Asian Journal of Research in Computer Science

A data center is a physical facility that organizations use to house their critical applications and data. An application delivery controller, router, switch, firewall, storage system, and server make up the design for the data center. Data security in the data center is critical due to these components' role in storing and managing critical business data and applications. An Android application has therefore been developed that can be used on smart phones to monitor and follow the performance of the data center camera monitoring system. Surveillance cameras in the data center allows the data center manager to monitor employees, machines, and all data center facilities from his office via his mobile phone, or even when he is out of the office, and to view a report of faults and maintenance to ensure the efficiency of the system. Using the application, the engineer can also control the cameras by panning and zooming in on the camera images in the data center, playback previous recordings of cameras, and review fault reports to find out the malfunctions of the monitoring system from anywhere with an Internet connection.

The structure, variety and quantity of some current web content are limited in efficient exploration due to difficulty in searching and locating a specific content.  A case is the Niger Delta University where there is no unified online structure holding relevant university data. This is because there is no common data model to manage the data for which such query can easily be interpreted semantically. Therefore, this paper presents the application of semantic web technology for the unification of university data management. This research prepares the ground for the advent of software agents and other applications that require structured data for their computational processes. The ontology development follows an iterative path of the Object-Oriented System Analysis and Design (OOSAD) methodology. SPARQL was used as the query language for testing the ontology. The result is a semantically structured data that is deployable and can be expanded and adapted in other institutions.

A classroom routine is nothing more than a well-practiced respond to a teacher's instruction. Most universities handle this allocation process with a manual procedure. The manual procedure gives various challenges and is inclined to mistakes. A better approach to reliably schedule class routine is to utilize a computer assisted web-based system. Therefore, in this work, focus is given on creating automatic class routines with teacher’s requirements. This work mainly consists of two parts, named Admin panel and User panel. In admin panel, we get some information like courses information, teacher’s information, room’s information etc. We can Update, Delete & Add this information. A class routine is then created based on these fields. In user panel, we get all of information about courses, associated teacher and rooms. In this panel we can see all this information & routine. Routine can be constructed by days, teacher’s and semester wise. We create this application by utilizing genetic algorithm, and implemented by using Python language. Exam Hall Invigilation is another aspect which still most universities handle manually. Therefore, an automatic Exam Hall Invigilation Management System is also developed in this work. We propose an improved algorithm to achieve automatic examination arrangement for invigilator based on greedy method. The system can configure to allocate any numbers of invigilators in different examination halls in such a way that each invigilator will get equal number of duties. This algorithm has written and implemented in Java-script language.

A spell checker is a tool that finds and corrects erroneous words and grammatical mistakes in a text document. Spelling error detection and correction techniques are widely used by text editing systems, search engines, text to speech and speech to text conversion systems, machine translation systems and optical character recognition systems. The spell checkers for European languages and some Indic languages are well developed. However, perhaps, owing to Tamil being a morphologically rich and agglutinative language this has been a challenging task. Erroneous words and grammatical mistakes can occur in sentences due to various reasons. Erroneous words can be classified into two categories, namely non-word errors and real-word errors. This work aims to correct non-word errors in Tamil documents by suggesting alternatives. The proposed approach uses letter-level and word-level n-gram, stemming and hash table techniques. Test results show that the suggestions generated by the system are with 95% accuracy.

An artificial neural network (ANN) is an information processing system established by simulating the structure and logical thinking of the human brain. It uses the interconnection between a large number of neurons to form a network system that can perform complex calculations, and is widely used. For various complex problems, by choosing different model structures and transfer functions, various neural networks can be formed and different expressions of the relationship between output and input can be obtained. Face recognition is one of the important research directions of ANN. It mainly refers to the automatic inference of identity, expression, age, gender and other attribute information through the analysis of facial images, videos or pictures and video collections of people. Widely used in mobile payment, safe city, criminal investigation and other fields. The origin, types and research progress of ANN are introduced, and the face recognition technology based on neural network are investigated.