EVALUATING INTERNET PROTOCOL VERSION 6 (IPv6) AGAINST VERSION 4 (IPv4)

This paper evaluates the performance of IPv6 against IPv4. IPv4 has address space shortages. The use of Classless Inter-Domain Routing (CIDR) and Network Address Translation (NAT) helped to address these shortages. However, Featuresbuilt into IPv6 such as autoconfiguration, IPSec, Mobility, Multiple addresses for hosts and networks, Multicastcommunication make it well worth the cost, time and effort required to migrate to it. Performance metrics used in order toanalyze the protocols are network delay, network drop, and throughput. Results showed that IPv6 is not better in terms ofpacket management than IPv4. The results also showed that IPv6 has higher delay, and packet drop than IPv4; though themargin between the values are however small. It was also found that IPv6 has a higher throughput. It is hereby concluded,that even though IPv4 is performing better, it will not solve the address limitation problem. This has made it inevitable torecommend IPv6 as a replacement for the IPv4.Keywords: Latency, Throughput, PacketDrop, NAT, Mobility, Autoconfiguration

MIGRATING BUSINESS SERVICES AND APPLICATIONS INTO THE CLOUD

Cloud computing has attracted a lot of hyperbole since it became a trendy topic for IT managers to talk about. Companiesfrequently trumpet their cloud enabled services but rarely give up details on precisely how they achieved this or how muchof their infrastructure has been fully migrated. Security and reliability of cloud services are often raised as concerns. Byunderstanding the basics of cloud computing and knowing how to assess important factors such as security and theidentification of systems that are suitable for migration, it becomes much easier to design and implement a cloud strategy.This paper provides the essential facts about the cloud computing, list some factors to prepare for when adopting cloudcomputing, consideration for managers migrating their services and applications into the cloud. It also discussed the meritsof going into the cloud.Keywords: Cloud Computing, Public Cloud, Service as a Service, Application Migration, Decision Makin

An Improved Technique for Multi-Dimensional Constrained Gradient Mining

Multi-dimensional Constrained Gradient Mining, which is an aspect of data mining, is based on mining constrained frequent gradient pattern pairs with significant difference in their measures in transactional database. Top-k Fp-growth with Gradient Pruning and Top-k Fp-growth with No Gradient Pruning were the two algorithms used for Multi-dimensional Constrained Gradient Mining in previous studies. However, these algorithms have their shortcomings. The first requires construction of Fp-tree before searching through the database and the second algorithm requires searching of database twice in finding frequent pattern pairs. These cause the problems of using large amount of time and memory space, which retrogressively make mining of database cumbersome.  Based on this anomaly, a new algorithm that combines Top-k Fp-growth with Gradient pruning and Top-k Fp-growth with No Gradient pruning is designed to eliminate these drawbacks. The new algorithm called Top-K Fp-growth with support Gradient pruning (SUPGRAP) employs the method of scanning the database once, by searching for the node and all the descendant of the node of every task at each level. The idea is to form projected Multidimensional Database and then find the Multidimensional patterns within the projected databases. The evaluation of the new algorithm shows significant improvement in terms of time and space required over the existing algorithms.  &nbsp

A Review of Voice-Base Person Identification: State-of-the-Art

Automated person identification and authentication systems are useful for national security, integrity of electoral processes, prevention of cybercrimes and many access control applications. This is a critical component of information and communication technology which is central to national development. The use of biometrics systems in identification is fast replacing traditional methods such as use of names, personal identification numbers codes, password, etc., since nature bestow individuals with distinct personal imprints and signatures. Different measures have been put in place for person identification, ranging from face, to fingerprint and so on. This paper highlights the key approaches and schemes developed in the last five decades for voice-based person identification systems. Voice-base recognition system has gained interest due to its non-intrusive technique of data acquisition and its increasing method of continually studying and adapting to the person’s changes. Information on the benefits and challenges of various biometric systems are also presented in this paper. The present and prominent voice-based recognition methods are discussed. It was observed that these systems application areas have covered intelligent monitoring, surveillance, population management, election forensics, immigration and border control

FORECAST PERFORMANCE OF UNIVARIATE TIME SERIES AND ARTIFICIAL NEURAL NETWORK MODELS

In this paper, the better model for forecasting Nigeria monthly Precipitation time series data that exhibit seasonal, periodic variations and non-linearity is determined. The models considered are Seasonal Autoregressive Integrated Moving Average (SARIMA), Fourier Autoregressive (FAR) and Artificial Neural Networks (ANN) models. The accuracy of the out-sample forecast of the model considered was measured based on the following forecast evaluations sum of square error (SSE), Mean square error (MSE) and Root mean square error RMSE. From the results, the FAR model forecast was better than that of SARIMA model based on the values of the forecast evaluations when seasonal and period in the series is considered and ANN model forecast was better that both FAR and SARIMA when the non-linear nature of the precipitation is considered. In conclusion, the FAR model is the most appropriate model for forecasting seasonal and periodic variations while the ANN model is the most suitable model for forecasting non-linearity in Nigeria monthly precipitation time series dat

A PREDICTIVE MODEL FOR ESTIMATING PETROLEUM CONSUMPTION USING MACHINE LEARNING APPROACH

This study is focused on predicting the consumption of Petroleum (Thousands of Barrels per year) in Nigeria. Autoregressive integrated moving average (ARIMA), Linear Regression (LR) and Random Forest Regression (RFR) models were fitted to predict the consumption of Petroleum. The prediction accuracy of these models was evaluated using Root Mean Square Error (RMSE), Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE) and Coefficient of determination (R^2 ) metrics. The Petroleum dataset spanned a period of 37 years (1980-2017) and it was spilted into train and test at the ratio of 70:30 respectively to reduce overfitting. The result obtained revealed that the two machine learning models: LR and RFR outperformed the ARIMA model with lower values of prediction accuracy in terms of MAE, MAPE, RMSE and

THE EFFECTS OF PALM OIL ON THE PHYSICAL APPEARANCE OF Clarias gariepinus DURING TRANSPORTATION

ABSTRACT:The study on the rate of water quality deterioration, bacterial load, survival percentage and physical appearance of transported adult Clarias gariepinus was carried out using palm oil as water additive and anti-stress at different concentrations, 904mgL -1 ,1808 mgL -1 and 2712 mgL -1 and compared to salt at 0.4% over a six hour transportation period. The adult fish were transported in a container at 2kg /litre of water in an open van while the water samples were at zero, second, fourth and sixth hours of transportation. Water quality, physical appearance and the survival rate of the fish within the various treatments were assessed at the end of the transportation exercise. The pH of transport water containing oil at 904mgL -1 , 1808mgL -1 and 2712mgL -1 was maintained during the course of transportation in contrast to the treatment containing 0.4% salt and the control whose pH changed at the second hour of transportation but the dissolved oxygen (DO), temperature, ammonium (NH 4 ), Nitrate (NO 3 ), Nitrite (NO 2 ) and chlorine (CI) of all the treatments followed the same trend while the bicarbonate (HCO 3 ) concentration of transport water containing 2712mgL -1 palm oil were maintained till the second hour before it changed at the fourth and sixth hours of transportation. The plate count agar (PCA) of all the treatments containing oil recorded more organisms than the treatment containing 0.4% salt and the control; but, the fish in all the treatments containing palm oil have an appearance not different from when freshly harvested in contrast to the control that had bruises and scars on the skin and the survival percentage of fish in all the treatments was between 95% -100%. It has been revealed that addition of palm oil at the varying concentrations kept the freshness of the fish during transportation thereby improving the market value of transported live catfish

An evaluation of biosecurity compliance levels and assessment of associated risk factors for highly pathogenic avian influenza H5N1 infection of live-bird-markets, Nigeria and Egypt

Live bird market (LBM) is integral component in the perpetuation of HPAI H5N1, while biosecurity is crucial and key to the prevention and control of infectious diseases. Biosecurity compliance level and risk factor assessments in 155LBMs was evaluated in Nigeria and Egypt through the administration of a 68-item biosecurity checklist, scored based on the modifications of previous qualitative data, and analysed for degree of compliance. LBMs were scored as "complied with a biosecurity item" if they had good-very good scores (4). All scores were coded and analysed using descriptive statistics and risk or protective factors were determined using univariable and multivariable logistic regression at p≤0.05. Trading of wild birds and other animal in the LBMs (Odd Ratio (OR)=34.90; p=0.01) and claims of hand disinfection after slaughter (OR=31.16; p=0.03) were significant risk factors while mandatory routine disinfection of markets (OR=0.13; p≤0.00), fencing and gates for live bird market (OR=0.02; p≤0.01) and hand washing after slaughter (OR=0.41; p≤0.05) were protective factors for and against the infection of Nigerian and Egyptian LBMs with the HPAI H5N1 virus. Almost all the LBMs complied poorly with most of the variables in the checklist (p≤0.05), but pathways to improved biosecurity in the LBMs existed. We concluded that the LBM operators play a critical role in the disruption of transmission of H5N1 virus infection through improved biosecurity and participatory epidemiology and multidisciplinary approach is needed.http://www.elsevier.com/locate/actatropica2017-12-31hb2017Veterinary Tropical Disease