KNOWLEDGE SHARING AMONG EMPLOYEES OF PUBLICLY OWNED BOOK PUBLISHING FIRMS IN NIGERIA

Knowledge sharing is crucial to the success of any organization as it is needed for knowledge creation, organizational learning and performance. This is especially the case with book publishing firms where their outputs are repositories of knowledge. However, a lack of technical expertise in the publishing industry has been reported in literature which might not be unconnected with knowledgeable workers in the sector leaving, retiring or passing on with their knowledge. Moreover, little is known about knowledge sharing among employees in this industry. Hence, in order to explore and understand this behaviour, descriptive survey design was adopted to investigate knowledge sharing among employees of publicly owned book publishing firms in Nigeria. Purposive sampling was used in selecting three publicly owned book publishing firms namely, Heinemann Publishers Plc, University Press Plc and Learn Africa Plc. Using both purposive and snowballing sampling techniques, 15 employees were selected from each firm. Data was collected through face-to-face interview, digitally recorded, transcribed and analysed thematically. Employees viewed knowledge sharing as a norm in the publishing industry since the process of book production requires team work; and knowledge sharing with subordinates reduces the burden of work on managers. Majority of the respondents would not share knowledge with colleagues from other publishing firms due to loss of competitive advantage and employee loyalty. Reciprocal benefit was the major motivating factor for knowledge sharing while others included enjoyment in helping others as well as personal and organizational reputation enhancement. Fear of loss of power, perceived pride, and competition were reported as challenges to knowledge sharing. Limiting inter-organizational knowledge sharing can restrict organizational learning and innovation which could have a negative impact on the industry’s performance overtime. Leadership styles that support and encourage knowledge sharing should be promoted in this industry

Cashless Policy and Customers' Satisfaction: A Study of Commercial Banks in Ogun State, Nigeria

The advent of cashless policy into the Nigerian banking sector has brought mixed feelings to all stakeholders in the sector.  The development has brought relief to a segment dominated by the operators (bankers), while the other segment dominated by the customers has complained about the challenges associated with the operation of the policy.  Therefore, this study seeks to investigate the customers’ satisfaction of the recently introduced cashless policy in Ogun State, Nigeria with a survey of bank customers in Abeokuta.  Data was collected with a well structural questionnaire and analyzed with descriptive statistics, while hypotheses formulated for the study were tested with correlation co-efficient.The findings of the study reveal that cashless policy contributed significantly to customers’ satisfaction in Ogun State. Also, the study revealed that cashless policy contributed significantly to customers’ satisfaction through electronic channels.Finally, the study concluded that the cashless policy is customer friendly and progressive. Hence, it was therefore recommended, among others, that infrastructures should be improved upon to ensure easy operation of the policy in Ogun state. Keywords: Cashless policy, Customers’ satisfaction, Nigerian banking sector, Customers’ orientation and Banking performanc

Pattern Recognition Neural Network and Class of Grades

We investigated the ability of neural network to recognise pattern by using pattern recognition neural network tool box to predict the class of Science laboratory technology students in Federal polytechnic Ilaro.  A total final results of 431 students of the department between 2005 and 2010 was used. The data contained results of ten courses offered by the students together with their GPA and the grade of each student. The marks scored by 420 students in each course together with the grade obtained in each course were used for training, testing and validation of the neural network. 11 student’s data were used for prediction purpose. We used a two-layer feed-forward network, with sigmoid hidden and output neurons (newpr), which can classify vectors arbitrarily well, given enough neurons in its hidden layer. The network was trained with scaled conjugate gradient backpropagation (trainscg). The marks scored by 294(70%) students in each course together with the grade obtained in each course were used for training, 63(15%) for testing and 63(15%) for validation of the neural network. The Grade were classified into five categories: Probation, Pass, lower credit, Upper credit and Distinction. We predict the type of grade based on scores of the students in each course. The training, validation and test were performed with different neuron numbers in the hidden layer i.e 20,15, 10 and 5 neurons. The results showed that among the ANN models, ANN 20 performed best with MSE= 1.511623803293947e-07 and Confusion= 0.061224489795918 followed by ANN 5 with MSE=1.804838395630207e-07 and Confusion= 0.052721088435374. Our research showed clearly that Neural network pattern recognition tools can predict student grade perfectly well if given enough data to train. Keywords: Pattern recognition, training, validation, neuron, confusion matri

Least square multi-class kernel machines with prior knowledge and applications.

In this study, the problem of discriminating between objects of two or more classes with (or without) prior knowledge is investigated. We present how a two-class discrimination model with or without prior knowledge can be extended to the case of multi-categorical discrimination with or without prior knowledge. The prior knowledge of interest is in the form of multiple polyhedral sets belonging to one or more categories, classes, or labels, and it is introduced as additional constraints into a classification model formulation. The solution of the knowledge-based support vector machine (KBSVM) model for two-class discrimination is characterized by a linear programming (LP) problem, and this is due to the specific norm (L1 or Linfinity) that is used to compute the distance between the two classes. We propose solutions to classification problems expressed as a single unconstrained optimization problem with (or without) prior knowledge via a regularized least square cost function in order to obtain a linear system of equations in input space and/or dual space induced by a kernel function that can be solved using matrix methods or iterative methods. Advantages of this formulation include the explicit expressions for the classification weights of the classifier(s); its ability to incorporate and handle prior knowledge directly to the classifiers; its ability to incorporate several classes in a single formulation and provide fast solutions to the optimal classification weights for multicategorical separation.Comparisons with other learning techniques such as the least square SVM & MSVM developed by Suykens & Vandewalle (1999b & 1999c), and the knowledge-based SVM developed by Fung et al. (2002) indicate that the regularized least square methods are more efficient in terms of misclassification testing error and computational time

Analysis of Elevation Models for Nigerian 2D Cadastre Height Determination

In Nigeria, the spatial requirements of cadastral map for the purposes of land registration are based on 2D planimetric boundary coordinates without consideration for the elevation component of geometric space. Whereas, recent development in technology and practises in many countries requires the inclusion of elevation component into the cadastre. The specific objectives of this study are to determine elevation values for existing 2D cadastre of the study area from different data sources and to analyze those elevation values using statistical means. Data were sourced from both primary and secondary sources; secondary data include a 30m by 30m resolution Global Digital Elevation Model (GDEM), Shuttle Radar Topographic Mission Data (SRTM), 1:50,000 topographic map and existing Digital Elevation Model (DEM) of the study area. Ten ground control points were established at 250m grid with Global Positioning System in differential mode and elevation data were obtained accordingly. Elevation values of selected existing planimetric controls (33) were also determined from adopted data sources and were compared using both the standard deviation and the Root Mean Square Error (RMSE). The vertical accuracy obtained from Topographic map data, existing DTM,  ASTER data and SRTM data were ± 1.860, ± 3.450, ± 5.309 and ±4.573 respectively relative to elevation values obtained from GPS observation of corresponding selected existing 2D planimetric controls. The degree of association between elevation values obtained from adopted data sources was strong and positive as shown from the regression analysis. The study established that only topographic map elevation data would presently fit GPS elevation data for 3D cadastre implementation for the study

Public Service Reforms and the Nigerian Telecommunications (NITEL) PLC

Due to fiscal maladministration in the public sector and consequent inefficiency of public corporations, the Nigerian government has opted for laissez faire reforms in the public sector. One of the public corporations the government has put up for sale is Nigerian Telecommunications (NITEL) PLC. This paper examines the privatization process of NITEL and consequent impact on NITEL employees

Relationship between personality traits and reproductive choices among women attending the psychiatric clinic of a Nigerian Teaching Hospital

Background: The study aimed to assess the relationship between personality traits and reproductive choices among women attending the psychiatric clinic at a Nigerian Teaching Hospital.Methods: The original study used a quasi-experimental pre-test post-test-controlled design though this article presents a cross sectional view of results. Two hundred females were recruited into the study. An interviewer-administered questionnaire was applied to the respondents which elicited information on background characteristics, baseline contraceptive indicators and personality traits. Data were analyzed using both descriptive and inferential methods.Results: The personality factors found to affect contraceptive use included high scores on Conscientiousness, Extraversion and Neuroticism, though only extraversion maintained this relationship on regression analysis. The personality factors found to affect pregnancy plan included high scores on Conscientiousness.Conclusions: This study showed a distinct relationship between specific personality traits and contraceptive use with neuroticism exhibiting a negative influence on use while conscientiousness exhibited a positive influence

Novel <i>IRF6 </i>mutations in families with Van Der Woude syndrome and popliteal pterygium syndrome from sub-Saharan Africa

Orofacial clefts (OFC) are complex genetic traits that are often classified as syndromic or nonsyndromic clefts. Currently, there are over 500 types of syndromic clefts in the Online Mendelian Inheritance in Man (OMIM) database, of which Van der Woude syndrome (VWS) is one of the most common (accounting for 2% of all OFC). Popliteal pterygium syndrome (PPS) is considered to be a more severe form of VWS. Mutations in the IRF6 gene have been reported worldwide to cause VWS and PPS. Here, we report studies of families with VWS and PPS in sub-Saharan Africa. We screened the DNA of eight families with VWS and one family with PPS from Nigeria and Ethiopia by Sanger sequencing of the most commonly affected exons in IRF6 (exons 3, 4, 7, and 9). For the VWS families, we found a novel nonsense variant in exon 4 (p.Lys66X), a novel splice-site variant in exon 4 (p.Pro126Pro), a novel missense variant in exon 4 (p.Phe230Leu), a previously reported splice-site variant in exon 7 that changes the acceptor splice site, and a known missense variant in exon 7 (p.Leu251Pro). A previously known missense variant was found in exon 4 (p.Arg84His) in the PPS family. All the mutations segregate in the families. Our data confirm the presence of IRF6-related VWS and PPS in sub-Saharan Africa and highlights the importance of screening for novel mutations in known genes when studying diverse global populations. This is important for counseling and prenatal diagnosis for high-risk families