Accuracy and stability analysis of path loss exponent measurement for localization in wireless sensor network

In wireless sensor network localization, path loss model is often used to provide a conversion between distance and received signal strength (RSS). Path loss exponent is one of the main environmental parameters for path loss model to characterize the rate of conversion. Therefore, the accuracy of path loss exponent directly influences the results of RSS-to-distance conversion. When the conversion requires distance estimation from RSS value, small error of measured path loss exponent could lead to large error of the conversion output. To improve the localization results, the approaches of measuring accurate parameters from different environments have become important. Different approaches provide different measurement stabilities, depending on the performance and robustness of the approach. This paper presents four calibration approaches to provide measurements of path loss exponent based on measurement arrangement and transmitter/receiver node’s allocation. These include one-line measurement, online-update spread locations measurement, online-update small-to big rectangular measurement, and online-update big-to-small rectangular measurement. The first two are general approaches, and the last two are our newly proposed approaches. Based on our research experiments, a comparison is presented among the four approaches in terms of accuracy and stability. The results show that both online-update rectangular measurements have better stability of measurements. For accuracy of measurement, online-update big-to-small rectangular measurement provides the best result after convergence

Measurement arrangement for the estimation of path loss exponent in wireless sensor network

Path loss model is generally used to relate distance and signal strength in wireless applications. This has been widely implemented in ranging, localization, and location tracking systems. A range of extension models have been proposed to enhance the performance for various environments and applications. Nevertheless, path loss exponent remains its significance as the main factor in the model regardless of how the model is varied. Based on the nature as an exponent of the model, inaccurate path loss exponent amplifies the error if it is used to estimate distance from received signal strength. Therefore, measurement of accurate value for path loss exponent becomes very important as it directly influences the output of distance estimation. Researchers have been studying the methods of measuring accurate path loss exponent in various environments. Instead of emphasizing the calculation process, this paper focuses more on the allocation of transmitters and receivers, and the arrangement among them. From the results obtained from experiments, properly arranged transmitter and receiver nodes provides better estimation of the path loss exponent. Based on the results, this paper also proposes a suitable nodes arrangement scheme for path loss exponent estimation

Effects of distributive justice, perceived organisational support and intrinsic motivation on Malaysian volunteer coaches' affective commitment

The influence of distributive justice in promoting affective commitment among volunteer coaches may be explained by perceived organisational support and intrinsic motivation. This paper examines the mediation of these psychological processes in relating distributive justice and affective commitment of 165 Malaysian public schools volunteer coaches. Results of structural equation modelling with AMOS analysis indicate that perceived organisation support serves as a mediator between distributive justice and affective commitment. Intrinsic motivation was found insignificantly related with distributive justice. However, both perceived organisation support and coaching intrinsic motivation have similar predictive propensity on affective commitment. Theoretical and practical implications were discussed

Clustering In Fingerprint Recognition System.

Clustering of fngerprints can help to reduce the complesity of the search process in a database

Challenges and Achievements of Senior Citizen Pursuing Open and Distance Learning

In the era of technology and borderless world, open and distance learning has become a choice for many adults who wish to pursue tertiary education. In responding to this development, many higher education institutions, including Open University Malaysia, have designed various academic programmes to meet the needs of adult learners. Senior citizens naturally experience a decline in their physical, cognitive, motor and memory abilities. Despite having to face such challenges, many senior citizens have enrolled at the Open University Malaysia. The objective of this study is to examine their academic performance, analyse it by gender, age and zone of learning centres; and identify the issues and challenges they faced. Senior citizens who graduated from two schools, the Faculty of Applied Social Sciences (now known as Cluster of Education and Social Sciences) and OUM Business School (now known as Cluster of Business and Management), were included in this study. Secondary data was used to analyse learners’ academic performance while interviews were conducted to identify the challenges they faced. The findings indicated that they had faced difficulties in relation to their health and information technology skills but still performed well. (Abstract by authors

Robustness of Physics-Informed Neural Networks to Noise in Sensor Data

Physics-Informed Neural Networks (PINNs) have been shown to be an effective way of incorporating physics-based domain knowledge into neural network models for many important real-world systems. They have been particularly effective as a means of inferring system information based on data, even in cases where data is scarce. Most of the current work however assumes the availability of high-quality data. In this work, we further conduct a preliminary investigation of the robustness of physics-informed neural networks to the magnitude of noise in the data. Interestingly, our experiments reveal that the inclusion of physics in the neural network is sufficient to negate the impact of noise in data originating from hypothetical low quality sensors with high signal-to-noise ratios of up to 1. The resultant predictions for this test case are seen to still match the predictive value obtained for equivalent data obtained from high-quality sensors with potentially 10x less noise. This further implies the utility of physics-informed neural network modeling for making sense of data from sensor networks in the future, especially with the advent of Industry 4.0 and the increasing trend towards ubiquitous deployment of low-cost sensors which are typically noisier

Investigative baseline reference on the status of pork pH, shear force, colour, drip and cooking loss in RYR1 mutation free, commercial 3-way crosses in Malaysia

This paper attempts to provide findings of an investigative study on the baseline status of the pork quality in Malaysia. With consumer preferences changing towards the selection of good quality meat for consumption, there is a need to establish an investigative reference for the operators in the industry to gauge the performance of their animals and pork quality. This is also important to increase the competitiveness among producers to continuously improve the pork quality available to consumers. In this study, 30 commercial three-way crossed female pigs were randomly selected from government accredited abattoirs from east and west Malaysia and longisimus dorsi were collected for the determination of pH, drip loss, cooking loss, shear force and colour. All animals were screened for the RYR1 gene and the results were then compiled with statistical analysis to obtain an investigative baseline pork quality data in Malaysia. The average pork quality obtained from this study falls within the category of Red, Soft and Exudative (RSE), with an average ultimate pH of 5.83, drip loss more than 5% and L* values at 45.94. We have proposed an investigative baseline meat quality data for Malaysian pork from the average commercial pork quality data obtained. The proposed investigative pork quality baseline data in Malaysian is comparable in terms of studies done in other established countries and/or with international standards and falls within the RSE category of acceptable quality. It provides an investigative benchmark for researchers and end-producers to judge the quality of pork in an objective manner, both for consumption and for export purpose. Moreover, continuous selection against the RYR1 gene has successfully removed the gene from the sample size above, but constant random monitoring is still advisable if farms aim to ensure the elimination of this gene from their herd