We propose a face recognition and notification system that can transform visual face information into tactile signals in order to help visually impaired people. The proposed system consists of a glasses type camera, a mobile computer and an electronic cane. The glasses type camera captures the frontal view of the user, and sends this image to mobile computer. The mobile computer starts to search for human's face in the image when obstacles are detected by ultrasonic sensors. In a case that human's face is detected, the mobile computer identifies detected face. At this time, Adaboost and compressive sensing are used as a detector and a classifier, respectively. After the identification procedures of the detected face, the identified face information is sent to controller attached to a cane using a Bluetooth communication. The controller generates motor control signals using Pulse Width Modulation (PWM) according to the recognized face labels. The vibration motor generates vibration patterns to inform the visually impaired person of the face recognition result. The experimental results of face recognition and notification system show that proposed system is helpful for visually impaired people by providing person identification results in front of him/her.

In this paper, we propose an improved single view metrology (SVM) algorithm to accurately measure the height of objects. In order to accurately measure the size of objects, vanishing points have to be correctly estimated. There are two methods to estimate vanishing points. First, the user has to choose some horizontal and vertical lines in real world. Then, the user finds the cross points of the lines. Second, the user can obtain the vanishing points by using software algorithm such as [6-9]. In the former method, the user has to choose the lines manually to obtain accurate vanishing points. On the other hand, the latter method uses software algorithm to automatically obtain vanishing points. In this paper, we apply image resizing and edge sharpening as a pre-processing to the algorithm in order to improve performance. The estimated vanishing points algorithm create four vanishing point candidates: two points are horizontal candidates and the other two points are vertical candidates. However, a common image has two horizontal vanishing points and one vertical vanishing point. Thus, we eliminate a vertical vanishing point candidate by analyzing the histogram of angle distribution of vanishing point candidates. Experimental results show that the proposed algorithm outperforms conventional methods, [6] and [7]. In addition, the algorithm obtains similar performance with manual method with less than 5% of the measurement error.

Energy-harvesting nodes in wireless sensor networks(WSNs) can be exhausted due to a heavy workload even though they can harvest energy from their environment. On contrast, they can sometimes fully charged, thus waste the harvested energy due to the limited battery-capacity. In order to utilize the harvested energy efficiently, we introduce a selective data compression and transmission range control scheme for energy-harvesting nodes. In this scheme, if the residual energy of a node is expected to run over the battery capacity, the node spends the surplus energy to exploit the data compression or the transmission range expansion; these operations can reduce the burden of intermediate nodes at the expanse of its own energy. Otherwise, the node performs only basic operations such as sensing or transmitting so as to avoid its blackout time. Simulation result verifies that the proposed scheme gathers more data with fewer number of blackout nodes than other schemes by consuming energy efficiently.

Nonvolatile memory (NVM) is being considered as an alternative of traditional memory devices such as SRAM and DRAM, which suffer from various limitations due to the technology scaling of modern integrated circuits. Although NVMs have advantages including nonvolatility, low leakage current, and high density, their inferior write performance in terms of energy and endurance becomes a major challenge to the successful design of NVM-based memory systems. In order to overcome the aforementioned drawback of the NVM, extensive research is required to develop energy- and endurance-aware optimization techniques for NVM-based memory systems. However, researchers have experienced difficulty in finding a suitable simulation tool to prototype and evaluate new NVM optimization schemes because existing simulation tools do not consider the feature of NVM devices. In this article, we introduce a NVM-based cache simulator to support rapid prototyping and evaluation of NVM-based caches, as well as energy- and endurance-aware NVM cache optimization schemes. We demonstrate that the proposed NVM cache simulator can easily prototype PRAM cache and PRAM+STT-RAM hybrid cache as well as evaluate various write traffic reduction schemes and wear leveling schemes.