Design and Fabrication of Radio Frequency Amplifier with 3 dB π-Network Attenuator Isolation

This paper presents the design and fabrication of radio frequency amplifier (RFA), which operates at 5.8 GHz unlicensed frequency for WiMAX application. The RFA designed used T-matching network consisting of lump reactive elements, 3 dB attenuator and microstrip line at the input and output impedance. The RFA developed in this project contribute a gain of 15.6 dB with overall noise figure of 2.4 dB. The overall measured bandwidth is 1.240 GHz with S parameters S11, S12 and S22 measured are -12.4 dB, -25.5 dB and -12.3 dB respectively. The isolation result shows that there is a significant contribution using 3 dB π-network. The RFA used FET transistor EPA018A from Excelics Semiconductor Inc

Study of EMG Feature Selection for Hand Motions Classification

In recent days, electromyography(EMG) pattern recognition has becoming one ofthe major interests in rehabilitation area. However, EMG feature set normally consists of relevant, redundant and irrelevant features. To achievehigh classification performance, the selection ofpotential features is critically important. Thus, this paper employs two recent feature selection methods namely competitive binary gray wolfoptimizer (CBGWO) and modified binary treegrowth algorithm (MBTGA) to evaluate the mostinformative EMG feature subset for efficient classification. The experimental results show thatCBGWO and MBTGA are not only improves theclassification performance, but also reduces thenumber of features.Keywords— Electromyography; feature extraction; time domain feature; featureselection; classificatio

An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics

For a decade, The Cancer Genome Atlas (TCGA) program collected clinicopathologic annotation data along with multi-platform molecular profiles of more than 11,000 human tumors across 33 different cancer types. TCGA clinical data contain key features representing the democratized nature of the data collection process. To ensure proper use of this large clinical dataset associated with genomic features, we developed a standardized dataset named the TCGA Pan-Cancer Clinical Data Resource (TCGA-CDR), which includes four major clinical outcome endpoints. In addition to detailing major challenges and statistical limitations encountered during the effort of integrating the acquired clinical data, we present a summary that includes endpoint usage recommendations for each cancer type. These TCGA-CDR findings appear to be consistent with cancer genomics studies independent of the TCGA effort and provide opportunities for investigating cancer biology using clinical correlates at an unprecedented scale. Analysis of clinicopathologic annotations for over 11,000 cancer patients in the TCGA program leads to the generation of TCGA Clinical Data Resource, which provides recommendations of clinical outcome endpoint usage for 33 cancer types

Microcontroller Implementation Of Single Phase Inverter Switching Strategies.

This paper presents the practical microcontroller implementation of single phase inverter switching strategies

Classification of Myoelectric Signal using Spectrogram Based Window Selection

This paper presents a study of the classification of myoelectric signal using spectrogram with different window sizes. The electromyography (EMG) signals of 40 hand movement types are collected from 10 subjects through NinaPro database. By employing spectrogram, the EMG signals are represented in time-frequency representation.  Ten features are extracted from spectrogram for performance evaluation. In this study, two classifiers namely support vector machine (SVM) and linear discriminate analysis (LDA) are used to evaluate the performance of spectrogram features in the classification of EMG signals. To determine the best window size in spectrogram, three different Hanning window sizes are examined. The experimental results indicate that by applying spectrogram with optimize window size and LDA, the highest mean classification accuracy of 91.29% is obtained

Hot red pepper powder as a safe alternative to antibiotics in organic poultry feed: An updated review

Globally, several studies have investigated the utilization and efficacy of promising medicinal herbal plants to enhance livestock and poultry production. The most commonly investigated phytobiotics in broiler ration were oregano, garlic, thyme, rosemary, black pepper, hot red pepper (HRP), and sage. Phytobiotics are classified on the basis of the medicinal properties of plants, their essential oil extracts, and their bioactive compounds. The majority of bioactive compounds in plants are secondary metabolites, such as terpenoids, phenolic, glycosides, and alkaloids. The composition and concentrations of these bioactive constitutes vary according to their biological factors and manufacturing and storage conditions. Furthermore, HRP is one of the most important and widely used spices in the human diet. Capsicum annum, that is, HRP, is a species of the plant genus Capsicum (pepper), which is a species native to southern North America and northern South America and is widely grown and utilized for its fresh or cooked fruits. Moreover, these fruits may be used as dried powders or processed forms of oleoresins. Researches have proven that C. annuum is the only plant that produces the alkaloid capsaicinoids. Approximately 48% of its active substances are capsaicin (8-methyl-N-vanillyl-6-nonemide), the main active compound responsible for the intense effects of HRP varieties and the main component inducing the hot flavor. This review aimed to highlight the effects of HRP as a phytobiotic in broiler nutrition and its mode of action as a possible alternative to antibiotics and clarify its impact on broiler and layer productivity

Ultrastructural pathology of nasal and tracheal mucosa of rabbits experimentally infected with Pasteurella multocida serotype D:1

Sixteen 8- to 9-week-old Pasteurella multocida-free New Zealand White rabbits were dividec into two equal groups. The first group was inoculated intranasally with P multocida serotype D:1 strain and the second group that was inoculated with phosphate-buffered saline (PBS) only was used as a control group. Pasteurella multocida was isolated from the nasal cavity of all infected rabbits in group 1 and from tracheal swabs of seven rabbits in this group. Four rabbits in group 1 died with clinical signs of septicaemia, two rabbits had mucopurulent nasal discharge and pneumonic lesions and the other two did not show any clinical signs or gross lesions. The ultrastructural changes detected were deciliation or clumping of cilia of ciliated epithelium, cellular swelling, vacuolation and sloughing. The subepithelial capillaries showed congestion, intravascular fibrin deposition, platelets aggregation and endothelial injury. Pasteurella multocida was observed attached to the injured endothelial cells. Heterophils, mast cells, vacuolated monocytes and macrophages infiltrated the lamina propria and between the degenerated epithelial cells. ©2001 Harcourt Publishers Ltd

Ultrastructural observation of nasal and pulmonary intracellular Pasteurella multocida A:3 in rabbits

Sixteen 8- to 9-week-old Pasteurella multocida-free rabbits were divided into two equal groups. Eight rabbits in one group were inoculated intranasally with P. multocida type A:3. The other eight were inoculated intranasally with phosphate-buffered saline and used as controls. Nasal swabs taken before and after inoculation were cultured for bacterial isolation. Post-mortem nasal swabs and lung samples were cultured for bacteriological isolation. Nasal mucosa and lung samples were collected and processed for transmission electron microscopy. Pasteurella multocida was isolated from the nasal cavity of all infected rabbits and from the lungs of four infected rabbits. Degenerative ultrastructural changes in epithelial cells and endothelial cells were seen in the infected rabbits. Deciliation of the cilated epithelium and hyperplasia of the goblet cells in the nasal mucosa were noted. Thickening of the alveolar septa due to hyperplasia of type II pneumocytes, swelling of the endothelial lining of capillaries and infiltration of inflammatory cells were also observed. Intracellular invasion of the nasal epithelial cells and of type II pneumocytes by the organism was observed. Coccobacilli were observed in membrane-bound vacuoles in the cytoplasm of these cells. The vacuoles were adjacent to the host-cell mitochondria and some of these vacuoles appeared to be fused to the mitochondrial membrane. Some type I pneumocytes with intracellular membrane-bound vacuoles containing bacterial cells showed protrusions, which appeared to detach into the alveolar lumina. These results indicated that P. multocida serotype A:3 in rabbits can invade the epithelial cell and cause structural changes in the interstitium, epithelium and endothelium. Heterophils and macrophages appear to play important roles in tissue injury

An Improved Retraining Scheme for Convolutional Neural Network

A feed-forward neural network artificial model, or multilayer perceptron (MLP), learns input samples adaptively and solves non-linear problems for data that are noisy and imprecise. Another variant of MLP, known as Convolutional Neural Network (CNN) has additional features such as weight sharing, local receptive field, and subsampling, making CNN superior in handling challenging pattern-recognition tasks. Although CNN has improved the performance of MLP, the complexity of its structure has caused retraining processes to become inefficient whenever new categories or neurons using a winner-takes-all approach are added at the classifier stage. Thus, it is necessary to retrain the complete network set when new categories are added to the network. However, such a retraining incurs additional cost and training time. In this paper, we propose a retraining scheme that could overcome the mentioned problem. The proposed retraining scheme generalizes the feature of extraction layers, hence the retraining process only involves the last two layers instead of the whole network. The design was evaluated on AT&T and JAFFE databases. The results obtained have proved that training an additional category is approximately more than 70 times faster than retraining the whole network architectur

Electromyography Signal Analysis Using Time and Frequency Domain for Health Screening System Task

Musculoskeletal disorder (MSDs) isone of the most popular issues of occupationalinjuries and disabilities. It has a big impact andcreates a big problem for industries to be resolved.In MSDs, electromyography (EMG) is one of themethods to be studied in order to detect MSDsproblem. This research focuses on the EMG signalanalysis by using time domain and frequencydomain (Welch Power Spectral Density) method.It gives more information from the signal and itis the most suitable method for classifying themoments in order to identify the behaviouralof the signals. Axial rotational reach and upperlevel reach task from Health Screening Program(HST) is performed using functional range ofmotion (FROM) by considering left and rightbiceps brachii muscles to be analysed. There aretwo parameters chosen for each time and for eachfrequency domain to be tested, which are meanan absolute value (MAV) and root mean square(RMS) for time domain. Median frequency (MDF)and mean frequency (MNF) are for frequencydomain. The results showed that frequencydomain analysis is able to give more parameterand information of the signal. Upper level reachacquires more effort to perform the task comparedto axial rotational reach for left and right bicepsbrachii. However, different performances ofthe signal obtained in classifying the momentsfrom t-test analysis due to p-value. The bestperformance to classify signal characteristics is thelowest p-value which is 7.369E-05 (MAV), 6.9504E-05 (RMS), 0.0054 (MDF). However, p-value for0.0515 is rejected because it is greater than 0.05.It is concluded that the frequency domain is ableto give more information of the signal, howeverfor classifications moments, time domain is bettercompared to the higher accuracy result. This studyis very important to give the idea in the futureanalysis of EMG signal in the aspect of detectingMSDs in human body in health screening task