1519 hits

Road accidents are increasing every year in Malaysia, and it is always challenging to collect reliable pre-crash data in the transportation community. Existing studies relied on simulators, police crash reports, questionnaires, and surveys to study Malaysia’s drivers’ behavior. Researchers previously criticized such methods for being biased and unreliable. To fill in the literature gap, this study presents the first naturalistic driving study in Malaysia. Thirty drivers were recruited to drive an instrumented vehicle for 750 km while collecting continuous driving data. The data acquisition system consists of various sensors such as OBDII, lidar, ultrasonic sensors, IMU, and GPS. Irrelevant data were filtered, and experts helped identify safety criteria regarding multiple driving metrics such as maximum acceptable speed limits, safe accelerations, safe decelerations, acceptable distances to vehicles ahead, and safe steering behavior. These thresholds were used to investigate the inf.....

1067 hits

This work proposes a pattern recognition model for static gestures in Malaysian Sign Language (MSL) based on Machine Learning (ML) techniques. The proposed model is divided into two phases, namely, data acquisition and data processing. The first phase involves capturing the required sign data, such as the shape and orientation of the hand, to construct a sensor-based SL dataset. The dataset is collected using a DataGlove device. This device is used to measure the motions of the fingers and wrists. Sixty-four features represent each sign in the dataset. The collected sensory dataset is cleaned in the second phase by removing redundant data. Then, the features are scaled and normalised to exhibit symmetrical behaviour and eliminate outliers. Then, ten different ML techniques are utilised based on real-time data for SL gesture recognition. Experimental results confirmed the efficacy of the proposed pattern recognition model compared with previous work. ? 2021..

944 hits

This study proposes a new real-time sign recognition system based on a wearable sensory glove, which has 17 sensors with 65 channels. We introduce the DataGlove to recognize various, possibly complex hand gestures of the Malaysian Sign Language (MSL). With 65 data channels, DataGlove can satisfy the requirement suggested by the analysis of hand anatomy, kinematic and gestures. Four groups of sensors were tested to select the optimal sensors that can capture hand gesture information. Also, a 3D-printed humanoid arm is used to validate the sensor mounted on the glove. In an extensive set of experiments to test our system, five well-known MSL participants were chosen to perform 75 gestures, all taken from the MSL numbers, alphabet, and words. The error rate was used to check system performance. Discussion confirms that the proposed system competes well with an advanced benchmark of previous works is up 100% based on 14 criteria in term of the type of captured signals, recognised gestures,.....

505 hits

Increasing demand for open-source software (OSS) has raised the value of efficient selection in terms of quality; usability is an essential quality factor that significantly affects system acceptability and sustainability. Most large and complex software packages partitioned across multiple portals and involve many users - each with their role in the software package; those users have different perspectives on the software package, defined by their knowledge, responsibilities, and commitments. Thus, a multi-perspective approach has been used in usability evaluation to overcome the challenge of inconsistency between users' perspectives; the inconsistency challenge would lead to an ill-advised decision on the selection of a suitable OSS. This study aimed to assist the public and private organizations in evaluating and selecting the most suitable OSS. The evaluation of the OSS software packages to choose the best one is a challenging task owing to (a) multiple evaluation criteria, (b) cri.....

662 hits