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

DESIGN OF AN INTEGRATED AGRARIAN DATA DIMENSIONAL DATA WAREHOUSE

The concept of the Data warehouse was developed to provide a single access point to data from a variety of sources. There isa need to have a single location for the storage and sharing of data that users can easily utilize to make effective and qualitybusiness decisions, rather than trying to traverse the multiple data sources that exist today. Although many frameworks havebeen developed to integrate these sources into a single database, a reliable framework has yet to be developed. A majorhindrance to achieving a reliable warehouse is the poor quality of data obtained from the data transformation stage in theextract, transfer and load process. This poor quality of data contributes to inaccurate and unreliable results and if this data isused for decision making, unforeseen critical business errors can occur. This work reviews the data integration andtransformation process in dimensional data warehouses and proposes a dual structure for data integration and metadata ofmulti-formatted data used for the design of dimensional data warehouse using Agrarian data collected from Ondo State,Nigeria as a case study.Keywords: Data Warehouse, Data Integration, Metadata, Agrarian data

Factors Influencing the Use of Information and Communication Technology in Real Estate Practice in Minna

The study explored motivating factors influencing the use of ICT in Minna.The target population were registered Estate Surveyors and Valuers domiciled and operating within the Minna property market. The respondents were extracted from the 2011 NIESV membership Directory.Survey data from 15 estate firms were collected to analyze the vital motivating factors influencing the use of ICT in real estate practice. A five point Likert scale was used to examine their opinions and spearman rank correlation was used to test if there is any relationship between internal and external motivating factors. The result indicated that increased productivity of staff, enhanced quality of customer services, knowledge sharing factor, information accessibility, improved decision making and time saving are the most influencing motivating factors while competitors' pressure, availability of ICT infrastructure, management and business size, reduced overall cost are less influencing motivating factors. The study further revealed that internal motivating factors strengthened the use of ICT in their domain. There is negative correlation between the internal and external motivating factors. Niger state branch of NIESV and ESVARBON should recommend the use of ICT to all estate firms and estate surveyors and valuers. Also, the work concludes by recommending further conduct of comprehensive indigenous research and development (R&D) in ICT driven real estate practice in Minna by liaison with various educational institutions offering estate management in their domain in order to be abreast of global best practices.Keywords: ICT, Real Estate Practice, Motivating Factors, Nigeri

Readiness of Nigerian Health‑Care Workers to Work during COVID‑19 Pandemic

Introduction: Health‑care professionals of all cadres are the utmost valuable resource during pandemics and maintaining an adequateworkforce of health professionals during an emergency is critical to ensure uninterrupted provision of services that are essential for patient care. Aim: Examine readiness of health‑care workers (HCWs) to provide service in the course of the COVID‑19 pandemic and the factors influencing their decision. Methodology: This was a cross‑sectional study of Nigerian health sector workers HCWs in the course of the COVID‑19 pandemic. The respondents were recruited using HCWs focus groups on WhatsApp and Telegram social medial platforms. Results: A total of 481 HCWs were recruited, consisting of 288 females and 193 males (M: F, 1:1.5), mean age = 30.71 ± 5.9 years. MostHCWs (97.3%) showed a willingness to provide service during the pandemic; 73.3% of the HCWs were willing to work if supplied with adequate personal protective equipment (PPE) although 5.8% were less willing to work without proper PPE. Factors supporting  unwillingness to work during the pandemic were: concerns about the lack of adequate testing for COVID‑19 (48.9%), lack of disability insurance plan (40.1%), fear of being infected (47.2%), and the risk of infection in family members (24.5%). The readiness to work was related to the job cadres of the HCWs (P = 0.001), while the provision of additional incentives and a change in the working conditions would influence the readiness of the HCWs to work. Conclusion: HCWs were ready to provide service in the course of the COVID‑19 pandemic if there was a safe work environment, although the availability of PPE and other personal factors would influence their willingness to work, while improvement in working conditions would motivate HCWs to work. Keywords: COVID‑19, health‑care workers, pandemic, personal protective equipmen

Isolation and Identification of Bacteria in Petroleum Hydrocarbons Polluted Soils in North-West Bayelsa State

Soil samples were analyzed to identify population of autochthonous aerobic heterotrophic bacteria (AHB) and hydrocarbon degrading bacteria (HDB) in soils of Bayelsa State. Soil samples collected from two locations (Okodia and Imiringi) at two different crude oil sites (polluted and unpolluted) at two soil depths (0-15cm and 15-30cm). Pour plate method using Nutrient Agar (NA), DeMan Rogosa and Sharp Agar (MRSA), Cetrimide Agar (CA) and Mannitol Salt Agar (MSA) were used for both total AHB and HDB counts incubated at 37oC for 24, 48 and 72 hours respectively. Results obtained were subjected to statistical analysis (ANOVA) using Turkey's test to separate means of significant difference (p<0.05). Results for bacterial population expressed in (CFU/g x 106) showed that Imiringi soils were significantly different from Okodia soils with polluted sites significantly different from unpolluted sites for both locations. However, soil depths for both locations and sites showed no significant differences. Furthermore, results showed no significant difference indicating that both bacteria are equally present in the locations, sites and soil depth respectively. Three HDB isolates were identified, namely: Pseudomonas aeroginosa, Staphylococcus aureus and Lactobacillus acidophilus. The bacteria isolates were two Gram-stain positive and one Gram-stain negative. Physico-chemical properties and rate of respiration of the bacteria from both locations were also analyzed. Results of the analyses showed that population of the HDB present in this study could be well utilized for bioremediation of soils in Bayelsa State and other crude oil exploration and exportation states within the Niger Delta for agricultural purposes via bio-augmentation and bio-stimulation methods

Rast i senzorni pokazatelji afričkog soma (Clarias gariepinus) hranjenog subletalnom dozom ekstrakta lišća nima (azadirahte) i njegovi antibakterijski učinci

The antibacterial effects of Neem leaf, the growth performance and sensory qualities of African catfish fed with Neem leaf inclusion were investigated in this study. Ninety (90) post-juvenile Clarias gariepinus (42.40 ± 2.50 g) were used. Experimental groups in triplicate were exposed bi-weekly to 3.5% and 7% LC50 of Neem leaves aqueous extract infused in commercial floating feed for four weeks, while the control group was exposed to untreated feed. The whole body length and weight of randomly sampled fish were taken for organo-somatic indices. Gills and skin samples were collected for bacteriological screening, while fish muscles were prepared for sensory acceptability tests. Mean feed intake was significantly (P<0.05) influenced by Neem leaf in the three treatment concentrations with an insignificant difference between the treated groups, but it was higher than in the control group. Mean weight gain was significantly higher (P<0.05) in the Neem fed fish than the control but insignificant the differences between treatment doses were insignificant, while the feed conversion ratio was significantly lower (P<0.05) in the Neem fed groups compared to the control, but the difference was insignificant between the treatment doses. All groups were apparently healthy looking with 100% survival. There was a considerable reduction in total bacterial count in both the gills and skin with the increase in Neem concentration. Micrococci spp. and Bacillus subtilis were not isolated in the gills but were present in the skin, while E. coli and Pseudomonas fluorescens were not suppressed in the skin. There was no significant difference (P<0.05) in all the sensory parameters across all groups. The inclusion of Neem leaf extract was shown to have a high antibacterial effect coupled with excellent growth performance and general acceptability of fish tissue.U ovom su radu istraženi antibakterijski učinci lišća nima, kao i rast i senzorni pokazatelji afričkog soma (Clarias gariepinus) hranjenog ovim lišćem. Upotrijebljeno je 90 odraslih afričkih somova (42,40 ± 2,50 g). Pokusna je skupina izložena tijekom dva tjedna 3,5 % i 7 % LC50 vodenom ekstraktu lišća nima dodanog u komercijalnu hranu tijekom četiri tjedna, dok je kontrolna skupina hranjena netretiranom hranom. Određena je tjelesna dužina i masa nasumično odabranih riba za provjeru organoleptičkih pokazatelja. Škrge i uzorci kože prikupljeni su za bakteriološku analizu, dok su uzorci mišića pripremljeni za senzornu analizu. Prosječna konzumacija hrane bila je pod znakovitim utjecajem (P < 0,05) lišća nima, neovisno o koncentraciji, u odnosu na kontrolnu skupinu. Prosječan prirast bio je znakovito viši (P < 0,05) u riba hranjenih lišćem nima u odnosu na kontrolnu skupinu, dok je konverzija hrane bila znakovito niža (P < 0,05) u skupini hranjenoj lišćem nima, neovisno o dozi. Ribe u svim skupinama bile su naizgled zdrave uz 100%-tno preživljenje. Utvrđen je zamjetan pad brojnosti ukupnih bakterija u škrgama i na koži s porastom koncentracije lišća nima. Bakterije Micrococci spp. i Bacillus subtilis nisu izolirane iz škrga, ali su utvrđene u koži, kao i E. coli i Pseudomonas fluorescens. Nisu utvrđene znakovite razlike senzornih pokazatelja. Dodatak lišća nima ima visok antibakterijski učinak praćen odličnim pokazateljima rasta te općom prihvatljivošću tkiva ribe za konzumaciju

Identification of pattern mining algorithm for rugby league players positional groups separation based on movement patterns

The application of pattern mining algorithms to extract movement patterns from sports big data can improve training specificity by facilitating a more granular evaluation of movement. Since movement patterns can only occur as consecutive, non-consecutive, or non-sequential, this study aimed to identify the best set of movement patterns for player movement profiling in professional rugby league and quantify the similarity among distinct movement patterns. Three pattern mining algorithms (l-length Closed Contiguous [LCCspm], Longest Common Subsequence [LCS] and AprioriClose) were used to extract patterns to profile elite rugby football league hookers (n = 22 players) and wingers (n = 28 players) match-games movements across 319 matches. Jaccard similarity score was used to quantify the similarity between algorithms’ movement patterns and machine learning classification modelling identified the best algorithm’s movement patterns to separate playing positions. LCCspm and LCS movement patterns shared a 0.19 Jaccard similarity score. AprioriClose movement patterns shared no significant Jaccard similarity with LCCspm (0.008) and LCS (0.009) patterns. The closed contiguous movement patterns profiled by LCCspm best-separated players into playing positions. Multi-layered Perceptron classification algorithm achieved the highest accuracy of 91.02% and precision, recall and F1 scores of 0.91 respectively. Therefore, we recommend the extraction of closed contiguous (consecutive) over non-consecutive and non-sequential movement patterns for separating groups of players

Concurrent pleomorphic adenoma in parapharyngeal space and submandibular gland

BACKGROUND: Pleomorphic adenoma in the parapharyngeal space either occurs de novo or as an extension from the deep lobe of the parotid gland. CASE PRESENTATION: A rare synchronous occurrence of pleomorphic adenoma in the parapharyngeal space and submandibular gland of a 48-year-old Nigerian male is reported. CONCLUSION: Pleomorphic adenoma concurrent in the parapharyngeal space and submandibular gland is very rare. A complete surgical excision of both tumors is the treatment of choice