Enhancing the Decision Making Process: An Ontology-based Approach

Decision making is a key activity for management in any organization, several decision making methods including Multi Criteria Decision Making (MCDM) have been used to assist this process especially when the decision involves multiple stakeholders and multiple criteria. These methods, which evaluate each alternative by a set of criteria, tend to be subjective in nature. However, although they are subjective it should be ensured that the decisions makers have as much knowledge about the alternatives as is possible. This would include understanding all the consequences of each alternative and all the effects of these consequences. This requires a thorough understanding of the domain within which the decision is being made. We argue that an organizational ontology provides this understanding and propose a method for integrating an ontology into typical multi-criteria decision making techniques. The overall aim of this method is to improve the decision making process. We demonstrate the applicability of this method by applying it to decision making at a university in the Caribbean

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

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

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

PRES, a diagnostic dilemma in pregnancy: three case series with unusual presentation

Authors report a series of three cases of unusual presentation of posterior reversible encephalopathy syndrome in pregnancy. First patient, 29 years old G2P1L1, who was a booked case at our hospital, presented with complain of no fetal movement perception for 3 days at 27 weeks of period of gestation. No history of hypertension and even no record of hypertension after admission. On USG detected to have severe early onset IUGR and AEDF in Umbilical artery doppler. Went in to spontaneous labor and delivered vaginally a preterm neonate of birth weight of 740 gms at 27 weeks 06 days of period of gestation. Postpartum period was uneventful till day four and on day five of postpartum she developed severe headache and seizure. MRI done which was suggestive of PRES. Second patient 27 years old primi gravida with 37 weeks 01 day, booked at our hospital with regular ANC visit brought with history of headache, vomiting with semi-conscious state with diminution of vision till finger count only. She developed seizure thrice while examination. Antenatal period was uneventful with no history of hypertension. Underwent emergency LSCS on same day and delivered a 2.8 kg healthy female neonate. Patient treated as a case of eclampsia and later MRI findings were suggestive of PRES. Third patient 19 years old primigravida booked ANC case at another hospital. She underwent emergency LSCS at 39 weeks POG for fetal distress at same hospital. Antenataly no history of hypertension or any other co-morbidity. On fourth post-op day, she developed headache and vomiting followed by one episode of seizure and after initial management she transferred to our hospital for further management. When we received patient, she was on Magsulph infusion considering postnatal eclampsia. We managed with Inj Lorazepam 2 mg intravenous and later with Inj Levetiracitam. Final diagnosis has been made as PRES after MRI and MRV brain. We found very atypical presentation of all three cases with difficulty in diagnosis and challenging management, so we are reporting these cases

Maternal and neonatal outcome of twin pregnancies with single fetal demise

 Background: In current study we managed twin pregnancies having single fetal demise with a successful outcome. Generally monochorionic and monoamniotic pregnancies are having high probability of complications, so we have to be more watchful in these pregnancies. Termination of pregnancy is not the only option as we can manage and prolong pregnancies with a good outcome by strict monitoring of patients. Aim of our study was to look for fetomaternal outcome in twin pregnancies with single fetal demise.Methods: This is a retrospective study done between July 2017 to June 2020 at Command hospital, Panchkula, Haryana. Total 3249 deliveries have been conducted during above said period. Out of which 47 deliveries were having twin pregnancy. We had six twin pregnancies who reported with one fetal demise. These cases were managed with regular monitoring of coagulation profile and strict fetal surveillance for surviving twin. The cases were studied for antenatal, postnatal and any neonatal complication.Results: No antenatal, postnatal maternal or any neonatal complication observed in this study. During study period we delivered total 3249 patients, out of which 47 were twin pregnancy. Out of these 47 (1.44%) twins’ pregnancies 33 (70.31%) were DADC and 14 (29.69%) DAMC. We studied six twin pregnancies who had single fetal demise. Conclusions: Even with single fetal demise pregnancies can be continued till term with strict monitoring for maternal and fetal complications. Termination is not the only answer in twin pregnancies with single fetal demise. Although our study was small, it indicates that in case of twin pregnancy with single fetal death and under good surveillance, the live fetus can be salvaged.

Determinants of Quality of Life of Sickle Cell Patients: A KDDM Process Model based Exploration

Sickle Cell Disease (SCD) is the most common single-gene disorder worldwide and has multiple and variable manifestations. The many medical complications associated with it such as acute chest syndrome and painful crises, along with a lack of normal functioning, may lead to various psychosocial problems such as depression, loneliness and impaired quality of life. A few studies have sought to examine the relationships between demographics, disease severity, depression, loneliness and quality of life of such patients. In this paper we apply the knowledge discovery via data mining (KDDM) process to explore factors which impact the quality of life of sickle cell patients in Jamaica to explicate knowledge which can be used by medical professionals. We use multiple modeling techniques such as Decision Trees, Regression and Regression splines to generate multiple models on the dataset and then present a best set of models to the medical professionals. This allows the medical professionals to select models which will assist them in the decision making process. The benefits of using the process model are highlighted in this study

Using Knowledge Management to Strengthen Information Security Policy Development in Developing Countries: Case - Jamaica

Information security incidents continue to grow exponentially amidst the development of advanced technological solutions aimed at protecting information system resources. Today, the growth in information systems’ breaches remains at an alarming rate. The strategies developed by malicious users are becoming more sophisticated in nature and are introduced unabated across various networks. However, security experts and developers are lagging behind in their response to the information security phenomenon. Today, developing countries continue struggling to effectively address information security issues and are becoming the main avenue for cyber criminals who capitalize on the weaknesses that exist in these regions. An effective response to information security requires a significant amount of resources. In developing countries there are limited human, financial and technological resources and weak legislative frameworks and these are fundamental requirements for combating cyber-crime. One major cyber-crime incident could be catastrophic for businesses and governments in these small, fragile economies and could have far reaching effects on their citizens. Knowledge management can be employed to assist in strengthening the capability of organizations and governments in the development of context-sensitive information security policies in developing regions. In this paper we present a knowledge acquisition model that brings together the two most widely adopted standards COBIT, ISO/IEC 27005 and tacit knowledge that exists in repositories (human) within the information security domain to support the development of context-sensitive information security policies. A quantitative methodology was used in the development of an artifact, preliminary evaluation was done using the informed argument approach and results and recommendations for future research are presented. This study can add to the limited literature on the use of knowledge management in the information security domain and the artifact presented can assist information security practitioners in small/medium-sized organizations