Generalization of Net Benefit of Diagnostic Tests into Multi-stage Clinical Conditions: A Collapsing Approach

Evaluating diagnostic tests based on benefit-risk involves both the tests’ accuracy and the clinical implications of the diagnostic errors. Diagnostic tests are commonly classified into two stages: either positive or negative for a clinical condition (diseased or non-diseased). However, some diseases have more than two stages, such as Alzheimer’s. In diseases with more than two stages, the benefits and risks of the clinical consequences could differ from stage to stage. I could not find any investigations to account for the difference in benefits and risks of tests with more than two stages in the literature. The benefit to cost values for each stage of the disease could be different. This dissertation extends the net benefit approach of evaluating diagnostic tests in binary disease cases to multi-stage clinical conditions. Consequently, I extend the diagnostic yield table to multi-stage clinical conditions. I develop a decision process based on net benefit for evaluating diagnostic tests. The decision process provides additional interpretation for rule-in or rule-out clinical conditions and their adverse consequences from unnecessary workups in multi-stage diseases. Numerical examples, as well as real data, are provided to illustrate the proposed measures

A Modified Distortion Measurement Algorithm for Shape Coding

Efficient encoding of object boundaries has become increasingly prominent in areas such as content-based storage and retrieval, studio and television post-production facilities, mobile communications and other real-time multimedia applications. The way distortion between the actual and approximated shapes is measured however, has a major impact upon the quality of the shape coding algorithms. In existing shape coding methods, the distortion measure do not generate an actual distortion value, so this paper proposes a new distortion measure, called a modified distortion measure for shape coding (DMSC) which incorporates an actual perceptual distance. The performance of the Operational Rate Distortion optimal algorithm [1] incorporating DMSC has been empirically evaluated upon a number of different natural and synthetic arbitrary shapes. Both qualitative and quantitative results confirm the superior results in comparison with the ORD lgorithm for all test shapes, without any increase in computational complexity

MCFFA-Net: Multi-Contextual Feature Fusion and Attention Guided Network for Apple Foliar Disease Classification

Numerous diseases cause severe economic loss in the apple production-based industry. Early disease identification in apple leaves can help to stop the spread of infections and provide better productivity. Therefore, it is crucial to study the identification and classification of different apple foliar diseases. Various traditional machine learning and deep learning methods have addressed and investigated this issue. However, it is still challenging to classify these diseases because of their complex background, variation in the diseased spot in the images, and the presence of several symptoms of multiple diseases on the same leaf. This paper proposes a novel transfer learning-based stacked ensemble architecture named MCFFA-Net, which is composed of three pre-trained architectures named MobileNetV2, DenseNet201, and InceptionResNetV2 as backbone networks. We also propose a novel multi-scale dilated residual convolution module to capture multi-scale contextual information with several dilated receptive fields from the extracted features. Channel-based attention mechanism is provided through squeeze and excitation networks to make the MCFFA-Net focused on the relevant information in the multi-receptive fields. The proposed MCFFA-Net achieves a classification accuracy of 90.86%.Comment: 7 pages, 6 figures, ICCIT 2022 submission, Conferenc

Experience of IM programs, perception of IMO and job outcomes: the frontline employee perspective

The thesis found that frontline employees’ (FLEs) experience of internal marketing (IM) programs positively influence their views of internal market orientation and their job outcomes of organisational identification and job satisfaction which then predicts FLEs’ customer oriented behaviour which is the targeted outcome of IM

Biological features of Chanda nama (Ambassidae) in the Old Brahmaputra River, Bangladesh

Biological features including sex ratio, length-frequency distributions (LFDs), size at sexual maturity, spawning season, length-weight relationships (LWRs) and condition factor of Chanda nama were studied in the Old Brahmaputra River, Bangladesh. There was no significant difference in sex ratio. LFDs indicated no significant differences in size between the sexes. Size at sexual maturity was estimated at ~3.0 cm standard length. Monthly variations in gonadosomatic index indicate that the main spawning season is from July to August. The LWRs showed isometric growth in males and positive allometric growth in females. Fulton’s condition factor varied in both sexes and was attributed to variations in GSI with maturity. The findings of this study will be helpful to formulate conservation and management strategies of C. nama population in the Old Brahmaputra River and surrounding ecosystems

Efficient Algorithm for Power Allocation in Relay-based Cognitive Radio Network

This paper addresses a cognitive radio (CR) network scenario where a relay is assigned to mitigate interference to primary users (PUs). We develop an average probability of successful secondary transmission (PSST) to introduce relay in the CR network. The power allocation is done using dual domain concept to maximize the system throughput as well as maintaining interference to an acceptable level and this approach is implemented in our paper that has a higher convergence rate. Furthermore, we propose an alternative approach that maintains a high throughput and at the same time reduces the computational complexity significantly. A detailed analysis is done before simulation. The simulated results validate the theoretical analysis