Feature extraction and ML techniques for static gesture recognition

The main objective of this study is to explore the utility of a neural network-based approach in hand gesture recognition. The proposed system presents two recognition algorithms to recognize a set of six specific static hand gestures, namely open, close, cut, paste, maximize, and minimize. The hand gesture image is passed through three stages: preprocessing, feature extraction, and classification. In the first method, the hand contour is used as a feature that treats scaling and translation of problems (in some cases). However, the complex moment algorithm is used to describe the hand gesture and to treat the rotation problem in addition to scaling and translation. The back-propagation learning algorithm is employed in the multilayer neural network classifier. The second method proposed in this article achieves better recognition rate than the first method.     

Integrating IPsec within OpenFlow Architecture for Secure Group Communication

Network securityprotocolssuch as IPsechave been used for many years to ensure robust end-to-end communication and are impor-tant in the context of SDN.Despite the widespread installation of IPsec to date,per-packet protection offered by the protocol isnot very compatible with OpenFlow and flow-like behavior.OpenFlow architecture cannot aggregate IPsec-ESP flows in transportmode or tunnel mode because layer-3 information is encrypted and therefore unreadable.In this paper,we propose using the Secu-rity Parameter Index(SPI)of IPsec within the OpenFlow architecture to identify and direct IPsec flows.Thisenables IPsec to con-form to the packet-based behavior of OpenFlow architecture.In addition,by distinguishing between IPsec flows,the architectureis particularly suited to secure group communication.     

Computing Travel Time Reliability in Transportation Networks with Multistates and Dependent Link Failures

The measurement of transportation network travel time reliability is imperative to provide drivers with accurate route guidance information and to generate the shortest path (or alternative paths) connecting origins and destinations, especially under conditions of varying demands and limited capacities. Previous studies assumed that link failures in a road network are statistically independent and that reliability probabilities are perfectly determinable. In real life, these assumptions are dubious, because the failure of a link in one particular area does not necessarily result in the complete failure of the neighboring link, but may lead to deterioration of its performance. This paper presents a new methodology to study the multistate system reliability analysis of transportation networks for which one cannot formulate an “all or nothing” type of failure criterion and in which dependent link failures are considered. The methodology is presented, using a numerical example, for computing the probability that travel time between an origin and a destination may exceed a threshold.     

Towards a unified visual framework in a binocular active robot vision system

This paper presents the results of an investigation and pilot study into an active binocular vision system that combines binocular vergence, object recognition and attention control in a unified framework. The prototype developed is capable of identifying, targeting, verging on and recognising objects in a cluttered scene without the need for calibration or other knowledge of the camera geometry. This is achieved by implementing all image analysis in a symbolic space without creating explicit pixel-space maps. The system structure is based on the ‘searchlight metaphor’ of biological systems. We present results of an investigation that yield a maximum vergence error of ～6.5 pixels, while ～85% of known objects were recognised in five different cluttered scenes. Finally a ‘stepping-stone’ visual search strategy was demonstrated, taking a total of 40 saccades to find two known objects in the workspace, neither of which appeared simultaneously within the field of view resulting from any individual saccade.     

On the design of multi-wavelength copy interconnects with reduced complexity

A multi-wavelength copy interconnect is a switching network capable of replicating a signal arriving at the input on a specific wavelength to one or more outputs possibly on different wavelengths. Such an interconnect can be useful in building optical multicast switches for wavelength division multiplexing (WDM) networks. In this article, we investigate, for the first time, the problem of designing copy networks that can simultaneously multicast input signals to a set of outputs while changing the wavelength of the replica according to the required routing pattern. We propose a novel multi-wavelength crossbar (MWX) switch that can switch an input signal on a specific wavelength to two different output wavelengths. The proposed MWX is used as a building block to construct two classes of multi-log_2N copy networks, namely, baseline and Bene? interconnects. The design space of the proposed interconnect classes is characterized and their hardware complexity is analyzed. We show that the proposed interconnects are transparent to existing multicast routing algorithms, and present simple routing algorithms for routing of multicast requests over the proposed designs. Comparisons with existing designs confirm that the proposed interconnects require a smaller number of space switches and wavelength conversion processes as compared to most conventional copy networks. In particular, for a large number of wavelengths and for any number of fibers the proposed design requires 50% less switching elements as compared to best available designs.     

An Efficient,Scalable Key Transport Scheme (ESKTS) for Delay/Disruption Tolerant Networks

In the past, security protocols including key transport protocols are designed with the assumption that there are two parties communication with each other and an adversary tries to intercept this communication. In Delay/Disruption Tolerant Networking (DTN), packet delivery relies on intermediate parties in the communication path to store and forward the packets. DTN security architecture requires that integrity and authentication should be verified at intermediate nodes as well as at end nodes and confidentiality should be maintained for end communicating parties. This requires new security protocols and key management to be defined for DTN as traditional end-to-end security protocols will not work with DTN. To contribute towards solving this problem, we propose a novel Efficient and Scalable Key Transport Scheme (ESKTS) to transport the symmetric key generated at a DTN node to other communicating body securely using public key cryptography and proxy signatures. It is unique effort to design a key transport protocol in compliance with DTN architecture. ESKTS ensures that integrity and authentication is achieved at hop-by-hop level as well as end-to-end level. It also ensures end-to-end confidentiality and freshness for end communicating parties. This scheme provides a secure symmetric key transport mechanism based on public key cryptography to exploit the unique bundle buffering characteristics of DTN to reduce communication and computation cost .     

High-sensitivity determination of birefringence in turbid media with enhanced polarization-sensitive optical coherence tomography

Polarization-sensitive optical coherence tomography provides high-resolution cross-sectional characterization of birefringence in turbid media. Weakly birefringent biological tissues such as the retinal nerve fiber layer (RNFL) require advanced speckle noise reduction for high-sensitivity measurement of form birefringence. We present a novel method for high-sensitivity birefringence quantification by using enhanced polarization-sensitive optical coherence tomography (EPS-OCT) and introduce the polarimetric signal-to-noise ratio, a mathematical tool for analyzing speckle noise in polarimetry. Multiple incident polarization states and non-linear fitting of normalized Stokes vectors allow determination of retardation with +/-1 degrees uncertainty with invariance to unknown unitary polarization transformations. Results from a weakly birefringent turbid film and in vivo primate RNFL are presented. In addition, we discuss the potential of EPS-OCT for noninvasive quantification of intracellular filamentous nanostructures, such as neurotubules in the RNFL that are lost during the progression of glaucoma.     

Flow and spawning habitat relationships for Dolly Varden: Understanding habitat–population dynamics in the Canadian Western Arctic

Northern form Dolly Varden (Salvelinus malma malma) have been designated as a species of Special Concern in Canada due to declines in population abundance and potential threats. Concern over detrimental effects of low flows on population abundance prompted research on how variability in discharge regimes influence habitat availability. Habitat suitability indices for prespawning and spawning adult anadromous Dolly Varden from two streams were integrated into a two‐dimensional hydrodynamic habitat model to assess the effect of flow variability on usable habitat. Regional hydrographs were used to identify an ecologically relevant range of flows that provided optimal spawning habitat for these populations and examine the relationship between abundance and discharge. Adults spawned in the tail end of pools at moderate water depths and water velocities, and used pebble‐ to cobble‐sized substrate for building redds; whereas, prespawning adults occupied deeper pools with moderate velocities and used cobble for cover. Model outputs showed that spawning habitat availability was optimized at flow rates between 1.6 and 3.0 m³/s and between 1.0 and 6.0 m³/s in Fish Hole Creek (FHC) and Little Fish Creek, respectively. A positive relationship between flows during the fall spawning period and abundance of the FHC population suggests that higher flows coinciding with optimal habitat availability may have contributed to positive recruitment. To strengthen and refine this habitat–population relationship for Dolly Varden in this area requires investigation of a broader suite of variables associated with environmental regimes and physical habitat in reaches used for spawning.     

Development of ensemble machine learning approaches for designing fiber-reinforced polymer composite strain prediction model

Engineering with Computers - Over the past few decades, it has been observed a remarkable progression in the development of computer aid models in the field of civil engineering. Machine learning...