Author: Dr.Aseel Khalid

One of the most common causes of functional frailty is major depressive disorder (MDD). MDD is a chronic condition that requires long-term therapy and professional assistance. Additionally, MDD effective treatment requires early detection. Unfortunately, it has intricated clinical characteristics that make early diagnosis and treatment difficult for clinicians. Furthermore, there are currently no clinically effective diagnostic biomarkers that can confirm an MDD diagnosis. However, electroencephalogram (EEG) data from the brain have recently been used to make a quantitative diagnosis of MDD. In addition, As being among the most cutting-edge artificial intelligence (AI) technologies, deep learning (DL) has exhibited superior performance in a wide range of real-world applications, from computer vision to healthcare. However, an additional challenge could be the extraction of information from the ECG raw data. This paper presents a method for converting EEG data to power spectral density (PSD) images, and then they were classified as healthy or MDD using a deep neural network for feature extraction and a machine learning (ML) classifier. When employing the proposed approach, the images formed from the PSD show a considerably improved performance in classification results. DOI link: Major depressive disorder diagnosis based on (PSD) imaging of electroencephalogram EEG and AI

Cognitive radio is a communication technology developed to solve the problem of spectrum scarcity. Detection ofenergy depending cooperative spectrum sensing represents a solution to enhance the throughput of CR since theinformation about primary signal absence are collected using many sensing nodes with diff erent channelconditions. However, the throughput cannot be maximized unless effi cient decision rules are used to combine thecollected information and produce right fi nal decision. In this paper, a unifi ed agreeable range detectingcalculation is used, and two decision rules are proposed to maximize the throughput of CR, these are: Middle PlusOne (MPO) rule, Double Threshold Soft Decision rule (DTSD). A complete sensing stage based on the proposedrules is designed and simulated via MATLAB (m-fi les) in the presence of AWGN and Rayleigh multipath fadingwhich has route delays range from 1 to 5 path delays for “ITU indoor channel model A,” while the reportingchannel is assumed to be free of errors. The simulation results showed that the proposed rules improvethroughput. Therefore, the use of the proposed rules can represent an effi cient way to enhance the throughput incognitive radio. DOI link : An Enhance Spectrum Sensing Algorithm for theCognitive Radio Network

This research is an exploration into developing a system for enabling Radio Frequency Identification (RFID) labels to be connected to the Internet while taking into account their unique impediments. Additionally, this mechanism enables the tag to be extraordinarily distinct and spoken to as a communication material capable of communicating with other participants, which can facilitate and rearrange the use of the “Internet of Things” concept in the not-too-distant future. To build a mechanism capable of connecting RFID labels to the Internet. The methods taken by various researchers are investigated and dissected, enabling a better understanding of the difficulties and shortcomings associated with RFID labels connected to the Internet. The analysis and examination have resulted in the creation of another system that allows use of TCP/IP. The structure established in this paper is predicated on the capability of RFID labels to be used as procedures (TCP forms) within a host. As a result, each procedure has a procedure ID or port number, which enables various members to identify and communicate with the tag through the process ID. This is accomplished through a built-in interpretation portion that converts the RFID tag’s authentic personality (ID) to a new ID that can be recognized as a TCP port number. The results of this paper show that the system worked effectively for the purpose for which it was designed. The results show that the actualized system enables RFID labels to be linked to the Internet and to be exceptionally distinct. Additionally, it enables labels to send and receive information and guidance outside of the RFID system, through the Internet, and from various members. The framework’s success would provide several experts with opportunities to actualize the concept of “Internet of Things.” DOI link: Advanced Smart Algorithm for Integrating RFID and – IoT Security

The next-generation communication system incorporates information technology (IT) and operations technology (OT) for generating, delivering, and collecting, and obtaining communication power. We plan to include a brief outline of internet of thing (IoT) communication and its context, along with security concerns that arise for IoT data on the network and some methods for detecting and avoiding cyber security threats. With the rise of the 5G networks, we introduce the smart network’s emergent technology and its opportunities and more cybersecurity issues. Whereas, finding or responding to a power outage is an essential part of system security That is why we will discuss the innumerable advantages of 5G networks and we must also cover the inevitable problems that we will encounter in power delivery. The use of smart IoT communication technologies is becoming more common in the energy sector, particularly with the network (5G. The smart network and energy flow integration Real-time data on generation, electricity distribution, and energy consumption is measured using computers and cutting-edge technologies. This information aids utility companies in managing electricity supply and demand, as well as price. While enhanced communication and information technologies are unquestionably crucial to the smart network DOL link : Open network structure and smart network to sharing cybersecurity within the 5G network