Signal and Image Processing

This report describes the design, implementation, evaluation and original enhancements to the Live-Wire method for 2D and 3D image segmentation. Live-Wire 2D employs a semi-automatic paradigm; the user is asked to select a few boundary points of the object to segment, to steer the process in the right direction, while the result is displayed in real time. In our implementation segmentation is extended to three dimensions by performing this process on a slice-by-slice basis. User's time and involvement is further reduced by allowing him to specify object contours in planes orthogonal to the slices. If these planes are chosen strategically, Live-Wire 3D can perform 2D segmentation in the plane of each slice automatically. This report also proposes two improvements to the original method, path heating and a new graph edge feature function based on variance of path properties along the boundary. We show that these improvements lead up to a 33% reduction in interaction with the user, and improved delineation in presence of strong interfering edges.

Illumination invariance remains the most researched, yet the most challenging aspect of automatic face recognition. In this paper we investigate the discriminative power of colour-based invariants in the presence of large illumination changes between training and test data, when appearance changes due to cast shadows and non-Lambertian effects are significant. Specifically, there are three main contributions: (i) we employ a more sophisticated photometric model of the camera and show how its parameters can be estimated, (ii) we derive several novel colour-based face invariants, and (iii) on a large database of video sequences we examine and evaluate the largest number of colour-based representations in the literature. Our results suggest that colour invariants do have a substantial discriminative power which may increase the robustness and accuracy of recognition from low resolution images.

Dynamically changing background ("dynamic background") still presents a great challenge to many motion-based video surveillance systems. In the context of event detection, it is a major source of false alarms. There is a strong need from the security industry either to detect and suppress these false alarms, or dampen the effects of background changes, so as to increase the sensitivity to meaningful events of interest. In this paper, we restrict our focus to one of the most common causes of dynamic background changes: that of swaying tree branches and their shadows under windy conditions. Considering the ultimate goal in a video analytics pipeline, we formulate a new dynamic background detection problem as a signal processing alternative to the previously described but unreliable computer vision-based approaches. Within this new framework, we directly reduce the number of false alarms by testing if the detected events are due to characteristic background motions. In addition, we introduce a new dataset suitable for the evaluation of dynamic background detection. It consists of real-world events detected by a commercial surveillance system from two static surveillance cameras. The research question we address is whether dynamic background can be detected reliably and efficiently using simple motion features and in the presence of similar but meaningful events such as loitering. Inspired by the tree aerodynamics theory, we propose a novel method named local variation persistence (LVP), that captures the key characteristics of swaying motions. The method is posed as a convex optimization problem whose variable is the local variation. We derive a computationally efficient algorithm for solving the optimization problem, the solution of which is then used to form a powerful detection statistic. On our newly collected dataset, we demonstrate that the proposed LVP achieves excellent detection results and outperforms the best alternative adapted from existing art in the dynamic background literature.

Year 2009 marks the completion of 50 years of the invention of CORDIC (COordinate Rotation DIgital Computer) by Jack E. Volder. The beauty of CORDIC lies in the fact that by simple shift-add operations, it can perform several computing tasks such as the calculation of trigonometric, hyperbolic and logarithmic functions, real and complex multiplications, division, square-root, solution of linear systems, eigenvalue estimation, singular value decomposition, QR factorization and many others. As a consequence, CORDIC has been utilized for applications in diverse areas such as signal and image processing, communication systems, robotics and 3-D graphics apart from general scientific and technical computation. In this article, we present a brief overview of the key developments in the CORDIC algorithms and architectures along with their potential and upcoming applications.

We would like to invite you to join this exciting new project as a chapter contributor. Since this is a textbook, a great deal of this chapter entails a survey on the topic under the paradigm of cyber-physical systems, what can be done onboard and remotely, the distributed nature of the system and some exercises on futurology (anticipating trends can shed some light on upcoming designs). IET will bring great visibility to your work. You are welcome to suggest another topic/chapter title if you feel it would be more suitable. Each chapter should be around 20-25 pages each and can be submitted as a Word or Latex File. The IET will send you additional information (formatting, permission form, etc.) with the contributor's agreement once you have agreed to contribute to the book. Visit https:// www.theiet.org/resources/author-hub/books/index.cfm to get all information you need as a contributor to an IET research-level book. Each book is expected to have a total number of 500 printed pages (based on approximately 550 words per page with a 20% allowance for figures and tables). We have included a tentative schedule and list of topics below. If this is something you would consider, please send me the title of your chapter, a short description/abstract of the chapter content, and your full contact details. We will expect original content and new results for this book. You can, of course, reuse published material but the percentage of material reuse for the chapter should be less than 40%. The IET will run a piracy software on the full manuscript to control that you are including original material and will reject chapters who contain a large amount of already-published material so please do take this into consideration.

Comparison of image processing techniques is critically important in deciding which algorithm, method, or metric to use for enhanced image assessment. Image fusion is a popular choice for various image enhancement applications such as overlay of two image products, refinement of image resolutions for alignment, and image combination for feature extraction and target recognition. Since image fusion is used in many geospatial and night vision applications, it is important to understand these techniques and provide a comparative study of the methods. In this paper, we conduct a comparative study on 12 selected image fusion metrics over six multiresolution image fusion algorithms for two different fusion schemes and input images with distortion. The analysis can be applied
to different image combination algorithms, image processing methods, and over a different choice of metrics that are of use to an image processing expert. The paper relates the results to an image quality measurement based on power spectrum and correlation analysis and serves as a summary of many contemporary techniques for objective assessment of image fusion algorithms.

The performance analysis of VLSI based Fast Efficient Lossless Image Compression System (FELICS) based techniques which involves various methods and parameter to be measured. Block Based Compression Algorithm is used to analyse the images within each pixel before the storage space processes and therefore the size of the memory gets reduced. Here, differential values are captured and quantized, then the differential coding scheme uses the concept of selecting the brightest pixel as the reference pixel. The difference between brightest pixel and successive pixel is calculated and quantized. Hence, their range is compressed and the spatial redundancy can be removed using BBC algorithm. Thus, the proposed scheme reduces the accumulation of error and also reduces the requirement of memory. Thus, the Peak Signal to Noise Ratio value can be improved and Bits per Pixel value can be reduced. This is created for any given input image and thus the input image may be of any form. After that the image is converted into the binary form or header file conversion and these files are implemented into Xilinx Platform Studio and analyzed.
The future scope of this module is that the quality of the image can be further improved with high peak signal to noise ratio value using some other compression techniques. This method can be further enhanced by the implementation of Field Programmable Gate Array kit.

As the problem of urban traffic congestion spreads, there is a pressing need for the control. Traffic problems nowadays are increasing because of the growing number of vehicles and the limited resources provided by current infrastructures. The simplest way for controlling a traffic light uses timer for each phase. Another way is to use electronic sensors in order to detect vehicles, and produce signal that cycles. We propose a system for controlling the traffic light by image processing.

Biomass co-firing with lignite represents an attractive solution for operating lignite-fired thermal power plants (TPP) with the dual advantage of using local renewable resources and  imultaneously reducing emissions. The subject of this study is technical and environmental investigation of the feasibility of the cofiring of Soma lignite with some dried agricultural residues in the Soma thermal power plant from the exergy analysis perspective, using THERMOFLEX simulation software. The use of biomass cofiring with poor quality coal could allow Turkey to comply with Kyoto commitments while benefiting from using indigenous fuel resources and reducing biomass waste disposal problems. Two technologies are considered; (1) direct cofiring, in which biomass is mixed with lignite in the same mill and fed into the boiler furnace and (2) parallel cofiring method, in which biomass is fired in a separate circulating fluidized bed boiler and produced steam is supplemented into the steam network of the power plant. The investigations reveal that both direct and parallel co-firing of the biomass could result in a significant decrease in fuel consumption, emissions and exergy destruction and a slight increase in the exergy efficiency of the Soma TPP. Olive waste, in particular, has a positive effect on general performance and emissions of the TPP, with fuel consumption, CO2 , SO2
and dust emissions, in direct co-firing dropping by approximately 20, 4, 19 and 18 percent, respectively, and in parallel co-firing by 26, 3, 20 and 25 percent, respectively.

This technical report update presents use case of CCSDS DVB-S2 for space telemetry. The DVB-S2 space telemetry blue book has been issue in 2013 by CCSDS. The following use cases are presented in the slides of this report :

- CNES DVB-S2 X-band use case for post-Pleiade

- CNES/ESA X-band telemetry for cubesats

- ESA/DGA ( with CNES support ) DVB-S2 coding for ARTEMIS – LOLA optical telemetry links

- Exemple of NASA’s future work on DVB-S2 Ka band space telemetry

- TDRS – ISS DVB-S2 Ka band coms

- NASA DVB-S2 modem test with HPA for telemetry

- DVB-S2 : Option for TDRS-Cubsat links using for instance VCM or ACM, HOM, Ka-band :

- DVB-S2 telemetry studied in China among other solutions

- Miniature DVB-S2 Ka-band telemetry transmitter Development activity for NASA-AMES center

- NASA LRCD DVB-S2 codes

- DVB-S2 LEO to GEO RF Cross Links

- Use of DVB-S2 telemetry by Aerospace corp

- Ka band for Cubesat with DVB-S2, exemple of DVB-S2 image telemetry for cubesat in Ka band

- NASA SBIR/STTR Technologies : DVB-S2 LEO-LEO Intersatellite links in Ka band

- DVB-S2 TM studied for cubesats for VHF links

- DVB-S2 Telemetry on DOVE-1 nanosatellite

- Constellation of more than 100 LEO nanosats with X-band DVB-S2 ACM telemetry : Flock

- DVB-S2 Telemetry on 6U-Cubsats : Cranfield University

- Pre-project use case DVB-S2 X-band telemetry

- High Efficiency transmitter for nanosatellite - master thesis - use of DVB-S2 - TU Delft & ISIS

- DVB-S2 Telemetry use case on GEOS-R (NOAA - NASA)

- Antartic Broadband nanosat DVB-S2 (Australia Space Research Program)

- EUMETSAT DVB-S2 use case to send meteo images to end users

- Use of DVB-S2 in Asia to send meteo and earth observation images to end users

- GEO-KOMPSAT-2 (Geostationary - Korea Multi-Purpose Satellite-2) Program / Cheollian-2 / GK-2

- Outernet cubesat LEO DTE data casting

- Exemple of Space Agency space telemetry ground network compatible with CCSDS DVB-S2 (NASA NEN and SN)

- Two Exemples of commercial space telemetry ground network compatible with DVB-S2

- Presentation of DVB-S2 eXtension (DVB-S2x)

- Technical possibility of reactive TT&C Ka band LEO terminal using a DVB-S2 variant via Inmarsat 5

As shown by the slides, numerous projects have already adopted or earmarked DVB-S2 for their near earth space telemetry, for a wide variety of scenarii ( LEO DTE, LEO-GEO ISLs, LEO-LEO ISLs, … ). Significant current and future use of the DVB-S2 CCSDS standard (CCSDS 131.3-B-1) for telemetry is a fact. CCSDS DVB-S2 telemetry is used in X band, Ka band and optical band, and also in VHF, UHF,  L and S band. Several space agencies are significant DVB-S2 telemetry users, and other earth observation operators as well

Our aim is to estimate the perspective-effected geometric distortion of a scene from a video feed. In contrast to most related previous work, in this task we are constrained to using low-level, spatio-temporally local motion features only. This particular challenge arises in many semi-automatic surveillance systems which alert a human operator to potential abnormalities in the scene. Low-level, spatio-temporally local motion features are sparse (and thus require comparatively little storage space) and sufficiently powerful in the context of video abnormality detection to reduce the need for human intervention by more than 100-fold. This paper introduces three significant contributions: (i) we describe a dense algorithm for perspective estimation which uses motion features to estimate the perspective distortion at each image locus and then polls all such local estimates to arrive at the globally best estimate, (ii) we also present an alternative coarse algorithm which subdivides the image frame into blocks, and uses motion features to derive block-specific motion characteristics and constrain the relationships between these characteristics, with the perspective estimate emerging as a result of a global optimization scheme, and (iii) we report the results of an evaluation using nine large sets acquired using existing close-circuit television (CCTV) cameras, not installed specifically for the purposes of this work. Our findings demonstrate that both of the proposed methods are successful, their accuracy matching that of human labelling using complete visual data (by the constraints of the setup unavailable to our algorithms).

The technique of direct and inverse fuzzy (F-)transforms of three different types is
introduced and approximating properties of the inverse F-transforms are described.
All three types of the direct F-transform are transformations from a function space
to a finite dimensional vector space. The first (ordinary) F-transform is constructed
on the basis of the ordinary algebra of reals, while the other two types of the F-
transform are constructed on the basis of residuated lattice.
The core idea of the technique of F-transforms is a fuzzy partition of a universe
into fuzzy subsets (factors, clusters, granules etc.). We claim that for a sufficient
representation of a function defined on this universe, we may consider its average
values over fuzzy subsets from the partition. Thus, a function can be associated
with a mapping from a set of fuzzy subsets to the set of its thus obtained average
values.
A number of theorems establishing best approximation properties of the inverse
F-transforms are proved. In fact, three types of the inverse F-transform are the best
approximations in average, from below, and from above respectively.
As one of many possible applications, we present a method of image compression
and reconstruction on the basis of the F-transform.

International Journal of Electrical and communication engineering (IJECE) is an open access peer-reviewed journal that publishes quality articles contributing new results in all areas of Applied Control Systems, Electrical Engineering and Electronics Engineering. The Journal of Electrical and communication engineering (IJECE) is an abstracted and indexed international journal of high quality devoted to the publication of original research papers from Control Systems, Electrical Engineering, Power Systems, Automation, Electronics Engineering, Networks and Communication Systems and their broad range of applications.

The performance of a photovoltaic (PV) panel is affected by its orientation and its tilt angle with the horizontal plane. This is because both of these parameters change the amount of solar energy received by the surface of the PV panel. A mathematical model was used to estimate the total solar radiation on the tilted PV surface, and to determine optimum tilt angles for a PV panel installed in Sanliurfa, Turkey. The optimum tilt angles were determined by searching for the values of angles for which the total radiation on the PV surface was maximum for the period studied. The study also investigated the effect of two-axis solar tracking on energy gain compared to a fixed PV panel. This study determined that the monthly optimum tilt angle for a PV panel changes throughout the year with its minimum value as 13° in June and maximum value as 61° in December. The results showed that the gains in the amount of solar radiation throughout the year received by the PV panel mounted at monthly optimum tilt angles with respect to seasonal optimum angles and tilt angel equal to latitude were 1.1% and 3.9%, respectively. Furthermore, daily average of 29.3% gain in total solar radiation results in an daily average of 34.6% gain in generated power with two-axis solar tracking compared to a south facing PV panel fixed at 14° tilt angle on a particular day in July in Sanliurfa, Turkey.

As Frame rate is the frequency at which an imaging device produces unique consecutive images called frames. Both video and photographic films capture a series of frames (still images) in rapid succession. For instance, the NTSCsystem delivers 29.97frames/s and PAL system delivers 25frames/s.Frame Rate Conversion algorithms are used in compression, video format conversion, quality enhancement, stereo vision, etc. The most popular application is format conversion. The difference in frame rates between film (generally 24 frames/s) and television (30 or 25 frames/s) meant that simply playing a film into a television camera would result in flickering when the film frame was changed in mid-field of the TV frame.Frame Rate Conversion makes the motion of objects smoother and therefore more pleasant for eyes. It allows slowing down the playback speed thus making the objects' movements more evident. In this paper we present an approach of converting the frame rate of a video by duplicating specific frames. Also, the recovery of the original video from the converted video is also performed.

Digital images often contain "noise" which takes away their clarity and sharpness. Most of the existing denoising algorithms do not offer the best solution because there are difficulties such as removing strong noise while leaving the features and other details of the image intact. Faced with the problem of denoising, we tried solving it with a Convolutional Neural Network architecture called the "U-Net". This paper deals with the training of a U-Net to remove 3 different kinds of noise: Gaussian, Blockiness, and Camera shake. Our results indicate the effectiveness of U-Net in denoising images while leaving their features and other details intact

The ability of Minkowski Functionals to characterize local structure in different biological tissue types has been demonstrated in a variety of medical image processing tasks. We introduce anisotropic Minkowski Functionals (AMFs) as a novel variant that captures the inherent anisotropy of the underlying gray-level structures. To quantify the anisotropy characterized by our approach, we further introduce a method to compute a quantitative measure motivated by a technique utilized in MR diffusion tensor imaging, namely fractional anisotropy. We showcase the applicability of our method in the research context of characterizing the local structure properties of trabecular bone micro-architecture in the proximal femur as visualized on multi-detector CT. To this end, AMFs were computed locally for each pixel of ROIs extracted from the head, neck and trochanter regions. Fractional anisotropy was then used to quantify the local anisotropy of the trabecular structures found in these ROIs and to compare its distribution in different anatomical regions. Our results suggest a significantly greater concentration of anisotropic trabecular structures in the head and neck regions when compared to the trochanter region (p < 10-4). We also evaluated the ability of such AMFs to predict bone strength in the femoral head of proximal femur specimens obtained from 50 donors. Our results suggest that such AMFs, when used in conjunction with multi-regression models, can outperform more conventional features such as BMD in predicting failure load. We conclude that such anisotropic Minkowski Functionals can capture valuable information regarding directional attributes of local structure, which may be useful in a wide scope of biomedical imaging applications.

This paper examines the capability, performance, and relevance of a signal processing toolkit in Java, a programming language for Web-based applications. Due to the simplicity, ease and application use of the toolkit and with the advanced Internet technologies such as Remote Method Invocation (RMI), a spectral estimation applet has been created in the Java environment. This toolkit also provides an interactive and visual approach in understanding the various theoretical concepts of spectral estimation and shows the need to create more application applets to better understand the various concepts of signal and image processing.

Applications based on Fast Fourier Transform (FFT) such as signal and image processing require high computational power, plus the ability to choose the algorithm and architecture to implement it. This paper explains the realization of a Split Radix FFT (SRFFT) processor based on a pipeline architecture reported before by the same authors. This architecture has as basic building blocks a Complex Butterfly and a Delay Commutator. The main advantages of this architecture are:

WebRTC includes a set of novel technologies and standards that provide high quality audio, video and arbitrary data exchange. By enabling rich interactivity experience, We-bRTC allows the users to directly interact with use of web and mobile applications without the need for additional plugins. The open standard Opus codec is a default audio codec employed by WebRTC for speech communication and music streaming with a wide range of bitrates supported. This range of bitrates is available for narrowband (300-3400 Hz), wideband (100-7000 Hz) up to super-wideband (50-14000 Hz) audio bandwidths. To estimate a quality experienced by the end user for voice transmission service, E-model standardized in the ITU-T Rec. G.107 (a narrowband version) and the ITU-T Rec. G.107.1 (a wideband version) can be used. With the upcoming extension towards the super-wideband E-model, it will be soon possible to estimate the quality of narrowband, wideband as well as super-wideband speech communication. In this paper, we calculate two codec specific parameters, namely the equipment impairment factor Ie and packet loss robustness Bpl for the super-wideband mode of the Opus codec using the instrumental method. The derived values make it possible to integrate the E-model in real-time communication applications including WebRTC to assess the quality experienced by the end user.

Deléchelle et al. proposed an analytical approach (formulated as a partial differential equation (PDE)) for sifting process. This PDE-based approach is applied on signals. The analytical approach has a behavior similar to that of the EMD proposed by Huang.

ABSTRACT The modern Great Basin of the interior western United States is characterized by surface winds with considerable spatial and temporal variabilities. Wind records from the second half of the 20th century for 12 Great Basin localities, analyzed with standard aeolian-sediment transport methods developed elsewhere in the world, reflect this complexity. The drift potential (DP) for aeolian deposits is generally moderate (DP 200– 400) in the western Great Basin and weak (DP b 200) in the central Great Basin where winds are
predominantly west-southwesterly. DP is relatively high (DP N 300) at the eastern edge of the Great Basin where the dominant prevailing wind direction is south-southwesterly. Both DP and resultant drift direction (RDD) are consistent with synoptic meteorological observations of the evolution of cold fronts in the Great Basin. Meteorological observations show that effective winds to produce dunes are most commonly the result of late winter–early spring cyclogenesis. There has been considerable temporal variability of DP in the latter half of the 20th century. Most of the Great Basin has experienced decreasing wind strength since 1973, consistent with recent studies of wind strength in North America and elsewhere. Dune morphology matches both localized RDD and temporal variations in DP reasonably well in the Great Basin. The results demonstrate that local topography can have an important influence on wind directionality, thus providing a cautionary note on the interpretation of dune morphology in the paleoclimatic and stratigraphic record.

Construction progress monitoring has been perceived as one of the key factors that prompt the achievement of a construction project. However, assessing the progress is time consuming, costly and obliges specialized personnel to reduce disagreements and approximate the actual performance to the original plan as close as possible. Image processing is a promising method that has been developed for automated monitoring of construction projects. It has attracted increasing attention for progress monitoring, quality assurance and work space analyses. Nonetheless, remarkable drawbacks still remain in image processing, particularly for outdoor environment such as construction progress monitoring. The principle downside of image processing goes back to the image resolution. Ambient lightning condition significantly affects the image quality which does affect the accuracy of data, extracted from related images. Much research strives to reduce the level of errors for data extraction but so far none has been able to deliver complete satisfactory and reliable result. In this research a novel approach based on thermal image analysis is presented. The new method consists of three phases: First, collecting the thermal and original images by utilizing Infrared-Camera. Second, estimating the position of captured images by the use of wireless sensor network implemented in the work space. Finally, the 3D plan will be updated automatically in the Building Information Modeling (BIM) software. The preliminary experimental results from an actual concrete building construction site show the feasibility of inferring the actual state of progress by the use of thermal images to overcome the limitation of vision monitoring. 

AUTOMATED CONSTRUCTION PROGRESS MONITORING USING THERMAL IMAGES AND WIRELESS SENSOR NETWORKS. Available from: https://www.researchgate.net/publication/275024236_AUTOMATED_CONSTRUCTION_PROGRESS_MONITORING_USING_THERMAL_IMAGES_AND_WIRELESS_SENSOR_NETWORKS#share [accessed Sep 11, 2015].

In this paper, we present a new complex electronic system for facilitating communication with severely disabled patients and telemonitoring their physiological parameters. The proposed assistive system includes three subsystems (Patient, Server, and Caretaker) connected to each other via the Internet. The two-way communication function is based on keywords technology using a WEB application implemented at the server level, and the application is accessed remotely from the patient’s laptop/tablet PC. The patient’s needs can be detected by using different switch-type sensors that are adapted to the patient’s physical condition or by using eye-tracking interfaces. The telemonitoring function is based on a wearable wireless sensor network, organized around the Internet of Things concept, and the sensors acquire different physiological parameters of the patients according to their needs. The mobile Caretaker device is represented by a Smartphone, which uses an Android application for communicating with patients and performing real-time monitoring of their physiological parameters.

Phronetic organizational research is an approach to the study of management and organizations focusing on ethics and power. It is based on a contemporary interpretation of the Aristotelian concept phronesis, usually as ‘prudence’. Phronesis is the ability to think and act in relation to values, to deliberate about ‘things that are good or bad for humans’ in the words of Aristotle (1976:1140a24–b12). Phronetic organizational research effectively provides answers to the following four value-rational questions, for specific problematics in management and organization studies: 1. Where are we going with this specific management problematic? 2. Who gains and who loses, and by which mechanisms of power? 3. Is this development desirable? 4. What, if anything, should we do about it?

The thesis concentrates on computational methods pertaining to ancient ostraca - ink on clay inscriptions, written in Hebrew. These texts originate from the biblical kingdoms of Israel and Judah, and dated to the late First Temple period (8th – early 6th centuries BCE). The ostraca are almost the sole remaining epigraphic evidence from the First Temple period and are therefore important for archaeological, historical, linguistic, and religious studies of this era. This “noisy” material offers a fertile ground for the development of various “robust” image analysis, image processing, computer vision and machine learning methods, dealing with the challenging domain of ancient documents’ analysis. The common procedures of modern epigraphers involve manual and labor-intensive steps, facing the risk of unintentionally mixing documentation with interpretation. Therefore, the main goal of this study is establishing a computerized paleographic framework for handling First Temple period epigraphic material. The major research questions, addressed in this thesis are: quality evaluation of manual facsimiles; quality evaluation of ostraca images; automatic binarization of the documents and its subsequent refinement; quality evaluation of binarizations on global and local levels; identification of different writers between inscriptions (two distinct methods are proposed); image segmentation (with improvements over the classical Chan-Vese algorithm); and letters’ shape prior estimation. The developed methods were tested on real-world archaeological and modern data and their results are found to be favorable.

Year 2009 marks the completion of 50 years of the invention of CORDIC (COordinate Rotation DIgital Computer) by Jack E. Volder. The beauty of CORDIC lies in the fact that by simple shift-add operations, it can perform several computing tasks such as the calculation of trigonometric, hyperbolic and logarithmic functions, real and complex multiplications, division, square-root, solution of linear systems, eigenvalue estimation, singular value decomposition, QR factorization and many others. As a consequence, CORDIC has been utilized for applications in diverse areas such as signal and image processing, communication systems, robotics and 3-D graphics apart from general scientific and technical computation. In this article, we present a brief overview of the key developments in the CORDIC algorithms and architectures along with their potential and upcoming applications.

This presentation aimed the major applications of Digital Image Processing techniques in Vision-based Intelligent Transportation Systems, which utilizes roadway/in-vehicle cameras for further processing. Some applications such as Automatic License-plate Recognition, Speed Measurement, Vehicle Count, Traffic Flow Estimation and Vehicle Type Classification are discussed in details in this document. The presentation took place as a workshop with the same name in Guilan University Research Festival 2018.

Everyday Millions of children are travelling to school by school bus from their homes. There is always a question in parent's mind that their children reaching school safely and also how safe using school bus for transportation of their children. This project presents an embedded system that monitor and automates pickup and drop-off of school children to enhance the safety of children during the daily transportation from and to school. This system consists of two main units, a bus unit and a school unit. The bus unit is used to detect when a child boards or leaves the bus and also location of. This information is communicated to the school unit that identifies which of the children did not board or leave the bus and also to the parent. The bus unit also consists of sensors which will alert the driver before and during journey. The school unit has web-based database-driven application that provides useful information about the children to its management and to authorized personal's.

Inverse Synthetic Aperture Radar (ISAR) provides a very effective technique for reconstructing high resolution Imagery from raw data collected by relatively small antenna. ISAR imaging is induced by target motion and is obtained by means of a signal processing that can be enabled both on and off-line. ISAR produces high-resolution on two- and three-dimensional images by taking into account the information in both down-range direction (received echoes from target scatterers in time domain) and cross-range direction (Doppler). ISAR radars are commonly used on vessels or aircraft and can provide a radar image of sufficient quality for target recognition. The ISAR image is often adequate to discriminate between various missiles, military aircraft, and civilian aircraft. This project deals with MATLAB based signal processing system to perform Range-Doppler processing in real-time for Linear FMCW (frequency Modulated Continuous Wave) radar systems. The Range-Doppler Image can be obtained after coherent integration of several frequency sweepings. Range-Doppler images can be used later for identification and classification algorithms.

This article presents results from the first statistically significant study of cost escalation in transportation infrastructure projects. Based on a sample of 258 transportation infrastructure projects worth US$90 billion and representing different project types, geographical regions, and historical periods, it is found with overwhelming statistical significance that the cost estimates used to decide whether such projects should be built are highly and systematically misleading. Underestimation cannot be explained by error and is best explained by strategic misrepresentation, that is, lying. The policy implications are clear: legislators, administrators, investors, media representatives, and members of the public who value honest numbers should not trust cost estimates and cost-benefit analyses produced by project promoters and their analysts.