Small Storage Devices Research Articles

CrowdDCNN: Deep convolution neural network for real-time crowd counting on IoT edge

Ensuring the safety and security of crowded places is a major concern for both the government and the public. Accurately and quickly estimating the number of people in a crowd is crucial for public safety, urban planning, and traffic monitoring. The existing methods have a minimum mean square error of 0.89 and require high storage space, making them inappropriate for crowd counting using low-computation and small-storage devices like single-board computers. Furthermore, these methods suffer from prediction time lag and are not suitable for live streaming. To tackle these challenges, this paper proposes a Deep Convolution Neural Network-based ‘CrowdDCNN’ model for crowd counting. This model reduces the value of mean square error by 0.29 and the size of the model by 80.01%. Additionally, the prediction time was decreased to 700 ms. Further, the ‘NoLag’ algorithm introduced in this paper is efficient in live crowd counting. Its O(1) time and space complexity make it appropriate for all devices, including single-board computers, laptops, and GPUs. The reported 0-p value during statistical analysis using Wilcoxon test, Friedman rank test, and paired t-test validates the superiority of the proposed model.

Perceptions About Data Security For Portable Storage Devices

The importance of securing data and information is a critical issue in todays world. These are no longer stored on a central system that is easy to protect and secure. Now everyone carries around small storage devices, which make guaranteeing that the information is guarded is much more complex and uncertain. This paper builds on the previous research of Knott & Steubes in the paper Encryption and Portable Data Storage, to be published in the Spring of 2011. In the previous work we identified the potential security issues that arise from using a portable storage device such as a USB flash drive. TrueCrypt software was introduced as an option that allows users to encrypt and hide data. The TrueCrypt software, which is publically available, is particularly useful for safeguarding data on USB flash drives that are easily compromised. A survey of undergraduate students was administered which focused on their practices and attitudes about security. It was found that there were strong associations between the use of flash drives, security, and the use of passwords.

Fuel cells and energy networks of electricity, heat, and hydrogen: A demonstration in hydrogen-fueled apartments

A demonstration was performed to evaluate our proposal of a residential energy system based on fuel cells and energy networks of electricity, hot water, and hydrogen. The demonstration was conducted from April 2007 to March 2009 in a small apartment building constructed for experimental purposes in Osaka City. Three small proton exchange membrane fuel cells were installed, and the electricity and hot water from the fuel cells were shared among 6 units via an internal electricity grid and hot water pipe. A hydrogen production facility, a small storage device, and a hydrogen pipe were installed to supply hydrogen to the fuel cells. Six families went about their normal daily lives using this system. The energy flow from hydrogen production to consumption was demonstrated. The results of fuel cell operation, energy supply, and energy demand, as well as an analysis of primary energy saving and CO2 emission mitigation are presented.