Solitary colonic neurofibroma in an African child

Neurofibromas are a group of heterogeneous neurocutaneous disorders. They are benign neoplasms consisting of neural and connective tissue components affecting any organ system. Gastrointestinal involvement in neurofibromatosis type 1 (NF1) are rare and are late manifestations of the disease, but in exceptional cases they can be the initial sign of neurofibromatosis in patients who have no external stigmata that arouse suspicion. Neurofibromatosis of the colon as a part of the NF1 is rare. Isolated colonic neurofibromatosis without other features suggestive of NF1 is rarely encountered in clinical practice. We report the case of a 12-year-old boy with an isolated colonic neurofibromatosis presenting with a right hypochondrial mass with no external features of NF1. We report this case as its presentation in children may give a diagnostic dilemma and the probability of malignant digestive disease associated with NF1 should be kept in mind, regardless of the age of the patient.Keywords: children, colonic, neurofibroma, rare, solitar

Template Matching Based Sign Language Recognition System for Android Devices

An android based sign language recognition system for selected English vocabularies was developed with the explicit objective to examine the specific characteristics that are responsible for gestures recognition. Also, a recognition model for the process was designed, implemented, and evaluated on 230 samples of hand gestures.  The collected samples were pre-processed and rescaled from 3024 ×4032 pixels to 245 ×350 pixels. The samples were examined for the specific characteristics using Oriented FAST and Rotated BRIEF, and the Principal Component Analysis used for feature extraction. The model was implemented in Android Studio using the template matching algorithm as its classifier. The performance of the system was evaluated using precision, recall, and accuracy as metrics. It was observed that the system obtained an average classification rate of 87%, an average precision value of 88% and 91% for the average recall rate on the test data of hand gestures.  The study, therefore, has successfully classified hand gestures for selected English vocabularies. The developed system will enhance the communication skills between hearing and hearing-impaired people, and also aid their teaching and learning processes. Future work include exploring state-of-the-art machining learning techniques such Generative Adversarial Networks (GANs) for large dataset to improve the accuracy of results. Keywords— Feature extraction; Gestures Recognition; Sign Language; Vocabulary, Android device

Measurement of penile size in healthy Nigerian newborns using conventional penile length measurement technique

Objectives We attempted to establish a standard penile length for male newborn Nigerians using the conventional penile length measurement technique.Summary Defining the normal penile size in the neonate is paramount to making accurate diagnosis of abnormalities of the penis and the medical and surgical management of these anomalies.Patients and methods We carried out a prospective cross-sectional study of all term male neonates within 72 h of birth from April 2013 to March 2014 in the three largest obstetric centres (University College Hospital, Adeoyo Maternity Hospital and Our Lady of Apostles Catholic Hospital) in Ibadan, Nigeria. They underwent clinical examination, and their penile sizes were measured using the conventional penile length measurement technique.Results A total of 675 male Nigerian newborns were studied. The mean penile length was 3.14 ±0.65 cm, and the mean penile width was 0.97± 0.15 cm.Conclusion The penile dimensions obtained are comparable with reported values in previous studies in other parts of the world

DESIGN AND SIMULATION OF AN EFFICIENT MODEL FOR CREDIT CARDS FRAUD DETECTION

In this study a model which can improve the accuracy and reliability of credit card fraud detection was proposed. This is with a few to mitigating contentious issues regarding online transaction of credit card, such as  amount of transactions that have resulted in payment default and the number of credit card fraud cases that have been recorded, all of which have put the economy in jeopardy.   To address this challenge,sample dataset was sourced from online repository database of Kaggle. The feature extraction on the data was performed using Principal Component Analysis (PCA). The credit card fraud detection model was designed using Neuro-fuzzy logic technique, clustering was done using Hierarchical Density Based Spatial Clustering of Application with Noise (HDBSCAN) .The simulation of the proposed model was done in Python programming environment.The performance evaluation of the model was carried out by comparing the proposed model with Neuro-Fuzzy (NF) technique using performance metrics such as precision, recall, F1-score and accuracy.  The simulation result showed that the proposed model (NF + HDBSCAN) had precision of 98.75%, recall of 98.70%, F1-Score of 97.65% and accuracy 99.75% . NF had Precision of 94.60%, recall of 94.50%, F1-Score of 95.50% and accuracy 95.70% using training dataset. Likewise, when test dataset were used, the proposed (NF + HDBSCAN) had precision of 93.50%, recall of 95.50%, F1-Score of 94.50% and accuracy 95.50%. NF had Precision of 92.50%, recall of 93.00%, F1-Score of 94.00% and accuracy 93.50%.  The simulation results of the proposed model was viable, reliable and showed possibility of being designed as module which could be  integrated into the existing credit card design for lowering fraud rate and assisting fraud investigators

PERFORMANCE EVALUATION OF TROPICAL BIOFUELLED FISH SMOKING STRUCTURES

Environmental and hygienic concerns associated with traditional fish smoking structures restrict the sale and consumption of smoked products to local markets. This study evaluated the performance of three(improved kiln oven (IKO), mud-type ovens (MTO) and extended drum ovens (EDO)) locally available Biofuelledfish smoking structures and proposed modifications to improve product quality.Three groups of prepared freshwater catfish (Clarias gariepinus) with average live weights of 1.93 kg±46 g, 1.92 kg±50 g and 1.86 kg±50 g was used as test samples. Smoking profiles, final moisture content (FMC), smoking time, smoking temperatures, percentage weight loss (WL) and organoleptic evaluation (ORE) were the performance indicators used during evaluatio

The role of fluoride on eruption of mandibular molar of albino rats

Eruption of the tooth is a complex and highly regulated process which can be influenced by genetic, environmental and systemic factors. Fluoride is found naturally in water as well as in foods and dental products. The first mandibular molar is the first molar to erupt and it is essential for  mastication of food. We studied the effect of fluoride on the eruption of the first mandibular molar in albino rats. Fluoride at different  concentrations was added to the water of pregnant albino rats while sterile water without fluoride was given to the control pregnant dams. The pregnant dams were allowed to deliver, and the heads of their pups carefully decapitated, and mandibles dissected out on days 10, 12, 15 and 18 for assessment of eruption pattern of the first molar while also measuring the mandibular length and breadth. The mandibles were then processed for hematoxylin and eosin staining. On gross examination, some of the teeth developed intraosseously while others were located mucosally, pre-occlusally or occlusally. There was significant reduction in both the birth weight and mandibular length as the fluoride concentration increased compared to the control but a significant increment in the mandibular breadth between the experimental groups in comparison with the control group on day 15 (p value <0.05). These findings suggest that high concentrations of fluoride could delay mandibular molars’ eruption and also cause low birth weight. Key Words: fluoride, mandibular molar, tooth eruptio

Assessment of Ecological Status and Tree Diversity in Watershed Area of Dandi Local Government Area in Kebbi State, Nigeria

This study assessed the ecological and tree diversity status of watershed area of Dandi local government area in Kebbi state using systematic sampling technique. Three transects of 300 m long were laid at 100 m intervals. On each transect, six sample plots of size 50 m x 50 m (0.25ha) were alternately laid at 50 m intervals. A total of 18 sample plots will be used for the study. Diameters at breast height (Dbh) of all the trees found in the plot with Dbh ≥ 5cm will be measured. Fourteen tree species belonging to 10 genera and 8 families were identified. Borassus aethiopum of the family Arecaceae was the most abundant species in the area with a relative density (RD) and diversity index (DI) of 0.296 and 0.08728 respectively. This was followed by Cocos nucifera in the Arecaceae family also, with RD and DI of 0.192 and 0.03662 respectively. Daniella oliveri of the family Fabaceae was the least represented species with RD and DI of 0.0018 and 0.00002 respectively. The overall tree species richness in the area was 0.0052

Evaluation of MgO-ZnO-Crab Shell Biofillers as Reinforcement for Biodegradable Polylactic Acid (PLA) Composite

Biodegradable polyester obtained from renewable, eco-friendly materials, and natural additives made from debris of production of seafood to create biocomposites is nowadays a possibility. This paper evaluates the physical, morphological, and chemical properties and the degradation stability of polylactic acid/biofillers (magnesium oxide/zinc oxide/crab shell particles) composite as a viable biocomposite material in bone engineering applications. The biofiller showed hygroscopic characteristics. Surface morphology of the composite showed fractured surfaces with interconnected pores suitable for bone cells’ implantation enhancement and propagation. Biofillers effect accelerates the precipitation of calcium apatite formation after 28 days of immersion. The XRD spectra confirmed high composite crystallinity structure of 93.4% due to the nucleation effects of the biofillers. The beneficial role of reinforcing polylactic acid polymer with biofiller showed average pH value of 7.36 and apparent porosity of 40%. Findings from this paper have revealed that the use of crab shell debris such as crab shell can become a resource in biocomposite fabrication. The addition of biofillers provided an effective reinforcement in polylactic acid polymer matrix and hence contributed towards sustainable developments of natural resource materials and biodegradable and bioresorbable material without polluting the environment

DEVELOPMENT OF AN IMPROVED DATABASE FOR YORUBA HANDWRITTEN CHARACTER

For improved human comprehension and autonomous machine perception, optical character recognition has been saddled with the task of translating printed or hand-written materials into digital text files. Many works have been proposed and implemented in the computerization of different human languages in the global community, but microscopic attempts have also been made to place Yoruba Handwritten Character on the board of Optical Character Recognition. This study developed a novel available dataset for research on offline Yoruba handwritten character recognition so as to fill the gaps in the existing knowledge. The developed database contains a total of 12,600 characters being made up of 70 classes from a total number of 200 writers, in which 80 % (10,500) is regarded as the training and validation dataset while the remaining 20 % (2,100) is regarded as testing dataset. The dataset is available on https://github.com/oluwashina90/Yoruba-handwritten-character-database. Hence, it is the complete and largest dataset available for Yoruba Handwritten character research

A REAL TIME FACE RECOGNITION SYSTEM USING ALEXNET DEEP CONVOLUTIONAL NETWORK TRANSFER LEARNING MODEL

. In the field of deep learning, facial recognition belongs to the computer vision category. In various applications such as access control system, security, attendance management etc., it has been widely used for authentication and identification purposes. In deep learning, transfer learning is a method of using a neural network model that is first trained on a problem similar to the problem that is being solved. The most commonly used face recognition methods are mainly based on template matching, geometric features based, algebraic and deep learning method. The advantage of template matching is that it is easy to implement, and the disadvantage is that it is difficult to deal with the pose and scale changes effectively. The most important issue, regardless of the method used in the face recognition system, is dimensionality and computational complexity, especially when operating on large databases. In this paper, we applied a transfer learning model based on AlexNet Deep convolutional network to develop a real time face recognition system that has a good robustness to face pose and illumination, reduce dimensionality, complexity and improved recognition accuracy. The system has a recognition accuracy of 98.95 %