A DESIGN OF AN OBJECT-ORIENTED DATABASE FOR EFFECTIVE DATA MINING

This paper focuses on the design of an object-oriented database (OODB), through incorporation of object-oriented programming (OOP) concepts into existing relational databases. The proposed approach makes use of the OOP concepts namely, inheritance, encapsulation and polymorphism to design an OODB and perform classification in it respectively. Usually, database is a collection of tables with common fields. In this study, those common fields are grouped together to form a single generalized table. The newly created table resembles the base class in the inheritance hierarchy. Polymorphism allows different classes to have methods of the same name and structure, performing different operations based on the calling object. The polymorphism is specifically employed to achieve classification in a simple and effective manner while Encapsulation ensures the hiding of the data and behavior of an object behind a limited and well-described interface. In Java terms, the limited and well-described interface is the set of public methods and attributes. The use of these object oriented concepts for the design of OODB ensures that even complex queries can be answered more efficiently. Particularly, data mining task and classification can be achieved in an effective manner.Â

SIMULATED ANNEALING FOR SOLVING THE TRAVELLING SALESMAN PROBLEM

In this paper we considered the use of Simulated Annealing for solving the Travelling Salesman Problem (TSP) which is NP-Complete. The algorithm searches solutions for the global minimum by perturbing existing solutions and replace if the new solution is better than the existing solution. The annealing process is controlled by some algorithmic parameters and thus the solution relies on the parameters set. Different parameters were used to know the best set of parameters. Generally the algorithm was tested and proved to be a good solver of TSP

HIERARCHICAL CLASSIFICATION OF MORPHOLOGICAL FEATURES OF TILAPIA CABREA

This article proposes an effective data visualization of multidimensional data. These displays are useful to represent the existence or absence of relationships among objects corresponding to hierarchical classifications, bifurcation or evolutionary structure. The display in this article used some morphological features of Tilapia Cabrea, as represented in the dendrogram or cluster tree which illustrates the successive fusions of objects into groups or divisions made at each successive stage of the analysis. Effectively, this clustering reduces the dimensionality and makes interpretations easier.Â

COMPARISON OF SELECTED IMAGE PROCESSING TECHNIQUES

Image as an important artifact faced with several constraints that may inhibit its usefulness. These constraints includes noise, Identification of objects in the image and extraction of features. In this paper, the denoising methods of Two Stages Image Denoising By Principal Component Analysis With Local Pixel Grouping(PCA - LPG) and Non Linear Filtering Algorithm For Underwater Images, the object identification methods of SCALE-INVARIANT FEATURE TRANSFORM (SIFT) and SPEEDED UP ROBUST FEATURES (SURF), the feature extraction methods of thresholding and subtraction and template matching are compared experimentally. The experimental evaluation of these algorithms made it possible to draw some conclusions. These conclusions are supported from the results of the implementations of each technique, hence the recommended technique for denoising is Local Pixel Grouping (PCA - LPG), the recommended technique for object identification is SPEEDED UP ROBUST FEATURES (SURF) and the recommended technique for feature extraction is tresholding and subtraction. The recommended techniques for each of the concept were implemented in C# programming language with the help of an open source computer vision library EmguCV

Pattern of rural-urban acquisition of pfcrt T76 allele among Nigerian children with acute uncomplicated Plasmodium falciparum malaria

Malaria caused by Plasmodium falciparum remains a public health problem in Nigerian children with treatment complicated by expansion of chloroquine resistant strains known to harbour a common K76T point mutation in their pfcrt alleles. Here, we report the outcome of a 2 – year (March 2000 – February 2002) molecular surveillance for pfcrtT76 in children aged 6 months – 13 years with acute uncomplicated falciparum malaria in rural and urban Lagos, Nigeria. Rural-urban pfcrtT76 acquisition of 48.7 vs. 73.7% and 67.3 vs. 74.6% due to monoclonal and polyclonal P. falciparum parasitaemia, respectively, were found in the two study years, suggesting unstable but increasing prevalence of pfcrt T76 allele acquisition in the rural area. Further analyses showed that acquisition of pfcrtT76 allele was independent of sex but occurred more in ≤ 5 – year old children than older children in both populations. The impacts of K76T mutation in pfcrt gene and immunity on the clinical efficacy of chloroquine against acute uncomplicated malaria are discussed.African Journal of Biotechnology Vol. 4 (4), pp. 361-366, 200

FORECASTING DISTRIBUTED DENIAL OF SERVICE ATTACK USING HIDDEN MARKOV MODEL

Distributed denial of service (DDoS) attack bombards the network with loads of packets and requests that consumes the system resources in terms of time, memory, and processors. This paper presents a proposed method for forecasting DDoS in networks. The proposed model employs hidden Markov model (HMM) to forecast DDoS attacks. The method uses the inherent characteristic features of DDoS to determine the observable states of the system.To avoid intractable computations, Kullback-Leibler divergence algorithm was employed to reduce the number of observable states to three. The proposed model is formulated and trained through experiments using DARPA 2000 data set and the preliminary resultsshows that the characteristic features of the DDoS and the entropy concept can be used to formulate an HMM to predict DDoS

FORECASTING DISTRIBUTED DENIAL OF SERVICE ATTACK USING HIDDEN MARKOV MODEL

Distributed denial of service (DDoS) attack bombards the network with loads of packets and requests that consumes the system resources in terms of time, memory, and processors. This paper presents a proposed method for forecasting DDoS in networks. The proposed model employs hidden Markov model (HMM) to forecast DDoS attacks. The method uses the inherent characteristic features of DDoS to determine the observable states of the system.  To avoid intractable computations, Kullback-Leibler divergence algorithm was employed to reduce the number of observable states to three. The proposed model is formulated and trained through experiments using DARPA 2000 data set and the preliminary results shows that the characteristic features of the DDoS and the entropy concept can be used to formulate an HMM to predict DDoS

Seminar Users in the Arabic Twitter Sphere

We introduce the notion of "seminar users", who are social media users engaged in propaganda in support of a political entity. We develop a framework that can identify such users with 84.4% precision and 76.1% recall. While our dataset is from the Arab region, omitting language-specific features has only a minor impact on classification performance, and thus, our approach could work for detecting seminar users in other parts of the world and in other languages. We further explored a controversial political topic to observe the prevalence and potential potency of such users. In our case study, we found that 25% of the users engaged in the topic are in fact seminar users and their tweets make nearly a third of the on-topic tweets. Moreover, they are often successful in affecting mainstream discourse with coordinated hashtag campaigns.Comment: to appear in SocInfo 201

Recurrence of cervical intraepithelial lesions after thermo-coagulation in HIV-positive and HIV-negative Nigerian women

Background: The burden of cervical cancer remains huge globally, more so in sub-Saharan Africa. Effectiveness of screening, rates of recurrence following treatment and factors driving these in Africans have not been sufficiently studied. The purpose of this study therefore was to investigate factors associated with recurrence of cervical intraepithelial lesions following thermo-coagulation in HIV-positive and HIV-negative Nigerian women using Visual Inspection with Acetic Acid (VIA) or Lugol’s Iodine (VILI) for diagnosis. Methods: A retrospective cohort study was conducted, recruiting participants from the cervical cancer “see and treat” program of IHVN. Data from 6 sites collected over a 4-year period was used. Inclusion criteria were: age ≥18 years, baseline HIV status known, VIA or VILI positive and thermo-coagulation done. Logistic regression was performed to examine the proportion of women with recurrence and to examine factors associated with recurrence. Results: Out of 177 women included in study, 67.8 % (120/177) were HIV-positive and 32.2 % (57/177) were HIV-negative. Recurrence occurred in 16.4 % (29/177) of participants; this was 18.3 % (22/120) in HIV-positive women compared to 12.3 % (7/57) in HIV-negative women but this difference was not statistically significant (p-value 0.31). Women aged ≥30 years were much less likely to develop recurrence, adjusted OR = 0.34 (95 % CI = 0.13, 0.92). Among HIV-positive women, CD4 count <200cells/mm3 was associated with recurrence, adjusted OR = 5.47 (95 % CI = 1.24, 24.18). Conclusion: Recurrence of VIA or VILI positive lesions after thermo-coagulation occurs in a significant proportion of women. HIV-positive women with low CD4 counts are at increased risk of recurrent lesions and may be related to immunosuppression

Community perception of school-based mass drug administration program for soil-transmitted helminths and Schistosomiasis in Ogun State, Nigeria

BACKGROUND: Neglected tropical diseases, such as soil-transmitted helminths and Schistosomiasis, are prevalent in sub-Saharan Africa, particularly Ogun State, Nigeria. School-based mass drug administration program is the primary control intervention, but the coverage and uptake of this intervention have been inadequate. This study aimed to investigate community perceptions of school-based mass drug administration programs for these infections in Ogun State, Nigeria, and identify the barriers to their uptake and coverage. METHODOLOGY/PRINCIPAL FINDINGS: The study used a qualitative research approach involving focus group discussions and in-depth interviews with community members and stakeholders engaged in neglected tropical disease control programs in Ogun State, Nigeria. A semi-structured questionnaire guided the exploration of ideas, and the data were analyzed using the QRS Nvivo 12 software package. The study found several barriers, such as the influence of parents, lack of sufficient knowledge, and side effects. The study recommended strategies such as improving community sensitization and engagement, drug distribution and performance, and enhancing partner collaboration and coordination to improve the school-based mass drug administration programs. CONCLUSIONS/SIGNIFICANCE: The study revealed correct perceptions of transmission but some misconceptions about disease causation, transmission, and drug safety. Participants expressed a desire for better sensitization campaigns and more assurances of their safety. The study recommends strengthening health education messages and increasing the visibility of on-site medical personnel. The findings have implications for improving the performance of these programs and reducing the burden of intestinal parasitic infections in the community. The study highlights the need for community engagement and education, health system support, and partner collaboration to successfully implement mass drug administration programs