Willingness to Share and Use Tacit Knowledge among Employees in Team-Based Organisations: Are the Dimensions of Interpersonal Trust Facilitators?

While the body of empirical literature on the correlates of general knowledge sharing behaviour is growing, literature that focuses on the predictor of willingness to share and use tacit knowledge is scarce. Moreover, in the few studies that consider tacit knowledge sharing, their focus tends to be on employees in non-profit organisations with little focus on those in profit oriented organisations. This study therefore investigated whether affect-based and cognitive-based trusts will predict willingness to share and use tacit knowledge among employees in team-based organisations in Nigeria. Data were collected from a sample of 487 team-based workers in Lagos, Nigeria. They responded to Affect-based and Cognition-based trusts Scales and Willingness to Share Tacit Knowledge and Use tacit knowledge Questionnaires. Hierarchical multiple regression analyses were used to test the hypotheses generated. The results revealed that team members’ willingness to share tacit knowledge was facilitated by affect-based and cognitive-based trusts. However, affect-based and cognitive-based trusts were not strong factors determining employees’ willingness to use tacit knowledge in team-based industries. Implications of the study were highlighted. Keywords: tacit knowledge exchange, trust, team-based organisations, Nigeri

Do Personal Resources Make a Difference in the Relation between Work-family Conflict and Burnout among Working Mothers?

Drawing on the conservation of resources theory, the present study addressed a vacuum in work-family conflict (WFC) literature by examining the moderating roles of personal resources (emotional intelligence and resilience) in the relationship between WFC (work interference with family─ WIF and family interference with work─ FIW) and burnout among working mothers. Data were collected from a sample of 615 working mothers in some Nigerian banks, and were analyzed with moderated hierarchical regression analysis. Results showed that high WIF and FIW were positively associated with overall burnout and its dimensions. Emotional intelligence and resilience acted as buffer in the relations of WIF and FIW with overall burnout and its dimensions. Specifically, the negative impacts of WIF and FIW on overall burnout and its dimensions were weaker for working mothers with higher emotional intelligence and resilience. These findings suggest that organisation can reduce or prevent the negative impact of WFC on burnout among working mothers by strengthening their personal or adaptive resources

TOWARDS EFFECTIVE PLANNING, DESIGN AND MONITORING OF DAMS IN NIGERIA

Besides serving as a center of tourist attraction, creating jobs for the unemployed, a rich source of fish and a fallback in times of drought, a dam also creates electricity from nothing other than the falling of water through its turbines. In Nigeria, like in many other parts of the world, dam projects are often seen as key to economic solution through hydroelectric power supply. The technology of dam construction in Nigeria is still experimental. There are so many unknown factors in dam design, construction and operation that may affect dam’s safety and performance. Relying on field experience from various parts of Nigeria, this paper examines the essential details necessary for consideration in dam planning and design using the complete and accurate information on the important variables such as technical, environmental, socio-cultural, economic or cultural factors. The results of these examined factors indicated that most of dam projects in Nigeria are not properly planned. The basic planning flaws include hydrologic, environmental and social factors which are seen by dam builders as obstacles to be ignored, covered up or surrogated to engineering in the project planning. Incorrect calculation of flood flows has lead to dam failures and reservoir siltation has drastically reduced the lifespan of dams, making one to conclude that the entire concept of dam safety as a design criterion is a new one. It appears that Nigeria will have to live with these flaws and some of these cost for sometimes to come. There is, therefore, the need for us to reduce these through proper planning, design and monitoring of our dams. It is recommended that a comprehensive dam safety study of all old dams (i.e. ≥ 20 years) be carried out. &nbsp

Comparative Analysis of Selected Heterogeneous Classifiers for Software Defects Prediction Using Filter-Based Feature Selection Methods

Classification techniques is a popular approach to predict software defects and it involves categorizing modules, which is represented by a set of metrics or code attributes into fault prone (FP) and non-fault prone (NFP) by means of a classification model. Nevertheless, there is existence of low quality, unreliable, redundant and noisy data which negatively affect the process of observing knowledge and useful pattern. Therefore, researchers need to retrieve relevant data from huge records using feature selection methods. Feature selection is the process of identifying the most relevant attributes and removing the redundant and irrelevant attributes. In this study, the researchers investigated the effect of filter feature selection on classification techniques in software defects prediction. Ten publicly available datasets of NASA and Metric Data Program software repository were used. The topmost discriminatory attributes of the dataset were evaluated using Principal Component Analysis (PCA), CFS and FilterSubsetEval. The datasets were classified by the selected classifiers which were carefully selected based on heterogeneity. Naïve Bayes was selected from Bayes category Classifier, KNN was selected from Instance Based Learner category, J48 Decision Tree from Trees Function classifier and Multilayer perceptron was selected from the neural network classifiers. The experimental results revealed that the application of feature selection to datasets before classification in software defects prediction is better and should be encouraged and Multilayer perceptron with FilterSubsetEval had the best accuracy. It can be concluded that feature selection methods are capable of improving the performance of learning algorithms in software defects prediction

Determinants of malnutrition of under-five children among rural households in the southwest, Nigeria

Malnutrition has been attributed to many deaths among under-five children in most of the developing countries including Nigeria. Understanding the determinants of malnutrition can provide insights in designing interventions for reducing the high rates of child malnutrition. This study focused on what determines the malnutrition of under-five children among rural households in the southwest, Nigeria. A multistage sampling technique was employed to select 395 households that had 487 under-five children. Data were collected on child’s, mother’s, household’s and community characteristics using a pre-tested structured questionnaire. Information on the child’s nutrition status was obtained using Mid Upper Arm Circumference (MUAC) tape. The data were analyzed using descriptive statistics and logit model with STATA 14 statistical package. The results revealed that the average age of under-five children was about 25 months and over 50% of them are girls with a malnutrition rate of 44.0%. The child’s sex, the child’s birth interval, cultivated farm size, mother’s education, water source, and distance to nearest health center significantly determined the child’s malnutrition in rural areas of southwest Nigeria. Given the findings of this research, it is suggested that; mothers should be advised to use contraceptives for child spacing; farmers should be enlightened on the need to implement modern farming practices that lead to optimum yield per land cultivated rather than increasing the size of cultivated farmland; there should be an improvement on women’s education as well as a potable water source; and health care facilities close to respondents’ residence should be provided

Bacteriological pollution indicators in Ogun River flowing through Abeokuta Metropolis

Water resources are significant part of integrated community development policy and good health. Hence, the need to reduce the impact of natural and anthropogenic pollution causes so as to enhance water quality. The bacteriological quality of the Ogun River was investigated to determine the sanitary conditions of the water body between March and August, 2014. Total heterotrophic bacteria counts (THBC), total coliform counts (TCC) and total Escherichia coli counts (TEC) using standard plate count and Most Probable Number (MPN) techniques were determined. The isolates were identified using 16SrRNA gene. Total heterotrophic bacteria counts varied between 1.13 × 106 and 4.1 × 107 CFU/ml, TCC ranged between 2.5 × 105 and 2.33× 107 CFU/ml and TEC was between 5 × 104 and 1.3 × 106 CFU/ml. Most Probable Number of coliforms in all samples varied between 120 and 1600 MPN/100 ml. Isolated microorganisms include Escherichia coli strain SUS9EC, Escherichia coli O157:H7 strain SSI7, Escherichia coli strain BW25113, Escherichia coli strain C-X1B, and Klebsiella oxytoca strain KU-5. One-wayanalysis of variance showed significant difference within the samples at (P<0.05).The results revealed high bacteria counts which is higher than the recommended value of 1.2 × 102 for THBC, a zero E. coli count and not more than 10 coliforms per 100 ml by World Health Organization standards for drinking water.Keywords: Water, bacteria, Escherichia coli, pollutio

OPTIMAL ROUTE DETERMINATION FOR POSTAL DELIVERY USING ANT COLONY OPTIMIZATION ALGORITHM

There are a lot of optimization challenges in the world, as we all know. The vehicle routing problem is one of the more complex and high-level problems. Vehicle Routing Problem is a real-life problem in the Postal Delivery System logistics and, if not properly attended to, can lead to wastage of resources that could have been directed towards other things. Several studies have been carried out to tackle this problem using different techniques and algorithms. This study used the Ant Colony Optimization Algorithm along with some powerful APIs to find an optimal route for the delivery of posts to customers in a Postal Delivering System. When Ant Colony Optimization Algorithm is used to solve the vehicle routing problem in transportation systems, each Ant's journey is mere “part” of a feasible solution. To put it in another way, numerous ants' pathways might make up a viable solution. Routes are determined for a delivery vehicle, with the objective of minimizing customer waiting time and operation cost. Experimental results indicate that the solution is optimal and more accurat

STRUCTURAL CHARACTERISTICS OF BATCH PROCESSED AGRO-WASTE FIBRES

The characterisation of agro-wastes fibres from Nigeria using X-ray diffraction (XRD) and Scanning Electron Microscopy (SEM) has been done. Fibres extracted from groundnut shell, coconut husk, rice husk, palm fruit bunch and palm fruit stalk are processed using two novel cellulose fibre production methods developed by the authors. Cellulose apparent crystallinity calculated using the deconvolution of the diffractometer trace shows that the amorphous portion of cellulose was permeable to hydrolysis yielding high crystallinity after treatment. All diffratograms show typical cellulose structure with well-defined 110, 200 and 040 peaks. Palm fruit fibres had the highest 200 crystalline cellulose peaks compared to others and it is an indication of rich cellulose content. Surface examination of the resulting fibres using SEM indicates the presence of regular cellulose network structure with some agglomerated laminated layer of thin leaves of cellulose microfibrils. The surfaces were relatively smooth indicating the removal of hemicellulose, lignin and pectin

A HYBRIDIZED ENCRYPTION SCHEME BASED ON ELLIPTIC CURVE CRYPTOGRAPHY FOR SECURING DATA IN SMART HEALTHCARE

Recent developments in smart healthcare have brought us a great deal of convenience. Connecting common objects to the Internet is made possible by the Internet of Things (IoT). These connected gadgets have sensors and actuators for data collection and transfer. However, if users' private health information is compromised or exposed, it will seriously harm their privacy and may endanger their lives. In order to encrypt data and establish perfectly alright access control for such sensitive information, attribute-based encryption (ABE) has typically been used. Traditional ABE, however, has a high processing overhead. As a result, an effective security system algorithm based on ABE and Fully Homomorphic Encryption (FHE) is developed to protect health-related data. ABE is a workable option for one-to-many communication and perfectly alright access management of encrypting data in a cloud environment. Without needing to decode the encrypted data, cloud servers can use the FHE algorithm to take valid actions on it. Because of its potential to provide excellent security with a tiny key size, elliptic curve cryptography (ECC) algorithm is also used. As a result, when compared to related existing methods in the literature, the suggested hybridized algorithm (ABE-FHE-ECC) has reduced computation and storage overheads. A comprehensive safety evidence clearly shows that the suggested method is protected by the Decisional Bilinear Diffie-Hellman postulate. The experimental results demonstrate that this system is more effective for devices with limited resources than the conventional ABE when the system’s performance is assessed by utilizing standard model