Determinants of Female-headed Households’ Livelihood Diversification Strategies Choice in Ambo District, Ethiopia

The study has concluded that diverse livelihood options are available and thus,Female - Headed Households pursue diverse range of activities that draw on their labor and time. However, the participation levels vary within Female - Headed Households(FHHs). The variation is mainly in terms of the activity they diversify into and conditions under which diversification are made. Generally, FHH participate in low-return and high risk and last resort activities. The study concludes that livelihood diversification strategies choice of FHH is determined by a number of factors. Hence, it is recommended that the livelihood of FHHs needs to be recognized and policy intervention should concentrate on improving access to assets within the aim of expanding livelihood options rather than assuming households are spatial homogenous and individual engage in one type of activity only

Certainty Modeling of a Decision Support System for Mobile Monitoring of Exercise-induced Respiratory Conditions

Mobile health systems in recent times, have notably improved the healthcare sector by empowering patients to actively participate in their health, and by facilitating access to healthcare professionals. Effective operation of these mobile systems nonetheless, requires high level of intelligence and expertise implemented in the form of decision support systems (DSS). However, common challenges in the implementation include generalization and reliability, due to the dynamics and incompleteness of information presented to the inference models. In this paper, we advance the use of ad hoc mobile decision support system to monitor and detect triggers and early symptoms of respiratory distress provoked by strenuous physical exertion. The focus is on the application of certainty theory to model inexact reasoning by the mobile monitoring system. The aim is to develop a mobile tool to assist patients in managing their conditions, and to provide objective clinical data to aid physicians in the screening, diagnosis, and treatment of the respiratory ailments. We present the proposed model architecture and then describe an application scenario in a clinical setting. We also show implementation of an aspect of the system that enables patients in the self-management of their conditions

Using knowledge management to assist in the transformation of the Jamaica Constabulary Force

Over several years Jamaica has suffered from a high crime rate which has negatively affected its economic growth. According to a United Nation Report (2008) Jamaica is categorized amongst the most dangerous countries in the world today. In such an environment the responsibilities of the police have increased, as more and more Jamaican gangs have international connections. This has negatively impacted the human and social capital, and security has become the primary focus area for all Jamaicans. For police to function effectively in such an environment the use of Information and Communications Technology (ICT) is needed for managing knowledge from multiple sources. In this paper we present the current status of knowledge management practices in the Jamaica Constabulary Force (JCF) which could be used to transform the JCF into a knowledge organization

South African specific complexities in aligning graduate attributes to employability

South African higher education (HE) cannot be compared to any other country’s HE systems due to the unique political landscape and structural narrative that it has undergone. Subsequent to the reorganisation of HEIs in 2004, a number of complexities arose. These included accessibility to education across race and the alignment of the South African HEIs to global pedagogic benchmarks. With the changing political landscape, transformations within higher education, socio economic inequities and changes in the workplace, researchers failed to cognize the impact of these factors on graduate employability. Changing graduate attributes to align with a decolonised curriculum and Fourth Industrial Revolution (4IR) workspaces were transiently underway when COVID-19 set a new narrative for the future of employability. This paper seeks to identify the impact of workplace changes and its direct influence on successful graduate employment and integration into the HE curriculum. The work environment has cursorily moved from 4IR to an advanced stage of the 4IR, where there is a full emphasis on digitisation, non-localised workspaces and is an ostensible playground for digital natives (Generation Z). This paper provides a systematic review of literature in the South African HE contexts that pertains to graduate attributes for employability within the workplace.  The adoption of malleable secondary data will allow for an understanding of the relationship between changing workplace environments and expectations from graduates. This correlation is directly linked to graduate attributes which students need to comply with from year one. The paper will provide context to changes which are required for the future success of graduates, and whether graduate attributes are adequate preparation for employability. A clinical model is recommended with an intervention to manage the risk factors of decolonisation of curriculum, the 4IR and multi-generational workplace and responses to COVID-19

An Algorithm to Extract Jamaican Geographic Locations from News Articles – Using NLP Techniques

Natural Language Processing (NLP) has long been used to extract information from large bodies of text. NLP is often used to intelligently parse large volumes of data where the manual alternative may be infeasible. Named Entity Recognition (NER) is used to extract named entities such as people, places or organizations from text written in natural language. Using NER, NLP algorithms can be created to extract the mentions of geographic locations of different types from current and archived news articles. This information can be used to add a spatial window into previously flat datasets, allowing users to access information by filtering location information. Information that is derived can be used to support intelligent decision making and influence expert systems. This paper describes the development of an algorithm that uses the principles of both NLP and NER to extract references to geographic locations within news articles. The algorithm has been developed using the NLTK and Pattern Web Toolkit for Python and performs with a precision and accuracy above eighty (80) percent

Analysis of cesarean deliveries in a tertiary hospital as per Robson ten group classification system

Background: Cesarean section is the most commonly performed surgery in the department of gynecology. However, it has its own merits and demerits which affect the mother and the baby in the present as well as subsequent pregnancies. There is a rising trend of cesarean deliveries not only in India but worldwide. So, there is a dire need to audit these cesarean sections and make necessary recommendations accordingly to curb the rising incidence of cesarean deliveries in near future. Hence, the present study analysed the leading groups contributing to high cesarean rates at a tertiary hospital of Armed Forces using Robson ten group classification.Methods: This study was conducted in a Tertiary Hospital of Armed Forces at Chandigarh. All patients who delivered in this hospital between January 2016 to December 2018 were included in this study as per the Robson ten group classification.Results: number of patients who delivered during the time period January 2016 to December 2018 was 3136. Number of patients who delivered vaginally during the same period was 1865. Number of patients who delivered through cesarean section were 1271. Group 5 was the leading contributor to cesarean deliveries followed by groups 2 and 4 subsequently. However, there was significant contribution by group10 to the list.Conclusions: Groups 5, 2 and 4 are the leading contributors to cesarean sections at our institute. So, author need to introspect the labour room protocols and change our norms especially about fetal distress based on CTG monitoring and perform versions in mal-presentations if not contra-indicated to reduce cesarean section rates in near future. Even rising rates of cesarean section in elderly primis, patients conceived after infertility treatment and increasing trends of cesarean delivery on maternal request needs to be checked to reduce the rates of primary cesarean sections