Age and gender identification have become a major part of the network, security care. It has common use in age specific content access for children. Social media uses it delivering layered ads marketing to extend it's reach. Face recognition developed great extent that we map further getting more useful results having different approaches. In this paper, propose deep CNN improve predication from significant can be obtained improvement seen various tasks such as face recognition. A simple...

Among the different types of malware, botnets are rising as most genuine risk against cybersecurity they give a stage to criminal operations (e.g., Distributed Denial Service (DDOS) attacks, malware dispersal, phishing, and click fraud identity theft). Existing botnet detection techniques work only on specific Command Control (C&C) protocols lack in providing early-stage detection. In this paper, we propose an approach for The proposed first selects optimal features using feature selection...

Diabetes type 1 is a chronic disease which increasing at an alarming rate throughout the world. Studies reveal that complications associated with diabetes can be reduced by proper management of continuously monitoring and forecasting blood glucose level patients. Objective. The prior prediction necessary to overcome lag time for insulin absorption in diabetic Method. In this research, we use continuous (CGM) data predict future using previous points. We compare two neural network techniques....

In this paper, design of a low cost autonomous vehicle based on neural network for navigation in unknown environments is presented. The equipped with four ultrasonic sensors hurdle distance measurement, wheel encoder measuring traveled, compass heading information, GPS receiver goal position GSM modem changing destination place run time and nonvolatile RAM storing waypoint data; all interfaced to AT89C52 microcontroller. microcontroller processes the information acquired from generates robot...

Researchers of various fields have always been interested in devising a fault-proof method for the prediction stock market. Extensive research has done using Machine Learning Algorithms like SVM, to successfully predict activity market machine learning algorithms mainly Support Vector (SVM). In this paper scenario which portfolio trading strategy is formulated algorithms. The will be considered profitable by judging its ability identify indices accurately and consistently, proposing positive...

With the increasing number of vehicles on road, it has become difficult to properly control flow traffic especially in large cities like Lahore. The proposed system uses a digital camera mounted stepper motor sense road. decision open lane is done after monitoring load. heavily loaded side turned for longer time. Thus intelligent because not using fixed time frame. also integrated with GSM, thus signals can be controlled help mobile case an emergency. MATLAB <sup...

Green Human Resource Management (henceforth, green HRM) has gained worldwide recognition nowadays. It brings together human capital for the welfare and sustainability of organization. HRM undertook eco-friendly resource practices, promoting higher efficiency, lowering costs, better relationships among employees. also helps organization reduce CO2 emissions by resorting to e-filing, online job advertising, conferencing, interview, advertisement so on forth. This study, therefore, aims examine...

Based on the limbic system theory of mammalian emotional brain, supervised brain learning-based pattern recognizer (BELPR) has been recently proposed for multi-input and multi-output classification problems. It offers features like: decreased time spatial complexity, faster training higher accuracy. BELPR deployed to classify a number benchmark datasets demonstrated its superior performance compared with conventional multilayer perceptron network. The goal this paper is further enhance...

A cheap guidance system based on AT89C52 microcontroller is developed for facilitating visually impaired people. Ultrasonic sensors are used to calculate distance of the obstacles around blind person guide user towards available path. Output in form voice which can hear e.g., right, left etc. In its advance mode, will be able recognize objects using image processing algorithms. Results presented show validity and performance system.

Automatic segmentation of lung lesions associated with COVID-19 in CT images requires large amount annotated volumes. Annotations mandate expert knowledge and are time-intensive to obtain through fully manual methods. Additionally, have inter-patient variations, some pathologies having similar visual appearance as healthy tissues. This poses a challenge when applying existing semi-automatic interactive techniques for data labelling. To address these challenges, we propose an efficient...

In order to facilitate the visually impaired person in navigation, we have developed a prototype guidance system. The main assumption of this system is that there are many straight paths different real world scenarios. These parallel edges, which when captured as an image seem converge single point called vanishing point. Proper feature extraction and mathematical modelling frame leads detection these edges. then calculated decision formed notifies blind about his/her deviation from path....

Introduction: Diabetes mellitus is one of the rapidly increasing diseases throughout world. Studies reveal that proper management blood glucose levels can reduce complications associated with diabetes type 1. Objective: We use only continuous data and predicted future level using previous data. Method: In this research, we input Continuous Glucose Monitoring (CGM) to train a feedforward neural network window model, get optimal for each subject in predicting prior values. have investigated...

A 2D simulator for vision based autonomous road following is designed using MATLAB. The provides options selecting image, placing hurdles on and the algorithm autonomously. With image containing selected, draws robot trajectory also plots error curves. real time implementation of simulated algorithms finally presented. can be employed to teach fundamental concepts in tasks.

Adaptive decayed brain emotional learning (ADBEL) is a computationally fast neural network and has shown promising results for online time series prediction problems. However, it not clear how to set the free parameters namely alpha, beta gamma of network. In this work, we present fuzzy logic based model adjusting these ADBEL in an manner which will jeopardize simplicity quickness The proposed uses error reward signals as inputs produces outputs. Further, employs small rule base vary order...

The Disturbance storm time (Dst) index is an important indicator of the occurrence geomagnetic storms, which can damage communication and power systems, as well as, affect Astronauts performance.Such potential consequences this fatal event has challenged researchers to develop Dst predictors, with some success.This paper presents design a computationally fast, neuro-fuzzy network forecast activity.The proposed combines class emotional neural networks neo-fuzzy neurons named, Neo-fuzzy...

Urinalysis is a significant technique used for determining and inspecting the urinary system. Urine has numerous chemical materials secreted; these can be to diagnose diseases conditions such as tract infection, diabetes, kidney diseases, pregnancy, at earliest. Accessing medical care health screenings are quite essential, but it become extremely difficult since screening techniques either very expensive or convoluted people of low-income communities. Despite fact, that urinalysis methods...

Abstract Background : Novel coronavirus disease (COVID-19) has led to a major public health crisis globally. Currently, myocardial damage is speculated be associated with COVID-19, which can seen as one of the main causes death patients COVID-19. Therefore, in this study, we aim investigate effects COVID-19 diagnosed on injury. Methods A prospective study was conducted among 201 Pakistan Military Hospital from April 1 August 31, 2020, including non-critical cases and critical cases. were...