Biblio

The aim of this paper is to explore the performance of two well-known wave energy converters (WECs) namely Floating Buoy Point Absorber (FBPA) and Oscillating Surge (OS) in onshore and offshore locations. To achieve clean energy targets by reducing greenhouse gas emissions, integration of renewable energy resources is continuously increasing all around the world. In addition to widespread renewable energy source such as wind and solar photovoltaic (PV), wave energy extracted from ocean is becoming more tangible day by day. In the literature, a number of WEC devices are reported. However, further investigations are still needed to better understand the behaviors of FBPA WEC and OS WEC under irregular wave conditions in onshore and offshore locations. Note that being surrounded by Bay of Bengal, Bangladesh has huge scope of utilizing wave power. To this end, FBPA WEC and OS WEC are simulated using the typical onshore and offshore wave height and wave period of the coastal area of Bangladesh. Afterwards, performances of the aforementioned two WECs are compared by analyzing their power output.

Embedded systems must address a multitude of potentially conflicting design constraints such as resiliency, energy, heat, cost, performance, security, etc., all in the face of highly dynamic operational behaviors and environmental conditions. By incorporating elements of intelligence, the hope is that the resulting “smart” embedded systems will function correctly and within desired constraints in spite of highly dynamic changes in the applications and the environment, as well as in the underlying software/hardware platforms. Since terms related to “smartness” (e.g., self-awareness, self-adaptivity, and autonomy) have been used loosely in many software and hardware computing contexts, we first present a taxonomy of “self-x” terms and use this taxonomy to relate major “smart” software and hardware computing efforts. A major attribute for smart embedded systems is the notion of self-awareness that enables an embedded system to monitor its own state and behavior, as well as the external environment, so as to adapt intelligently. Toward this end, we use a System-on-Chip perspective to show how the CyberPhysical System-on-Chip (CPSoC) exemplar platform achieves self-awareness through a combination of cross-layer sensing, actuation, self-aware adaptations, and online learning. We conclude with some thoughts on open challenges and research directions.

As a very valuable cultural heritage, palm leaf manuscripts offer a new challenge in document analysis system due to the specific characteristics on physical support of the manuscript. With the aim of finding an optimal binarization method for palm leaf manuscript images, creating a new ground truth binarized image is a necessary step in document analysis of palm leaf manuscript. But, regarding to the human intervention in ground truthing process, an important remark about the subjectivity effect on the construction of ground truth binarized image has been analysed and reported. In this paper, we present an experiment in a real condition to analyse the existance of human subjectivity on the construction of ground truth binarized image of palm leaf manuscript images and to measure quantitatively the ground truth variability with several binarization evaluation metrics.