A Logical Model and Data Placement Strategies for MEMS Storage Devices

MEMS storage devices are new non-volatile secondary storages that have outstanding advantages over magnetic disks. MEMS storage devices, however, are much different from magnetic disks in the structure and access characteristics. They have thousands of heads called probe tips and provide the following two major access facilities: (1) flexibility: freely selecting a set of probe tips for accessing data, (2) parallelism: simultaneously reading and writing data with the set of probe tips selected. Due to these characteristics, it is nontrivial to find data placements that fully utilize the capability of MEMS storage devices. In this paper, we propose a simple logical model called the Region-Sector (RS) model that abstracts major characteristics affecting data retrieval performance, such as flexibility and parallelism, from the physical MEMS storage model. We also suggest heuristic data placement strategies based on the RS model and derive new data placements for relational data and two-dimensional spatial data by using those strategies. Experimental results show that the proposed data placements improve the data retrieval performance by up to 4.0 times for relational data and by up to 4.8 times for two-dimensional spatial data of approximately 320 Mbytes compared with those of existing data placements. Further, these improvements are expected to be more marked as the database size grows.Comment: 37 page

Energy Academic Group Compilation of Abstracts 2012-2016

This report highlights the breadth of energy-related student research at NPS and reinforces the importance of energy as an integral aspect of today's Naval enterprise. The abstracts provided are from theses and a capstone project report completed by December 2012-March 2016 graduates.http://archive.org/details/energyacademicgr109454991

Review of flexible energy harvesting for bioengineering in alignment with SDG

To cater to the extensive body movements and deformations necessitated by biomedical equipment flexible piezoelectrics emerge as a promising solution for energy harvesting. This review research delves into the potential of Flexible Piezoelectric Materials (FPM) as a sustainable solution for clean and affordable energy, aligning with the United Nations' Sustainable Development Goals (SDGs). By systematically examining the secondary functions of stretchability, hybrid energy harvesting, and self-healing, the study aims to comprehensively understand these materials' mechanisms, strategies, and relationships between structural characteristics and properties. The research highlights the significance of designing piezoelectric materials that can conform to the curvilinear shape of the human body, enabling sustainable and efficient mechanical energy capture for various applications, such as biosensors and actuators. The study identifies critical areas for future investigation, including the commercialization of stretchable piezoelectric systems, prevention of unintended interference in hybrid energy harvesters, development of consistent wearability metrics, and enhancement of the elastic piezoelectric material, electrode circuit, and substrate for improved stretchability and comfort. In conclusion, this review research offers valuable insights into developing and implementing FPM as a promising and innovative approach to harnessing clean, affordable energy in line with the SDGs.</p

Review of flexible energy harvesting for bioengineering in alignment with SDG

To cater to the extensive body movements and deformations necessitated by biomedical equipment flexible piezoelectrics emerge as a promising solution for energy harvesting. This review research delves into the potential of Flexible Piezoelectric Materials (FPM) as a sustainable solution for clean and affordable energy, aligning with the United Nations' Sustainable Development Goals (SDGs). By systematically examining the secondary functions of stretchability, hybrid energy harvesting, and self-healing, the study aims to comprehensively understand these materials' mechanisms, strategies, and relationships between structural characteristics and properties. The research highlights the significance of designing piezoelectric materials that can conform to the curvilinear shape of the human body, enabling sustainable and efficient mechanical energy capture for various applications, such as biosensors and actuators. The study identifies critical areas for future investigation, including the commercialization of stretchable piezoelectric systems, prevention of unintended interference in hybrid energy harvesters, development of consistent wearability metrics, and enhancement of the elastic piezoelectric material, electrode circuit, and substrate for improved stretchability and comfort. In conclusion, this review research offers valuable insights into developing and implementing FPM as a promising and innovative approach to harnessing clean, affordable energy in line with the SDGs.</p

An inertial motion capture framework for constructing body sensor networks

Motion capture is the process of measuring and subsequently reconstructing the movement of an animated object or being in virtual space. Virtual reconstructions of human motion play an important role in numerous application areas such as animation, medical science, ergonomics, etc. While optical motion capture systems are the industry standard, inertial body sensor networks are becoming viable alternatives due to portability, practicality and cost. This thesis presents an innovative inertial motion capture framework for constructing body sensor networks through software environments, smartphones and web technologies. The first component of the framework is a unique inertial motion capture software environment aimed at providing an improved experimentation environment, accompanied by programming scaffolding and a driver development kit, for users interested in studying or engineering body sensor networks. The software environment provides a bespoke 3D engine for kinematic motion visualisations and a set of tools for hardware integration. The software environment is used to develop the hardware behind a prototype motion capture suit focused on low-power consumption and hardware-centricity. Additional inertial measurement units, which are available commercially, are also integrated to demonstrate the functionality the software environment while providing the framework with additional sources for motion data. The smartphone is the most ubiquitous computing technology and its worldwide uptake has prompted many advances in wearable inertial sensing technologies. Smartphones contain gyroscopes, accelerometers and magnetometers, a combination of sensors that is commonly found in inertial measurement units. This thesis presents a mobile application that investigates whether the smartphone is capable of inertial motion capture by constructing a novel omnidirectional body sensor network. This thesis proposes a novel use for web technologies through the development of the Motion Cloud, a repository and gateway for inertial data. Web technologies have the potential to replace motion capture file formats with online repositories and to set a new standard for how motion data is stored. From a single inertial measurement unit to a more complex body sensor network, the proposed architecture is extendable and facilitates the integration of any inertial hardware configuration. The Motion Cloud’s data can be accessed through an application-programming interface or through a web portal that provides users with the functionality for visualising and exporting the motion data

A High Density Micro-Electrocorticography Device for a Rodent Model

Electrocorticography (ECoG) is a methodology for stable mapping of the brain surface using local field potentials (LFPs) with a wide cortical region, high signal fidelity, and minimal invasiveness to brain tissue. To compare surface ECoG signals with inter-cortical neuronal activity, we fabricated a flexible handcrafted ECoG electrode made with economically available materials. This research is on a Lewis rat implanted with a handcrafted 256-channel, non-penetrative ECoG electrode covering an area of 7mm x 7mm on the cortical surface. This device was placed on the motor and somatosensory cortex of the brain to record signals with an active animal. The recordings are acquired by using the Synapse Software and the Tucker-Davis Technologies acquisition system to monitor and analyze electrophysiological signals within the amplitude range of 200µV for local field potentials. This demonstrates how reactive channels and their spatiotemporal and frequency-specific characteristics can be identified by means of this method