Investigation of graphene channel interaction with yeast cell for cell counting application

Graphene superior and unique properties make it a suitable material for biosensor. In this work, graphene interaction with yeast cell is investigated for development of graphenebased cell counter. The fabricated graphene channel was characterized by means of two-terminal and solution-gated three-terminal measurement setup. The correlation between graphene channel resistance and cell concentration was confirmed. The yeast cell was found to give n-type doping which modulate the conductivity of graphene channel

Rasch strategies for evaluating quality of the conceptions and alternative assessment survey (CETAS)

Due to society demand for educational development, education in Malaysia has begun to utilize alternative assessment approach in schools and universities. This study developed Conceptions and Alternative Assessment Survey (CETAS) to examine lecturers’ conceptions of assessment (AC) and their practice of alternative assessment (AAP). In order for CETAS to be useful, a pilot study was conducted to examine quality of items in using Rasch Analysis approach. A total of 38 lecturers involved in this study. After item analysis, this study found that four items, Item 7 (AC), Item 8 (AC), Item 16 (AAP) and Item 30 (AAP) did not meet the requirement of fit statistics analysis and local item dependency. Therefore, four items were deleted while other 58 are suitable to be used for measuring the intended constructs. In addition, the scale calibration analysis also revealed that Scale 3 (slightly disagree) was not well-functioning. Therefore, after consideration of analysis and expert review, Scale 3 was collapsed leaving CETAS with 5 scales. Nevertheless, CETAS has a good item and person reliability and can be used to examine lecturers’ conceptions of assessment and their practices of alternative assessment

A Significant Feature Selection in the Mahalanobis Taguchi System using Modified-Bees Algorithm

This paper compares the performance of orthogonal array (OA), modified-Bees Algorithm (mBA) and conventional Bees Algorithm (BA) in significant feature selection scheme (optimization) of the Mahalanobis-Taguchi System (MTS) methodology. The main contribution of this work is to address both performances in terms of computing cost i.e. computing time as well as classification accuracy rate. Several studies have been conducted to evaluate the performance of OA against other heuristic search techniques in MTS methodology however, discussions in terms of the computing speed performances were found to be lacking. Instead, the accuracy performances were given the emphasis by drawing criticisms towards the deployment of OA as ineffective as compared to other state-of-the-art heuristic algorithms. Bees Algorithm (BA) is one heuristic search technique that discovers optimal (or near optimal) solutions using search strategy mimics the social behaviour of a honeybee colony. In this comparison work, modified-BA (mBA) is introduced into the optimization scheme of MTS with a modification on its neighbourhood search mechanism from the original BA. Instead of searching in random mode, a backward selection method is proposed. MD is used as the result assessment metric while the larger-the-better type of SNR is deployed as the algorithm\u27s objective function. The historical heart liver disease data are used as the case study on which the comparisons between OA, mBA and BA performances specifically in terms of the computing speed are made and addressed. The outcomes showed a promising performance of the mBA as compared to OA with a comparable classification accuracy rate. Eventhough OA outperformed mBA in terms of computational speed, the MTS manage to classify at the expense of lower number of variables suggested by mBA. The mBA also converges faster than the conventional BA in finding the potential solution of the case problem

Review of feature extraction approaches on biomedical text classification

The overcoming volume of online biomedical literature causes congestion of data and difficulties in organizing these documents and also to retrieve the required documents from the database, especially in the Medline database. One of the solutions to surpass the overwhelming of documents is to apply classification. However, each document must be represented by a set of terminology or feature vectors. The identification of terminology or feature from biomedical literature is one of the most important and challenging tasks in text classification. This is due to a large number of new features and entities that appear in the biomedical domain. In addition, combining sets of features from different terminological resources leads to naming conflicts such as homonymous use of names and terminological ambiguities. Therefore, the purpose of this research is to investigate and evaluate the effective ways for extracting the relevant and meaningful features in order to increase the classification accuracy and improve the performance of web searches. Towards this effort, we conduct several classification experiments to evaluate and compare the effectiveness of feature extraction approaches for extracting the relevant and informative features from the biomedical literature. For our experiments, we use two different sets of features, which are a set of features that are extracted using the Genia tagger tool and set of features that are extracted by medical experts from Pusat Perubatan Universiti Kebangsaan Malaysia (PPUKM). The results show the performance of classification using features that are extracted by medical experts outperform the performance of classification using the Genia Tagger tool when applying feature selection method

A mobile game SDK for remote collaborative between two users in augmented and virtual reality

Remote collaboration is important in Augmented Reality (AR) and Virtual Reality (VR) that allow users to communicate and interact with each other. Mobile games are gaining its popularity due to its portability and lower in cost. Software Development Kit (SDK) allows developer to speed up the development process. However, most of the collaboration of these technologies only focus on either AR or VR independently. Besides, most AR and VR that had been developed are only available in expensive devices but not in mobile devices. Therefore, this research aims to create a remote collaboration between AR and VR with mobile games. There are four phases have been carried out, analysis phases, development phase, construction phase and evaluation phase. The evaluation has been performed and it is based on the usability and user acceptance. The usability results show the application is accepted by the user. User acceptance results show the application works accordingly. Based on the results, this research has successfully produced a working SDK for remote collaboration between AR and VR with mobile games

Effect of scanning parameters on dose-response of radiochromic films irradiated with photon and electron beams

Proper dosimetry settings are crucial in radiotherapy to ensure accurate radiation dose delivery. This work evaluated scanning parameters as affecting factors in reading the dose-response of EBT2 and EBT3 radiochromic films (RCFs) irradiated with clinical photon and electron beams. The RCFs were digitised using Epson� Expression� 10000XL flatbed scanner and image analyses of net optical density (netOD) were conducted using five scanning parameters i.e. film type, resolution, image bit depth, colour to grayscale transformation and image inversion. The results showed that increasing spatial resolution and deepening colour depth did not improve film sensitivity, while grayscale scanning caused sensitivity reduction below than that detected in the Red-channel. It is also evident that invert and colour negative film type selection negated netOD values, hence unsuitable for scanning RCFs. In conclusion, choosing appropriate scanning parameters are important to maintain preciseness and reproducibility in films dosimetry

Radiobiological Characterization of the Radiosensitization Effects by Gold Nanoparticles for Megavoltage Clinical Radiotherapy Beams

Gold nanoparticles (AuNPs) have been experimentally proven to induce radiosensitization effects particularly for kilovoltage photon beam. Theoretically, AuNPs bombarded with kilovoltage photon beam would increase the photoelectric interactions cross section and hence increase cell death. Despite the intriguing finding, this type of beam is not common in clinical radiotherapy and possesses limited application compare to megavoltage beams. In this study, quantification of the radiosensitization effects acquired from clinical megavoltage photon, electron, and high-dose rate (HDR) gamma rays from Ir-192 source were conducted. In addition, radiobiological characterization of the cell survival curves that are commonly described by linear-quadratic (LQ) model was also evaluated using multi-target (MT) and repairable conditionally repairable (RCR) model. Significant sensitization enhancement ratios (SER) were obtained particularly for 15 MeV electron beams in which the amplification of radiation effects by AuNPs is up to the factor of 1.78. The results also demonstrate validity of experimental models to describe the cell survival curve and determine the radiosensitization effects. However, slight variation was observed for SER values computed from each model which indicate the importance to specify the quantification method. Adoption of radiobiological models and their parameters could also be employed as indicator to explain the mechanistic events in the AuNPs radiosensitization effects. As conclusion effective radiosensitization by megavoltage clinical radiotherapy beams could be achieved and precise radiobiological characterization drawn from radiobiological models may provide insight towards radiobiological impacts induced by AuNPs

Dose enhancement effects by different size of gold nanoparticles under irradiation of megavoltage photon beam

Gold nanoparticles (AuNPs) have been extensively investigated as dose enhancement agent to increase the lethal dose to the tumourswhile minimizing dose to the normal tissue. Their intriguing properties and characteristics such as small size and shape provide favorable option in increasing radiotherapy therapeutic efficiency. In this study, the effects of AuNPs size on the dose enhancement effects irradiated under megavoltage photon beams were investigated. The study was conducted in-vitro on HeLa cells using AuNPs of 5 nm and 15 nm sizes. The cells samples were incubated with AuNPs and irradiated with photon beam of energy 6 MV and 10 MV at 100 cm SSD and 10 cm x10 cm field size. Clonogenic assay were performed to observe the dose enhancement effects on cell survival. Dose enhancement factor (DEF) were extrapolated and evaluated from the cell survival curves. The results show that both sizes of AuNPs produce dose enhancement with the larger size AuNPs of 15 nm produce more dose enhancement compare to 5 nm AuNPs for 6 MV photon beam. Dose enhancements were observed for 10 MV photon beams but DEF for both sizes AuNPs shows no differences. In conclusion, larger size AuNPs produce higher dose enhancement compare to small size of AuNPs which conclude that nanoparticles size is important factor that need to be taken into account for AuNPs to be applied in radiotherapy