Statistical Analysis of the Impact of Women in National Development

Women have been left out in the past national development plans, even their contributions to Gross National Product (GNP) of the nation have been treated as insignificant. The situation is further worsened by illiteracy, poverty, pest, and diseases, fire and other natural disasters. Many bodies had championed the course of the rural women in recent times notable among which are Better life for Rural Women (BLRW), Family Support Programme (FSP), Family Economic Advancement Programme (FEAP), and National Council for Women Society, empower and better the lots of women. Without doubt this research has through its discovery supported the fact that women are contributing immensely to national economic development through divers’ roles they play in their rest. These with other reasons had falsified the notion that women are subordinate to men in rural and national development. Finally, it is suggested in the study that greater access to education, credit land and technology will go a long way to improve women’s lots in the nation and in their contribution to national development, particularly in the local government to women in the rural communities of the country. Keywords: Development, Women, Econom

IMPROVING THE DEPENDABILITY OF DESTINATION RECOMMENDATIONS USING INFORMATION ON SOCIAL ASPECTS

Prior knowledge of the social aspects of prospective destinations can be very influential in making travel destination decisions, especially in instances where social concerns do exist about specific destinations. In this paper, we describe the implementation of an ontology-enabled Hybrid Destination Recommender System (HDRS) that leverages an ontological description of five specific social attributes of major Nigerian cities, and hybrid architecture of content-based and case-based filtering techniques to generate personalised top-n destination recommendations. An empirical usability test was conducted on the system, which revealed that the dependability of recommendations from Destination Recommender Systems (DRS) could be improved if the semantic representation of social attributes information of destinations is made a factor in the destination recommendation process

Improving the Dependability of Destination Recommendations using Information on Social Aspects

Prior knowledge of the social aspects of prospective destinations can be very influential in making travel destination decisions, especially in instances where social concerns do exist about specific destinations. In this paper, we describe the implementation of an ontology-enabled Hybrid Destination Recommender System (HDRS) that leverages an ontological description of five specific social attributes of major Nigerian cities, and hybrid architecture of content-based and case-based filtering techniques to generate personalised top-n destination recommendations. An empirical usability test was conducted on the system, which revealed that the dependability of recommendations from Destination Recommender Systems (DRS) could be improved if the semantic representation of social attributes information of destinations is made a factor in the destination recommendation process.Content-based filtering; Recommender Systems; Ontology; Social Attributes, Destination recommendation

Building an Ontology-Based Framework for Tourism Recommendation Services

The tourism product has an intangible nature in that customers cannot physically evallfate the services on offer until practically experienced. This makes having access to ;credible;"i\nd authentic information about tourism products before the actual experience very valuable. An Ontology being a formal, explicit specification of concepts of a domain provides a viable platform for the development of credible knowledge-based tourism information services. In this paper, we present an approach aimed at enabling assorted intelligent reco=endations services in tourism support systems using ontologies. A suite of tourism ontologies was developed and engaged to enable a prototypical e-tourism system with various knowledge-based reco=endation capabilities. A usability evaluation of the system yields encouraging results as a demonstration of the viability of our approach

Automated classification of African embroidery patterns using cellular learning automata and support vector machines

Embroidery is the art that is majorly practised in Nigeria, which requires creativity and skills. However, differentiating between two standard embroidery patterns pose challenges to wearers of the patterns. This study developed a classification system to improve the embroiderer to user relationship. The specific characteristics are used as feature sets to classify two common African embroidery patterns (handmade and tinko) are shape, brightness, thickness and colour. The system developed and simulated in MATLAB 2016a environment employed Cellular Learning Automata (CLA) and Support Vector Machine (SVM) as its classifier. The classification performance of the proposed system was evaluated using precision, recall, and accuracy. The system obtained an average precision of 0.93, average recall of 0.81, and average accuracy of 0.97 in classifying the handmade and tinko embroidery patterns considered in this study. This study also presented an experimental result of three validation models for training and testing the dataset used in this study. The model developed an improved and refined embroiderer for eliminating stress related to the manual pattern identification process

A 12-month prospective study of intra-abdominal hypertension and abdominal compartment syndrome incidence and outcomes at a tertiary hospital in Nigeria

Background: Peritoneal sepsis is a life-threatening emergency, more so in the low- and middle-income countries (LMICs) where immediate hospital presentation for much needed urgent surgical care is the exception rather than the norm. Continued research into the multifactorial aetiopathogenesis responsible for the high level of morbidity and mortality is necessary. We aimed to determine the incidence of intra-abdominal hypertension (IAH) and abdominal compartment syndrome (ACS) in patients presenting with generalized peritonitis in a tertiary hospital in Nigeria. Methods: We conducted a prospective study involving recruitment of consenting patients managed for generalized peritonitis over 12 months. Results: Fifty-seven consenting and appropriate patients were recruited over the course of the study and managed as per study protocol. The duration of symptoms ranged between 11 hours and 7 days. All patients had varying degrees of IAH and ACS at presentation with generalized peritonitis. A laparotomy with definitive surgery was done in 51 patients (89%), with 6 patients (11%) having only a bedside peritoneal drain inserted for decompression. Significant improvement of the respiratory rate (P < 0.001), oxygen saturation (P = 0.041), and urinary output (P = 0.021) only occurred after decompression by laparotomy or tube drainage. The consecutive mean ± standard deviation (SD) intra-abdominal pressures measured, respectively, at presentation, immediately postsurgery, then postoperatively at 6 h, 24 h, and 72 h reflected significant improvement at each point (respectively in cmH2O: 11.4 ± 6.03, 6.58 ± 5.58, 5.78 ± 3.29, 4.73 ± 2.86, 6.72 ± 5.18; P < 0.001). Conclusions: IAH and ACS are not uncommon in our setting, and ACS at presentation is a significant predictor of mortality in patients with peritoneal sepsis. Surgical decompression invariably leads to an improvement in all clinical variables investigated. Keywords: intra-abdominal hypertension; abdominal compartment syndrome; peritonitis; laparotomy; percutaneous catheter decompression; Nigeria

Service learning as a means to understanding the socio-economic privileges and inequalities of individuals who are deaf or hard of hearing

Complexities surround the social inclusion and socio-economic independence of people who are deaf and/or hard of hearing (DHH). The socio-economic challenges faced by the DHH have been exposed globally over the years and their experience of socio-economic discrepancies in Nigeria as well as other countries in Sub-Saharan Africa is well documented in literature. Although government and non-governmental agencies have made some effort to alleviate the socio-economic challenges faced by the DHH, such effort has not yielded the desired results. Leveraging on the assumptions and principles of social learning theory, this intellectual piece advanced service learning as a socio-learning approach to ameliorate the socio-economic challenges and eliminate the social inequalities faced by the DHH. It was expected that the model presented in this study would respond actively to the goals of the Nigerian National Policy of Education and further enthrone a sustainable inclusive society where the DHH could lead an economically independent life. Implications for policies and research were presented in the paper

Improving the Dependability of Destination Recommendations using Information on Social Aspects

Prior knowledge of the social aspects of prospective destinations can be very influential in making travel destination decisions, especially in instances where social concerns do exist about specific destinations. In this paper, we describe the implementation of an ontology-enabled Hybrid Destination Recommender System (HDRS) that leverages an ontological description of five specific social attributes of major Nigerian cities, and hybrid architecture of content-based and case-based filtering techniques to generate personalised top-n destination recommendations. An empirical usability test was conducted on the system, which revealed that the dependability of recommendations from Destination Recommender Systems (DRS) could be improved if the semantic representation of social attributes information of destinations is made a factor in the destination recommendation process

Improving the Dependability of Destination Recommendations using Information on Social Aspects

Prior knowledge of the social aspects of prospective destinations can be very influential in making travel destination decisions, especially in instances where social concerns do exist about specific destinations. In this paper, we describe the implementation of an ontology-enabled Hybrid Destination Recommender System (HDRS) that leverages an ontological description of five specific social attributes of major Nigerian cities, and hybrid architecture of content-based and case-based filtering techniques to generate personalised top-n destination recommendations. An empirical usability test was conducted on the system, which revealed that the dependability of recommendations from Destination Recommender Systems (DRS) could be improved if the semantic representation of social attributes information of destinations is made a factor in the destination recommendation process