Implementation of Back Propagation Neural Network with PCA for Face Recognition

Face recognition is truly one of the demanding fields of biometric image processing system Within this paper we have implemented Back Propagation Neural Network for face recognition using MATLAB where feature extraction and face identification system completely depend on Principal Component Analysis PCA Face images are multidimensional and variable data Hence we cannot directly apply Back Propagation Neural Network to classify face without extracting the core area of face So the dimensionality of face image is reduced by the Principal Component Analysis algorithm then we have to explore unique feature for all stored database images called eigenfaces of eigenvectors These unique features or eigenvectors are given as parallel input to the Back Propagation Neural Network BPNN for recognition of given test images Here test image is taken from the integrated webcam which is applied to the BPNN trained network The maximum output of the tested network gives the index of recognized face image BPNN employing PCA is more robust and reliable than PCA based face recognition syste

Implementation and Performance Analysis of Different Hand Gesture Recognition Methods

In recent few years, hand gesture recognition is one of the advanced grooming technologies in the era of human-computer interaction and computer vision due to a wide area of application in the real world. But it is a very complicated task to recognize hand gesture easily due to gesture orientation, light condition, complex background, translation and scaling of gesture images. To remove this limitation, several research works have developed which is successfully decrease this complexity. However, the intention of this paper is proposed and compared four different hand gesture recognition system and apply some optimization technique on it which ridiculously increased the existing model accuracy and model running time. After employed the optimization tricks, the adjusted gesture recognition model accuracy was 93.21% and the run time was 224 seconds which was 2.14% and 248 seconds faster than an existing similar hand gesture recognition model. The overall achievement of this paper could be applied for smart home control, camera control, robot control, medical system, natural talk, and many other fields in computer vision and human-computer interaction

Performance Analysis of TCP Tahoe, Reno, New Reno, Sack and Vegas using NS-2

The Transmission Control Protocol TCP is the dominating end-to-end protocol on the internet today but still it faces congestion problems in some cases To overcome congestion problems several congestion control and avoiding mechanisms namely Tahoe Reno Vegas and Sack etc all with different features and advantages but with maximal throughput as main objective which are termed as the clones of TCP have been incorporated into TCP IP protocol for handling congestion efficiently in different network scenarios However one clone cannot be suitable for each case So this paper has investigated the characteristics of the mentioned clones and calculated throughputs of them in simulated environment varying various performances metrics such as delay buffer size error rate number of traffic and bandwidth for finding which one is the best for what scenario The performance of these clones for varying network conditions and settings can effectively be evaluated using NS-2 In this work by doing simulation in NS-2 environment the throughputs of some exiting TCP implementations are calculated considering various metrics and then the calculated throughputs are compared among one another These comparisons show that which one is suitable in which case

Enhancing Transmission Capacity of a Cognitive Radio Network by Joint Spatial-Temporal Sensing with Cooperative Communication Strategy

In static cognitive radio network a secondary transmitter communicates directly with a secondary receiver only when the spectrum is not occupied by any primary user. The secondary user has to stop its transmission when no spectrum holes exist. To improve the transmission capacity, in this paper we approach to combine cognitive radio network with cooperative communication strategy employing spatial sensing as well as temporal sensing. In our proposed scheme when primary user is active, a secondary user transmits to another secondary user via a relay channel. By enabling the use of both the direct and relay channels, the transmission performance of the secondary system can be improved significantly. Our information-theoretic analysis as well as numerical results show that the proposed scheme significantly reduces the average symbol error probability compared to schemes based on pure temporal or spatial sensing

An Energy conserving routing scheme for wireless body sensor nanonetwork communication

Current developments in nanotechnology make electromagnetic communication possible at the nanoscale for applications involving body sensor networks (BSNs). This specialized branch of wireless sensor networks, drawing attention from diverse fields, such as engineering, medicine, biology, physics, and computer science, has emerged as an important research area contributing to medical treatment, social welfare, and sports. The concept is based on the interaction of integrated nanoscale machines by means of wireless communications. One key hurdle for advancing nanocommunications is the lack of an apposite networking protocol to address the upcoming needs of the nanonetworks. Recently, some key challenges have been identified, such as nanonodes with extreme energy constraints, limited computational capabilities, terahertz frequency bands with limited transmission range, and so on, in designing protocols for wireless nanosensor networks. This work proposes an improved performance scheme of nanocommunication over terahertz bands for wireless BSNs making it suitable for smart e-health applications. The scheme contains - a new energy-efficient forwarding routine for electromagnetic communication in wireless nanonetworks consisting of hybrid clusters with centralized scheduling; a model designed for channel behavior taking into account the aggregated impact of molecular absorption, spreading loss, and shadowing; and an energy model for energy harvesting and consumption. The outage probability is derived for both single and multilinks and extended to determine the outage capacity. The outage probability for a multilink is derived using a cooperative fusion technique at a predefined fusion node. Simulated using a nano-sim simulator, performance of the proposed model has been evaluated for energy efficiency, outage capacity, and outage probability. The results demonstrate the efficiency of the proposed scheme through maximized energy utilization in both single and multihop communications; multisensor fusion at the fusion node enhances the link quality of the transmission

Big Data - Supply Chain Management Framework for Forecasting: Data Preprocessing and Machine Learning Techniques

This article intends to systematically identify and comparatively analyze state-of-the-art supply chain (SC) forecasting strategies and technologies. A novel framework has been proposed incorporating Big Data Analytics in SC Management (problem identification, data sources, exploratory data analysis, machine-learning model training, hyperparameter tuning, performance evaluation, and optimization), forecasting effects on human-workforce, inventory, and overall SC. Initially, the need to collect data according to SC strategy and how to collect them has been discussed. The article discusses the need for different types of forecasting according to the period or SC objective. The SC KPIs and the error-measurement systems have been recommended to optimize the top-performing model. The adverse effects of phantom inventory on forecasting and the dependence of managerial decisions on the SC KPIs for determining model performance parameters and improving operations management, transparency, and planning efficiency have been illustrated. The cyclic connection within the framework introduces preprocessing optimization based on the post-process KPIs, optimizing the overall control process (inventory management, workforce determination, cost, production and capacity planning). The contribution of this research lies in the standard SC process framework proposal, recommended forecasting data analysis, forecasting effects on SC performance, machine learning algorithms optimization followed, and in shedding light on future research

Conservative Management of Median Nerve Brachial Plexopathy after Microwave-based MiraDry Treatment for Axillary Hyperhidrosis

Axillary hyperhidrosis is characterized by excessive sweating of the armpits, which can significantly affect quality of life. A new microwave-based therapy, MiraDry (Miramar labs, Sunnyvale, Calif.), is a promising minimally-invasive treatment option. We report a case of unilateral brachial plexus thermal injury in a thin 19-year-old man treated for axillary hyperhidrosis with the MiraDry system. He initially experienced swelling and pain in the left hand and was prescribed 1 week of methylprednisolone. He then presented 1 week later with induration and swelling of bilateral axillae with swelling of left thumb, left index, and left long fingers, decreased sensation in median nerve distribution of the left hand, and the inability to flex the left index finger DIP joint. EMG showed absent median nerve motor and sensory function, consistent with median nerve plexopathy. He was conservatively managed with close observation and regular occupational hand therapy appointments. At his 12-month follow-up, there was complete return of left pronator teres strength, thumb flexion, and index finger flexion. Decreased sensation remained at the tip of the left index finger. We report the case of median nerve palsy after MiraDry therapy for axillary hyperhidrosis in a thin young man. We recommend using low-energy settings and pre-procedural ultrasound for young, thin patients because of the more superficial course of the brachial plexus within the axilla

Convalescent Serum Therapy as Rapid Advance Treatment for Ebola in West Africa

The 2014 public health crisis in Guinea, Liberia, and Sierra Leone has brought Ebola Viral Disease (EVD) to everyone’s attention. Discovered in 1976, this deadly disease infrequently struck in remote areas of Africa. This article will critically review the literature and describe the pathobiology, transmission, signs and symptoms, diagnosis, treatment, and prevention of EVDwhich, was predicted by the Centers for Disease Control to potentially infect 1.4 million persons in Liberia and Sierra Leone by January 2015 (“Questions and Answers”, 2014). Thankfully this worst case scenario did not occur and we may be experiencing natural burn out of the outbreak along with the results of aggressive education and supportive treatment as in Sierra Leone. There is no established treatment for EVD despite successes in non-human models. The WHO endorsed Convalescent Blood Products (“Potential for use of…,” 2014) after it showed promise in Democratic Republic of Congo. In 2014, American Ebola patients recovered after receiving Convalescent Serum Therapy (CST) with experimental therapies like Zmapp, TKM-Ebola, and Brincidofovir. We may have missed the window of opportunity to establish the efficacy of these potential therapies, which may have unprecedented implications for health status, healthcare infrastructure development in the future, and the economic viability of the sub-region for decades to come. Additionally, an endemic area will pose a threat to the rest of the world as a potential incubator/exporter of this dangerous viral illness

Análise de desenhos experimentais com outliers

Primary purpose of the article is to develop outlier robust designs. As a matter of fact, negative effect of outliers in any experimental settings is established where the outliers at any specific design point can destroy the features of the design for which it is being developed. It is attempted here in this article to develop a version of robustness for central composite designs which may protect it for outliers by introducing the idea of minimax outlying effect. This involves the calculation of the degree of outlying effect(s) outlier(s) may produce and then minimize the maximum of these outlying effects in an attempt to equalize the influence of all design points. On comparison, these outlier robust designs are proved to be more optimal, on the scales of A, D, and E optimalities, against existing conventional rotatable, orthogonal, and other such designs. The outlier robust designs, developed here, are suitable for settings prone to outliers where conventional designs fail to represent and analyze the processes and systems.El objetivo principal del artículo es desarrollar diseños robustos atípicos. De hecho, el efecto negativo de los valores atípicos en cualquier configuración experimental se establece donde los valores atípicos en cualquier punto de diseño específico pueden destruir las características del diseño para el que se está desarrollando. En este artículo se intenta desarrollar una versión de robustez para los diseños compuestos centrales que pueden protegerlo de los valores atípicos mediante la introducción de la idea del efecto periférico minimax. Esto implica el cálculo del grado de efecto (s) externo (s) que puede producir un valor atípico y luego minimizar el máximo de estos efectos externos en un intento de igualar la influencia de todos los puntos de diseño. En comparación, se demuestra que estos diseños robustos atípicos son más óptimos, en las escalas de las optimidades A, D y E, frente a los diseños convencionales existentes, ortogonales, rotativos y otros similares. Los diseños robustos atípicos, desarrollados aquí, son adecuados para configuraciones propensas a los valores atípicos en los que los diseños convencionales no representan ni analizan los procesos y sistemas.Objetivo principal do artigo é desenvolver projetos robustos outlier. De fato, o efeito negativo de outliers em qualquer ambiente experimental é estabelecido onde os outliers em qualquer ponto de design específico podem destruir os recursos do design para o qual ele está sendo desenvolvido. Neste artigo, tenta-se desenvolver uma versão de robustez para projetos compostos centrais que possam protegê-lo de outliers, introduzindo a ideia de efeito periférico minimax. Isso envolve o cálculo do grau de efeito (s) outlier (s) outlier (s) pode produzir e, em seguida, minimizar o máximo desses efeitos periféricos em uma tentativa de equalizar a influência de todos os pontos do projeto. Em comparação, esses designs robustos discrepantes são comprovadamente mais otimizados, nas escalas de otimalidades A, D e E, contra os designs convencionais rotacionais, ortogonais e outros existentes. Os designs robustos outlier, desenvolvidos aqui, são adequados para configurações propensas a outliers em que projetos convencionais não representam e analisam os processos e sistemas