We propose CNNEnsem model, an ensemble model to efficiently classify respiratory diseases from respiratory sound data. The classification accuracy of an ensemble model is proposed based on the classification models and verified on application of CNNEnsem model. For CNNEnsem model, two convolutional neural networks are proposed and tested using MFCC (mel-frequency cepstrum coefficients) images and time-domain waveform images of respiratory sounds. These two types of images provide distinguishing features of different types of respiratory diseases. The proposed models are evaluated on the ICBHI 2017 dataset to classify respiratory diseases. To validate CNNEnsem model, its accuracy for disease classification is compared with that of both the individual convolutional neural networks and existing models. The CNNEnsem model achieves a classification accuracy of 99.46%, which outperforms similar methods.

The inland container supply chain is vital for countries such as Malaysia where more than 50% of the country’s cargo movements are containerized. The hauliers provide the transport of containers and their performance affects the inland container supply chain performance and national logistics performance. New practices and new forms of information sharing have emerged due to the advancement of information systems. This study explores how information are shared among members in the inland container supply chain, how does it benefit the hauliers and subsequently their performance and how information sharing can be further improved. Twelve participants from the haulier companies were selected and interviewed. The transcribed data were analysed using Nvivo11. Findings indicate that information is mainly shared through the information systems of the hauliers and the information systems of other supply chain members. However, benefits to the hauliers in sharing the information was not present. Too much of data, duplication of data entry and information systems working in silos were identified as the main challenges. Information shared by the hauliers to the depots and the port terminals were not equitable to the hauliers and does not improve their performance. Data entry automation and information systems integration are expected to improve the information sharing. More importantly, opportunistic behaviour of organizations in the supply chain has to be curtailed and subsequently information asymmetry has to be reduced for the information shared to be mutually beneficial and equitable for the hauliers to realize the information sharing benefits.

Objective: From a computerized image analysis prospective, early diagnosis of lung infections demonstrates the analysis of Corona Virus Disease based on a clinical Computed Tomography (CT) is the mainstay of diagnostic imaging evaluation of thoracic disorders. Methods: Sensitivity and specificity are the two most important indicators in selection of medical imaging devices for lunge screening. Lunge images taken Computed Tomography (CT) and CT collected from patients. Results: The statistical features extracted from the histograms of the regions of interest revealed that CT modality registered the highest scores, in the differentiation between normal, and lunge infections tissues. Conclusion: They were then studied and compared for sensitivity and specificity results. The sensitivity and specificity sensitivity increases on the expense of specificity, and vice versa. The data of this study revealed that, CT high sensitivity.

COVID-19 have been known to the scientific community recently. The present study was aimed to explain the correlation between the body mass index and the levels of plasma lipid profile in patients with COVID-19 infection. The present study was carried out on 112 patients with COVID-19 infection. Patients were divided into two groups according to the infection severity (mild and severe). Also, each group was divided into two subgroups according to the patient’s body mass index. The body mass index of males and females with mild COVID-19 infection ranged from 31- 32. Also, the body mass index of males and females with severe COVID-19 infection ranged from 23- 25. All patients with mild COVID-19 infection had a normal level of D-dimer, lactate dehydrogenase, ferritin, C-reactive protein, serum creatinine, total cholesterol, triacylglycerols and high-density lipoprotein-cholesterol (HDL-C) when compared to normal range. However, levels of plasma, triacylglycerols, d-dimer, lactate dehydrogenase, ferritin, C-reactive protein and serum creatinine of patients with severe COVID-19 infection were significant increase when compared to normal range. Also, plasma total cholesterol and high-density lipoprotein-cholesterol (HDL-C) of patients with severe COVID-19 infection were significant decrease when compared to normal control (p< 0.05). Conclusion: The levels of the biochemical parameters was corelated with the patient body mass index and the infection severity.

With increasing development of wireless communication network, Unmanned Aerial Vehicle(UAV) has emerged as a flying platform for wireless communication with efficient coverage, capacity and reliability but UAV as a FANET(Flying Ad-hoc Network) has some communication issues due to mobility of networks that leads to change in topology of network. In this paper we propose a hybridization of Self-organization based clustering scheme(SOCS) with k-means algorithm for cluster formation, cluster management, selection of cluster head and cluster members and use Firefly Optimization for routing mechanism of cluster. Evaluation of performance with experimental results obtained compared with existing SOCS using Glowworm Swarm Optimization(GSO) in terms of cluster building time, cluster lifetime, energy consumption, probability of delivery success.

In this paper, we prove (i) if $T$ is class $p$-$wA(s,t)$ operator and\n$\\Tst$ is quasinormal (resp., normal), then $T$ is quasinormal (resp., normal),\n(ii) if $T$ and $T^*$ are class $p$-$wA(s,t)$ operator, then $T$ is normal, (iii) the normal parts of quasisimilar class $p$-$wA(s,t)$ operators are unitarily equivalent, and (iv) Fuglede-Putnam type theorem holds for a class class $p$-$wA(s,t)$ operator $T$ for $0

Environmental pollution from anthropogenic cause considerable irreparable damage to aquatic ecosystems as well as public health as rapid industrialization and urbanization releases numerous toxic substances into the water bodies without treatment. Despite the sordid state of most of water bodies in the nascent Niger Delta ecological zone, there are some organisms especially microbes and benthos were comfortably thriving, and the species diversity is used as a prime aspect in biological monitoring, which is considered to be a valuable parameter in determining the health status of the environment. Three stations within the lower Niger Rivers were chosen for this study. Station A as selected based on its pollution load as a result of sewage disposal and public defecation, B is use for human recreational and agricultural activities, while C has no activities and far away from other stations, thus serves as a reference station. Water and sediments samples were collected monthly in triplicates for twelve months and a total of one hundred and forty four were examines for this investigation. Isolates were identified by morphological and biochemical characterization using taxonomy scheme, fungi was based on the microscopic features of hyphal mass, nature of fruiting bodies and morphology of cells and spores and the planktons were microscopically identified using electron microscope, while macro-invertebrates were identified using taxonomic keys. Results show the present of bacteria and fungi with hydrocarbon utilizing potentials, zooplanktons (Cyclops,rotifers,Cladocera) and macro-invertebrates (oysters, leeches and Aporrectodea longa) were abundant varyly. Physiochemical parameters of water samples were above the recommendation limits.

The shoulder subluxation is a most significant problem in post stroke hemiplegics, resulting in pain and loss of function. Surface electrical stimulation was found to reduce existing subluxation, but showed no significant improvement in motor function. The main purpose of this study was to determine the short term effects of neuromuscular electrical stimulation and motor activity eliciting exercises in preventing the occurrence of shoulder pain and subluxation and in enhancing early shoulder mobility. Two groups’ pre test – post test experimental study design. The total number of participants consists of 16 acute stroke patients (upto 2 weeks) involving MCA of both sexes between 40 and 80 years with no history of shoulder pain and subluxation. 16 patients are randomly assigned to a control or experimental group, 8 in each. They had their first assessment within 48 hours of their stroke. The experimental group received electrical stimulation for half an hour per session, twice a day for a week and also they are given motor activity eliciting exercises for another half an hour. The control group received Bobath based exercises. All patients are assessed a week after treatment. The shoulder pain was assessed by Numeric pain Rating Scale (NRS); shoulder motor function by the Fugl - Meyer assessment (FMA - shoulder component) scale. At baseline, patients in both groups are similar. After the intervention, the treatment group showed significant effect in preventing the occurrence of shoulder pain and subluxation and also showed significant improvement in shoulder motor function. The present study concluded that the Neuromuscular electrical stimulation (NMES) and motor activity eliciting exercises have short term effect in preventing the occurrence of post stroke shoulder pain and subluxation and also in improving shoulder motor function.