Delay optimized zero-forcing channel shortening algorithm for wireless communication

In Orthogonal Frequency Division Multiplexing and Discrete Multitone transceivers, a guard interval called Cyclic Prefix (CP) is inserted to avoid inter-symbol interference. The length of the CP is usually greater than the impulse response of the channel resulting in a loss of useful data carriers. In order to avoid long CP, a time domain equalizer is used to shorten the channel. In this paper, we propose a method to include a delay in the zero-forcing equalizer and obtain an optimal value of the delay, based on the location of zeros of the channel. The performance of the algorithms is studied using numerical simulations.

Communication: Benzene dimer-The free energy landscape

Establishing the relative orientation of the two benzene molecules in the dimer has remained an enigmatic challenge. Consensus has narrowed the choice of structures to either a T-shape, that may be tilted, or a parallel displaced arrangement, but the relatively small energy differences makes identifying the global minimum difficult. Here we report an ab initio Car-Parrinello Molecular Dynamics based metadynamics computation of the free-energy landscape of the benzene dimer. Our calculations show that although competing structures may be isoenergetic, free energy always favors a tilted T-shape geometry at all temperatures where the bound benzene dimer exist. (C) 2013 AIP Publishing LLC.

A prototype of a first-responder indoor localization system

In this paper we present an approach to build a prototype. model of a first-responder localization system intended for disaster relief operations. This system is useful to monitor and track the positions of the first-responders in an indoor environment, where GPS is not available. Each member of the first responder team is equipped with two zero-velocity-update-aided inertial navigation systems, one on each foot, a camera mounted on a helmet, and a processing platform strapped around the waist of the first responder, which fuses the data from the different sensors. The fusion algorithm runs real-time on the processing platform. The video is also processed using the DSP core of the computing machine. The processed data consisting of position, velocity, heading information along with video streams is transmitted to the command and control system via a local infrastructure WiFi network. A centralized cooperative localization algorithm, utilizing the information from Ultra Wideband based inter-agent ranging devices combined with the position estimates and uncertainties of each first responder, has also been implemented.

CAVVA: Computational Affective Video-in-Video Advertising

Advertising is ubiquitous in the online community and more so in the ever-growing and popular online video delivery websites (e. g., YouTube). Video advertising is becoming increasingly popular on these websites. In addition to the existing pre-roll/post-roll advertising and contextual advertising, this paper proposes an in-stream video advertising strategy-Computational Affective Video-in-Video Advertising (CAVVA). Humans being emotional creatures are driven by emotions as well as rational thought. We believe that emotions play a major role in influencing the buying behavior of users and hence propose a video advertising strategy which takes into account the emotional impact of the videos as well as advertisements. Given a video and a set of advertisements, we identify candidate advertisement insertion points (step 1) and also identify the suitable advertisements (step 2) according to theories from marketing and consumer psychology. We formulate this two part problem as a single optimization function in a non-linear 0-1 integer programming framework and provide a genetic algorithm based solution. We evaluate CAVVA using a subjective user-study and eye-tracking experiment. Through these experiments, we demonstrate that CAVVA achieves a good balance between the following seemingly conflicting goals of (a) minimizing the user disturbance because of advertisement insertion while (b) enhancing the user engagement with the advertising content. We compare our method with existing advertising strategies and show that CAVVA can enhance the user's experience and also help increase the monetization potential of the advertising content.

H.264 COMPRESSED VIDEO CLASSIFICATION USING HISTOGRAM OF ORIENTED MOTION VECTORS (HOMV)

In this paper, we have proposed a simple and effective approach to classify H.264 compressed videos, by capturing orientation information from the motion vectors. Our major contribution involves computing Histogram of Oriented Motion Vectors (HOMV) for overlapping hierarchical Space-Time cubes. The Space-Time cubes selected are partially overlapped. HOMV is found to be very effective to define the motion characteristics of these cubes. We then use Bag of Features (B OF) approach to define the video as histogram of HOMV keywords, obtained using k-means clustering. The video feature, thus computed, is found to be very effective in classifying videos. We demonstrate our results with experiments on two large publicly available video database.

Harmonic Current Injection based Powerline Communication Method for Grid Connected Single Phase Inverters in Domestic Microgrids

The following paper presents a Powerline Communication (PLC) Method for Single Phase interfaced inverters in domestic microgrids. The PLC method is based on the injection of a repeating sequence of a specific harmonic, which is then modulated on the fundamental component of the grid current supplied by the inverters to the microgrid. The power flow and information exchange are simultaneously accomplished by the grid interacting inverters based on current programmed vector control, hence there is no need for dedicated hardware. Simulation results have been shown for inter-inverter communication under different operating conditions to propose the viability. These simulations have been experimentally validated and the corresponding results have also been presented in the paper.

Scheduling for Stable and Reliable Communication Over Multiaccess Channels and Degraded Broadcast Channels

We model communication of bursty sources: 1) over multiaccess channels, with either independent decoding or joint decoding and 2) over degraded broadcast channels, by a discrete-time multiclass processor sharing queue. We utilize error exponents to give a characterization of the processor sharing queue. We analyze the processor sharing queue model for the stable region of message arrival rates, and show the existence of scheduling policies for which the stability region converges to the information-theoretic capacity region in an appropriate limiting sense.

Cooperative Communication of UAV to Perform Multi-task Using Nature Inspired Techniques

In this paper, the approach for assigning cooperative communication of Uninhabited Aerial Vehicles (UAV) to perform multiple tasks on multiple targets is posed as a combinatorial optimization problem. The multiple task such as classification, attack and verification of target using UAV is employed using nature inspired techniques such as Artificial Immune System (AIS), Particle Swarm Optimization (PSO) and Virtual Bee Algorithm (VBA). The nature inspired techniques have an advantage over classical combinatorial optimization methods like prohibitive computational complexity to solve this NP-hard problem. Using the algorithms we find the best sequence in which to attack and destroy the targets while minimizing the total distance traveled or the maximum distance traveled by an UAV. The performance analysis of the UAV to classify, attack and verify the target is evaluated using AIS, PSO and VBA.

A Communication-Theoretic Framework for 2-DMR Channel Modeling: Performance Evaluation of Coding and Signal Processing Methods

We develop a communication theoretic framework for modeling 2-D magnetic recording channels. Using the model, we define the signal-to-noise ratio (SNR) for the channel considering several physical parameters, such as the channel bit density, code rate, bit aspect ratio, and noise parameters. We analyze the problem of optimizing the bit aspect ratio for maximizing SNR. The read channel architecture comprises a novel 2-D joint self-iterating equalizer and detection system with noise prediction capability. We evaluate the system performance based on our channel model through simulations. The coded performance with the 2-D equalizer detector indicates similar to 5.5 dB of SNR gain over uncoded data.

RAPID HUMAN ACTION RECOGNITION IN H.264/AVC COMPRESSED DOMAIN FOR VIDEO SURVEILLANCE

This paper discusses a novel high-speed approach for human action recognition in H. 264/AVC compressed domain. The proposed algorithm utilizes cues from quantization parameters and motion vectors extracted from the compressed video sequence for feature extraction and further classification using Support Vector Machines (SVM). The ultimate goal of our work is to portray a much faster algorithm than pixel domain counterparts, with comparable accuracy, utilizing only the sparse information from compressed video. Partial decoding rules out the complexity of full decoding, and minimizes computational load and memory usage, which can effect in reduced hardware utilization and fast recognition results. The proposed approach can handle illumination changes, scale, and appearance variations, and is robust in outdoor as well as indoor testing scenarios. We have tested our method on two benchmark action datasets and achieved more than 85% accuracy. The proposed algorithm classifies actions with speed (>2000 fps) approximately 100 times more than existing state-of-the-art pixel-domain algorithms.

Performance Analysis of a Cooperative MAC Protocol of Wireless Ad Hoc Networks

Different medium access control (MAC) layer protocols, for example, IEEE 802.11 series and others are used in wireless local area networks. They have limitation in handling bulk data transfer applications, like video-on-demand, videoconference, etc. To avoid this problem a cooperative MAC protocol environment has been introduced, which enables the MAC protocol of a node to use its nearby nodes MAC protocol as and when required. We have found on various occasions that specified cooperative MAC establishes cooperative transmissions to send the specified data to the destination. In this paper we propose cooperative MAC priority (CoopMACPri) protocol which exploits the advantages of priority value given by the upper layers for selection of different paths to nodes running heterogeneous applications in a wireless ad hoc network environment. The CoopMACPri protocol improves the system throughput and minimizes energy consumption. Using a Markov chain model, we developed a model to analyse the performance of CoopMACPri protocol; and also derived closed-form expression of saturated system throughput and energy consumption. Performance evaluations validate the accuracy of the theoretical analysis, and also show that the performance of CoopMACPri protocol varies with the number of nodes. We observed that the simulation results and analysis reflects the effectiveness of the proposed protocol as per the specifications.

Role of the loop L-4,L-5 in allosteric regulation in mtHsp70s: in vivo significance of domain communication and its implications in protein translocation

Mitochondrial Hsp70 (mtHsp70) is essential for a vast repertoire of functions, including protein import, and requires effective interdomain communication for efficient partner-protein interactions. However, the in vivo functional significance of allosteric regulation in eukaryotes is poorly defined. Using integrated biochemical and yeast genetic approaches, we provide compelling evidence that a conserved substrate-binding domain (SBD) loop, L-4,L-5, plays a critical role in allosteric communication governing mtHsp70 chaperone functions across species. In yeast, a temperature-sensitive L-4,L-5 mutation (E467A) disrupts bidirectional domain communication, leading to compromised protein import and mitochondrial function. Loop L-4,L-5 functions synergistically with the linker in modulating the allosteric interface and conformational transitions between SBD and the nucleotide-binding domain (NBD), thus regulating interdomain communication. Second-site intragenic suppressors of E467A isolated within the SBD suppress domain communication defects by conformationally altering the allosteric interface, thereby restoring import and growth phenotypes. Strikingly, the suppressor mutations highlight that restoration of communication from NBD to SBD alone is the minimum essential requirement for effective in vivo function when primed at higher basal ATPase activity, mimicking the J-protein-bound state. Together these findings provide the first mechanistic insights into critical regions within the SBD of mtHsp70s regulating interdomain communication, thus highlighting its importance in protein translocation and mitochondrial biogenesis.

On the Communication Complexity of Secret Key Generation in the Multiterminal Source Model

Communication complexity refers to the minimum rate of public communication required for generating a maximal-rate secret key (SK) in the multiterminal source model of Csiszar and Narayan. Tyagi recently characterized this communication complexity for a two-terminal system. We extend the ideas in Tyagi's work to derive a lower bound on communication complexity in the general multiterminal setting. In the important special case of the complete graph pairwise independent network (PIN) model, our bound allows us to determine the exact linear communication complexity, i.e., the communication complexity when the communication and SK are restricted to be linear functions of the randomness available at the terminals.

Crowd Flow Segmentation based on Motion Vectors in H.264 Compressed Domain

In this work, we have explored the prospect of segmenting crowd flow in H. 264 compressed videos by merely using motion vectors. The motion vectors are extracted by partially decoding the corresponding video sequence in the H. 264 compressed domain. The region of interest ie., crowd flow region is extracted and the motion vectors that spans the region of interest is preprocessed and a collective representation of the motion vectors for the entire video is obtained. The obtained motion vectors for the corresponding video is then clustered by using EM algorithm. Finally, the clusters which converges to a single flow are merged together based on the bhattacharya distance measure between the histogram of the of the orientation of the motion vectors at the boundaries of the clusters. We had implemented our proposed approach on the complex crowd flow dataset provided by 1] and compared our results by using Jaccard measure. Since we are performing crowd flow segmentation in the compressed domain using only motion vectors, our proposed approach performs much faster compared to other pixel domain counterparts still retaining better accuracy.