A study of wireless sensor networks with focus on node localization

Abstract only availableDue to research in low-power, cheap wireless communications, Wireless Sensor Networks (WSN) has become one of the most exciting new fields of interest within computer science and engineering. Just as the Internet has made data readily available to many users, so will wireless sensor network, but on a different and larger scale. Because of Wireless Sensor Networks, we will be able to receive measurements of the physical phenomena around us, leading to their understanding and ultimately the utilization of this information for a wide range of applications. This research allows the evaluation of the many requirements that a wireless system must meet in order to be considered an effective WSN. Furthermore, because of these requirements, there still exist several unresolved research issues. Wireless Senor Networks are composed of individual of sensor nodes. Once the nodes are deployed, it is very important to be able to determine where each node is; furthermore, the position of the nodes need not be engineered or pre-determined. Being able to immediately locate a sensor node without having to rely on satellites or any other external infrastructure is one of the major research components of Wireless Sensor Networks that has received a great deal of attention.Louis Stokes Missouri Alliance for Minority Participatio

A Microphone Array System for Multimedia Applications with Near-Field Signal Targets

A microphone array beamforming system is proposed for multimedia communication applications using four sets of small planar arrays mounted on a computer monitor. A new virtual array approach is employed such that the original signals received by the array elements are weighted and delayed to synthesize a large, nonuniformly spaced, harmonically nested virtual array covering the frequency band [50, 7000] Hz of the wideband telephony. Subband multirate processing and near-field beamforming techniques are then used jointly by the nested virtual array to improve the performances in reverberant environments. A new beamforming algorithm is also proposed using a broadband near-field spherically isotropic noise model for array optimization. The near-field noise model assumes a large number of broadband random noises uniformly distributed over a sphere with a finite radius in contrast to the conventional far-field isotropic noise model which has an infinite radius. The radius of the noise model, thus, adds a design parameter in addition to its power for tradeoffs between performance and robustness. It is shown that the near-field beamformers designed by the new algorithm can achieve more than 8-dB reverberation suppression while maintaining sufficient robustness against background noises and signal location errors. Computer simulations and real room experiments also show that the proposed array beamforming system reduces beampattern variations for broadband signals, obtains strong noise and reverberation suppression, and improves the sound quality for near-field targets

Self-healing control flow protection in sensor applications

Since sensors do not have a sophisticated hardware archi-tecture or an operating system to manage code for safety, attacks injecting code to exploit memory-related vulnerabil-ities can present threats to sensor applications. In a sen-sor’s simple memory architecture, injected code can alter the control flow of a sensor application to either misuse ex-isting routines or download other malicious code to achieve attacks. To protect the control flow, this paper proposes a self-healing scheme that can detect attacks attempting to alter the control flow and then recover sensor applications to normal operations with minimum overhead. The self-healing scheme embeds diversified protection code at partic-ular locations to enforce access control in program memory. Both the access control code and the recovery code are de-signed to be resilient to control flow attacks that attempt to evade the protection. Furthermore, the self-healing scheme directly processes application code at the machine instruc-tion level, instead of performing control or data analysis on source code. The implementation and evaluation show that the self-healing scheme is lightweight in protecting sensor applications

Sciences for The 2.5-meter Wide Field Survey Telescope (WFST)

The Wide Field Survey Telescope (WFST) is a dedicated photometric survey facility under construction jointly by the University of Science and Technology of China and Purple Mountain Observatory. It is equipped with a primary mirror of 2.5m in diameter, an active optical system, and a mosaic CCD camera of 0.73 Gpix on the main focus plane to achieve high-quality imaging over a field of view of 6.5 square degrees. The installation of WFST in the Lenghu observing site is planned to happen in the summer of 2023, and the operation is scheduled to commence within three months afterward. WFST will scan the northern sky in four optical bands (u, g, r, and i) at cadences from hourly/daily to semi-weekly in the deep high-cadence survey (DHS) and the wide field survey (WFS) programs, respectively. WFS reaches a depth of 22.27, 23.32, 22.84, and 22.31 in AB magnitudes in a nominal 30-second exposure in the four bands during a photometric night, respectively, enabling us to search tremendous amount of transients in the low-z universe and systematically investigate the variability of Galactic and extragalactic objects. Intranight 90s exposures as deep as 23 and 24 mag in u and g bands via DHS provide a unique opportunity to facilitate explorations of energetic transients in demand for high sensitivity, including the electromagnetic counterparts of gravitational-wave events detected by the second/third-generation GW detectors, supernovae within a few hours of their explosions, tidal disruption events and luminous fast optical transients even beyond a redshift of 1. Meanwhile, the final 6-year co-added images, anticipated to reach g about 25.5 mag in WFS or even deeper by 1.5 mag in DHS, will be of significant value to general Galactic and extragalactic sciences. The highly uniform legacy surveys of WFST will also serve as an indispensable complement to those of LSST which monitors the southern sky.Comment: 46 pages, submitted to SCMP

Two Image-Template Operations for Binary Image Processing

This paper presents two new image algebra image-template operations match and mismatch derived from the general image-template product. These image algebra operations extend the binary morphological erosion and dilation operations and can be used to express elegantly most of binary image processing algorithms in a more natural way than binary morphological operations from the image processing viewpoint. In addition, the match and mismatch operations are easy to implement efficiently on SIMD bit-serial parallel computers. Keywords image algebra, mathematical morphology, binary image processing 1 . Introduction Binary image processing involves manipulating binary images consisting of only 1-pixels and 0-pixels. Binary image processing techniques are employed by binary machine vision systems in the detection and recognition of objects or object defects [3]. Binary morphology is an algebraic system concerning with analysis of shapes. It plays an important role in machine vision, since sh..

Image Algebra Techniques for Binary Image Component Labeling with Local Operators

. Binary image component labeling is a fundamental process in image processing and computer vision. This paper presents several image component labeling algorithms with local operators expressed in the language of image algebra. These algorithms are then analyzed for their time and space complexities. Keywords: image algebra, image component labeling, local operator 1. Introduction Labeling the connected components of a binary image is a fundamental process in image analysis and machine vision [1]. The process of labeling assigns a unique label to each connected component in the image. All the black pixels should be labeled, and pixels of a connected component should be assigned the same label. Once an image has been labeled, the components which correspond to different objects can be studied, described, and possibly recognized by higher level image analysis processes. It follows from the connectedness of image components in a binary image that labels can be propagated locally among ..