Asian Journal of Research in Computer Science

This paper essentially addresses the importance and contribution of digitalization in the creation and implementation of public policies, thus analyzing the activity of the Municipal Administration in Gjilan, Vitia, and Kamenica, the principles on which it relies and administrative bodies as an important part of administration. First, the importance of Public Administration and its principles is presented, then Municipal Administration and Ethics in Municipal Administration. It then analyzes E-Government and E-Kiosk as an important structure of the administration and the role it has given so far in administrative reform as one of the advantages for the integration of Municipal Administrations, strong management and use of information technology for a smooth-running of work quickly and accurately, especially in protecting the health of citizens from the Covid-19 Pandemic. To achieve the purpose of this paper, the method of surveying citizens directly through questionnaires was used. The questions are mostly qualitative and they are closed-type, open-type, but there are also Liker type. The questionnaire was used to survey 60 participants from the Municipality of Gjilan, 50 participants from the Municipality of Vitia and 50 participants from the Municipality of Kamenica. After completing the questionnaire, it was concluded that the digitalization of the Municipal Administration requires well-trained staff and continuous   maintenance of information systems. E-Government should be the main goal in the reform of the municipal administration, which will promote radical changes such as: a   new way of management, discussions and communication, more efficient and faster   decision-making, access for all to services, elimination of corruption and administrative  silence. It is a driving force for the reorganization and renewal of administration services. It also protects the health of citizens from contagious diseases, especially during the Covid-19 Pandemic.

Swarm based optimization algorithms are a collection of intelligent techniques in the field of Artificial Intelligence (AI) were developed for simulating the intelligent behavior of animals. Over the years ago, problems complexity increased in a means that it is very difficult for basic mathematical approaches to obtain an optimum solution in an optimal time, this leads the researchers to develop various algorithms base on the natural behaviors of living beings for solving problems. This paper present a review for Cat Swarm Optimization (CSO), which is a powerful metaheuristic swarm-based optimization algorithm inspired by behaviors of cats in the Nature for solving optimization problems. Since its first appearances in 2006, CSO has been improved and applied in different fields by many researchers. In this review, we majorly focus on the original CSO algorithm and some improved branches of CSO family algorithms. Some examples of utilizing CSO to solve problems in engineering are also reviewed.

Vehicular communications, referring to information exchange among vehicles, and infrastructures. It has attracted a lot of attentions recently due to its great potential to support intelligent transportation, various safety applications, and on-road infotainment. The aim of technologies such as Vehicle-to-Vehicl (V2V) and Vehicle to-Every-thibg (V2X) Vehicle-to very-thing is to include models of connectivity that can be used in various application contexts by vehicles. However, the routing reliability of these ever-changing networks needs to be paid special attention. The link reliability is defined as the probability that a direct communication link between two vehicles will stay continuously available over a specified period. Furthermore, the link reliability value is accurately calculated using the location, direction and velocity information of vehicles along the road.

A brain tumor is a problem that threatens life and impedes the normal working of the human body. The brain tumor needs to be identified early for the proper diagnosis and effective treatment planning. Tumor segmentation from an MRI brain image is one of the most focused areas of the medical community, provided that MRI is non-invasive imaging. Brain tumor segmentation involves distinguishing abnormal brain tissue from normal brain tissue. This paper presents a systematic literature review of brain tumor segmentation strategies and the classification of abnormalities and normality in MRI images based on various deep learning techniques, interbreeding. It requires presentation and quantitative analysis, from standard segmentation and classification methods to the best class strategies.

Brain-Computer Interfaces (BCI) are systems that can translate the brain activity patterns of a user into messages or commands for an interactive application. The brain activity which is processed by the BCI systems is usually measured using Electroencephalography (EEG). The BCI system uses oscillatory Electroencephalography (EEG) signals, recorded using specific mental activity, as input and provides a control option by its output. A brain-computer interface uses electrophysiological signals to control the remote devices. They consist of electrodes applied to the scalp of an individual or worn in an electrode cap. The computer processes the EEG signals and uses it in order to accomplish tasks such as communication and environmental control.