Bolanle Oladejo

Résumé: This dispensation is an era of knowledge explosion and its exploitation in any organization or institution is inevitably required if there would be attainment of progress in the competitive environment to which it belongs to. It is imperative to establish a system of ...

<b>By using this dataset you agree to cite:</b><b><br></b> Manescu, P., Shaw, M.J., Elmi, M., Neary‐Zajiczek, L., Claveau, R., Pawar, V., Kokkinos, I., Oyinloye, G., Bendkowski, C., Oladejo, O.A., Oladejo, B.F., Clark, T., Timm, D., Shawe‐Taylor, J., Srinivasan, M.A., Lagunju, I., Sodeinde, O., Brown, B.J. and Fernandez‐Reyes, D. (2020), <b>Expert‐Level Automated Malaria Diagnosis on Routine Blood Films with Deep Neural Networks</b>. Am J Hematol. Accepted Author Manuscript. doi:10.1002/ajh.25827<br><b>Dataset Licence:</b> CC BY-NC-SA 4.0<br>----------------------------------------------------------------------------------<br><b>Context: </b>Thick Blood Films (TBF) remains the gold standard for diagnosing malaria in sub-Saharan regions. TBF relies on the availability of a trained human microscopist to visually inspect Giemsa stained blood smears under a light microscope to identify and count the <i>P. falciparum</i> parasites. This is time-consuming and subject to human error. A wrong diagnosis of malaria can have negative consequences for patients and for anti-malarial therapy resources. Over-treatment, in the long run, leads to parasite resistance.<br>----------------------------------------------------------------------------------<br><b>Dataset Image acquisition: </b>Image fields from Giemsa stained thick blood smears were captured using a upright brightfield microscope (Olympus BX63) fitted with a 100X/1.4NA objective lens, a motorised stage (Prior Scientific) and a colour camera (Edge 5.5c, PCO). Each image field covers an area of 166 μm x 142 μm (2560x2160 pixels). A z-stack comprising 14 focal planes with a separation of 0.5 μm was captured at each position with a camera exposure time of 50 ms. The z-stacks were projected onto a single plane using a wavelet-based extended depth of field algorithm.<br>----------------------------------------------------------------------------------<br><b>FILE: </b><b>FASTMAL_THICK_FILMS.zip</b>Contains<b> o</b>bject-level annotations. The uncompressed folder contains a nu [...]

Knowledge representation, knowledge management, economic intelligence, temporal properties, temporal reasoning, knowledge exploitation Mots clefs: Représentation de connaissances, gestion de connaissance, intelligence économique, raisonnement temporal, exploitation de connaissance, propriété temporal Palabras clave: Representación de conocimiento, administración del conocimiento, inteligencia colectiva, características temporales, razonamiento temporal, explotación del conocimiento People have to make important decisions within a time frame. Hence, it is imperative to employ means or strategy to aid effective decision making. Consequently, Economic Intelligence (EI) has emerged as a field to aid strategic and timely decision making in an organization. In the course of attaining this goal: it is indispensable to be more optimistic towards provision for conservation of intellectual resource invested into the process of decision making. This intellectual resource is nothing else but th...

The increase in the population of students in the higher institute of learning and crave for literacy has brought about the expansion of academic activities in our Universities. This has caused clashes in the use of limited available resources of each institution. In the past, ways have been sought to consider how the resources could be maximized, but to no avail. Sequel to this, this work aimed at developing an automated timetabling system which solved the problem faced in examinations scheduling. The optimization technique used was Genetic Algorithm (GA) for the scheduling. Automated exam invigilation timetabling system was developed and tested. A Faculty of Science in a reputable institution of learning in Nigeria was selected as a case study. The use of GA was suitable for solving problem(s) such as, under-utilization of available resources, clashes in scheduled courses ’ examination, faced by timetable scheduler, due to its optimization approach. GA is efficient for maximizing ...

The knowledge of what career to specialize in could be a late discovery for adults who have traded their youthful years through several professions/vocations but found no fulfillment. On the other hand, it could be a strenuous exercise for children and youths who are exposed to different academic areas. The aim of this project is to develop a career-advisor expert system based on Myer-Briggs Personality Assessment. It advises the user based on his/her personality. This is achieved through the method of creating facts from the Myers-Briggs Type Indicator (MBTI) thereby mapping them to common Careers using a rule-based system based on the sixteen Personality Types (according to Myers-Briggs). All these facts and rules form the database whereas ―Prolog‖ which stands for ―Programming in Logic‖ is the tool used for the implementation. The results of the query determine whether an advisee should choose a particular career or not. It displays ―true‖ if he/she could choose the predetermined...

Software projects failure has been a reoccurring problem in software development domain. The advent of applying engineering principles to software development initiated the need to produce software products systematically to solve the problems of poor software quality, late deliveries, and cost overruns. Requirement engineering is the first phase in software development process and the major output of this phase is the Software requirements document. This document usually written in natural language contains both functional and non-functional system requirements. However, due to the informal nature of natural language, it is prone to a lot of errors, which if not detected early enough has an adverse effect on the success of the software project. Hence, this work aimed at the development of an NLP based model for quality assurance of Software requirements. Using two major techniques which are Natural Language Processing and information extraction techniques, the developed NLP model w...

There is a paradigm shift from the era of information overload to knowledge economy era. Knowledge is an invaluable but intangible asset in knowledge-driven economy for gaining competitive edge and organizational productivity. By and large, Knowledge Management (KM) is increasingly prominent and applicable to virtually every organization due to the promise of cost-effective retention and transfer of human and socio-cultural knowledge. The law firm, being a knowledge – intensive domain is not an exception of thriving organization positively influenced by KM for effective and efficient management of human resources as well as legal issues. Amongst diverse specialties in legal profession is Intellectual Property (IP) Rights management. However, oftentimes, the law firm stakeholders experience difficulty in accessing relevant information and/or knowledge related to the IP rights of their clients. Moreover, when information is even accessed, comprehending its vast content and context has...

Computer vision (CV) -based techniques are being deployed to solve the problem of Crack Detection in metallic and concrete surfaces. This is because the Human-oriented inspections being used have drawbacks in the area of cost and manpower. One of the deployed CV techniques is the Deep Convolutional Neural Network (DCNN). Existing DCNN based crack detection models have a challenge of performing poorly when tested on images taken at a different location from the training images, hence crack localization is required. Thus, this research develops a location invariant crack detection and localization (LICDAL) model in unconstrained oil pipeline images using DCNN. LICDAL is developed by applying transfer learning on the Faster Region based CNN (Faster R-CNN). The model is made location invariant by gathering images of cracked oil pipeline from various locations. The collected images are split into a 70%:30% ratio for training and testing set. LICDAL is evaluated using the mean Average Pre...

Knowledge representation is an essential criterion to capitalization of knowledge in organizations. There is need for organizations to employ strategic methods to ensure optimal innovation and effective decision making. Thus, Economic Intelligence proffers strategy to ...

Plant disease detection and classification have undergone successful researches using Convolutional Neural Network (CNN); however, due to the intrinsic inability of max pooling layer in CNN, it fails to capture the pose, view and orientation of images. It also requires large training data and fails to learn the spatial relationship of the features in an object. Thus, Capsule Network (CapsNet) is a novel deep learning model proposed to overcome the shortcomings of CNN. We developed an optimized Capsule Network model for classification problem using banana leaf diseases as a case study. The two dataset classes include Bacterial Wilt and Black Sigatoka, with healthy leaves. The developed model adequately classified the banana bacterial wilt, black sigatoka and healthy leaves with a test accuracy of 95%. Its outper-formed three variants of CNN architectures implemented (a trained CNN model from scratch, LeNet5 and ResNet50) with respect to rotation invariance.

The shift from industrial economy to knowledge economy in today's world has revolutionalized strategic planning in organizations as well as their problem solving approaches. The point of focus today is knowledge and service production with more emphasis been laid on knowledge capital. Many organizations are investing on tools that facilitate knowledge sharing among their employees and they are as well promoting and encouraging collaboration among their staff in order to build the organization's knowledge capital with the ultimate goal of creating a lasting competitive advantage for their organizations. One of the current leading approaches used for solving organization's decision problem is the Economic Intelligence (EI) approach which involves interactions among various actors called EI actors. These actors collaborate to ensure the overall success of the decision problem solving process. In the course of the collaboration, the actors express knowledge which could be capitalized for future reuse. In this paper, we propose in the first place, an annotation model for knowledge elicitation among EI actors. Because of the need to build a knowledge capital, we also propose a dynamic knowledge capitalisation approach for managing knowledge produced by the actors. Finally, the need to manage the interactions and the interdependencies among collaborating EI actors, led to our third proposition which constitute an awareness mechanism for group work management.

Abstract: People have to make important decisions within a time frame. Hence, it is imperative to employ means or strategy to aid effective decision making. Consequently, Economic Intelligence (EI) has emerged as a field to aid strategic and timely decision ...

Abstract: Knowledge is attributed to human whose problem-solving behavior is subjective and complex. In today's knowledge economy, the need to manage knowledge produced by a community of actors cannot be overemphasized. This is due to the fact that actors ...