Showing papers in "IEEE Transactions on Consumer Electronics in 2011"
TL;DR: An optical wireless indoor localization using light emitting diodes (LEDs) and using the phase difference, time difference of arrival (TDOA) localization algorithm is employed, and the indoor location accuracy is less than 1 cm.
Abstract: We propose an optical wireless indoor localization using light emitting diodes (LEDs) and demonstrate it via simulation. Unique frequency addresses are assigned to each LED lamp, and transmitted through the light radiated by the LED. Using the phase difference, time difference of arrival (TDOA) localization algorithm is employed. Because the proposed localization method used pre-installed LED ceiling lamps, no additional infrastructure for localization is required to install and therefore, inexpensive system can be realized. The performance of the proposed localization method is evaluated by computer simulation, and the indoor location accuracy is less than 1 cm in the space of 5m x 5 m x 3 m.
340 citations
TL;DR: The experiment results show that the proposed method of iterative recursive weighted average filter will improve the accuracy of RSSI localization on the condition of lower computation complexity, and the achieved localization is more accurate in the polynomial fitting than in the log-normal shadowing model.
Abstract: An effective indoor localization method of hybrid RSSI/TDOA is proposed to reduce the big errors occurred during indoor RSSI localization and high cost paid by TDOA localization. It measures RSSI with iterative recursive weighted average filter, and polynomial model is obtained to fitting the RSSI measurement and to obtain polynomial model. Furthermore the hybrid RSSI/TDOA localization algorithm is employed. The experiment results show that the proposed method of iterative recursive weighted average filter will improve the accuracy of RSSI localization on the condition of lower computation complexity, and the achieved localization is more accurate in the polynomial fitting than in the log-normal shadowing model. Moreover, the indoor location accuracy in the experiment is approximate 0.5 meter that satisfies the precision requirement of indoors location precision.
129 citations
TL;DR: A system for elderly care by recognizing six abnormal activities; forward fall, backward fall, chest pain, faint, vomit, and headache, selected from the daily life activities of elderly people is presented.
Abstract: Video sensor based human activity recognition systems have potential applications in life care and health care areas. The paper presents a system for elderly care by recognizing six abnormal activities; forward fall, backward fall, chest pain, faint, vomit, and headache, selected from the daily life activities of elderly people. Privacy of elderly people is ensured by automatically extracting the binary silhouettes from video activities. Two problems are addressed in this research, which decrease recognition accuracy during the process of abnormal human activity recognition (HAR) system development. First, the problem of continuous changing distance of a moving person from two viewpoints is resolved by using the R-transform. R-transform extracts periodic, scale and translation invariant features from the sequences of activities. Second, the high similarities in postures of different activities is significantly improved by using the kernel discriminant analysis (KDA). KDA increases discrimination between different classes of activities by using non-linear technique. Hidden markov model (HMM) is used for training and recognition of activities. The system is evaluated against linear discriminant analysis (LDA) on the original silhouette features and LDA on the R-transform features. Average recognition rate of 95.8% proves the feasibility of the system for elderly care at home.
119 citations
TL;DR: A new algorithm in reversible data hiding, with the application associated with the quick response (QR) codes, so that the QR codes can be hidden into the original image, and considerable increase in embedding capacity can be expected.
Abstract: In this paper, we propose a new algorithm in reversible data hiding, with the application associated with the quick response (QR) codes. QR codes are random patterns, which can be commonly observed on the corner of posters or webpages. The goal of QR codes aims at convenienceoriented applications for mobile phone users. People can use the mobile phone cameras to capture QR code at the corner of web page, and then the hyperlink corresponding to the QR code can be accessed instantly. Since QR code looks like random noise and it occupies a corner of the original image, its existence can greatly reduce the value of the original content. Thus, how to retain the value of original image, while keeping the capability for the instant access for webpages, would be the major concern of this paper. With the aid of our reversible data hiding technique, the QR codes can be hidden into the original image, and considerable increase in embedding capacity can be expected. Next, we propose a scheme such that when the image containing the QR code is browsed, the hyperlink corresponding to the QR code is accessed first. Then, the QR code could get vanished and the original image would be recovered to retain the information conveyed therein. Simulation results demonstrate the applicability of the proposed algorithm.
114 citations
TL;DR: A novel complexity control method for the near future HEVC encoders running on power-constrained devices based on a decision algorithm that dynamically adjusts the depth of the Coding Units (CU) defined by quad-tree structures.
Abstract: The emerging High Efficiency Video Coding (HEVC) standard is expected to require much more processing power than its predecessors due to the higher algorithmic complexity of new coding tools and associated data structures. This paper proposes a novel complexity control method for the near future HEVC encoders running on power-constrained devices. The proposed method is based on a decision algorithm that dynamically adjusts the depth of the Coding Units (CU) defined by quad-tree structures. New evidence about the relationship between CU depth and coding complexity is used to selectively constrain the CU depth in order to not exceed a predefined complexity target. The experimental results show that the encoder computational complexity can be downscaled by up to 60% at the cost of negligible loss of rate-distortion (RD) performance. The proposed method finds application in the near future multimedia portable devices using HEVC codecs.
108 citations
TL;DR: The proposed intelligent image processing method uses the red-green-blue (RGB) color background modeling with a sensitivity parameter to extract moving regions, the morphology to eliminate noises, and the blob-labeling to group moving objects to track moving objects fast.
Abstract: This paper deals with an intelligent image processing method for the video surveillance systems. We propose a technology detecting and tracking multiple moving objects, which can be applied to consumer electronics such as home and business surveillance systems consisting of an internet protocol (IP) camera and a network video recorder (NVR). A real-time surveillance system needs to detect moving objects robustly against noises and environment. So the proposed method uses the red-green-blue (RGB) color background modeling with a sensitivity parameter to extract moving regions, the morphology to eliminate noises, and the blob-labeling to group moving objects. To track moving objects fast, the proposed method predicts the velocity and the direction of the groups formed by moving objects. Finally, the experiments show that the proposed method has the robustness against the environmental influences and the speed, which are suitable for the real- time surveillance system.
104 citations
TL;DR: A SEDMS that operates through interaction between a smart energy distribution system and a smart monitoring and control system that monitors information about power consumption, a user¿s situation and surroundings as well as controls appliances using dynamic patterns is proposed.
Abstract: Emerging green IT and smart grid technologies have changed electric power infrastructure more efficiently. These technologies enable a power system operator and a consumer to improve energy efficiency and reduce greenhouse gas emissions by optimizing energy distribution and management. There are many studies of these topics with the trend of green IT and smart grid technology. However, existing systems are still not effectively implemented in home and building because of their architectural limitations. Therefore, in this paper, we propose a smart energy distribution and management system (SEDMS) that operates through interaction between a smart energy distribution system and a smart monitoring and control system. Proposed system monitors information about power consumption, a user?s situation and surroundings as well as controls appliances using dynamic patterns. Because SEDMS is connected with the existing power grid and with the newrenewable energy system, we consider integration of new renewable energy system through electric power control. We implemented proposed system in test-bed and carry out some experiments. The results show that a reduction of the service response time and the power consumption are approximately 45.6% and 9-17% respectively.
102 citations
TL;DR: A Self-adapting intelligent system used for providing building control and energy saving services in buildings and an energy-efficiency self-clustering sensor network (ESSN) and a node type indicator based routing (NTIR) protocol that considers the requirements of WSNs, such as network lifetime and system resource management.
Abstract: Recent advances in ubiquitous technologies facilitate context-aware systems which can offer situation-based services. Wireless sensor networks (WSNs) have become increasingly important in recent years due to their ability to monitor and manage situational information for various intelligent services in ubiquitous environments. However, existing energy management systems are not effectively implemented in home and building environments due to their architectural limitations, such as static system architecture and a finite battery lifetime. Therefore, in this paper, we propose a Self-adapting intelligent system used for providing building control and energy saving services in buildings. Our system consists of a gateway (selfadapting intelligent gateway) and a sensor (self-adapting intelligent sensor). In addition, we also propose an energy-efficiency self-clustering sensor network (ESSN) and a node type indicator based routing (NTIR) protocol that considers the requirements of WSNs, such as network lifetime and system resource management. In order to verify the efficiency of our system, we implemented our system in real test bed and conducted experiments. The results show that autonomous power saving using our system is approximately 16-24% depending on the number of SIS.
98 citations
TL;DR: Media Cloud is proposed, a middleware for Set-top boxes for classifying, searching, and delivering media inside home network and across the cloud that interoperates with UPnP and DLNA.
Abstract: Cloud computing allows accessing resources across Internet transparently: requiring no expertise in, or control over the underlying infrastructure. There is an increasing interest in sharing media files with family and friends. However, UPnP or DLNA were not designed for media distribution beyond the boundaries of a local network and manage media files through web applications can be tedious. To overcome this problem, we propose Media Cloud, a middleware for Set-top boxes for classifying, searching, and delivering media inside home network and across the cloud that interoperates with UPnP and DLNA.
97 citations
TL;DR: A touch controller is proposed for on-cell capacitive touch screen panel systems that adopts the differential sensing method to enhance the dynamic range of sensing voltage and to be robust to display noise.
Abstract: A touch controller is proposed for on-cell capacitive touch screen panel systems. The proposed IC adopts the differential sensing method to enhance the dynamic range of sensing voltage and to be robust to display noise. The measurement results show that the maximum reporting rate, jitter tolerance, and signal-to-noise ratio (SNR) are 140 Hz, ±0.3 mm, and 12 dB, respectively, when evaluated with a 13.3-inch wide extended graphics array (WXGA) liquid crystal display (LCD) panel with the on-cell touch screen. The proposed IC fabricated via 0.35 μm CMOS process technology occupies a silicon area of 4 mm × 5 mm and consumes a power of 19 mW when the supply voltage is 3.3 V.
95 citations
TL;DR: This paper presents a highly integrated VLSI implementation of a mixed bio-signal lossless data compressor capable of handling multichannel electroencephalogram (EEG), electrocardiogram (ECG) and diffuse optical tomography (DOT) bio-Signal data for reduced storage and communication bandwidth requirements in portable, wireless brain-heart monitoring systems used in hospital or home care settings.
Abstract: This paper presents a highly integrated VLSI implementation of a mixed bio-signal lossless data compressor capable of handling multichannel electroencephalogram (EEG), electrocardiogram (ECG) and diffuse optical tomography (DOT) bio-signal data for reduced storage and communication bandwidth requirements in portable, wireless brain-heart monitoring systems used in hospital or home care settings. The compressor integrated in a multiprocessor brain-heart monitoring IC comprises 15 k gates and 12 kbits of RAM, occupying a total area of 58 k μm2 in 65 nm CMOS technology. Results demonstrate an average compression ratio (CR) of 2.05, and a simulated power consumption of 170 μW at an operating condition of 24 MHz clock and 1.0 V core voltage. Nominal power savings of 43% and 47% at the transmitter can be achieved when employing Bluetooth and Zigbee transceivers, respectively.
TL;DR: This paper proposes a resource-aware management system with hierarchical smart home resource model, using the home context information which defines the information convergence model of heterogeneous home resources and builds a home knowledge by constructing a resource relation graph.
Abstract: With the advent of smart home devices including Smart TV or smart appliances, home becomes smarter. Smart home is a complex environment where heterogeneous smart devices and appliances are connected to each other to provide various smart services. As the home environments become smarter and more complex, the need for an effective managing mechanism with minimum user's intervention is growing. However, just only putting together all the individual information of each resource is not enough, since it is very hard to catch out overall home situation without the relation information between the managed resources. In this paper, we propose a resource-aware management system with hierarchical smart home resource model, using the home context information which defines the information convergence model of heterogeneous home resources and builds a home knowledge by constructing a resource relation graph. The proposed system can accelerate deployment of advanced future smart home service features such as context-aware dynamic service composition, autonomous fault management systems. In addition, it allows cost effective remote maintenance system with highly convenient manageability. We implemented the prototype system of our proposed architecture and evaluated the performance on the query response time of home resources and relations in a real environment. Results showed that it has acceptable performance for navigating or control of home information and excellent improvements in terms of relation based search. We anticipate that the proposed system will bring the huge benefits not only to the consumers, home network service providers but also to the home network maintenance companies in terms of ease of management, and diagnostic effectiveness.
TL;DR: The design and implementation of a new indoor security system with a jumping robot as the surveillance terminal and some pyroelectric infrared (PIR) sensor nodes form a ZigBee wireless sensor network (WSN).
Abstract: Mobile robots are now widely used in various surveillance and security applications. But most of them are wheeled and tracked robots that can not work well to overcome stairs, doorsills and other obstacles in cluttered indoor environments. This paper presents the design and implementation of a new indoor security system with a jumping robot as the surveillance terminal. The jumping robot, a gateway and some pyroelectric infrared (PIR) sensor nodes form a ZigBee wireless sensor network (WSN). The sensor nodes are installed above the doors and windows of the house to detect intruders and send intrusion detection messages to the robot. The robot can jump to the sensor coverage area to take photos and send them to the gateway and the home server. The remote house owner will get these photos through Internet. A prototype system has been implemented and some performance tests have been done. Experimental results show that the robot can jump up on a desk of 105cm high to perform the surveillance task. A 3k-byte captured photo can be transmitted to the gateway in 3.68s with 0.1% loss rate by 5 hops1.
TL;DR: The subjective and objective performance evaluation shows that the proposed enhancement method yields better results without changing image original color in comparison with the conventional methods.
Abstract: The main objective of image enhancement is to improve some characteristic of an image to make it visually better one. This paper proposes a method for enhancing the color images based on nonlinear transfer function and pixel neighborhood by preserving details. In the proposed method, the image enhancement is applied only on the V (luminance value) component of the HSV color image and H and S component are kept unchanged to prevent the degradation of color balance between HSV components. The V channel is enhanced in two steps. First the V component image is divided into smaller overlapping blocks and for each pixel inside the block the luminance enhancement is carried out using nonlinear transfer function. In the second step, each pixel is further enhanced for the adjustment of the image contrast depending upon the center pixel value and its neighborhood pixel values. Finally, original H and S component image and enhanced V component image are converted back to RGB image. The subjective and objective performance evaluation shows that the proposed enhancement method yields better results without changing image original color in comparison with the conventional methods.
TL;DR: The system architecture of the testbed deployed on a real street along with the preliminary experiments are described and the open challenges and research directions on designing a future intelligent road lighting system are discussed.
Abstract: Traditional road lighting systems are outdated and should be replaced with systems which can sense their environment, i.e., users and their consumer electronics (CE) devices, and react intelligently. Realizing such a system requires an interdisciplinary approach which analyzes the efficient system architecture and communication technology while taking into account the user needs. To understand these necessities, subjective experiments should be conducted in a practical testbed, similar to ours. In this paper, we first present the state-of-the-art solutions in the literature. Then, we describe the system architecture of our testbed deployed on a real street along with the preliminary experiments. Finally, we discuss the open challenges and research directions on designing a future intelligent road lighting system.
TL;DR: New k factor decision method and highlight compression operator are proposed to enhance the appearance and naturalness of rendered High Dynamic Range (HDR) images and shows better rendering in terms of naturalness and dark area details than the previous tone-mapping algorithm.
Abstract: In this paper, new k factor decision method and highlight compression operator are proposed to enhance the appearance and naturalness of rendered High Dynamic Range (HDR) images. The retinex algorithm is one of the outstanding local operators, which well preserves local contrast in highlights. However, the retinex algorithm gives a worse overall appearance and undistinguishable dark area contrast than global operators or other local operators in some cases. The most prominent improvement of the proposed method is that the decision method of the k factor, which is one of the parameters in retinex algorithm, is proposed by using the dynamic range in images. The proposed parameter decision method enhances the overall quality and preference of the image and solves any parameter setting problems. Also, dark area details become more distinguishable by the highlight compression operator. According to the results of many HDR image experiments, the proposed method shows better rendering in terms of naturalness and dark area details than the previous tone-mapping algorithm.1.
TL;DR: This paper indicates that the proxy-based CCN scheme can provide lower communication overhead, shorter download time, and lower energy consumption in mobile environments.
Abstract: Rapid developments in mobile technology have transformed mobile phones into personal multimedia devices. Due to these advancements, user created mobile content is on the increase, both in terms of quality and quantity. In addition, content sharing is getting popular in home networks as well as in social community networks. To keep pace with such movements, the new networking technology named as content centric networking (CCN) optimized for content sharing has appeared. However, it has little consideration for mobile consumer devices. So, this paper indicates that the proxy-based CCN scheme can provide lower communication overhead, shorter download time, and lower energy consumption in mobile environments.
TL;DR: Experimental results show that the proposed method reduces geometric errors efficiently without any visual distortion, and generates the rectified multi-view image in very short processing time.
Abstract: In this paper, we present an image rectification method for the multi-view image captured by a parallel multicamera arrangement. Since most multi-camera arrangements are manually adjusted, there exist misalignments with the camera positions and orientations. These misalignments cause geometric errors that can be a serious obstruction to three-dimensional (3D) image processing and applications. Moreover, different internal characteristics of cameras increase geometric errors. In order to minimize those geometric errors, we design an ideal multi-camera arrangement and then calculate the multi-view image rectifying transform (MIRT). Experimental results show that the proposed method reduces geometric errors efficiently without any visual distortion, and generates the rectified multi-view image in very short processing time.
TL;DR: A Reduced-Reference (RR) quality metric for colour plus depth 3D video transmission using the extracted edge information of depth maps and extracted information from the corresponding colour image in the areas in the proximity of edges is proposed.
Abstract: 3D video services will soon capture the mass market due to the advancement of immersive video technologies (e.g., availability of "3D-Ready" TV monitors at affordable prices) and supportive infrastructure (e.g., high bandwidth communication links). In order to provide demanding customers with a better service over unreliable communication channels, system parameters (e.g., operating conditions of the transmission system) can be updated "on the fly". 3D video quality measured at the receiver side can be used as feedback information to fine tune the system parameters. However, measuring 3D video quality is a challenge due to the complex nature of 3D perceptual attributes such as overall image quality, depth perception, etc. In addition, the use of Full-Reference (FR) quality metrics is not a viable solution due to the need of the original 3D video sequence at the receiver side. This paper therefore proposes a Reduced-Reference (RR) quality metric for colour plus depth 3D video transmission using the extracted edge information of depth maps and extracted information from the corresponding colour image in the areas in the proximity of edges. This work is motivated by the fact that the edges/contours of the depth map can represent different depth levels and identify the main foreground objects of the corresponding colour image and hence can be used in quality evaluations. The performance of the method is evaluated for different compression ratios and network conditions and it shows good results compared to its counterpart FR quality metric, with a lower overhead for side-information.
TL;DR: This paper proposes a technique to reduce the number of IFFT operations to half at the expense of a slight PAPR degradation.
Abstract: One of the effective methods used for reducing peak to average power ratio (PAPR) in OFDM systems is partial transmit sequence (PTS). In the conventional PTS (CPTS) several inverse fast Fourier transform (IFFT) operations and complicated calculation to obtain optimum phase sequence, increase the computational complexity of C-PTS. In this paper, we propose a technique to reduce the number of IFFT operations to half at the expense of a slight PAPR degradation. Simulations are performed with QPSK modulation with OFDM signal and Saleh model power amplifier. The effects of digital predistortion (DPD) to increase the linearity and efficiency of the Saleh model power amplifier (PA) are also examined.
TL;DR: The development and characterization of a surveillance robot with automatic docking and recharging capabilities for home security and a docking method based on the self-localization of the robot and the infrared detectors of the docking station is proposed.
Abstract: This paper presents the development and characterization of a surveillance robot with automatic docking and recharging capabilities for home security. The proposed system is composed of a surveillance robot and a docking station. The palm-sized surveillance robot has a triangular shape with three wheels. It communicates with the general wireless home router through WiFi. It communicates with the docking station through ZigBee and serves as a mobile wireless sensor network gateway. The docking station has a trapezoidal structure with an arc-shaped docking interface. A docking method based on the self-localization of the robot and the infrared detectors of the docking station is proposed. The robot can return to the docking station for recharging operations when the on-board battery is too low. The experimental results show that the prototype robot achieved a success rate of 90% after 60 different docking attempts.
TL;DR: A flash translation layer called zFTL is presented, which reduces the amount of data written to NAND flash memory by supporting on-line, transparent data compression based on the X-Match algorithm and proposes a novel prediction scheme that identifies incompressible data in advance without going through full compression.
Abstract: Flash translation layers play an important role in determining the storage performance and lifetime of NAND flash-based consumer electronics devices. In this paper, we present a flash translation layer called zFTL, which reduces the amount of data written to NAND flash memory by supporting on-line, transparent data compression based on the X-Match algorithm. To minimize compression overhead and power consumption, we also propose a novel prediction scheme that identifies incompressible data in advance without going through full compression. Our evaluations with five real-world workloads show that zFTL successfully enhances storage performance and lifetime by improving the write amplification factor (WAF) by a factor of 2.6 (geometric mean) compared to the case without compression support. In addition, we find that the proposed prediction scheme is effective in reducing power consumption by skipping compression for incompressible data.
TL;DR: A user centric approach to authentication for home networks using a zero-knowledge-proof (ZKP) authentication is used to leverage the emerging cloud infrastructure allowing users to temporarily transfer their service and content rights within a trusted environment such as a friend's home.
Abstract: A user centric approach to authentication for home networks is proposed. A zero-knowledge-proof (ZKP) authentication is used to leverage the emerging cloud infrastructure allowing users to temporarily transfer their service and content rights within a trusted environment such as a friend's home. This approach enables the sharing of personalized content and more sophisticated network-based services over a conventional TCP/IP infrastructure. Experimental results derived from a reference prototype are presented. These demonstrate the practicality of the underlying approach. The potential to develop new cloud services for "social" home networks is also discussed.
TL;DR: A new intelligent interoperability framework for smart home systems execution as well as coordinating them in a federated manner based on Simple Object Access Protocol (SOAP) technology that provides platform independent interoperation among heterogeneous systems.
Abstract: Recent advancements in smart home systems have increased the utilization of consumer devices and appliances in home environment. However, many of these devices and appliances exhibit certain degree of heterogeneity and do not adapt towards joint execution of operation. Hence, it is rather difficult to perform interoperation especially to realize desired services preferred by home users. In this paper, we propose a new intelligent interoperability framework for smart home systems execution as well as coordinating them in a federated manner. The framework core is based on Simple Object Access Protocol (SOAP) technology that provides platform independent interoperation among heterogeneous systems. We have implemented the interoperability framework with several home devices to demonstrate their effectiveness for interoperation. The performance of the framework was tested in Local Area Network (LAN) environment and proves to be reliable in smart home setting1.
TL;DR: From simulation results, it is confirmed that the proposed clipping scheme has slightly better performance than conventional PLC system.
Abstract: In this paper, we propose clipping scheme and equalizer as methods to reduce the effects of impulsive noise and channel attenuation in power line communication (PLC) system. Clipping is cutting off the amplitude of the received signal over threshold level without its phase change in order to reduce noise effects. The equalizer compensates for effects of PLC channel. The performance is evaluated in terms of bit error rate (BER). From simulation results, it is confirmed that the proposed clipping scheme has slightly better performance than conventional PLC system. The results of the paper can be applied to PLC systems for smart grid.
TL;DR: An improved version of the Moving KMeans algorithm called Enhanced Moving K-Means (EMKM) algorithm, which significantly outperform the other conventional clustering algorithms.
Abstract: As of now, numerous improvements have been carried out to increase the performance of previous existing algorithms for image segmentation with the limitation lying on the intra clustering variance. However, most of them tend to have met with inadequate results. This paper presents an improved version of the Moving KMeans algorithm called Enhanced Moving K-Means (EMKM) algorithm. In the proposed EMKM, the moving concept of the conventional Moving K-Means (i.e. certain members of the cluster with the highest fitness value are forced to become the members of the clusters with the smallest fitness value) is enhanced. Two versions of EMKM, namely EMKM-1and EMKM-2 are proposed. The qualitative and quantitative analyses have been performed to measure the efficiency of both EMKM algorithms over the conventional algorithms (i.e. K-Means, Moving KMeans, and Fuzzy C-Means) and the latest clustering algorithms (i.e. AMKM and AFMKM). It is investigated that the proposed algorithms significantly outperform the other conventional clustering algorithms.
TL;DR: A compression-aware flash translation layer (FTL) is devised, called CaFTL, which supports compressionaware address mapping and garbage collection for BlueZIP and can increase the lifetime of the SSD prototype by 26% as well as improve read and write performance by 20% and 27%, respectively, on average.
Abstract: The performance and lifetime of highperformance solid-state drives (SSDs) can be improved by data compression, which can reduce the amount of data physically transferred from/to flash memory In this paper, we present our experience of building a high-performance solid-state drive using a hardware accelerated compression module called BlueZIP In order to fully exploit the BlueZIP module, we devise a compression-aware flash translation layer (FTL), called CaFTL, which supports compressionaware address mapping and garbage collection for BlueZIP For poorly compressed pages, CaFTL supports selective compression so that unnecessary compression can be avoided We have implemented a complete SSD prototype with BlueZIP on an FPGA-based custom SSD platform and evaluated its effectiveness using realistic workloads Our evaluation results show that BlueZIP can increase the lifetime of the SSD prototype by 26% as well as improve read and write performance by 20% and 27%, respectively, on average1
TL;DR: This paper designs and implements a home embedded surveillance system with ultra-low alert power and uses the Majority Voting Mechanism (MVM) to manage the sensor groups to enhance the probability of multiple sensors sensing and reduces the system's power consumption.
Abstract: In this paper we design and implement a home embedded surveillance system with ultra-low alert power. Traditional surveillance systems suffer from an unnecessary waste of power and the shortcomings of memory conditions in the absence of invasion. In this design we use Pyroelectric Infrared sensors (PIR) and pressure sensors as the alert group in windows and doors where an intruder must pass through. These low-power alert sensors wake up the MCU (Micro Controller Unit) which has power management for the ultrasonic sensors and PIR sensors indoors. This state transition method saves a large number of sensors required for the alert power. We also use the Majority Voting Mechanism (MVM) to manage the sensor groups to enhance the probability of multiple sensors sensing. After the MCU sends the sensor signals to the embedded system, the program starts the Web camera. Our sensing experiment shows that we reduce the system's power consumption.
TL;DR: The proposed CR scheme can solve recent spectrum shortage problem in Wi-Fi networks due to traffic explosion by smart phones and proposes K-out-of-N-rule which is the most efficient cooperative sensing rule by analytical and numerical results.
Abstract: This paper presents cooperative spectrum sensing techniques for cognitive radio (CR) systems. The spectrum sensing detects the presence of a primary user (service) on an associated spectrum. The accuracy of spectrum sensing depends on both sensing time and number of sensing nodes (i.e. secondary users) participating in the sensing process. We derive optimal number of secondary users for cooperative spectrum sensing to minimize spectrum detection error probability and optimal spectrum sensing time to maximize data transmission throughput. A system model which consists of a primary TV spectrum and multiple Wi-Fi secondary users is considered. The proposed CR scheme can solve recent spectrum shortage problem in Wi-Fi networks due to traffic explosion by smart phones. We propose K-out-of-N-rule which is the most efficient cooperative sensing rule by analytical and numerical results.
TL;DR: This paper introduces a low complexity MVD coding algorithm that adaptively utilizes the texture and depth map correlation and proposes four efficient techniques, including depth information based fast mode size decision, adaptive disparity estimation in texture coding, motion vector sharing based on the texture image similarity correlation and the SKIP mode decision in depth coding.
Abstract: Multiview video plus depth (MVD) is a new 3D video format that would support 3D applications developed by MPEG. Such a format is a combination of texture video and associated depth maps. Consequently, for the efficient transmission of 3D video signals, the compression of texture video and also the depth maps is required. Since high computational complexity of jointly coding between the texture video and depth map is still an open question, this paper introduces a low complexity MVD coding algorithm that adaptively utilizes the texture and depth map correlation. Based on the correlation, we propose four efficient techniques, including depth information based fast mode size decision, adaptive disparity estimation in texture coding, motion vector sharing based on the texture image similarity correlation and the SKIP mode decision in depth coding. Experimental results show that the proposed algorithm can significantly reduce the computational complexity of MVD coding while improve the coding performance and achieve better rendering quality1.