Now showing 1 - 5 of 378
- ItemOpen AccessEnhancing Knowledge Organization Through Implicit Collaboration in Crowdsourcing Process(Nomos Verlagsgesellschaft mbH & Co. KG, 2021) Odumuyiwa, V.; Zaid, Y.A; Barber, O.This paper presents our approach in removing noisy labels from crowdsourced data and enhancing understanding and communication through crowdsourcing process aimed at creating metadata for describing digitalized artworks of a University Library Museum. A responsive Web application was created for the crowdsourcing activity and made open to the University community for interested individuals to participate in annotating the images. The collected annotation in form of tags were preprocessed and filtered to generate a subset of tags by removing duplicates and also eliminating some noisy labels using majority voting. The resulting subset was used as labels for the images for a second round of crowdsourcing process where users chose from the filtered labels. Comparing the output of the second round with the label (tags) from an expert shows a high level of similarity between the selected tags and the expert generated tags.
- ItemOpen AccessAbout Crawling Scheduling Problems.(CEUR Workshop Proceedings, 2017-09) Pechnikov, A.A; Chernobrovkin, D.I; Nwohiri, A.MThis paper investigates the task of scheduling jobs across several servers in a software system similar to the Enterprise Desktop Grid. One of the features of this system is that it has a specific area of action –collects outbound hyperlinks for a given set of websites. The target set is scanned continuously (and regularly) at certain time intervals. Data obtained from previous scans are used to construct the next scanning task for the purpose of enhancing efficiency (shortening the scanning time in this case). A mathematical model for minimizing the scanning time for a batch mode is constructed; an approximate algorithm for the solution of the model is proposed. A series of experiments are carried out in a real software system. The results obtained from the experiments enabled to compare the proposed batch mode with the known round robin mode. This revealed the advantagesand disadvantages of the batch mode
- ItemOpen AccessInfluence of Personality Traits on Posttraumatic Growth: a Study of Adult Outpatient Clinic, Igbobi Orthopaedics Hospital Lagos, Nigeria(2018) Akinwale, G.A; Akinsola, E.F; Muhammad-Bashir, AFull papers attached
- ItemOpen AccessDo Upbringing and Formal Education Influence Ethical Decision Making? A Study of Professional Accountants in Nigeria(2018-08-16) Oboh, C.SThis paper examined the influence of upbringing and education on specific processes, named ethical recognition, ethical judgment, and ethical intention, involved in the ethical decision making of professional accountants in Nigeria. Primary data were obtained from 329 professional accountants with the aid of a structured questionnaire containing four different vignettes of ethical dilemmas. The results of Kendall's tau-b correlation analysis and Kruskal-Wallis and Jonckheere-Terpstra tests showed that strictness of upbringing and level of education significantly influenced the ethical decision-making process of professional accountants. The paper concluded that upbringing and education are significant determinants of ethical recognition and ethical intention and not ethical judgment. Therefore, stricter upbringing and higher level of education may aid ethical decision making in dilemmatic situations at the workplace. Future theorising and empirical study in ethical decision-making should consider the roles of upbringing and education.
- ItemOpen AccessA Salient Invariant Feature Descriptor for Human Action Recognition(2018) Omisore, A.M; Abebe, Y.A; Isnkaye, F.O; Ojokoh, B.A; Azeez, N.A; Wang, LThe dramatic progress of studies in human action recognition has being attributed to challenges inherent with conventional methods such as bag-of-words based description. As a result, researchers in the field of computer vision are still making efforts towards achieving structured interpretation of complex activities between multiple objects. This study proposes Pyramid of Histogram Oriented Gradients (PHOG) computed from Depth Motion Maps in a video stream as a new feature descriptor for recognition of human activities. The proposed method has two steps which includes construction of depth motion maps from frames in sequence of a given video, and representation of images in each frame using PHOG. The latter step reflects local shapes and spatial layouts of images in three views of the depth maps. 1_2- regularized Collaborative Representation Classifier was adopted for classification of human activities in the processed depth images. Performance of the proposed invariant method was evaluated by using the MSR Action3D dataset, and compared ~ith that of conventional methods. Our result shows that our novel invariant feature descriptor improves the average rate of activity recognition with up to 12.52%with respect to conventional methods.