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In recent years, there are an increase in the mortality rate due to Chronic obstructive pulmonary disease (COPD) patients and it is estimated that it will increase in the coming years. Traditional methods take a long time to identify these diseases because a lot of clinical tests has to be performed for getting the confirmation, however with the advent of intelligent techniques as well as looking at the potential of the powerful techniques for predicting other critical diseases, it is believed that it would help to detect the chronic diseases at an early stage in a precise manner. In this paper, an attempt has been made to detect COPD patients and at the same time, it could distinguish the stages such as the early stage of chronic obstructive pulmonary disease patients (ESCP) and the Advanced stage of COPD patients (ASCP). We have used the Recursive Feature Elimination, Cross-Validated (RFECV) feature selection method to select features and then we consult the doctors, those are expert in the field to recommend the features among the features selected using RFECV method. The features selected using the doctor recommendation called features reduction with doctor recommendation (FRDR). After selecting two groups of features, we have used different machine learning algorithms to compare the performance of the algorithms as well as the importance of the features. It was found that the features selected using the RFECV method could able to provide accuracy of 96%, whereas the features selected with doctor recommendation name FRDR could able to provide accuracy of 90%. Although there is a difference of result in both the methods but overall, both set of features produces a good result. So, it is recommended that this approach would help distinguish different stages in real-life situations.

Nanosheet FETs (NSFETs) are expected as future devices that replace FinFETs beyond the 5nm node. Despite the importance of the devices, few studies report the impact of NSFETs in the full-chip level. Therefore, this paper presents NS3K, the first 3nm NSFET library, and presents the results in a full-chip scale. Based on our results, 3nm NSFET reduces power by −27.4%, total wirelength by −25.8%, number of cells by −8.5%, and area by −47.6% over 5nm FinFET, respectively, due to better devices and interconnect scaling. However, careful device/layout designs followed by routing-resource considering standard cells are required to maximize the advantages of 3nm technology.

This work presents a distributed message-passing (MP) strategy for cooperative localization of autonomous vehicles in vehicle-to-everything (V2X) networks. The reliability of vehicular localization requires vehicles to accurately estimate their locations without the dependency on a centralized manager or powerful computational resource. A simplified MP technique that parameterizes the probability distributions of vehicles’ locations in terms of pairs of average and accuracy is developed to meet these goals. The evaluation of the developed strategy shows that the localization is carried out in sufficient quality, with additional insights regarding appropriate settings for usage of cooperative localization.

In this article, we present an initial study of phantom sensation synthesis on the back side of the head. We proposed to render a vibrotactile flow between the temple, occipital, and parietal regions on the head using four actuators. Taking into account that humans perceive a vibrotactile stimulation on selected locations differently loud, we normalized a perceived amplitude of respective actuators through psychophysical experiment. By pairwise actuating of adjoined actuators, we rendered ten patterns of vibrotactile flow in different directions and evaluated through additional psychophysical experiment. The results shown 86 percent of the identification accuracy where the user felt continuous vibrotactile flow between active actuators.

We present a novel systematic design framework for general under-actuated tendon-driven (UATD) robotic systems to exhibit desired behaviors both during the free motion and the contact task. For this, we propose stiffness decomposition, which enables us to completely decompose the configuration space of the UATD robotic systems into the actuated space (with full actuation via active tendons) and the un-actuated space (with no actuation, only with passive compliance and contact wrench). The behavior in the actuated space is then fully-controllable, thus, the attainment of the desired behaviors, particularly those during the contact task, hinges upon that in the un-actuated space. For this, relying on the stiffness decomposition, we optimize the design parameters (e.g., tendon routing, pulley radius, passive compliance, etc.) to ensure the deformation in the un-actuated space as directional (e.g., for adaptive grasping) and minimized (e.g., pushing with posture maintained) for different contact wrench sets as possible, while also rendering the free motion to be as compliant and backdrivable as possible. The presented framework is then applied to design a UATD robotic finger and experimentally verified with the robot able to mimic the behavior of human index finger both during the free motion and pinch-pushing.

The application of congestion control can have a significant detriment to the quality of service experienced at higher layers, especially under high packet loss rates. The effects of throughput loss due to the congestion control misinterpreting packet losses in poor channels is further compounded for applications such as HTTP and video leading to a significant decrease in the user's quality of service. Therefore, we consider the application of congestion control to transport layer packet streams that use error-correction coding in order to recover from packet losses. We introduce a modified AIMD approach, develop an approximate mathematic model suited to performance analysis, and present extensive experimental measurements in both the lab and the “wild” to evaluate performance. Our measurements highlight the potential for remarkable performance gains, in terms of throughput and upper layer quality of service, when using coded transports., United States. Dept. of Defense. Assistant Secretary of Defense for Research & Engineering (United States. Air Force Contract FA8721-05-C-0002)

Gene prioritization is a class of methods for discovering genes implicated in the onset and progression of a disease. As candidate genes are ranked based on similarity to known disease genes according to different set of criteria, the overall aggregation of these ranked datasets is a vital step of the prioritization procedure. Aggregation of different lists of ordered genes is accomplished either via classical order statistics analysis or via combinatorial ordinal data fusion. We propose a novel approach to combinatorial gene prioritization via Linear Programming (LP) optimization and use the recently introduced weighted Kendall τ distance to assess similarities between rankings. The weighted Kendall τ distance allows for constructing aggregates that have higher accuracy at the top of the ranking, usually tested experimentally, and it can also accommodate ties in rankings and handle negative outliers. In addition, the Kendall distance does not use quantitative data which in many instances may be unreliable. We illustrate the performance of the prioritization method on a set of test genes pertaining to the Bardet-Biedl syndrome, schizophrenia, and HIV and show that the combinatorial method matches or outperforms state-of-the art algorithms such as ToppGene.

Metagenomics is an emerging field of molecular biology concerned with analyzing the genomes of environmental samples comprising many different diverse organisms. Given the nature of metagenomic data, one usually has to sequence the genomic material of all organisms in a batch, leading to a mix of reads coming from different DNA sequences. In deep high-throughput sequencing experiments, the volume of the raw reads is extremely high, frequently exceeding 600 Gb. With an ever increasing demand for storing such reads for future studies, the issue of efficient metagenomic compression becomes of paramount importance. We present the first known approach to metagenome read compression, termed MCUIUC (Metagenomic Compression at UIUC). The gist of the proposed algorithm is to perform classification of reads based on unique organism identifiers, followed by reference-based alignment of reads for individually identified organisms, and metagenomic assembly of unclassified reads. Once assembly and classification are completed, lossless reference based compression is performed via positional encoding. We evaluate the performance of the algorithm on moderate sized synthetic metagenomic samples involving 15 randomly selected organisms and describe future directions for improving the proposed compression method.

A characterization of systematic network coding over multi-hop wireless networks is key towards understanding the trade-off between complexity and delay performance of networks that preserve the systematic structure. This paper studies the case of a relay channel, where the source's objective is to deliver a given number of data packets to a receiver with the aid of a relay. The source broadcasts to both the receiver and the relay using one frequency, while the relay uses another frequency for transmissions to the receiver, allowing for a full-duplex operation of the relay. We analyze the decoding complexity and delay performance of two types of relays: one that preserves the systematic structure of the code from the source; another that does not. A systematic relay forwards uncoded packets upon reception, but transmits coded packets to the receiver after receiving the first coded packet from the source. On the other hand, a non-systematic relay always transmits linear combinations of previously received packets. We compare the performance of these two alternatives by analytically characterizing the expected transmission completion time as well as the number of uncoded packets forwarded by the relay. Our numerical results show that, for a poor channel between the source and the receiver, preserving the systematic structure at the relay (i) allows a significant increase in the number of uncoded packets received by the receiver, thus reducing the decoding complexity, and (ii) preserves close to optimal delay performance., Interconnect Focus Center (United States. Defense Advanced Research Projects Agency and Semiconductor Research Corporation) (Award RA306-S1), NBC Universal Television (Award PO 3000087512), United States. Air Force Office of Scientific Research (Award FA9550-09-1-0196), United States. Defense Advanced Research Projects Agency (Award 18870740-37362-C)

The deterministic wireless relay network model, introduced by Avestimehr et al., has been proposed for approximating Gaussian relay networks. This model, known as the ADT network model, takes into account the broadcast nature of wireless medium and interference. Avestimehr et al. showed that the Min-cut Max-flow theorem holds in the ADT network. In this paper, we show that the ADT network model can be described within the algebraic network coding framework introduced by Koetter and Medard. We prove that the ADT network problem can be captured by a single matrix, called the "system matrix". We show that the min-cut of an ADT network is the rank of the system matrix; thus, eliminating the need to optimize over exponential number of cuts between two nodes to compute the min-cut of an ADT network. We extend the capacity characterization for ADT networks to a more general set of connections. Our algebraic approach not only provides the Min-cut Max-flow theorem for a single unicast/multicast connection, but also extends to non-multicast connections such as multiple multicast, disjoint multicast, and two-level multicast. We also provide sufficiency conditions for achievability in ADT networks for any general connection set. In addition, we show that the random linear network coding, a randomized distributed algorithm for network code construction, achieves capacity for the connections listed above. Finally, we extend the ADT networks to those with random erasures and cycles (thus, allowing bi-directional links). Note that ADT network was proposed for approximating the wireless networks; however, ADT network is acyclic. Furthermore, ADT network does not model the stochastic nature of the wireless links. With our algebraic framework, we incorporate both cycles as well as random failures into ADT network model., 9 pages, 12 figures, submitted to Allerton Conference

In our previous work "An Algebraic Watchdog for Wireless Network Coding", we proposed a new scheme in which nodes can detect malicious behaviors probabilistically, police their downstream neighbors locally using overheard messages; thus, provide a secure global "self-checking network". As the first building block of such a system, we focused on a two-hop network, and presented a graphical model to understand the inference process by which nodes police their downstream neighbors and to compute the probabilities of misdetection and false detection. In this paper, we extend the Algebraic Watchdog to a more general network setting, and propose a protocol in which we can establish "trust" in coded systems in a distributed manner. We develop a graphical model to detect the presence of an adversarial node downstream within a general two-hop network. The structure of the graphical model (a trellis) lends itself to well-known algorithms, such as Viterbi algorithm, that can compute the probabilities of misdetection and false detection. Using this as a building block, we generalize our scheme to multi-hop networks. We show analytically that as long as the min-cut is not dominated by the Byzantine adversaries, upstream nodes can monitor downstream neighbors and allow reliable communication with certain probability. Finally, we present preliminary simulation results that support our analysis., 5 pages, 2 figures, to appear in IEEE ITW Dublin 2010

This paper proposes a fast and efficient multi-processor architecture for devices a requiring high speed performance. The proposed method connects four basic processor modules (BPM) including CPU's in a pipeline shape to enhance execution speed. Also, using a specific BPM selectively regarding to multimedia applications increases the efficiency, and has more flexibility by software implementation for needed functions without hardware replacement than using a hardware accelerator. This has been implemented using Verilog HDL and its performance is compared and analyzed in terms of complexity and speed of execution. Even the complexity of the proposed architecture increases 20% compared with the multi-core CPU method, speed increases 52%.

Multi-resolution codes enable multicast at different rates to different receivers, a setup that is often desirable for graphics or video streaming. We propose a simple, distributed, two-stage message passing algorithm to generate network codes for single-source multicast of multi-resolution codes. The goal of this "pushback algorithm" is to maximize the total rate achieved by all receivers, while guaranteeing decodability of the base layer at each receiver. By conducting pushback and code generation stages, this algorithm takes advantage of inter-layer as well as intra-layer coding. Numerical simulations show that in terms of total rate achieved, the pushback algorithm outperforms routing and intra-layer coding schemes, even with codeword sizes as small as 10 bits. In addition, the performance gap widens as the number of receivers and the number of nodes in the network increases. We also observe that naiive inter-layer coding schemes may perform worse than intra-layer schemes under certain network conditions., Comment: 9 pages, 16 figures, submitted to IEEE INFOCOM 2010

In this paper, we propose a multi-stage OVSF code generator using single code index. The performances of the conventional methods such as logic gates, counter or LUT are evaluated in terms of complexity, speed and power dissipation according to various spreading factors used in UMTS systems. The results are applied to our multi-stage design in order to implement the most efficient code generator. The proposed structure that is synthesized in Samsung 0.35 µm CMOS library decreases the power consumption up to 26.5%. It needs 203 more gates compared to the counter based generator which is the most efficient among the conventional methods, which can be ignored in terms of the whole chip area.

Network coding increases throughput and is robust against failures and erasures. However, since it allows mixing of information within the network, a single corrupted packet generated by a Byzantine attacker can easily contaminate the information to multiple destinations. In this paper, we study the transmission overhead associated with three different schemes for detecting Byzantine adversaries at a node using network coding: end-to-end error correction, packet-based Byzantine detection scheme, and generation-based Byzantine detection scheme. In end-to-end error correction, it is known that we can correct up to the min-cut between the source and destinations. However, if we use Byzantine detection schemes, we can detect polluted data, drop them, and therefore, only transmit valid data. For the dropped data, the destinations perform erasure correction, which is computationally lighter than error correction. We show that, with enough attackers present in the network, Byzantine detection schemes may improve the throughput of the network since we choose to forward only reliable information. When the probability of attack is high, a packet-based detection scheme is the most bandwidth efficient; however, when the probability of attack is low, the overhead involved with signing each packet becomes costly, and the generation-based scheme may be preferred. Finally, we characterize the tradeoff between generation size and overhead of detection in bits as the probability of attack increases in the network., 7 pages, 5 figures, MILCOM 2008

By improving our understanding of epithelial cell tubulogenesis in vitro we should improve our understanding of how these cells organize to form normal tissues such as the ducts and lobules that make up breast tissue. We do not fully understand how these ducts and lobules form. Because it is difficult to directly control and observe epithelial cell morphogenesis in vivo, we study it using in vitro culture systems. They are more easily controlled and observed. One of the most well studied models of tubulogenesis uses Madin-Darby canine kidney (MDCK) cells in culture systems: single cell layered cysts form tubules when exposed to hepatocyte growth factor (HGF). We have developed an in silico analogue that mimics the fundamental cell-level operating principles and system-level phenotypes of in vitro MDCK tubulogenesis. The creation and validation of the analogue required the specification and questioning of currently held assumptions. The analogue can be used to test hypotheses about mechanisms and in silico operating principles that may have in vitro counterparts. By increasing our understanding of the operating principles that govern in vitro epithelial cell growth and organization we are better positioned to understand how best to manipulate these operating principles to achieve specific tissue engineering objectives.

We consider the problem of serving multicast flows in a crossbar switch. We show that linear network coding across packets of a flow can sustain traffic patterns that cannot be served if network coding were not allowed. Thus, network coding leads to a larger rate region in a multicast crossbar switch. We demonstrate a traffic pattern which requires a switch speedup if coding is not allowed, whereas, with coding the speedup requirement is eliminated completely. In addition to throughput benefits, coding simplifies the characterization of the rate region. We give a graph-theoretic characterization of the rate region with fanout splitting and intra-flow coding, in terms of the stable set polytope of the 'enhanced conflict graph' of the traffic pattern. Such a formulation is not known in the case of fanout splitting without coding. We show that computing the offline schedule (i.e. using prior knowledge of the flow arrival rates) can be reduced to certain graph coloring problems. Finally, we propose online algorithms (i.e. using only the current queue occupancy information) for multicast scheduling based on our graph-theoretic formulation. In particular, we show that a maximum weighted stable set algorithm stabilizes the queues for all rates within the rate region., 9 pages, submitted to IEEE INFOCOM 2007