ABSTRACT:- The use of technologies from many fields, such as mass spectrometry, next-generation sequencing, or image processing, is common in experiments in the life sciences. Complex scripts are frequently used to govern data flow, data transformation, and statistical analysis when passing data between such tools. Such scripts not only tend to be platform dependant, but also tend to expand as the experiment goes on and are rarely clearly documented, which makes the experiment harder to reproduce. Workflow systems like KNIME Analytics Platform, which offers a platform for graphically linking tools and ensures the same results across various operating systems, aim to address these issues. systems that are frequently employed in the biological sciences and describe how they compare and contrast with KNIME. KNIME is an open source program that enables programmers and scientists to share their own extensions with the scientific community. The unified data model of KNIME allows for interoperability, and we describe a few additions from the life sciences that make it easier to explore, analyze, and visualize data. In addition, we mention additional workflow. According to the American Cancer Society, skin cancer is the most prevalent form of malignancy in humans. It is typically identified visually, with first clinical screenings, dermoscopic (skin-related) analysis, a biopsy, and histological examinations as potential follow-up steps. Errors (mutations) in the DNA of skin cells are the cause of skin cancer. The cells proliferate out of control and aggregate into a mass of cancer cells as a result of the mutations. In this paper, convolutional neural networks are used to attempt to categorize photos of skin lesions. The deep neural networks demonstrate enormous potential for classifying images while taking into account the extreme environmental heterogeneity. Due to the current state of technology, it is imperative to use machines rather than people to address the widespread problem of skin cancer. One of the best ways to address skin cancer issues is deep learning. Huge data, virtual reality, augmented reality, and miniservices are all used in the new research area of deep learning in contemporary technology. The advent of powerful arithmetic capabilities enabled deep learning applications using Mobile net (CNN) to revolutionize image classification. The various forms of skin cancer can be categorized using deep learning. Transfer Learning was used during the training on many models. The model's best level of accuracy was over 77.333 %. To guarantee the validity and reproducibility of the aforementioned result, the dataset employed is openly accessible.

Keywords: Artificial Intelligence (AI), Convolutional Neural Networks (CNNs), Deep Learning (DL), Skin Cancer, Image Classification, Knime Analytics Platform Software etc.

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This paper describes three schemes to implement Direction of Arrival Estimation (DOA) that is used and implemented in real Antenna system. The variation between those algorithms is important in means of accuracy and complexity of implementation such mathematical models in actual system of Antenna. The use of mathematical analysis is very helpful to understand the process of DOA estimation and each part of the algorithms in the study, so that can be used further to implement algorithms and work on MATLAB to investigate and evaluate the performance of each one in relative with the others and how they act when they put in same conditions with different number of samples and using different factors. The used algorithms for the study are the conventional algorithms Bartlett & Capon, in contrast with more advanced algorithm MUSIC Multiple-Signal-Classifications, which is introduced as the main focus in the study. Simulation of DOA is made using MATLAB and the mathematical implementation of the three algorithms. The results of comparing thealgorithms shows that varying number of samples taken has a crucial role on determining Direction of Arrival or the incident angle of the input stray-signal at the arrays of the smart antenna which senses the direction based on the algorithm operated in the smart antenna system, the use of the three algorithms in different number of samples had shown a performance change of accuracy of estimation in different way for an algorithm in comparison to another algorithm in many circumstances, the more prevailing fact is that the more number of samples the more accuracy of estimation, but in case of less samples the Bartlett algorithm showed better performance in compare to other algorithms, as for Capon algorithm it suffers accuracy at low number of samples and need high number of samples to act more accurately, as for MUSIC algorithm it shows the best overall performance as adapting fast to the angle of estimation with high accuracy in response to an efficient number of samples.

ABSTRACT:- This paper introduces design of different compensators and their output response for speed control of Direct Current (DC) motor with One and Two Degree of Freedom. DC motors are used in many industrial and commercial applications require higher performance, reliability, variable speed, easier controlling stability, accuracy, speed and position control of motor is required. In this paper in order to simulate the approach a MATLAB/SIMULINK model having one and two degree of freedom phase lead, phase lag and phase lead-lag compensators are constructed to control the modeled Direct Current (DC) motor for enhancement of static & dynamic response. In addition to that, the effect of adding two degree of freedom compensators on the transient and steady state response of the system is studied.

Keywords: DC Motor, Phase Lead Compensator, Phase Lag Compensator, Phase Lag-Lead, MATLAB/Simulink etc

Traditional education depends on a set of basic elements, the most important of which are the educational curriculum, the lecturer, and the student, but these basic elements have been added to a new element in distance education, which is the electronic environment. During the COVID19 pandemic that began at the end of 2019 and the rapid transformation from traditional education to distance education and the involvement of distance education in implementing pre-prepared educational plans. This rapid transformation, in which the elements of education were not developed and not prepared in advance, led to the emergence of some problems in the educational outputs. Distance education, although its basic elements are the same as those of traditional education, the method of implementing it differed by introducing a new essential element, which is the electronic environment through which educational plans are implemented. In this research paper, the most important and influential actors in the educational process of distance learning and the problems resulting from this rapid transformation will be studied, then find appropriate solutions to keep pace with the development in the educational process, through an evaluation study of the experience of the Faculty of Science at Gharyan University. The results of this research will be useful to implement changes in the educational system and to meet the requirements of modern educational standards for higher education.

ABSTRACT In this paper, modeling, simulation and performance analysis of the three phase permanent magnet brushless direct current (PMBLDC) motor using Fuzzy Logic Controller (FLC), Genetic Algorithm controller (FGAC), hybrid Neuro-Genetic Algorithm Controller (NGAC), Hybrid -Fuzzy controller (NFC) and Hybrid Neuro-Fuzzy controller (NFC) based on Genetic Algorithm (GA) under the effect of external load for improving the transient and steady state response is presented. The applications of the three phase permanent magnet brushless direct current (PMBLDC) motor are increasing day by day. In order to have proper utilization of these motors and to control them effectively it is important to have proper mathematical modeling of these motors. Similarly effective control these motors are also essential to have successful application of the devices across multiple domains. This paper handles both these important aspects. A m been derived to represent a three phase permanent magnet brushless direct current (PMBLDC) motor model, its utility can be noted from the fact that different motors can be analyzed easily using the proposed model. The mathematical model was subjected to open loop and closed loop analysis to study the stability and performance. In this paper in order to validate the approach a MATLAB/SIMULINK model having intelligent controllers are constructed to control the modeled three phase permanent magnet brushless direct current (PMBLDC) motor under the effect of external disturbances for enhancement of static & dynamic response. 

Keywords Permanent Magnet Brushless Direct Current (PMBLDC) motor, Fuzzy Logic Controller (FLC), Genetic Algorithm (GA), Hybrid Neuro-Fuzzy controller (NFC) based on Genetic Algorithm GA, MATLAB/Simulink etc.

Abstract:- In this paper, modeling, simulation and performance analysis of the permanent magnet brushless direct current (PMBLDC) motor using classical controller (PID Controller) and optimal controllers ( Linear Quadratic Regulator (LQR) and Linear Quadratic Gaussian (LQG) optimal Controllers Based on Kalman Filter) for disturbance attenuation and noise suppression is presented. The applications of the permanent magnet brushless direct current (PMBLDC) motor are increasing day by day. In order to have proper utilization of these motors and to control them effectively it is important to have proper mathematical modeling of these motors. Similarly effective control these motors are also essential to have successful application of the devices across multiple domains. This paper handles both these important aspects. A mathematical model has been derived to represent permanent magnet brushless direct current (PMBLDC) motor model to study the stability and performance. In order to maintain the stability and to achieve the best performance by reducing disturbance attenuation and noise suppression, the three optimal controllers are developed in this paper. the system performance simulation of these optimal controllers with PID controller is presented using MATLAB program to control the modeled permanent magnet brushless direct current (PMBLDC) motor for disturbance attenuation and noise suppression.. The simulation results show that and Linear Quadratic Gaussian (LQG) Based on Kalman Filter with PID controller provides best as compared to PID controller, Linear Quadratic Regulator (LQR) with PID controller and Kalman Filter with PID controller.

Keyword: Permanent Magnet Brushless Direct Current (PMBLDC) motor, PID Controller, Linear Quadratic Regulator (LQR), Linear Quadratic Gaussian (LQG), Integral Linear Quadratic Regulator , MATLAB/Simulink etc. 

Since the last century, universities in developed countries have begun to work on technology transfer. Thus, the process of marketing the technologies discovered by those universities became an engine of economic growth, as these universities played a significant role in bringing innovative ideas to the market. Since then, technology transfer activities that were previously practiced by elite universities have received attention due to increasing university revenues, creating research links between academia and industry.

In this paper, we review the aspects related to the process of technology transfer in terms of its importance, and its model of work in universities, starting with the phase of discovering and evaluating the invention, the phase of patenting, and ending with the phase of marketing. The working mechanism of Technology Transfer Office (TTO) and the infrastructure necessary to establish these offices and the role of entrepreneurship and innovation centers in universities to perform their role effectively is also highlighted. The research aims to design an optimal dynamic and flexible model of the TTO at the University of Gharyan rearranging some traditional components and establish additional innovation pathways and make it more effective.

Keywords:Technology Transfer Office (TTO); Technological Transfer models; economic development.

In recent years, wireless communication systems have a high demand for high data throughput, high quality and spectrum efficiency. Massive MIMO is one of the new ideas in 5G. The idea is to expand the conventional MIMO system by installing large number of antennas in the base station to make better use of spatial diversity in order to provide higher throughput while using the same spectrum. However, in order to separate users and data streams and eliminate interference, an effective channel estimation technique with minimum overhead is crucial. In this paper, we propose a channel estimation technique to estimate the channel state information based on Kalman Filter. The received predetermined data is used by Kalman filter to estimate the channel, which is then used to detect the following data symbols in the same frame. The effectiveness of the proposed scheme is compared to the well-known Least square (LS) and Minimum Mean square Error (MMSE) schemes. The performance of the proposed scheme is assessed using computer simulation, and the obtained results for the proposed channel estimation demonstrate improved bit error rate performance in time-varying Rayleigh fading channels.

MANETs is a type of Mobile Ad Hoc Networks and it contains a set of nodes that do not need central management to communicate with each other because each node can act as a sender, receiver and router at the same time. All these nodes can perform self-configuration. The ad hoc stationary or mobile networks face many challenges such as limited bandwidth, congestion and data transfer speed. Therefore, it is extremely important to develop an intelligent routing protocol to encounter these challenges. An evaluation study is also important to perform the backoff contention window effectively in order to know the obstacles and avoid them. This paper concentrates on the performance of backoff contention window using the main routing protocols such as DSR, DSDV and AODV for MANETs networks in crowded areas with random movement. The important parameters which include network throughput …