A morphable model for the synthesis of 3D faces

Energy sustainability and environmental preservation have become worldwide concerns with the many manifestations of climate change and the continually increasing demand for energy. As cities and nations become more technologically advanced, electricity consumption rises to levels that may no longer be manageable if left unattended. The Smart Grid offers an answer to the shift to more sustainable technologies such as distributed generation and microgrids. A general public awareness and adequate attention from potential researchers and policy makers is crucial. This paper presents an overview of the Smart Grid with its general features, functionalities and characteristics. It presents the Smart Grid fundamental and related technologies and have identified the research activities, challenges and issues. It demonstrates how these technologies have shaped the modern electricity grid and continued to evolve and strengthen its role in the better alignment of energy demand and supply. Smart Grid implementation and practices in various locations are also unveiled. Concrete energy policies facilitate Smart Grid initiatives across the nations. Interestingly, Smart Grid practices in different regions barely indicate competition but rather an unbordered community of similar aspirations and shared lessons.

A review of the development of Smart Grid technologies

A survey on smart grid technologies and applications

Extensive empirical studies presented in this article confirm that the quality of radio communication between low-power sensor devices varies significantly with time and environment. This phenomenon indicates that the previous topology control solutions, which use static transmission power, transmission range, and link quality, might not be effective in the physical world. To address this issue, online transmission power control that adapts to external changes is necessary. This article presents ATPC, a lightweight algorithm for Adaptive Transmission Power Control in wireless sensor networks. In ATPC, each node builds a model for each of its neighbors, describing the correlation between transmission power and link quality. With this model, we employ a feedback-based transmission power control algorithm to dynamically maintain individual link quality over time. The intellectual contribution of this work lies in a novel pairwise transmission power control, which is significantly different from existing node-level or network-level power control methods. Also different from most existing simulation work, the ATPC design is guided by extensive field experiments of link quality dynamics at various locations over a long period of time. The results from the real-world experiments demonstrate that (1) with pairwise adjustment, ATPC achieves more energy savings with a finer tuning capability, and (2) with online control, ATPC is robust even with environmental changes over time.

ATPC: Adaptive Transmission Power Control for Wireless Sensor Networks

Wireless sensor networks (WSNs) are envisioned to be an important enabling technology for smart grid (SG) due to the low cost, ease of deployment, and versatility of WSNs. Limited battery energy is the tightest resource constraint on WSNs. Transmission power control and data packet size optimization are powerful mechanisms for prolonging network lifetime and improving energy efficiency. Increasing transmission power will reduce the bit error rate (BER) on some links, however, utilizing the highest power level will lead to inefficient use of battery energy because on links with low path loss achieving low BER is possible without the need to use the highest power level. Utilizing a large packet size is beneficial for increasing the payload-to-overhead ratio, yet, lower packet sizes have the advantage of lower packet error rate. Furthermore, transmission power level assignment and packet size selection are interrelated. Therefore, joint optimization of transmission power level and packet size is of utmost importance in WSN lifetime maximization. In this study, we construct a detailed link layer model by employing the characteristics of Tmote Sky WSN nodes and channel characteristics based on actual measurements of SG path loss for various environments. A novel mixed integer programming framework is created by using the aforementioned link layer model for WSN lifetime maximization by joint optimization of transmission power level and data packet size. We analyzed the WSN performance by systematic exploration of the parameter space for various SG environments through the numerical solutions of the optimization model.

Packet Size Optimization in Wireless Sensor Networks for Smart Grid Applications

Transmission power control has paramount importance in the design of energy-efficient wireless sensor networks (WSNs). In this paper, we systematically explore the effects of various transmission power control strategies on WSN lifetime with an emphasis on discretization of power levels and strategies for transmission power assignment. We investigate the effects of the granularity of power levels on energy dissipation characteristics through a linear programming framework by modifying a well known and heavily utilized continuous transmission power model (HCB model). We also investigate various transmission power assignment strategies by using two sets of experimental data on Mica motes. A novel family of mathematical programming models are developed to analyze the performance of these strategies. Bandwidth requirements of the proposed transmission power assignment strategies are also investigated. Numerical analysis of our models are performed to characterize the effects of various design parameters and to comparethe relative performance of transmission power assignment strategies. Our results show that the granularity of discrete energy consumption has a profound impact on WSN lifetime, furthermore, more fine-grained control of transmission power (i.e., link level control) can extend network lifetime up to 20% in comparison to optimally-assigned network-level single transmission power.

The Impact of Transmission Power Control Strategies on Lifetime of Wireless Sensor Networks

Presented on March 2, 2018 at 12:00 p.m. in the Klaus Advanced Computing Building, Room 1116W.

rtCaptcha: A Real-Time Captcha Based Liveness Detection System

File carving techniques allow for recovery of files from storage devices in the absence of any file system metadata. When data are encoded and compressed, the current paradigm of carving requires the knowledge of the compression and encoding settings to succeed. In this paper, we advance the state of the art in JPEG file carving by introducing the ability to recover fragments of a JPEG file when the associated file header is missing. To realize this, we examined JPEG file headers of a large number of images collected from Flickr photo sharing site to identify their structural characteristics. Our carving approach utilizes this information in a new technique that performs two tasks. First, it decompresses the incomplete file data to obtain a spatial domain representation. Second, it determines the spatial domain parameters to produce a perceptually meaningful image. Recovery results on a variety of JPEG file fragments show that given the knowledge of Huffman code tables, our technique can very reliably identify the remaining decoder settings for all fragments of size 4 KiB or above. Although errors due to detection of image width, placement of image blocks, and color and brightness adjustments can occur, these errors reduce significantly when fragment sizes are >32 KiB.

Carving Orphaned JPEG File Fragments

Traffic lights are installed at intersections mostly for traffic management. Traffic signals turn on during the amount of time determined. Intelligent traffic management systems emerge as a need to handle the dynamicity of traffic. These systems are first implemented on simulators in order to mimic the real life situations before realization.

Yet, we have implemented a real time traffic simulator with an adaptive fuzzy inference algorithm that arranges the foreseen light signal duration. It changes the time duration of lights depending on waiting vehicles behind green and red lights at crossroad. The simulation has also been supported with real time graphical visualization. Given a scenario, it creates random traffic flows according to specified parameters. Next, obtained results have been interpreted in the simulation environment.

According to inferences from adaptive environment, TSK (Takagi-Sugeno-Kang) and Mamdani models have also been implemented to give baselines for verification. Several experiments have been conducted and compared against classical techniques such as Webster (1958) Road research technical paper No 39 and HCM (2000) TRB, special report 209, statistically to demonstrate the effectiveness of the proposed method.

A real time traffic simulator utilizing an adaptive fuzzy inference mechanism by tuning fuzzy parameters

Compression history of an audio may reveal very useful information when traces of tampering has to be investigated or quality of an audio has to be evaluated. Motivated by this, we introduce two methods that can discriminate between single and double compressed audio and can identify compression codec and bit rate of an audio. The first method utilizes audio quality measures to realize this and operates on decoded audio. The second method, alternatively, works on coded audio, effectively the audio bit stream, and characterizes randomness and chaotic properties of the bit stream to achieve these tasks. Unlike the existing work in the literature, which are proposed mainly for MP3 encoded audio, both methods can be applied to all encoding formats. Extensive tests have been performed to test the performance of both methods under various settings. Results show that both methods can be very reliably used to obtain information on compression history of an audio.

Erkam Uzun

Papers

The Impact of Transmission Power Control Strategies on Lifetime of Wireless Sensor Networks

rtCaptcha: A Real-Time Captcha Based Liveness Detection System

Carving Orphaned JPEG File Fragments

A real time traffic simulator utilizing an adaptive fuzzy inference mechanism by tuning fuzzy parameters

Methods for identifying traces of compression in audio