Planning proposals and land value change : a case study of Singapore using GIS

Thesis (M.C.P.)--Massachusetts Institute of Technology, Dept. of Urban Studies and Planning, 1996.Includes bibliographical references (leaves 76-79).by Wong Kok-Wai.M.C.P

Establishing a framework for visualizing music mood using visual texture

There are many researches that introduce various techniques of browsing and discovering music using “visual forms” to the listeners.“Visual forms” include album cover, colour and mood picture are used to represent music mood in a way that can be easily understood by listeners.It has been proven that visual texture can represent mood too.However there is no research that uses visual texture to represent music mood.In this research, we are proposing a framework for visualising music mood using visual texture.The framework will assist digital music service developers to design visual textures that can represent music mood in a digital music collection application or website. In order to establish the framework, we went through three different stages of the design process.In this paper, we present the three different stages and justify why they are required

Construction of Fuzzy Signature from Data: An Example of SARS Pre-clinical Diagnosis System

There are many areas where objects with very complex and sometimes interdependent features are to be classified; similarities and dissimilarities are to be evaluated. This makes a complex decision model difficult to construct effectively. Fuzzy signatures are introduced to handle complex structured data and interdependent feature problems. Fuzzy signatures can also used in cases where data is missing. This paper presents the concept of a fuzzy signature and how its flexibility can be used to quickly construct a medical pre-clinical diagnosis system. A Severe Acute Respiratory Syndrome (SARS) pre-clinical diagnosis system using fuzzy signatures is constructed as an example to show many advantages of the fuzzy signature. With the use of this fuzzy signature structure, complex decision models in the medical field should be able to be constructed more effectively

Relevance Judgment Convergence Degree – A Measure of Inconsistency among Assessors for Information Retrieval

Relevance judgment of human assessors is inherently subjective and dynamic when evaluation datasets are created for Information Retrieval (IR) systems. However, a small group of experts’ relevance judgment results are usually taken as ground truth to “objectively” evaluate the performance of the IR systems. Recent trends intend to employ a group of judges, such as outsourcing, to alleviate the potentially biased judgment results stemmed from using only a single expert’s judgment. Nevertheless, different judges may have different opinions and may not agree with each other, and the inconsistency in human relevance judgment may affect the IR system evaluation results. In this research, we introduce a Relevance Judgment Convergence Degree (RJCD) to measure the quality of queries in the evaluation datasets. Experimental results reveal a strong correlation coefficient between the proposed RJCD score and the performance differences between the two IR systems

The impact of topical mupirocin on peritoneal dialysis infection rates in Singapore general hospital.

Background. Peritonitis and exit-site infections (ESI) are major causes of technique failure and morbidity in peritoneal dialysis (PD) patients. Topical mupirocin on the exit-site has been shown to reduce such complications and prolong life in PD. Since the year 2000, such an approach has been adopted for our new incident PD population. We now report the results of this new protocol. We also studied the effect of co-morbidity on peritonitis occurrence. Methods. A total of 740 incident PD patients were studied. Patients were divided into two groups based on year of entry into PD (Group 1 from January 1998–December 1999 without topical mupirocin and Group 2 from January 2000–March 2004 with topical mupirocin). Variables studied included gender, age, diabetic status, ischaemic heart disease, peripheral vascular disease, cerebrovascular disease and serum albumin. Results. Topical mupirocin at the exit-site has led to a significant reduction in peritonitis rate (0.443 vs 0.339 episodes/patient-year; P<0.0005) and ESI (0.168 vs 0.156 episodes/patient-year; P<0.005) attributed primarily to the significant reduction in Staphylococcus aureus infections. There was an unexpected finding of lower Pseudomonas aeruginosa peritonitis in the mupirocin group (P<0.005). Stepwise multiple logistic regression analysis revealed that only mupirocin application and serum albumin were significant predictors of peritonitis. Conclusions. Our study, although limited by its retrospective nature, demonstrated that topical mupirocin was associated with a significant reduction in ESI and peritonitis with unexpected findings of lower Pseudomonas peritonitis. Serum albumin prior to the initiation of PD was a strong predictor of subsequent peritonitis. Mupirocin, with its low toxicity, ease of application and demonstrable beneficial effect in reducing ESI and peritonitis is now used on all incident PD patients

Unlocking social media and user generated content as a data source for knowledge management

The pervasiveness of Social Media and user-generated content has triggered an exponential increase in global data volumes. However, due to collection and extraction challenges, data in many feeds, embedded comments, reviews and testimonials are inaccessible as a generic data source. This paper incorporates Knowledge Management framework as a paradigm for knowledge management and data value extraction. This framework embodies solutions to unlock the potential of UGC as a rich, real-time data source for analytical applications. The contributions described in this paper are threefold. Firstly, a method for automatically navigating pagination systems to expose UGC for collection is presented. This is evaluated using browser emulation integrated with dynamic data collection. Secondly, a new method for collecting social data without any a priori knowledge of the sites is introduced. Finally, a new testbed is developed to reflect the current state of internet sites and shared publicly to encourage future research. The discussion benchmarks the new algorithm alongside existing data extraction techniques and provides evidence of the increased amount of UGC data made accessible by the new algorithm

EEG Signal Analysis of Writing and Typing between Adults with Dyslexia and Normal Controls

EEG is one of the most useful techniques used to represent behaviours of the brain and helps explore valuable insights through the measurement of brain electrical activity. Hence, plays a vital role in detecting neurological conditions. In this paper, we identify some unique EEG patterns pertaining to dyslexia, which is a learning disability with a neurological origin. Although EEG signals hold important insights of brain behaviours, uncovering these insights are not always straightforward due to its complexity. We tackle this using machine learning and uncover unique EEG signals generated in adults with dyslexia during writing and typing as well as optimal EEG electrodes and brain regions for classification. This study revealed that the greater level of difficulties seen in individuals with dyslexia during writing and typing compared to normal controls are reflected in the brainwave signal patterns