Lung cancer is one of the most serious and prevalent diseases, causing many deaths each year. Though CT scan images are mostly used in the diagnosis of cancer, the assessment of scans is an error-prone and time-consuming task. Machine learning and AI-based models can identify and classify types of lung cancer quite accurately, which helps in the early-stage detection of lung cancer that can increase the survival rate. In this paper, Convolutional Neural Network is used to classify Adenocarcinoma, squamous cell carcinoma and normal case CT scan images from the Chest CT Scan Images Dataset using different combinations of hidden layers and parameters in CNN models. The proposed model was trained on 1000 CT Scan Images of cancerous and non-c

The interaction in the city is reflected in the movement of people motivated by their activities and their economic and social goals, which include many variables subject to the planning process in the interpretation of this movement and the mapping of trends of transport intensity through the concept of transport function and its functional relationships with the uses of the earth in the sustainability and effectiveness of the movement of transport and Economic activity and population movement. Transport planners are concerned with the requirements of land use, which are linked to and included in the transport planning process as a factor for the future transport needs. There is a strong relationship between the transport system

Research on the automated extraction of essential data from an electrocardiography (ECG) recording has been a significant topic for a long time. The main focus of digital processing processes is to measure fiducial points that determine the beginning and end of the P, QRS, and T waves based on their waveform properties. The presence of unavoidable noise during ECG data collection and inherent physiological differences among individuals make it challenging to accurately identify these reference points, resulting in suboptimal performance. This is done through several primary stages that rely on the idea of preliminary processing of the ECG electrical signal through a set of steps (preparing raw data and converting them into files tha

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The development of microcontroller is used in monitoring and data acquisition recently. This development has born various architectures for spreading and interfacing the microcontroller in network environment. Some of existing architecture suffers from redundant in resources, extra processing, high cost and delay in response. This paper presents flexible concise architecture for building distributed microcontroller networked system. The system consists of only one server, works through the internet, and a set of microcontrollers distributed in different sites. Each microcontroller is connected through the Ethernet to the internet. In this system the client requesting data from certain side is accomplished through just one server that is in

In today's world, most business, regardless of size, believe that access to Internet is imperative if they are going to complete effectively. Yet connecting a private computer (or a network) to the Internet can expose critical or confidential data to malicious attack from anywhere in the world since unprotected connections to the Internet (or any network topology) leaves the user computer vulnerable to hacker attacks and other Internet threats. Therefore, to provide high degree of protection to the network and network's user, Firewall need to be used.

Firewall provides a barrier between the user computer and the Internet (i.e. it prevents unauthor

In this paper, a Modified Weighted Low Energy Adaptive Clustering Hierarchy (MW-LEACH) protocol is implemented to improve the Quality of Service (QoS) in Wireless Sensor Network (WSN) with mobile sink node. The Quality of Service is measured in terms of Throughput Ratio (TR), Packet Loss Ratio (PLR) and Energy Consumption (EC). The protocol is implemented based on Python simulation. Simulation Results showed that the proposed protocol provides better Quality of Service in comparison with Weighted Low Energy Cluster Hierarchy (W-LEACH) protocol by 63%.