A Decentralised Scheduling Tool For An Efficient Information Packet Distribution

Time is an expensive resource and it is an asset to those who respect and use it efficiently. As regards information delivery services, there have been so much delay and loss of information packets in the process of delivery. In this study, we demonstrate the effect of a scheduling algorithm on the speed and reliability of information delivery.Anew decentralized scheduling algorithm and mail delivery and an example of manual mail delivery samples is presented to prove the effect of a proposed scheduling tool on information packets distribution. We useda set of mail information from a private mail bag as locations against some resource agents used in delivering the mail and we applied the algorithm on these locations to see its effects on the time of delivery. The time spam was studied from applying the algorithm and from manually sorting them. The comparism showed differences in the time duration. The research demonstrates the influence of scheduling algorithm on the delivery of mails.We concluded that handling mail procedures using a decentralized scheduling algorithm would have great effects on information management and transfer. These effects should be considered in setting up any information services especially, one with many users. Key words:information delivery, mail, scheduling packets, algorithm data sorting

Applying Data Mining Research Methodologies on Information Systems

In this paper we considered several frameworks for data mining. These frameworks are based on different approaches, including inductive databases approach, the reductionist statistical approaches, data compression approach, constructive induction approach and some others. We considered advantages and limitations of these frameworks. We presented the view on data mining research as continuous and never- ending development process of an adaptive DM system towards the efficient utilization of available DM techniques for solving a current problem impacted by the dynamically changing environment. We discussed one of the traditional information systems frameworks and, drawing the analogy to this framework, we considered a data mining system as the special kind of adaptive information system. We adapted the information systems development framework for the context of data-mining systems development

Use cases in software development: an investigation in its roles and values

This research work identifies the roles and values of USE CASES in software development, and analysed the concept of USE CASES critically in other to ascertain their usefulness in achieving a user’s requirement when applied to a system development methodology. We examined the major considerations for deploying advanced UML modelling by considering the best approach for a programmer to get to the source code by putting the right aspect of the UML to work at the right stage of a system life cycle in an object (OO) oriented analysis and design practice. research has found out that to achieve a successful object oriented programming design and implementation, an analyst should strive to drive an OO software design from USE CASE

Securing an Information Systems from Threats: A Critical Review

The technology behind information systems in today’s world has been embedded in nearly every aspect of our lives. Thus, the idea of securing our information systems and/or computer networks has become very paramount. Owing to the significance of computer networks in transporting the information and knowledge generated by the increased diversity and sophistication of computational machinery, it would be very imperative to engage the services of network security professionals to manage the resources that are passed through the various terminals (end points) of the these network, so as to achieve a maximum reliability of the information passed, making sure that this is achieved without creating a discrepancy between the security and usability of such network. This paper examines the various techniques involved in securely maintaining the safe states of an active computer network, its resources and the information it carries. We examined techniques of compromising an information system by breaking into the system without authorised access (Hacking), we also looked at the various phases of digital analysis of an already compromised system, and then we investigated the tools and techniques for digitally analysing a compromised system in other to bring it back to a safe stat

Large spatial datasets: Present Challenges, future opportunities

The key advantages of a well-designed multidimensional database is its ability to allow as many users as possible across an organisation to simultaneously gain access and view of the same data. Large spatial datasets evolve from scientific activities (from recent days) that tends to generate large databases which always come in a scale nearing terabyte of data size and in most cases are multidimensional. In this paper, we look at the issues pertaining to large spatial datasets; its feature (for example views), architecture, access methods and most importantly design technologies. We also looked at some ways of possibly improving the performance of some of the existing algorithms for managing large spatial datasets. The study reveals that the major challenges militating against effective management of large spatial datasets is storage utilization and computational complexity (both of which are characterised by the size of spatial big data which now tends to exceeds the capacity of commonly used spatial computing systems owing to their volume, variety and velocity). These problems fortunately can be combated by employing functional programming method or parallelization techniques

An Effective Approach to Predicting Large Dataset in Spatial Data Mining Area

Due to enormous quantities of spatial satellite images, telecommunication images, health related tools etc., it is often impractical for users to have detailed and thorough examination of spatial data (S). Large dataset is very common and pervasive in a number of application areas. Discovering or predicting patterns from these datasets is very vital. This research focused on developing new methods, models and techniques for accomplishing advanced spatial data mining (ASDM) tasks. The algorithms were designed to challenge state-of-the-art data technologies and they are tested with randomly generated and actual real-world data. Two main approaches were adopted to achieve the objectives (1) identifying the actual data types (DTs), data structures and spatial content of a given dataset (to make our model versatile and robust) and (2) integrating these data types into an appropriate database management system (DBMS) framework, for easy management and manipulation. These two approaches helped to discover the general and varying types of patterns that exist within any given dataset non-spatial, spatial or even temporal (because spatial data are always influenced by temporal agents) datasets. An iterative method was adopted for system development methodology in this study. The method was adopted as a strategy to combat the irregularity that often exists within spatial datasets. In the course of this study, some of the challenges we encountered which also doubled as current challenges facing spatial data mining includes: (a) time complexity in availing useful data for analysis, (b) time complexity in loading data to storage and (c) difficulties in discovering spatial, non-spatial and temporal correlations between different data objects. However, despite the above challenges, there are some opportunities that spatial data can benefit from including: Cloud computing, Spark technology, Parallelisation, and Bulk-loading methods. Techniques and application areas of spatial data mining (SDM) were identified and their strength and limitations were equally documented. Finally, new methods and algorithms for mining very large data of spatial/non-spatial bias were created. The proposed models/systems are documented in the sections as follows: (a) Development of a new technique for parallel indexing of large dataset (PaX-DBSCAN), (b) Development of new techniques for clustering (X-DBSCAN) in a learning process, (c) Development of a new technique for detecting human skin in an image, (d) Development of a new technique for finding face in an image, (e) Development of a novel technique for management of large spatial and non-spatial datasets (aX-tree). The most prominent among our methods is the new structure used in (c) above -- packed maintained k-dimensional tree (Pmkd-tree), for fast spatial indexing and querying. The structure is a combination system that combines all the proposed algorithms to produce one solid, standard, useful and quality system. The intention of the new final algorithm (system) is to combine the entire initial proposed algorithms to come up with one strong generic effective tool for predicting large dataset SDM area, which it is capable of finding patterns that exist among spatial or non-spatial objects in a DBMS. In addition to Pmkd-tree, we also implemented a novel spatial structure, packed quad-tree (Pquad-Tree), to balance and speed up the performance of the regular quad-tree. Our systems so far have shown a manifestation of efficiency in terms of performance, storage and speed. The final Systems (Pmkd-tree and Pquad-Tree) are generic systems that are flexible, robust, light and stable. They are explicit spatial models for analysing any given problem and for predicting objects as spatially distributed events, using basic SDM algorithms. They can be applied to pattern matching, image processing, computer vision, bioinformatics, information retrieval, machine learning (classification and clustering) and many other computational tasks

Short-Run and Long-Run Effects of Non-Oil Trade Export on Economic Growth in Nigeria

This study examined the short and long run effects of non-oil trade export on economic growth in Nigeria. Descriptive statistics and inferential statistics (unit root test, Johansen cointegration and error correction mechanism) were employed as the estimation techniques. The time series data on non-oil export (proxied by non-oil total trade, balance of trade, exchange rate and inflation rate); and economic growth (proxied by growth rate of Real Gross Domestic Product) were sourced and obtained from the Central Bank of Nigeria Statistical Bulletin and Nigerian Bureau of Statistics over a period of thirty (33) years (1986–2018). The study showed that non-oil total trade, balance of trade and exchange rate have positive and significant effects on economic growth in Nigeria while inflation rate has no significant effect on economic growth in Nigeria. Based on the finding of the study, it was concluded that non-oil trade export has positive and significant effects in the short run and long run on economic growth in Nigeria. It is recommended that full attention should be directed to the non-oil sector in other to make our produce competitive in international market

UNIVERSITY STUDENTS UTILIZATION OF ACADEMIC LIBRARY: A CASE STUDY OF JOSEPH AYO BABALOLA UNIVERSITY IKEJI-ARAKEJI, OSUN STATE NIGERIA

This study examines the utilization of the university library collections and services among students of Joseph Ayo Babalola University, Ikeji- Arakeji, Nigeria. The specific objectives of the study are to find out among the students the frequency of the use of the library collections and services, the purposes of using library collections and services, find out the availability and adequacy of the library collections and services, know the methods of accessing the library collections, determine the students’ level of satisfaction with the library collections and services, unveil the problems confronted in the use of the library collections and services and suggest means of solving the problems to improve the overall library efficiency . The study adopted the use of social survey research method. The main instruments for gathering data for the study are questionnaire and the Students’ Attendance Register at the Porters’ Lodge in the Library. The researchers also conducted personal observations to complement and support the information provided by the students. The findings showed that students use the library mostly during examination and a general poor patronage of the library, adequate book and journal collections, inadequate government publications, rudimentary method of accessing the library collections and a general satisfaction of the library services. The problems confronting use of the library were identified as lack of awareness of library resources, inadequate provision of photocopying services, deficient manual catalogue and inaccessible Online Public Access Catalogue (OPAC), Suggestions were recommended for the improvement of library services

An approach for Mining Complex Spatial Dataset

Spatial data mining organizes by location what is interesting as such, specific features of spatial data mining (including observations that are not independent and spatial autocorrelation among the features) that preclude the use of general purpose data mining algorithms poses a serious challenge in the task of mining meaningful patterns from spatial systems. This creates the complexity that characterises complex spatial systems. Thus, the major challenge for a spatial data miner in trying to build a general complex spatial model would be; to be able to integrate the elements of these complex systems in a way that is optimally effective in any particular case. We have examined ways of creating explicit spatial model that represents an application of mining techniques capable of analysing data from a complex spatial system and then producing information that would be useful in various disciplines where spatial data form the basis of general interest