Pollution from quarry activities has a substantial environmental impact on many countries. This issue should be addressed accordingly as its impact may introduce various health-related problems to the surrounding community. One alternative is to increase awareness for the younger generation and society at large. However, environmental data modelling, specifically on quarry activities, has thus far targeted engineers and professionals, not school children, such as for knowledge exploration or learning material. At the same time, the number of students enrolling in STEM courses is continuously declining. Hence, this research aims to develop the environmental virtual interactive based education and learning model called PRInK to foster STEM education. Five components of the proposed model were identified: a) Computer-Assisted Learning; b) Motivation Level; c) Green Environmental Data; d) Learning Outcome; and e) Problem Context. The actual environmental scientific data were used in the simulation and visualisation. Experts in these fields verified the components. The result of the analysis reveals 17 groups of elements, which were further categorised into 58 sub-elements. The model then was validated through prototype development and users validation. The testing and validation of the prototype were carried out on secondary school children, with the results proving the usability and practicality of the model and showed the increased STEM motivation and interest. The PRInK model and the prototype increase society’s awareness about environmental issues starting from school, increase STEM interest and improve the overall quality of life through a shared understanding for future generations.
Green and sustainability issues are being considered as the alternative effort to ensure the long-time usage and durable of a software. The overall target for green software is to produce sustainable software products with minimal negative impact on the environment. In general, sustainability in software is associated with the ability to operate in a longer time and viable in their environments. Issues regarding sustainability are usually based on economy, social, and environmental view. In order to achieve and maintain sustainability in software, software process should undergo and comply with green. Previous studies emphasis on green hardware in respect to energy consumption, power consumption, waste reduction and disposal. However, it seems lack of studies on green software even though software has impact indirectly to the environment and to the software itself. This paper presents the empirical study conducted in Malaysia to investigate the sustainable practices in software process toward achieving green process and environment. One hundred and two (102) participants were involved in this survey and most of them were software engineers and software developers. The results reveal that the sustainability practices are important and relevant for green software process.
The potential of indoor unmanned aerial vehicle (UAV) localization is paramount for diversified applications within large industrial sites, such as hangars, malls, warehouses, production lines, etc. In such real-time applications, autonomous UAV location is required constantly. This paper comprehensively reviews radio signal-based wireless technologies, machine learning (ML) algorithms and ranging techniques that are used for UAV indoor positioning systems. UAV indoor localization typically relies on vision-based techniques coupled with inertial sensing in indoor Global Positioning System (GPS)-denied situations, such as visual odometry or simultaneous localization and mapping employing 2D/3D cameras or laser rangefinders. This work critically reviews the research and systems related to mini-UAV localization in indoor environments. It also provides a guide and technical comparison perspective of different technologies, presenting their main advantages and disadvantages. Finally, it discusses various open issues and highlights future directions for UAV indoor localization.
Software ageing is a phenomenon that normally occurs in a long running software. Progressive degradation of software performance is a symptom that shows software is getting aged and old. Researchers believe that the ageing phenomenon can be delayed by applying anti-ageing techniques towards the software or also known as software rejuvenation. Software ageing factors are classified into two categories: internal and external factors. This study focuses on external factors of software ageing, and are categorized into three main factors: environment, human and functional. These three factors were derived from empirical study that been conducted involving fifty software practitioners in Malaysia. The anti-ageing model (SEANA model) is proposed to support in preventing the software from prematurely aged, thus prolong its usage and sustainable in their environment. SEANA model is implemented in collaboration with a government agency in Malaysia to verify and validate the model in real environment. The prototype of SEANA model was developed and applied in the real case study. Furthermore, the anti-ageing guideline and actions are suggested for ageing factors to delay the ageing phenomenon in application software and further support the greenness and sustainability of software products.
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