan²,

Anbukkarasi

et al. 2023

ACE

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Dog breed identification is one of the challenging task in animal husbandry. Knowing what a dog was bred for can assist you in predicting and comprehending its behavior. Most breeds were created with a specific goal in mind: to have the desire to achieve something specific. Dogs retain part of that drive as pets in our homes, and without a good outlet for that energy, it might manifest in undesirable ways. Developing a deep learning model, that can identify the breed of the dog with high accuracy, using this model one can easily identify the dog breed which makes easier for them to train the dog, so that we cant wait for the experts and no need for spending money for identifying the dog breed, using the mobile phones we can easily identify our dog breed simply using its image. This paper deals with an advanced classification model was designed which identifies the breed of the dog. A training dataset consisting of more than 10000 images is used, CNN is used for the classification and the accuracy is achieved using Resnet50 architecture which is highest when compared to other models.

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Workforce optimisation for improving customer experience in urban transportation using heuristic mathematical model

Cited by 10 publications

References 0 publications

The Security Algorithm ESS-BR22-002 for enhancing the security of the data

The Security Algorithm ESS-BR22-002 for enhancing the security of the data

Identification of Kidney Related Disease Using Deep Learning

ResNet50 Architecture Based Dog Breed Identification Using Deep Learning

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