ANALYZING EMPLOYEE ATTRITION USING DECISION TREE ALGORITHMS

Employee turnover is a serious concern in knowledge based organizations. When employees leave an organization, theycarry with them invaluable tacit knowledge which is often the source of competitive advantage for the business. In order foran organization to continually have a higher competitive advantage over its competition, it should make it a duty to minimizeemployee attrition. This study identifies employee related attributes that contribute to the prediction of employees’ attritionin organizations. Three hundred and nine (309) complete records of employees of one of the Higher Institutions in Nigeriawho worked in and left the institution between 1978 and 2006 were used for the study. The demographic and job relatedrecords of the employee were the main data which were used to classify the employee into some predefined attrition classes.Waikato Environment for Knowledge Analysis (WEKA) and See5 for Windows were used to generate decision tree modelsand rule-sets. The results of the decision tree models and rule-sets generated were then used for developing a a predictivemodel that was used to predict new cases of employee attrition. A framework for a software tool that can implement therules generated in this study was also proposed.Keywords: Employee Attrition, Decision Tree Analysis, Data Minin

ASSESSING RESOURCE USE EFFICIENCY AND INVESTMENT IN COCOA ENTERPRISE: A CASE OF OSUN STATE, NIGERIA

This study determined resource use efficiency and investment in cocoa production in Osun state, Nigeria. Specifically, described the socioeconomic characteristics of cocoa farmers; determined the factors affecting cocoa production; determined the resource use efficiency in cocoa production; and estimated profitability of investment in cocoa production in the study area. The study was conducted in Osun state, south-western Nigeria. A multi-stage sampling procedure was used for selecting respondents for this study. A total number of 120 households were selected for the study.  Data were analyzed using Descriptive statistics, Multiple Regression, Marginal value and budgetary analysis. The results for the entire respondents showed average values of 52 years for age, 26years for year of experience, 9 for household size, and 3.85 for farm size. Returns to scale (RTS) was 1.599. Years spent in formal education (p<0.05), farm size (p<0.05), volume of insecticide used (p<0.01), labour (p<0.01) positively and significantly influenced output of cocoa farmers. Resource use efficiency shows that family labour is 1.333, insecticide (2.575), fungicide (2.667), land (0.267), and hired labour (0.745). The estimated costs and return of cocoa farmers per hectare of land on the average in the study area were N 115,481.70 and N 156,518.30 per annum whereas the total revenue on the average was N272000, while the gross margin and net income were N166729.30 and N156518.30, respectively. The benefit cost ratio and labour efficiency ratio were 2.36 and 3.18, respectively. Following the findings of the study, the government and non-governmental agencies should ensure that farm inputs are made available to the cocoa farmers at the right time, quantity, quality and also at subsidized prices. 

ORGANIZATIONAL CLIMATE, LEADERSHIP STYLE AND EMOTIONAL INTELLIGENCE AS PREDICTORS OF QUALITY OF WORK LIFE AMONG BANK WORKERS IN IBADAN, NIGERIA

The effects of organizational climate, leadership style and emotional intelligence on the quality of work life were investigated in this study. The participants were two hundred and fifty bank workers drawn from selected commercial banks within Ibadan metropolis. Three research questions and hypotheses were raised in the study. Four valid and standardized instruments were administered on the participants. Pearson product moment correlation, multiple regression analysis and analysis of variance were used to analyse data at 0.05 level of significance. The result shows that the three independent variables when combined were effective in predicting quality of work life. The three variables contributed significantly to quality of work life of the participants with leadership styles as the most potent predictor in the study.. the result also show there was also a significant difference in quality of work life among participants with Democratic, Autocratic and Laissez faire leadership with contributions of democratic style being the most potent. Based on the findings, it is suggested that management should take into cognizance the importance and roles of emotional intelligence and leadership styles in enhancing quality of work life among employee

THE FREDERICK HERZBERG TWO FACTOR THEORY OF JOB SATISFACTION AND ITS APPLICATION TO BUSINESS RESEARCH

This paper critically examines Frederick Herzberg’s two factors theory of job satisfaction and its application to business research. The two factor theory of motivation explains the factors that employees find satisfactory and non-satisfactory in their place of employment. These factors are the hygiene factors and motivators. The hygiene factors when present are characterized by insufficiency that can’t satisfy the employees in their work place but the motivators which refers to the nature of the job, provide satisfaction and lead to better motivation. This paper adds to the present knowledge on what motivates employees in industries and academics with the aid of other theories that relate to the Frederick Herzberg theory. It therefore creates a template for re-evaluation of the thinking and viewpoint that motivator factors are rated above hygiene factors in every organization

Animal models of rheumatoid pain: experimental systems and insights.

Severe chronic pain is one of the hallmarks and most debilitating manifestations of inflammatory arthritis. It represents a significant problem in the clinical management of patients with common chronic inflammatory joint conditions such as rheumatoid arthritis, psoriatic arthritis and spondyloarthropathies. The functional links between peripheral inflammatory signals and the establishment of the neuroadaptive mechanisms acting in nociceptors and in the central nervous system in the establishment of chronic and neuropathic pain are still poorly understood, representing an area of intense study and translational priority. Several well-established inducible and spontaneous animal models are available to study the onset, progression and chronicization of inflammatory joint disease, and have been instrumental in elucidating its immunopathogenesis. However, quantitative assessment of pain in animal models is technically and conceptually challenging, and it is only in recent years that inflammatory arthritis models have begun to be utilized systematically in experimental pain studies using behavioral and neurophysiological approaches to characterize acute and chronic pain stages. This article aims primarily to provide clinical and experimental rheumatologists with an overview of current animal models of arthritis pain, and to summarize emerging findings, challenges and unanswered questions in the field

Evaluation of denoising strategies to address motion-correlated artifacts in resting-state functional magnetic resonance imaging data from the human connectome roject

Like all resting-state functional connectivity data, the data from the Human Connectome Project (HCP) are adversely affected by structured noise artifacts arising from head motion and physiological processes. Functional connectivity estimates (Pearson's correlation coefficients) were inflated for high-motion time points and for high-motion participants. This inflation occurred across the brain, suggesting the presence of globally distributed artifacts. The degree of inflation was further increased for connections between nearby regions compared with distant regions, suggesting the presence of distance-dependent spatially specific artifacts. We evaluated several denoising methods: censoring high-motion time points, motion regression, the FMRIB independent component analysis-based X-noiseifier (FIX), and mean grayordinate time series regression (MGTR; as a proxy for global signal regression). The results suggest that FIX denoising reduced both types of artifacts, but left substantial global artifacts behind. MGTR significantly reduced global artifacts, but left substantial spatially specific artifacts behind. Censoring high-motion time points resulted in a small reduction of distance-dependent and global artifacts, eliminating neither type. All denoising strategies left differences between high- and low-motion participants, but only MGTR substantially reduced those differences. Ultimately, functional connectivity estimates from HCP data showed spatially specific and globally distributed artifacts, and the most effective approach to address both types of motion-correlated artifacts was a combination of FIX and MGTR

Estimation of Human Health Risk Due to Heavy Metals around Schools and Auto-Mobile Workshops near Frequented Roads in Kaduna State, Nigeria

Heavy metals are widely known for their potential to cause carcinogenic and non-carcinogenic health risks. In this work, the carcinogenic and non-carcinogenic health risks associated with heavy metals in the vicinity of schools and auto mechanic workshops close to busy roads in Kaduna state was assessed using NEX CG EDXRF MODEL with brand name RIGAKU situated at a UTM Laboratory, Malaysia. The obtained heavy metals concentrations were used to estimate the health effects that might result from exposure to carcinogenic and non-carcinogenic chemicals for both the population ages using US EPA methodology. Findings indicated that in some locations the carcinogenic and non-carcinogenic hazards associated with exposure for residents was greater than the US EPA acceptable thresholds of 10-4 and 1 respectively. This indicated that the heavy metals may result to unacceptable carcinogenic and non-carcinogenic risks, which is an issue of concern in public health especially looking at the way school children play around these areas. The present study therefore provides scientific basis for strategies required to protect human and environmental health in schools and automobile workshops

Functional Assessment of the Medicago truncatula

The Medicago truncatula NIP/LATD (for Numerous Infections and Polyphenolics/Lateral root-organ Defective) gene encodes a protein found in a clade of nitrate transporters within the large NRT1(PTR) family that also encodes transporters of dipeptides and tripeptides, dicarboxylates, auxin, and abscisic acid. Of the NRT1(PTR) members known to transport nitrate, most are low-affinity transporters. Here, we show that M. truncatula nip/latd mutants are more defective in their lateral root responses to nitrate provided at low (250 μm) concentrations than at higher (5 mm) concentrations; however, nitrate uptake experiments showed no discernible differences in uptake in the mutants. Heterologous expression experiments showed that MtNIP/LATD encodes a nitrate transporter: expression in Xenopus laevis oocytes conferred upon the oocytes the ability to take up nitrate from the medium with high affinity, and expression of MtNIP/LATD in an Arabidopsis chl1(nrt1.1) mutant rescued the chlorate susceptibility phenotype. X. laevis oocytes expressing mutant Mtnip-1 and Mtlatd were unable to take up nitrate from the medium, but oocytes expressing the less severe Mtnip-3 allele were proficient in nitrate transport. M. truncatula nip/latd mutants have pleiotropic defects in nodulation and root architecture. Expression of the Arabidopsis NRT1.1 gene in mutant Mtnip-1 roots partially rescued Mtnip-1 for root architecture defects but not for nodulation defects. This suggests that the spectrum of activities inherent in AtNRT1.1 is different from that possessed by MtNIP/LATD, but it could also reflect stability differences of each protein in M. truncatula. Collectively, the data show that MtNIP/LATD is a high-affinity nitrate transporter and suggest that it could have another function