Search

This paper describes the study of overlapping leukaemia cells based on geometric features for identification and classification. Geometric features of blood cells are proposed to identify and classify overlapping cells into groups based on different overlapping degrees and the number of overlapped cells. In the proposed method, the percentage of average accuracy for identifying overlapping cells reached 98 percent. The proposed method can segment white blood cells from the overlapping cells with an overlapping degree of 70 percent. Improved Watershed Algorithm successfully increased 36.89 percent of accuracy in WBC segmentation. It reduced 46.12 percent of the over-segmentation problem. Tests of cell counting are conducted in the two stages, which are before and after the process of identification and classification of overlapping cells. The average percentage of total cell count is 83.31 percent, the average percentage of WBC counting is 84.8 percent, and the average percentage of RBC counting is 60.55 percent. The proposed method is efficient in identifying and classifying overlapping cells for increasing the accuracy of cell counting.

Sinusoidal oscillators are often used in many industrial applications. Hartley oscillator is the basic kind of sinusoidal oscillators, so the study of its performance is decisive. While designing a sinusoidal oscillator, the traditional Barkhausen criterion is widely used for its simplicity, however it is only necessary condition for oscillating. If the device characteristic changes in some way, the Barkhausen criterion may yield false results. A new necessary and sufficient oscillation criterion for Hartley oscillator is firstly proposed in this research to take the place of the traditional Barkharsen criterion based on our recent research (Chen’s Electric Unifying Approach). The proposed approach is a simple oscillation determining criterion which builds up a stable sinusoidal oscillator. The derived oscillation criterion reveals an accurate oscillating condition and a more precise oscillating frequency.

OBJECTIVE Hyaluronic acid (HA) can be degraded over time. However, persistence of the effects after injection laryngoplasty (IL) for unilateral vocal fold paralysis (UVFP), longer than expected from HA longevity, has been observed. The purpose of the study was to develop a methodology with clinical utility for objective evaluation of the temporal change in HA volume after IL using artificial intelligence (AI)-based ultrasonic assessment. DESIGN, SETTING AND PARTICIPANTS Imaging phantoms simulating injected HA were built in different volumes for designing the algorithm for machine learning. Subsequently, five adult patients who had undergone IL with HA for UVFP were recruited for clinical evaluation. MAIN OUTCOME MEASURES Estimated volumes were evaluated for injected HA by the automatic algorithm as well as voice outcomes at 2 weeks, and 2 and 6 months after IL. RESULTS On imaging phantoms, contours on each frame were described well by the algorithm and the volume could be estimated accordingly. The error rates were 0%-9.2%. Moreover, the resultant contours of the HA area were captured in detail for all participants. The estimated volume decreased to an average of 65.76% remaining at 2 months and to a minimal amount at 6 months while glottal closure remained improved. CONCLUSION The volume change of the injected HA over time for an individual was estimated non-invasively by AI-based ultrasonic image analysis. The prolonged effect after treatment, longer than HA longevity, was demonstrated objectively for the first time. The information is beneficial to achieve optimal cost-effectiveness of IL and improve the life quality of the patients.

Image search is a challenging process in the field of Content Based Image Retrieval (CBIR). Image search-by-example, search-by-keyword and search-by-sketch methods seldom provide user interface that allows user to accurately formulate their search intent easily. To overcome such issue, a novel image search interface-Semantic Visual Query Builder (SeVQer) is proposed as a non-verbal interface which allows user to drag and drop from the image data provided to formulate user query. The drag and drop mechanism minimizes the difficulty of verbalizing query image into keywords or sketching a correct drawing of the query image. SeVQer was implemented and compared with 3 image search methods (search-by-example, search-by-keyword and search-by-sketch) in terms of task completion time and user satisfaction using traffic images. SeVQer achieved statistically significant lower task completion time with an average of 28 sec, a promising 50% reduction than search-by-sketch (average of 56 sec). The significance of this work is two-fold: the SeVQer user interface allows user to easily formulate intent specific query, while the novel architecture and methodology reduces the semantic gap in general.

In this research, we developed a serious game prototype for the visually impaired children in learning spatial navigation skills in a virtual environment. By providing audio and haptic feedback, the game, 'Hungry Cat', helps the players to gain spatial information about the virtual rooms while exploring various game levels. Two evaluations were conducted to assess the effectiveness of the learning tool. The first test was the food finding test which required the participants to locate food within the game level they have just explored. The second was the wire net test which allowed the participants to demonstrate their spatial mental map of the room. The performance of different groups of the visually impaired children such as between low vision and no vision, and with learning difficulty and without learning difficulty are also compared. Results showed that the visually impaired children are able to construct a spatial mental map of the virtual rooms after attempting all the levels in the game.

Mean daily rainfall of more than 30mm could result in flood hazard. Accurate prediction of rainfall intensity could help in forecasting of flash flood and help to save lives and properties. One of the common machine learning techniques in rainfall prediction is Radial Basis Function (RBF) neural network. Rainfall intensity is classified into four categories, i.e. light ( 50mm) in this study. The rainfall intensity categories is forecasted using the RBF network model utilizing the daily meteorology data for Kuching, Sarawak, Malaysia. The input vectors being considered for the RBF network model are minimum, maximum and mean temperature (°C), mean relative humidity (%), mean wind speed (m/s), mean sea level pressure (hPa) and mean precipitation (mm) for the year 2009 to 2013. The prime focus in this paper is to analyse the ramification of the training data size, number of hidden neurons, and different input variables (i.e. combination of meteorology data) in influencing the performance of the RBF network model. From this study, it could be concluded that, the factor that would influence the performance of the RBF model is only the input variables used, if and only if the network model is equipped with sufficient number of hidden neurons and trained with adequate number of training data. Another interesting observation from this study is that, the RBF network model produced consistent result throughout the testing using a specific hidden neuron number when the RBF network is retrained and tested.

Signature is an important legal personal identification. Selecting a good feature representation is a significant step in designing a signature verification system. Single resolution function approach used in on-line signature verification faces the difficulty in identifying the intra-class variations of the features extracted. Such an approach might cause the acceptance of forged signatures that have similar patterns as the original and the rejection of genuine signatures that have high intra-class variations. This paper discusses the intra-class variation representation in on-line signature verification using wavelet and fractal analysis. With the achievement performance of an average improvement of 18% in genuine test verification rate and 7% in forged test verification rate compared to the single resolution function approach, it proves that the intra-class variations are important for on-line signature verification.

Building upon social exchange theory which explains how power is gained and lost in the process of influence between an agent and the target, this article hypothesized the impact of supervisors’ and subordinates’ power bases on the usage of influence tactics by the supervisors. Bases of power of supervisors, subordinates and influence tactics were conceptualized as seven-, seven- and nine-dimensional constructs, respectively. Three hundred and eighty-five pairs of Malaysian managers and executives working in large multinational companies participated. Currently, the manufacturing sector is considered as one of the cornerstone of Malaysia’s economic diversification strategy. The findings suggested that supervisors apply various influence tactics on their subordinates.

On-site measurements from rain gauge provide important information for the design, construction, and operation of water resources engineering projects, groundwater potentials, and the water supply and irrigation systems. A dense gauging network is needed to accurately characterize the variation of rainfall over a region, unfitting for conditions with limited networks, such as in Sarawak, Malaysia. Hence, satellite-based algorithm estimates are introduced as an innovative solution to these challenges. With accessibility to dataset retrievals from public domain websites, it has become a useful source to measure rainfall for a wider coverage area at finer temporal resolution. This paper aims to investigate the rainfall estimates prepared by Tropical Rainfall Measuring Mission (TRMM) to explain whether it is suitable to represent the distribution of extreme rainfall in Sungai Sarawak Basin. Based on the findings, more uniform correlations for the investigated storms can be observed for low to medium altitude (>40 MASL). It is found for the investigated events of Jan 05-11, 2009: the normalized root mean square error (NRMSE = 36.7 %); and good correlation (CC = 0.9). These findings suggest that satellite algorithm estimations from TRMM are suitable to represent the spatial distribution of extreme rainfall.

Segmentation is the process of extracting points, lines or regions, which are then used as inputs for complementary tasks such as registration, measurement, movement analysis, visualization , etc in MRI. The noise in MR images degrades the image quality and also affect on the segmentation process which can lead to wrong diagnosis. The main aim of this study is to suggest a system to enhance the quality of the human brain MRI. In the proposed system, median filter is used for image enhancement of brain MRI and fuzzy c-means for segmentation purpose. The proposed method is completely automatic that is there is no user involvement in the proposed system. The system is tested on different kinds of brain MR images and proved robust against noise as well as segments the images fast with improvements.

Resumo Objetivo: Este trabalho busca examinar o relacionamento entre os determinantes do desempenho organizacional, como apoio da alta administração, foco no cliente, orientação dos funcionários, orientação tecnológica e orientação empreendedora na Malásia. Metodologia: Um projeto de pesquisa quantitativa foi aplicado para este estudo. Os dados foram coletados através de pesquisa por questionários aplicados a donos de negócio e gerentes sêniores que trabalham em PMEs localizadas em três estados malaios, utilizando a técnica da amostragem orientada. O SmartPLS 2.0 (M3) foi utilizado para testar as hipóteses. Resultados: Os resultados sugerem que a orientação tecnológica e a orientação empreendedora são fatores significativos de sucesso para as PMEs em termos do desempenho financeiro e não financeiro. Além disso, descobriu-se que o apoio da alta administração está significativa e positivamente relacionado ao desempenho financeiro. Contribuições: A análise empírica indica que a orientação tecnológica e a orientação empreendedora agregam mais valor ao desempenho organizacional. Portanto, é vital para as PMEs focar nesses dois fatores críticos de sucesso para melhorar o seu desempenho. Abstract Purpose: This paper seeks to examine the relationship between the determinants of organizational performance such as top management support, customer focus, employees’ orientation, technology orientation, and entrepreneurial orientation in Malaysia. Design/methodology/approach: A quantitative research design was applied for this study. Data was collected through survey questionnaires applied to business owners and senior managers working in SMEs located in three Malaysian states, using purposive sampling technique. SmartPLS 2.0 (M3) was applied to test the hypotheses. Findings: The findings suggest that both technology and entrepreneurial orientations are significant success factors for SMEs in terms of financial and non-financial performance. In addition, top management support is found to be significantly and positively related to financial performance. Originality/value: The empirical analysis indicates that technology orientation and entrepreneurial orientation add more value to organizational performance. Therefore, it is vital for SMEs to focus on these two critical success factors in order to improve their performance.