Semantics-based clustering approach for similar research area detection

The manual process of searching out individuals in an already existing research field is cumbersome and time-consuming. Prominent and rookie researchers alike are predisposed to seek existing research publications in a research field of interest before coming up with a thesis. From extant literature, automated similar research area detection systems have been developed to solve this problem. However, most of them use keyword-matching techniques, which do not sufficiently capture the implicit semantics of keywords thereby leaving out some research articles. In this study, we propose the use of Ontology-based pre-processing, Latent Semantic Indexing and K-Means Clustering to develop a prototype similar research area detection system, that can be used to determine similar research domain publications. Our proposed system solves the challenge of high dimensionality and data sparsity faced by the traditional document clustering technique. Our system is evaluated with randomly selected publications from faculties in Nigerian universities and results show that the integration of ontologies in preprocessing provides more accurate clustering results

A maximum entropy classification scheme for phishing detection using parsimonious features

Over the years, electronic mail (e-mail) has been the target of several malicious attacks. Phishing is one of the most recognizable forms of manipulation aimed at e-mail users and usually, employs social engineering to trick innocent users into supplying sensitive information into an imposter website. Attacks from phishing emails can result in the exposure of confidential information, financial loss, data misuse, and others. This paper presents the implementation of a maximum entropy (ME) classification method for an efficient approach to the identification of phishing emails. Our result showed that maximum entropy with parsimonious feature space gives a better classification precision than both the Naïve Bayes and support vector machine (SVM)

Semantics-based clustering approach for similar research area detection

The manual process of searching out individuals in an already existing research field is cumbersome and time-consuming. Prominent and rookie researchers alike are predisposed to seek existing research publications in a research field of interest before coming up with a thesis. From extant literature, automated similar research area detection systems have been developed to solve this problem. However, most of them use keyword-matching techniques, which do not sufficiently capture the implicit semantics of keywords thereby leaving out some research articles. In this study, we propose the use of ontology-based pre-processing, Latent Semantic Indexing and K-Means Clustering to develop a prototype similar research area detection system, that can be used to determine similar research domain publications. Our proposed system solves the challenge of high dimensionality and data sparsity faced by the traditional document clustering technique. Our system is evaluated with randomly selected publications from faculties in Nigerian universities and results show that the integration of ontologies in preprocessing provides more accurate clustering results

A Maximum Entropy Classification Scheme for Phishing Detection using Parsimonous Features

Over the years, electronic mail (e-mail) has been the target of several malicious attacks. Phishing is one of the most recognizable forms of manipulation aimed at e-mail users and usually, employs social engineering to trick innocent users into supplying sensitive information into an imposter website. Attacks from phishing emails can result in the exposure of confidential information, financial loss, data misuse, and others. This paper presents the implementation of a maximum entropy (ME) classification method for an efficient approach to the identification of phishing emails. Our result showed that maximum entropy with parsimonious feature space gives a better classification precision than both the Naïve Bayes and support vector machine (SVM

Medication Adherence A Review and Lessons for Developing Countries

Most of the time, complete adherence to prescribed medication is a big step towards recovery from either chronic or acute diseases, but patients often are unaware of the adverse effects that could arise from inconsistency in adherence. The inability of patients to adhere to prescription can affect the potency of some effective therapies known to treat many conditions, and passive compliance may result in the development of resistant to the drug causing a need for treatment modification. Shockingly, more than half of the drugs prescribed for patients with chronic conditions like diabetes and hypertension were found not to be taken as recommended. Adherence is so important because it can assist clinicians in successful supervision of evidence-based treatment of patients; therefore this paper presents an overview of medication adherence, non-technology and technology-based approaches, and lessons for developing countries. Keywords—Medication adherence; prescription; ehealth; developing countrie

Medication Adherence: A Review and Lessons for Developing Countries

Most of the time, complete adherence to prescribed medication is a big step towards recovery from either chronic or acute diseases, but patients often are unaware of the adverse effects that could arise from inconsistency in adherence. The inability of patients to adhere to prescription can affect the potency of some effective therapies known to treat many conditions, and passive compliance may result in the development of resistant to drug causing a need for treatment modification. Shockingly, more than half of the drugs prescribed for patients with chronic conditions like diabetes and hypertension were found not to be taken as recommended.  Adherence is so important because it can assist clinicians in successful supervision of evidence-based treatment of patients; therefore this paper presents an overview of medication adherence, non-technology and technology-based approaches, and lessons for developing countries

Medication Adherence: A Review and Lessons for Developing Countries

Most of the time, complete adherence to prescribed medication is a big step towards recovery from either chronic or acute diseases, but patients often are unaware of the adverse effects that could arise from inconsistency in adherence. The inability of patients to adhere to prescription can affect the potency of some effective therapies known to treat many conditions, and passive compliance may result in the development of resistant to drug causing a need for treatment modification. Shockingly, more than half of the drugs prescribed for patients with chronic conditions like diabetes and hypertension were found not to be taken as recommended.  Adherence is so important because it can assist clinicians in successful supervision of evidence-based treatment of patients; therefore this paper presents an overview of medication adherence, non-technology and technology-based approaches, and lessons for developing countries

Impact of Agricultural Education on Students’ Career Choice: A Survey

Agriculture has become the bedrock of some growing economy in the world but the discovery of crude oil and other resources in a developing country like Nigeria has led to the extreme decline in the practice. Many youths now have either low or no interested in agriculture and the majority of the people that are actively practicing are the older generation. This study revisits the impact of education on students interest in agriculture as a professional career. The study was carried out in an agriculture-based uni-versity with a state of the art equipment. Our findings show that 64% of agricul-ture students who participated in this survey are willing to pursue agriculture-related careers. Likewise, there is a significant relationship between the student’s gender and farm ownership, with 84% of male students likelier to own farms. Also, our results have shown that students in higher levels have more interests in agriculture compared to students at lower levels and this invariably increases the possibilities of their pursuing agriculture-related careers or businesses

Current State of ICT in Healthcare Delivery in Developing Countries

Electronic health is one of the most popular applications of information and communication technologies and it has contributed immensely to health delivery through the provision of quality health service and ubiquitous access at a lower cost. Even though this mode of health service is increasingly becoming known or used in developing nations, these countries are faced with a myriad of challenges when implementing and deploying e-health services on both small and large scale. It is estimated that the Africa population alone carries the highest percentage of the world’s global diseases despite its certain level of e-health adoption. This paper aims at analyzing the progress so far and the current state of e-health in developing countries, particularly Africa, and proposes a framework for further improvement. Keywords—E-health, developing countries, framework, ICT, healthcare

E-Prescription in Nigeria: A Survey

Electronic prescribing or Electronic prescription (EP) is the computer-based electronic generation and transmission of a prescription. EP systems help to increase accuracy and safety of patient prescription and reduce costs through improved legibility and electronic delivery. The motivation for EP is greater safety of drug use and to counter the current unacceptable levels of adverse drug events. This study evaluated the feasibility of hospitals in Nigeria to adopt an EP system. A survey was conducted in four hospitals in Nigeria to determine the economic, technical and organisational feasibility of adopting eprescribing. Respondents included 42 medical practitioners - doctors, pharmacists, pharmacy technicians and assistants - working at the hospitals at the time of the survey. Respondents felt that implementation of an EP system is economically feasible (p=0.031) and organisationally feasible (p=0.032) but were ambivalent as to whether it is technically feasible (p=0.446). However, inadequate funding by the government does not provide for the health sector to acquire the necessary resources and training skills. Keywords: E-Prescription; E Health; Survey; Nigeria