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In this paper, we demonstrate an automatic image analysis for Micro Total Analysis Systems (μTAS) or Lab-on-Paper (LoP). By placing fiducial markers on μTAS, application can crop image and remove bending distortions, also it can perform colorimetric analysis. With previously taken photo of μTAS device with applied reagents, user can determine ie. illness presence by uploading photo into the program. In the paper was prepared μTAS sheet, algorithm for finding fiducial points and software for colorimetric analysis written in Matlab.

The proliferation of digital information is leading to a wide range of applications which make it desirable to display data easily in many locations, all changeable and updateable. The difficulty in achieving such ubiquitous displays is the cost of signage, the cost of installation, and the software and systems to control the information being sent to each of these signs. In this paper we will talk about a networked system of such signs which are made from gyricon electronic paper. Gyricon electronic paper is a reflective, bistable display which can be made in large web sheets at a reasonable price. Since it does not require a backlight nor does it require power to refresh the display image, such technology is ideal for making signs which can be run on batteries with extremely long battery life, often not needing replacement for years. The display also has a very broad illumination scattering profile which makes it readily viewable from any angle. The basic operating mechanism of the display, its manufacturing technique, and achieved performance will be described, along with the description of a networked solution using many such signs controlled with system software to identify speakers and meetings in conference rooms, hospitality suites, or classrooms in universities. Systems will also be shown which are adapted to retail pricing signage and others which can be used for large format outdoor billboards.

Based on the unique characteristic, the paper currency numbers can be put into record and the automatic identification equipment for paper currency numbers is supplied to currency circulation market in order to provide convenience for financial sectors to trace the fiduciary circulation socially and provide effective supervision on paper currency. Simultaneously it is favorable for identifying forged notes, blacklisting the forged notes numbers and solving the major social problems, such as armor cash carrier robbery, money laundering. For the purpose of recognizing the paper currency numbers, a recognition algorithm based on neural network is presented in the paper. Number lines in original paper currency images can be draw out through image processing, such as image de-noising, skew correction, segmentation, and image normalization. According to the different characteristics between digits and letters in serial number, two kinds of classifiers are designed. With the characteristics of associative memory, optimization-compute and rapid convergence, the Discrete Hopfield Neural Network (DHNN) is utilized to recognize the letters; with the characteristics of simple structure, quick learning and global optimum, the Radial-Basis Function Neural Network (RBFNN) is adopted to identify the digits. Then the final recognition results are obtained by combining the two kinds of recognition results in regular sequence. Through the simulation tests, it is confirmed by simulation results that the recognition algorithm of combination of two kinds of recognition methods has such advantages as high recognition rate and faster recognition simultaneously, which is worthy of broad application prospect.

In this paper, we show that the communication channel known as writing in memory with defective cells is a relevant information-theoretical model for a specific case of passive warden steganography when the sender embeds a secret message into a subset C of the cover object X without sharing C with the recipient. The set C, which is also called the selection channel, could be arbitrary, determined by the sender from the cover object using a deterministic, pseudo-random, or a truly random process. We call this steganography "writing on wet paper" and realize it using a simple variable-rate random linear code that gives the sender a convenient flexibility and control over the embedding process and is thus suitable for practical implementation. The importance of the wet paper scenario for covert communication is discussed within the context of adaptive steganography and perturbed quantization steganography. Heuristic arguments supported by tests using blind steganalysis indicate that the wet paper steganography provides improved steganographic security and is less vulnerable to steganalytic attacks compared with existing methods with shared selection channels.

An automatic recognition system for Paper Currency Numbers was developed in this paper. The paper currency number can be recognized and recorded by this system at the same time of binding. At First, an image of 8 bits grey-scale was acquired by CCD camera, and then some output number clusters can be through process of segmentation by Grey Ridge-Valley algorithm, orientation by projection, and character recognition by structure-analyzing algorithm. Results of experiments demonstrated that the proposed algorithm of gray ridges and valleys can extract feature effectively, the algorithm of distance of traversing number body orientation acute, and this system achieves a high recognition rate and a fast recognition speed. It still reached the practical degree. The system has applied national patent.

Since the terrible events of 11 Sep 2001 the response to security vulnerabilities has been to throw “Guns, Gates and Guards” at the problem. Three years later and it is clear that, although this may have had a short-term effect, it is unsustainable and unaffordable in the long term. The war on terrorism is going to be fought for a very long time. Defending against terrorism and enhancing the resilience and robustness of society and its processes now requires constant vigilance. Only technology can provide that vigilance at an efficiency that can provide certainty of detection and fast response. A technology led approach, integrating with people and their processes calls for innovation and a new generation of technology that fuses the physical world with the logical world. This approach is measurable in terms of capability and investment, in the way that the previous Newtonian security approach of cause and effect is not. This paper will address this new security environment and the different approach that R&D has to take to ensure that life and Democracy thrive and terrorism is defeated.

This paper describes a passive millimeter-wave image scanner that leverages technologies previously developed for a video-rate passive millimeter-wave camera (PMC) [1, 2]. The imager has a prime focus elliptical frequency scanned antenna operating in the 75-93 GHz millimeter-wave band, a low noise receiver and a vertical beam former that allows the instantaneous capture of 128 pixel (vertical) column images in 1/30th of a second, with 2-3 K sensitivity. Two dimensional images are created by mechanically rotating the antenna, which produces a 128x60 raster image in 2 seconds. By integrating (averaging) images over a longer time period, we have demonstrated a sub-degree temperature resolution. This sensor has proven itself as a low cost tool for studying the potential of W-band passive imaging for various applications.

This paper first gives an overview of state-of-the-art simulation of semiconductor laser devices. The relevant physical models for multi dimensional, electro thermal, and optical simulation as well as an advanced active region model are reviewed. The second part of this work deals with the management of laser simulation projects and the extraction of the relevant data from simulation results. A new tool called PCM Explorer is presented that is suitable for the integration of numerical models in the design and manufacturing process of semiconductor lasers. Both the device performance as well as the process yield can be predicted with the combination of a comprehensive device simulator, some measurement data for calibration purposes, and the statistical process evaluation tool.

This review paper is based on the 2004 UCLA Seminar on Imaging and Informatics (http://www.radnet.ucla.edu/Arrowhead2004/) which is a joint endeavour between the UCLA and the CARS organization, focussing on workflow analysis tools and the digital operating room. Eleven specific presentations of the Arrowhead Seminar have been summarized in this review referring to redesigning perioperative care for a high velocity OR, intraoperative ultrasound process and model, surgical workflow and surgical PACS, an integrated view , interactions in the surgical OR, workflow automation strategies and target applications, visualisation solutions for the operating room, navigating the fifth dimension, and design of digital operating rooms and interventional suites

Hybrid soft computing models, based by neural, fuzzy and evolutionary computation technologies, have been applied to a large number of classification, prediction, and control problems. This paper focuses on one of such applications and presents a systematic process for building a predictive model to estimate time-to-breakage and provide a web break tendency indicator in the wet-end part of paper making machines. Through successive information refinement of information gleaned from sensor readings via data analysis, principal component analysis (PCA), adaptive neural fuzzy inference system (ANFIS), and trending analysis, a break tendency indicator was built. Output of this indicator is the break margin. The break margin is then interpreted using a stoplight metaphor. This interpretation provides a more gradual web break sensitivity indicator, since it uses more classes compared to a binary indicator. By generating an accurate web break tendency indicator with enough lead-time, we help in the overall control of the paper making cycle by minimizing down time and improving productivity.

The Humanitarian Demining Research and Development Program of Night Vision and Electronic Sensors Directorate (NVESD), under the direction of the Office of Assistant Secretary of Defense for Special Operations and Low-Intensity Conflict (OASD/SOLIC) and with participation from the International Test and Evaluation Project (ITEP) for Humanitarian Demining, conducted an in-country field evaluation of HSTAMIDS in the region of Humanitarian Demining Unit #1 (HMAU1) in Thailand. Participants included the US Humanitarian Demining Team of NVESD, ITEP personnel, Thailand Mine Action Center (TMAC), HALO Trust organization from Cambodia, and CyTerra Corporation. The primary objectives were to demonstrate the performance of the U.S. Army's latest handheld multisensor mine detector, the AN/PSS-14, in a demining environment in comparison to the performance of the metal detector being used by the local deminers and also to assess the performance of the trained deminers after limited experience and training with the HSTAMIDS.© (2005) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

Dynamic Networked Combat Capability is a transformational concept to enable network centric warfare at the tactical level - the immediate attack of targets of opportunity using any and all assets available: any sensor, any effect generator and any decider against any target. More specifically, the DARPA goal is to provide enabling technologies that will permit the Services to build such a capability.

Drinking water is one of the nation's key infrastructure assets that have been deemed vulnerable to deliberate terrorist attacks. While the threat to reservoir systems and water sources is deemed to be minimal, the vulnerability of the drinking water distribution systems to accidental or deliberate contamination due to a backflow event is becoming a well-recognized possibility. The myriad possible points of incursion into a distribution system and the ease of mounting a backflow event, combined with the fact that little or no quality monitoring occurs after the water has left the treatment plant, makes the danger of such an attack acute. This was clearly stated in a General Accounting Office (GAO) report to Congress that listed the vulnerability of the distribution system to attack as the largest security risk to water supplies. Prior to this there has not been a system capable of detecting such an event and alerting the system's managers so that effects of an attack or accident can be contained. The general scientific consensus is that no practical, available, or cost-effective real-time technology exists to detect and mitigate intentional attacks or accidental incursions in drinking water distribution systems. The rapid detection and identification of breaches of security in the water distribution system is crucial in initiating appropriate corrective action. The ability of a technology system to detect incursion on a real time basis and give indications as to the cause could dramatically reduce the impact of any such scenario. As the vulnerability of the distribution system becomes more widely recognized, the development of a system such as the one described will be an invaluable tool in maintaining the integrity of the nations drinking water supply.© (2005) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

Using Synopsys TCAD tools, several examples of advanced process and device modeling are presented for full-frame CCD image sensors. The topics covered in these examples include channel potential, charge capacity, charge transport, and charge blooming. The simulations provide in depth analysis of the basic principles of operation of CCDs and cover some aspects of antiblooming protection.

An IETM is intended to be the functional equivalent of a paper-based Technical Manual (TM), and in most cases a total replacement for paper manual. In this paper, we will describe some of document image understanding technologies applied to the conversion of paper-based TMs to IETMs. Using these advanced technologies allow us to convert paper-based TMs to class 1/2 IETMs. However, these were not sufficient for an automated integrated logistics support system in the ROC Department of Defense. An advanced IETM system is therefore required. Such class 4/5 like IETM system could provide intelligent display of information and other user applications such as diagnostics, intelligent design and manufacturing, or computer-managed training. The author has developed some of the advanced functions, and examples will be shown to demonstrate the new aspect of IETMs.

Bioterrorism is no longer a hypothetical construct but a reality. Nevertheless, disease detection and intervention currently remain largely reliant on clinical assessment. Technology providing early detection of disease could impact the care of individual patients and the evolution of epidemic spread. Hyperspectral Imaging (HSI) is a remote sensing technology developed originally by the Department of Defense that combines high-resolution imaging with chemical spectroscopy. In other medical applications HSI is emerging as a new means of early or more sensitive detection of changes in tissue that can be used to define pathology, predict clinical outcomes and adapt therapy. As a small, robust, camera based, non-invasive device, HSI may be well suited to aid in defense against biological warfare or epidemic disease by providing early detection or confirmation of disease and by monitoring the efficacy of vaccination or therapy. Crossover applications exist in the evaluation and treatment of emerging diseases. HSI is well suited to be a screening tool to provide earlier or more accurate detection of disease in an at risk population to better treat and contain disease.

The threat of counterfeiting in Bank Notes and other Security Documents is steadily increasing with the continuous improvement of printing and copying technologies. The perfect reproduction of a document is indeed reachable with the right combination of technique and economics. Our only protection is to make it difficult by introducing artefacts which appear only through the counterfeiting process or reduce significantly the efficiency of that process. Today more than 150 million of banknotes are counterfeited each year and that amount is on the rise. This quantity is small compared to the total amount of currency available in the world which is estimated at 380 billion dollars [1] but it is nevertheless a problem that have to be faced not only for the loss of money but, more importantly for the kind of use made of the counterfeited bills in the troubled world in which we are living today. A number of methods are available to defeat counterfeiting none of which are conpletely satisfactory. The difficulty is not as much the prevention of the duplication than doing it while safegarding the intinsic properties (durability) of the documents as far as permanent readability, resistance to wear etc. satisfactory. The difficulty is not as much the prevention of the duplication than doing it while safegarding the intinsic properties (durability) of the documents as far as permanent readability, resistance to wear etc. Basic approaches are: 1. The light switch: a transparent coating which becomes opaque during any attempt of duplication. 2. An alternative to this first approach is an ink which becomes transparent at the time of duplication. 3. The use of a substrate (Paper stock) whose optical density will rise to that of the printed graphic on the bill at the time of copying. This would be a true interactive paper. 4. Luminescent materials that would blind the photoreceptor during exposure. Such material could be in the substrate or in the printing ink. 5. Introduction of an artefact in the printed copy through a hologram hidden in a transparent coating or embossed in the substrate. All approaches have been investigated to a certain extent with variable success. We will report hereafter the results of investigations made by the author on alternatives (1) and (2) in this Laboratory and at the University of Texas at El Paso under contract from the National Bank of Belgium and with the collaboration of the CNRS in Paris and the University of Marseille France.

How should hospital administrators compare the security risks of paper-based and computerized patient record systems. There is a general tendency to assume that because computer networks potentially provide broad access to hospital archives, computerized patient records are less secure than paper records and increase the risk of breaches of patient confidentiality. This assumption is ill-founded on two grounds. Reasons exist to say that the computerized patient record provides better access to patient information while enhancing overall information system security. A range of options with different trade-offs between access and security exist in both paper-based and computerized records management systems. The relative accessibility and security of any particular patient record management system depends, therefore, on administrative choice, not simply on the intrinsic features of paper or computerized information management systems.

The challenge in providing picture archiving and communication systems (PACS) in the modern managed care environment is to justify its cost, while still providing the required services. The only solution which achieves the economic goal is the elimination of film and its associated costs in favor of PACS. Recognizing that some hardcopy will always be desired, an acceptable inexpensive paper print alternative is required. Our initial networked paper printed solution has replaced all film use in nuclear medicine while still providing economical color and monochrome paper output when required. Extensions of this print architecture for ultrasound, CT and MR are planned for the near future.

A system has been built that embeds arbitrary digital data in an iconic representation of a text image. For encoding, a page image containing text is analyzed for the text regions. A highly reduced image of the page is generated, with an iconic version of the text that encodes an input data stream substituting for the text regions. The data is encoded into modulations of rectangular iconic representations of text words, where the length, height and vertical positioning of rectangles, as well as the spacing between rectangles, can all be independently varied. No correspondence need be maintained between the words in the document and the word icons. Word icons or other marks on each line can be used for identifying, calibrating and justifying iconic text. Decoding proceeds by finding iconic lines and determining the iconic word sizes and locations. Word icons printed with 8x reduction are reliably decoded from 300 ppi binary scans. One application is to present iconified first pages of many documents on a sheet of paper, where the URL of each document is encoded in its icon. Icon scanning and selection then allows retrieval of the full document. Another use is to print an icon on every page of a document, containing meta-information about the document or the specific page, such as the version, revision history, keywords, authorization, or a signed hashing of the full image for authentication.

A software application for correlating and fusing information products from multiple dissimilar sensors is presented. The Tactical Multi Sensor Fusion (TMSF) system is a C ++ object oriented application implementing data correlation and fusion algorithms which provide decision aids for identifying, locating, and determining the status of processing equipment within suspected weapons of mass destruction (WMD) sites. The TMSF system also provides valuable information for assessing weapon delivery accuracy and effectiveness. The TMSF architecture is designed to handle an arbitrary number of sensor and information types, by creating new C ++ class objects. Three specific sensor data types are currently used in the correlation and fusion process. When deployed against suspected WMD sites in a real world scenario, the selected sensor suite provides site characterization information during preattack covert surveillance through post-attack battle damage assessment (BDA). The three sensors are: 1) Tactical Unattended Ground Sensor (TUGS): Seismic/Acoustic in-ground sensors which, when used in sufficient numbers, provides equipment identification, location, and activity with the appropriate error estimates. 2) Forward Looking Infra Red (FLIR): The recorded images from an attack aircraft FLIR pod are used to determine weapon location, time, criticality of detonation, and post detonation venting. 3) Weapon Borne Sensors (WBS): A weapon borne sensor is used to relay information with respect to the construction of the WMD site under attack. This primarily consists of the number and types of layers of resistance met by the weapon as it penetrates the buried facility prior to detonation. All sensor data are interpreted from flat ASCII files as a list of individual event reports, and are correlated with respect to location, ID, and time. The correlation process groups event reports for like-events as reported by different sensors. The correlated groups are then fused into composite site characterization objects (SCO) using Bayes maximum likelihood based algorithms to obtain a fused location, ID, and time estimate. An image overlay is used to locate each identified processing equipment on an overhead site image. This composite view of the fusion results gives the Measurement and Signals Intelligence (MASINT) specialist, intelligence analyst, or military targeteer the capability to interpret the fusion results without the need for tedious, accident prone, numerical data analysis. TMSF reads and displays the National Imagery Transmission Format (NITF 2.0) image files as well as other commercially available formats.

Distributing a radiographic image with the verbal report would help to avoid misunderstanding and would aid the referring physician in understanding better the severity of the disease described. With magnetic resonance imaging it is customary in our practice to distribute a copy of the examination to the referring physician. Distributing a film copy of the image is expensive. Based on our initial experience with the Scitex paper printer, we believe that this system provides a paper image of sufficient quality that it would be acceptable as a referrer's copy. Paper copies are cheaper to produce and can be more easily filed with the remainder of the patient's paper based medical record. This presentation discusses the printing method employed by the Scitex printer, demonstrates comparisons between Scitex and laser print images, and discusses the current problems of interfacing the printer to image acquisition devices. As we develop our image management and communication system (IMAC), we anticipate that a need for hard copy images will remain. We discuss the role that we believe this paper printer serves in an IMAC film independent system.© (1994) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

Integer versions of subdivision and corner cutting algorithms of NURBS curves are presented. The algorithms are used to render NURBS curves of any degree on a raster device by either computing a polygonal approximation or by turning on pixels that are closest to the curve. Because of the integer arithmetic used, the algorithms are easily cast in hardware.

The goal of the research described in this paper is the design of an intelligent computer vision system to automatically extract information from paper-based maps and answer queries related to spatial features and structure a geographical data. The foundation to such a system is a set. of powerful image analysis algorithms to operate on digitized images of paper-based maps. Efficient algorithms to orient map images, detect symbols, identify and track various types of lines, follow closed contours, compute distances, find shortest paths, etc. have been developed. An intelligent query processor analyzes the queries presented by the user in a predefined syntax, controls the operation of the image processing algorithms, and interacts with the user. The query processor is written in LISP and calls image analysis routines written in FORTRAN. In this paper we describe the image analysis algorithms and present their effectiveness in extracting information from a simplified map image of 2,048 x 2,048 pixels.© (1988) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

In this paper we discuss the electrical and physical properties of interconnection structures that impact the per-formance of computer systems. These considerations are illustrated with three examples of such devices found in atypical main -frame. The requirements for the future are then presented. The ability of new technologies, electrical andoptical for satisfying these requirements are discussed. 1. INTRODUCTION The performance of a modern main -frame computer system depends on the speed of the integrated circuits used tocarry out the logic operations and the electrical characteristics of the interconnection structures used to transport signalsbetween these circuits. A basic measure of system performance is cycle time, the time necessary to perform a funda-mental operation. A computer instruction can involve one or more fundamental operations and may take one or morecycles to complete. Interconnection structures can be roughly divided into those that have a large effect on cycle timeand those that do not. For example, multichip modules, onto which logic chips are directly attached, fall into the formercategory since electrical pulses often travel between different chips to complete a logic operation [1]. Depending on theway the logic is partitioned, critical paths might also exist between circuits on different modules. Then the propertiesof the boards to which the modules are connected will also play a significant role in the cycle time. This type of com-puter interconnection scheme is illustrated in figure 1 where it can be observed that one level of commonly used elec-tronic packaging, the single chip module, has been eliminated.

Traditionally, multiple format recording emulsions for medical video imaging have utilized a film (transparent) base. The major reason for this is probably because the film and camera manufacturers felt the diagnostician is accustomed to viewing x-ray images on a film base and would prefer to view video images that way also. Because of the need to keep radiation exposure to patients at a minimum and the fact that photographic emulsions are generally very inefficient in utilizing x-ray radiation, a film base was the logical requirement for direct x-ray imaging as it enabled the image to be recorded by two emulsions rather than one. The transparent base thus allows viewing a photograph which is the result of the additive effect of the two emulsions. The use of transparent base imposed specific requirements that necessitated the development of a whole complex of equipment designed for the particular use of film such as the processing machines, their chemical solutions, and the famous viewbox and alternators that characterize the radiology departments of today.

E-learning device is widely used in our daily life. However mobile e-learning machine is not satisfied as expected. Most mobile e-learning device is a static learning device, unable to fulfill the requirement of collaboration, long standby time, usage under strong sunlight. To meet these requirements, we developed a learning machine based on electronic paper. This paper will discuss the software consideration of the device. The software is a knowledge navigation system, the navigation system is based on Ontology. Research shows that combine frame Ontology and description logic together can afford a uniform interface to user application.

An experimental high resolution cathode ray tube (CRT) printer was developed to produce high quality 3. 5in. x 5 in. and 4 in. x 6 in. photographic prints. A monochrome CRT utilizing red green and blue filtration was used to sequenlially expose continuous-tone color images directly onto conventional photographic paper. A summary of the design and implementation of the printer at the systems level will be presented. The design approach taken to meet the system quality requirements is described from the electrical mechanical and optical points of view. In addition the presentation will emphasize the design challenges of implementing a CRT imager and the solutions to the unique problems it presents. Other concerns discussed in detail include spatial resolution and bit resolution image size and magnification colorimetry and paper response matching. Sample prints of test patterns and scanned images will be shown. 1.

The paper presents approaches for functional integration of automated system databases by means of artificial intelligence. The peculiarities of turning to account the database in the systems with the usage of a fuzzy implementation of functions were analyzed. Requirements for the normalization of such databases were defined. The question of data equivalence in conditions of uncertainty and collisions in the presence of the databases functional integration is considered and the model to reveal their possible occurrence is devised. The paper also presents evaluation method of standardization of integrated database normalization.

Modern physics experiments requires construction of advanced, modular measurement systems for data processing and registration purposes. Components are often designed in one of the common mechanical and electrical standards, e.g. VME or uTCA. The paper is focused on measurement systems using FPGAs as data processing blocks, especially for plasma diagnostics using GEM detectors with data quality monitoring aspects. In the article is proposed standardized model of HDL FPGA firmware implementation, for use in a wide range of different measurement system. The effort was made in term of flexible implementation of data quality monitoring along with source data dynamic selection. In the paper is discussed standard measurement system model followed by detailed model of FPGA firmware for modular measurement systems. Considered are both: functional blocks and data buses. In the summary, necessary blocks and signal lines are described. Implementation of firmware following the presented rules should provide modular design, with ease of change different parts of it. The key benefit is construction of universal, modular HDL design, that can be applied in different measurement system with simple adjustments.

Due to its capability of capturing the kinematic properties of a target object, radar micro-Doppler signatures (m-DS) play an important role in radar target classification. This is particularly evident from the remarkable number of research papers published every year on m-DS for various applications. However, most of these works rely on the support vector machine (SVM) for target classification. It is well known that training an SVM is computationally expensive due to its nature of search to locate the supporting vectors. In this paper, the classifier learning problem is addressed by a total error rate (TER) minimization where an analytic solution is available. This largely reduces the search time in the learning phase. The analytically obtained TER solution is globally optimal with respect to the classification total error count rate. Moreover, our empirical results show that TER outperforms SVM in terms of classification accuracy and computational efficiency on a five-category radar classification problem.

The main problem associated with using symmetric/ asymmetric keys is how to securely store and exchange the keys between the parties over open networks particularly in the open environment such as cloud computing. Public Key Infrastructure (PKI) have been providing a practical solution for session key exchange for loads of web services. The key limitation of PKI solution is not only the need for a trusted third partly (e.g. certificate authority) but also the absent link between data owner and the encryption keys. The latter is arguably more important where accessing data needs to be linked with identify of the owner. Currently available key exchange protocols depend on using trusted couriers or secure channels, which can be subject to man-in-the-middle attack and various other attacks. This paper proposes a new protocol for Key Exchange using Biometric Identity Based Encryption (KE-BIBE) that enables parties to securely exchange cryptographic keys even an adversary is monitoring the communication channel between the parties. The proposed protocol combines biometrics with IBE in order to provide a secure way to access symmetric keys based on the identity of the users in unsecure environment. In the KE-BIOBE protocol, the message is first encrypted by the data owner using a traditional symmetric key before migrating it to a cloud storage. The symmetric key is then encrypted using public biometrics of the users selected by data owner to decrypt the message based on Fuzzy Identity-Based Encryption. Only the selected users will be able to decrypt the message by providing a fresh sample of their biometric data. The paper argues that the proposed solution eliminates the needs for a key distribution centre in traditional cryptography. It will also give data owner the power of fine-grained sharing of encrypted data by control who can access their data.

The OpenOrbiter I spacecraft is the culmination of significant work on reducing the cost levels of a CubeSat-class spacecraft. By redesigning the spacecraft from the ground up, down to the component level, to use readily available electronic and physical components, the cost of CubeSat construction has been significantly reduced. This paper provides an overview of the OpenOrbiter I mission, to date. It then focuses on the benefits that can be provided by the lower-cost, low-risk spacecraft. The paper discusses the prospective utility of this mission paradigm for the defense, homeland security and intelligence communities.

The paper describes the MATLAB (MathWorks) programs that were developed during the REU workshop 1 to implement The Aerospace Corporation developed Unified Game-based Acquisition Framework and Advanced Game - based Mathematical Framework (UGAF-AGMF) and its associated War-Gaming Engine (WGE) models. Each game can be played from the perspectives of the Department of Defense Acquisition Authority (DAA) or of an individual contractor (KTR). The programs also implement Aerospace’s optimum “Program and Technical Baseline (PTB) and associated acquisition” strategy that combines low Total Ownership Cost (TOC) with innovative designs while still meeting warfighter needs. The paper also describes the Bayesian Acquisition War-Gaming approach using Monte Carlo simulations, a numerical analysis technique to account for uncertainty in decision making, which simulate the PTB development and acquisition processes and will detail the procedure of the implementation and the interactions between the games.

The paper discusses recent results of flight tests performed with the Hensoldt (former Airbus DS Electronics and Border Security) LiDAR system in brownout. The SferiSense® LiDAR system was mounted on a Mi-2 test platform as part of the complete DVE system SFERION® to undergo the tests. To optimize brownout capabilities minor modifications were performed on the sensor firmware over the SferiSense® serial LiDAR system which is in operational use on the NH90 transport helicopter. Also dust echoes were filtered out by a real-time filtering algorithm. Numerous approaches into own ship generated dust (light to heavy) as well as fan generated dust clouds (chalk 2 scenarios) were performed. The paper discusses the results and shows under which conditions the LiDAR can still look through the dust cloud. Also the contribution of high resolution real-time 3D LiDAR data to the DVE system usage is discussed.

Behavioral Analytics (BA) relies on digital breadcrumbs to build user profiles and create clusters of entities that exhibit a large degree of similarity. The prevailing assumption is that an entity will assimilate the group behavior of the cluster it belongs to. Our understanding of BA and its application in different domains continues to evolve and is a direct result of the growing interest in Machine Learning research. When trying to detect security threats, we use BA techniques to identify anomalies, defined in this paper as deviation from the group behavior. Early research papers in this field reveal a high number of false positives where a security alert is triggered based on deviation from the cluster learned behavior but still within the norm of what the system defines as an acceptable behavior. Further, domain specific security policies tend to be narrow and inadequately represent what an entity can do. Hence, they: a) limit the amount of useful data during the learning phase; and, b) lead to violation of policy during the execution phase. In this paper, we propose a framework for future research on the role of policies and behavior security in a coalition setting with emphasis on anomaly detection and individual's deviation from group activities.

Partially observable group activities (POGA) occurring in confined spaces are epitomized by their limited observability of the objects and actions involved. In many POGA scenarios, different objects are being used by human operators for the conduct of various operations. In this paper, we describe the ontology of such as POGA in the context of In-Vehicle Group Activity (IVGA) recognition. Initially, we describe the virtue of ontology modeling in the context of IVGA and show how such an ontology and a priori knowledge about the classes of in-vehicle activities can be fused for inference of human actions that consequentially leads to understanding of human activity inside the confined space of a vehicle. In this paper, we treat the problem of “action-object” as a duality problem. We postulate a correlation between observed human actions and the object that is being utilized within those actions, and conversely, if an object being handled is recognized, we may be able to expect a number of actions that are likely to be performed on that object. In this study, we use partially observable human postural sequences to recognition actions. Inspired by convolutional neural networks (CNNs) learning capability, we present an architecture design using a new CNN model to learn “action-object” perception from surveillance videos. In this study, we apply a sequential Deep Hidden Markov Model (DHMM) as a post-processor to CNN to decode realized observations into recognized actions and activities. To generate the needed imagery data set for the training and testing of these new methods, we use the IRIS virtual simulation software to generate high-fidelity and dynamic animated scenarios that depict in-vehicle group activities under different operational contexts. The results of our comparative investigation are discussed and presented in detail.

In this paper a solution is presented aiming to assist the early detection and localization of a fire incident by exploiting crowdsourcing and unofficial civilian online reports. It consists of two components: (a) the potential fire incident detection and (b) the visualization component. The first component comprises two modules that run in parallel and aim to collect reports posted on public platforms and conclude to potential fire incident locations. It collects the public reports, distinguishes reports that refer to a potential fire incident and store the corresponding information in a structured way. The second module aggregates all these stored reports and conclude to a probable fire location, based on the amount of reports per area, the time and location of these reports. In further the result is entered to a fusion module which combines it with information collected by sensors if available in order to provide a more accurate fire event detection capability. The visualization component is a fully – operational public information channel which provides accurate and up-to-date information about active and past fires, raises awareness about forest fires and the relevant hazards among citizens. The channel has visualization capabilities for presenting in an efficient way information regarding detected fire incidents fire expansion areas, and relevant information such as detecting sensors and reporting origin. The paper concludes with insight to current CONOPS end user with regards to the inclusion of the proposed solution to the current CONOPS of fire detection.

Open architecture in the context of defense applications encourages collaboration across government agencies and academia. This paper describes a success story in the implementation of an open architecture framework that fosters transparency and modularity in the context of Environmental Awareness for Sensor and Emitter Employment (EASEE), a complex physics-based software package for modeling the effects of terrain and atmospheric conditions on signal propagation and sensor performance. Among the highlighted features in this paper are: (1) a code refactorization to separate sensitive parts of EASEE, thus allowing collaborators the opportunity to view and interact with non-sensitive parts of the EASEE framework with the end goal of supporting collaborative innovation, (2) a data exchange and validation effort to enable the dynamic addition of signatures within EASEE thus supporting a modular notion that components can be easily added or removed to the software without requiring recompilation by developers, and (3) a flexible and extensible XML interface, which aids in decoupling graphical user interfaces from EASEE’s calculation engine, and thus encourages adaptability to many different defense applications. In addition to the outlined points above, this paper also addresses EASEE’s ability to interface with both proprietary systems such as ArcGIS. A specific use case regarding the implementation of an ArcGIS toolbar that leverages EASEE’s XML interface and enables users to set up an EASEE-compliant configuration for probability of detection or optimal sensor placement calculations in various modalities is discussed as well.

Copyright 2017 Society of Photo-Optical Instrumentation Engineers. One print or electronic copy may be made for personal use only. Systematic reproduction and distribution, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper are prohibited. In terms of contemporary art, time-based media generally refers to artworks that have duration as a dimension and unfold to the viewer over time, that could be a video, slide, film, computer-based technologies or audio. As part of this category, holography pushes this visual-oriented narrative a step further, which brings a real 3D image to invite and allow audiences revisiting the scene of the past, at the moment of recording in space and time. Audiences could also experience the kinetic holographic aesthetics through constantly moving the viewing point or illumination source, which creates dynamic visual effects. In other words, when the audience and hologram remain still, the holographic image can only be perceived statically. This unique form of expression is not created by virtual simulation; the principal of wavefront reconstruction process made holographic art exceptional from other time-based media. This project integrates 3D printing technology to explore the nature of material aesthetics, transiting between material world and holographic space. In addition, this series of creation also reveals the unique temporal quality of a hologram’s presence and absence, an ambiguous relationship existing in this media. © (2017) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.

In this paper, we propose a kernel version of the credal classification rule (CCR) to perform the classification in a feature space of high dimension. Kernels based approaches have become popular for several years to solve supervised or unsupervised learning problems. In this paper, our method is extended to the CCR. It is realized by replacing the inner product with an appropriate positive definite function, and the corresponding algorithms are called kernel Credal Classification Rule (KCCR). The approach is applied to the classification of the generated and real data to evaluate and compare the performance of the KCCR method with other classification methods.

The paper considers the problem of fast nonlinear mapping of hyperspectral data. The analysis of various ways to speed-up the nonlinear mapping algorithm is performed, including stochastic algorithms, methods based on space partitioning, interpolation techniques, and parallel implementations using modern parallel architecture. The general scheme for hyperspectral data processing that summarizes the analyzed methods and algorithms is given with recommendations. Experimental results for the proposed technique are presented for well-known hyperspectral images. Possible applications of the technique for hyperspectral image analysis are discussed in the paper.

In the conventional face recognition, most researchers focused on enhancing the precision which input data was already the member of database. However, they paid less necessary attention to confirm whether the input data belonged to database. This paper proposed an approach of face recognition using two-dimensional principal component analysis (2DPCA). It designed a novel composite classifier founded by statistical technique. Moreover, this paper utilized the advantages of SVM and Logic Regression in field of classification and therefore made its accuracy improved a lot. To test the performance of the composite classifier, the experiments were implemented on the ORL and the FERET database and the result was shown and evaluated.

According to the complexity and the lack of intelligent analysis method of combine harvester blockage fault , this paper puts forward a method , based on the combination of BP neural network (BPNN)and DS evidence theory , for combine harvester blockage fault diagnosis. Choosing cutting table auger, conveyer trough, threshing cylinder and grain conveying auger as the study, this paper divides the condition of combine harvester into four categories, namely, normal, slightly blocking, blockage, severe blockage, which being as an identification framework for DS evidence theory. BP neural network is used for analysing speed information of monitoring points and distributing basic probability for each proposition in the identification framework. Dempster combination rule converged information at different time to obtain diagnostic results.Test results show that this method can timely and accurately judge the work state of combine harvester, the blocking fault warning time will be increased to 2 seconds and the success probability of blocking fault warning reach more than 90%.

Due to harsh working conditions, the components of hydraulic excavator are subject to large amount of alternating load and random load during the operation and they are seriously damaged. The test of load signal and preparation of load spectrum for the hydraulic excavator are studied in this paper. In the first place, pretreatment of filtering and noise reduction for load signal is conducted based on experimental test on site and experimental working condition analysis. After the load signal is processed in sections, distribution fitting is performed for information like mean amplitude after rain flow counting with the approach of probability statistics to get the probability distribution function for mean value and amplitude value. Finally the two dimensional load spectrum for mean amplitude is obtained and program spectrum loading solution of fatigue experiment is given. The study of load signal test and load spectrum preparation method for hydraulic excavator conducted in this paper is of great significance for clarification of load distribution of excavator and further reliability test of excavator.

Facing the increasing environment crisis, how to improve energy efficiency is the important problem. Power big data is main support tool to realize demand side management and response. With the promotion of smart power consumption, distributed clean energy and electric vehicles etc get wide application; meanwhile, the continuous development of the Internet of things technology, more applications access the endings in the grid power link, which leads to that a large number of electric terminal equipment, new energy access smart grid, and it will produce massive heterogeneous and multi-state electricity data. These data produce the power grid enterprise's precious wealth, as the power big data. How to transform it into valuable knowledge and effective operation becomes an important problem, it needs to interoperate in the smart grid. In this paper, we had researched the various applications of power big data and integrate the cloud computing and big data technology, which include electricity consumption online monitoring, the short-term power load forecasting and the analysis of the energy efficiency. Based on Hadoop, HBase and Hive etc., we realize the ETL and OLAP functions; and we also adopt the parallel computing framework to achieve the power load forecasting algorithms and propose a parallel locally weighted linear regression model; we study on energy efficiency rating model to comprehensive evaluate the level of energy consumption of electricity users, which allows users to understand their real-time energy consumption situation, adjust their electricity behavior to reduce energy consumption, it provides decision-making basis for the user. With an intelligent industrial park as example, this paper complete electricity management. Therefore, in the future, power big data will provide decision-making support tools for energy conservation and emissions reduction.

The last few years showed that a high risk of asynchronous threats is given in every day life. Especially in large crowds a high probability of asynchronous attacks is evident. High observational abilities to detect threats are desirable. Consequently highly trained security and observation personal is needed. This paper evaluates the effectiveness of a training methodology to enhance performance of observation personnel engaging in a specific target identification task. For this purpose a crowd simulation video is utilized. The study first provides a measurement of the base performance before the training sessions. Furthermore a training procedure will be performed. Base performance will then be compared to the after training performance in order to look for a training effect. A thorough evaluation of both the training sessions as well as the overall performance will be done in this paper. A specific hypotheses based metric is used. Results will be discussed in order to provide guidelines for the design of training for observational tasks.

In this paper, we analyze the characteristics of pseudo-random code, by the case of m sequence. Depending on the description of coding theory, we introduce the jamming methods. We simulate the interference effect or probability model by the means of MATLAB to consolidate. In accordance with the length of decoding time the adversary spends, we find out the optimal formula and optimal coefficients based on machine learning, then we get the new optimal interference code. First, when it comes to the phase of recognition, this study judges the effect of interference by the way of simulating the length of time over the decoding period of laser seeker. Then, we use laser active deception jamming simulate interference process in the tracking phase in the next block. In this study we choose the method of laser active deception jamming. In order to improve the performance of the interference, this paper simulates the model by MATLAB software. We find out the least number of pulse intervals which must be received, then we can make the conclusion that the precise interval number of the laser pointer for m sequence encoding. In order to find the shortest space, we make the choice of the greatest common divisor method. Then, combining with the coding regularity that has been found before, we restore pulse interval of pseudo-random code, which has been already received. Finally, we can control the time period of laser interference, get the optimal interference code, and also increase the probability of interference as well.

Design and analysis of an optical system is often a multidisciplinary task, and can involve the use of specialized software packages for imaging, mechanics, and illumination. This paper will present a case study on the design and analysis of a basic heads-up display (HUD) for automotive use. The emphasis will be on the special requirements of a HUD visual system and on the tools and techniques needed to accomplish the design. The first section of this paper will present an overview of the imaging design using commercially available imaging design software. Topics addressed in this section include modeling the windshield, visualizing the imaging performance, using constraints and freeform surfaces to improve the system, and meeting specific visual performance specifications with design/analysis methods. The second section will address the use of a CAD program to design a basic mechanical structure to support and protect the optics. This section will also discuss some of the issues and limitations involved in translating data between a CAD program and a lens design or illumination program. Typical issues that arise include the precision of optical surface prescriptions, surface and material properties, and the management of large data files. In the final section, the combined optical and mechanical package will be considered, using an illumination design program for stray light analysis. The stray light analysis will be directed primarily toward finding, visualizing, and quantifying unexpected ray paths. Techniques for sorting optical ray paths by path length, power, and elements or materials encountered will be discussed, along with methods for estimating the impact of stray light on the optical system performance.

While hyperspectral data shares rich spectrum information, it has numbers of bands with high correlation coefficients, causing great data redundancy. A reasonable band selection is important for subsequent processing. Bands with large amount of information and low correlation should be selected. On this basis, according to the needs of target detection applications, the spectral characteristics of the objects of interest are taken into consideration in this paper, and a new method based on spectrum difference is proposed. Firstly, according to the spectrum differences of targets of interest, a difference matrix which represents the different spectral reflectance of different targets in different bands is structured. By setting a threshold, the bands satisfying the conditions would be left, constituting a subset of bands. Then, the correlation coefficients between bands are calculated and correlation matrix is given. According to the size of the correlation coefficient, the bands can be set into several groups. At last, the conception of normalized variance is used on behalf of the information content of each band. The bands are sorted by the value of its normalized variance. Set needing number of bands, and the optimum band combination solution can be get by these three steps. This method retains the greatest degree of difference between the target of interest and is easy to achieve by computer automatically. Besides, false color image synthesis experiment is carried out using the bands selected by this method as well as other 3 methods to show the performance of method in this paper.