The study examines the barriers towards the roles of the family in child’s literacy. It adopted an 11 item questionnaire known as FACHIL as the main instrument. 532 pupils whose age range from 8-13 years were the respondents. The instrument was validated by colleagues who are experts in the area of study and a test retest exercise whose result was 0.75 was adopted to ascertain the instrument’s degree of reliability. Percentages, means and chi-square were used to analyze the data. It established that there is literacy skills among the pupils. Employment and collaboration with teachers as well as teaching and studying with the children were found to be credibly carried out by the families as their roles towards the child’s literacy. Although parents’ literacy level, absence of family library, commitment by parents to examine the children’s book were found as limiting factors. Gender and the nature of schools attended by children were considered to hold significant influence on the child’s literacy level. It was recommended that mass enlightenment is needed to enable the families to effectively discharge their functions.

The present study on Activity Based Approach enhance achievement in sciences of class-VII students. Activity Based Approach consisted of different activities for the all round development of children at the elementary level. Activity should be prepared by low cost material which is available in the locality. Hence it is concluded that Activity Based Approach is significantly effective than the traditional approach of teaching.

This study is presenting an empirical justification for the inclusion of private sector participation in municipal solid waste management. It is derived from a study of waste management in metropolitan Lagos. Primary data were obtained through interviews and ten questionnaires with the various stakeholders and secondary data were collated from the archives of relevant agencies, especially Lagos Waste Management Authority (LAWMA) websites, Digital libraries and earlier studies. The study reveals that the private sector which comprises of the highway managers and the private sector participant (PSP) collected more than 70% of the waste volume even in the experimental stage. This is a pointer to the potential of this sector as a strong ally and a more efficient one at that.

Failure mode, effects and criticality analysis (FMECA) is an extension of failure mode and effects analysis (FMEA). FMEA is a bottom-up, inductive analytical method which may be performed at either the functional or piece-part level. FMECA extends FMEA by including a criticality analysis, which is used to chart the probability of failure modes against the severity of their consequences. The result highlights failure modes with relatively high probability and severity of consequences, allowing remedial effort to be directed where it will produce the greatest value. The objective of FMECA is to identify all failure modes in a system design. Its purpose is to find all critical and catastrophic failures that can be minimised at the earliest

The paper presents construction I.metal couplingIntroduction metal coupling of high torsional flexibility. In addition, the paper presents preliminary tests results which enable to determine the above characteristics

Security has been a major issue where crime is increasing exponentially and everybody wants to take proper measures to prevent intrusion. There is a need to automate so that user can enhance the technological advancement in such a way that a person getting off the office does not get melted with the hot climate. To minimize thefts and prison breaks we came with purely a new security system. This is a security system which is based on use of vibration sensors. The sensors are reinforced inside the floor, roof, side walls which are arranged with uniform distance between them. The sensor which senses vibration continuously over a period of time is used for detecting the tunnel boring/wall breaking activity. An algorithm is developed for detecting the tunnel boring/wall breaking activity which raises the alarm when one of the above activities is detected. The alarm is raised locally through a siren, informs the owner of the shop through GSM, and a message is sent to the police control room.

Detecting micro calcifications - early breast cancer indicators – is visually tough while recognizing malignant tumors is a highly complicated issue. Digital mammography ensures early breast cancer detection through digital mammograms locating suspicious areas with benign/- malignant micro calcifications. Early detection is vital in treatment and survival of breast cancer as there are no sure ways to prevent it. This paper presents a method of tumor prediction based on extracting features from mammogram using Gabor filter with Discrete cosine transform and classify the features using Neural Network.

The paper points to a coverage of the latest research techniques and findings relating to the econometric analysis of financial markets. It contains a wealth of new materials reflecting the developments during the last decade or so. Particular attention is paid to the wide range of nonlinear models that are used to analyze financial data observed at high frequencies and to the long memory characteristics found in financial time series. There is also a discussion, briefly, of the treatment of volatility, chaos, the Fed model, stochastic estimation and Bayesian estimation, the Fed model and tail dependent time series models.

Weeds are often one of the biggest problems encountered by farmer in conventional agriculture. Maximum productivity of crops can be achieved by proper weeds management. Applying excessive herbicide uniformly throughout the field has an adverse effect on the environment. An automated weed control system which can differentiate the weeds and crops from the digital image could be a feasible solution for this problem. This paper demonstrates Naïve Bayes, SVM (Support Vector Machine) and C 4.5 classification algorithm for classifying the weeds and investigates the performance analysis among these three algorithms. In this study 400 sample images over five species were taken where each and every species contains 80 images. The result has shown that Naïve Bayes classification algorithm achieve the highest accuracy (99.3%) among these three classifier.

The paper examined the changing status of Bini women occasioned by the upsurge and endemic nature of the phenomenon of trafficking for the purpose of transactional sex. It engaged ethnographic methods of data collection with the use of house-hold based interviews, Focus Group Discussions (FGDs) using vignette stories and key informants interviewings. Data were analyzed based on emerged themes. Findings revealed that “successful” trafficked Bini women enjoyed high socio-economic status in their families of procreation especially where family members were the direct recipients of the proceeds from transactional sex. Most mothers of “successfully” trafficked victims wielded greater influence in family of procreation than was the case in traditional Benin family structure and prior to the era of trafficking in the study area. In addition, girl children that are “successful” victims of trafficking are highly revered by their older male siblings, as long as they sent “hard currency” from overseas. The paper concluded that many uneducated women still perceive trafficking and transactional sex as empowering initiatives to protect women from the oppressive culture, which had hindered their access to critical economic resources, but privileged the male gender.