Query: Verification based ECG biometrics with cardiac irregular conditions using heartbeat level and segment level information fusion

Relevant passages:
Analysis of Human Electrocardiogram for Biometric Recognition <=SEP=> Security concerns increase as the technology for falsification advances. There are strong evidences that a difficult to falsify biometric trait, the human heartbeat, can be used for identity recognition. Existing solutions for biometric recognition from electrocardiogram (ECG) signals are based on temporal and amplitude distances between detected fiducial points. Such methods rely heavily on the accuracy of fiducial detection, which is still an open problem due to the difficulty in exact localization of wave boundaries. This paper presents a systematic analysis for human identification from ECG data. A fiducial-detection-based framework that incorporates analytic and appearance attributes is first introduced. The appearance-based approach needs detection of one fiducial point only. Further, to completely relax the detection of fiducial points, a new approach based on autocorrelation (AC) in conjunction with discrete cosine transform (DCT) is proposed. Experimentation demonstrates that the AC/DCT method produces comparable recognition accuracy with the fiducial-detection-based approach.

Within-class covariance normalization for SVM-based speaker recognition <=SEP=> This paper extends the within-class covariance normalizat ion (WCCN) technique described in [1, 2] for training generaliz ed linear kernels. We describe a practical procedure for apply ing WCCN to an SVM-based speaker recognition system where the input feature vectors reside in a high-dimensional space. O ur approach involves using principal component analysis (PCA) t o split the original feature space into two subspaces: a low-dimens ional “PCA space” and a high-dimensional “PCA-complement space. ” After performing WCCN in the PCA space, we concatenate the resulting feature vectors with a weighted version of their P CAcomplements. When applied to a state-of-the-art MLLR-SVM speaker recognition system, this approach achieves improv ements of up to 22% in EER and 28% in minimum decision cost function (DCF) over our previous baseline. We also achieve substanti al improvements over an MLLR-SVM system that performs WCCN in the PCA space but discards the PCA-complement.

ECG Biometric Recognition: A Comparative Analysis <=SEP=> The electrocardiogram (ECG) is an emerging biometric modality that has seen about 13 years of development in peer-reviewed literature, and as such deserves a systematic review and discussion of the associated methods and findings. In this paper, we review most of the techniques that have been applied to the use of the electrocardiogram for biometric recognition. In particular, we categorize the methodologies based on the features and the classification schemes. Finally, a comparative analysis of the authentication performance of a few of the ECG biometric systems is presented, using our inhouse database. The comparative study includes the cases where training and testing data come from the same and different sessions (days). The authentication results show that most of the algorithms that have been proposed for ECG-based biometrics perform well when the training and testing data come from the same session. However, when training and testing data come from different sessions, a performance degradation occurs. Multiple training sessions were incorporated to diminish the loss in performance. That notwithstanding, only a few of the proposed ECG recognition algorithms appear to be able to support performance improvement due to multiple training sessions. Only three of these algorithms produced equal error rates (EERs) in the single digits, including an EER of 5.5% using a method proposed by us.

ECG to identify individuals <=SEP=> The electrocardiogram (ECG also called EKG) trace expresses cardiac features that are unique to an individual. The ECG processing followed a logical series of experiments with quantifiable metrics. Data filters were designed based upon the observed noise sources. Fiducial points were identified on the filtered data and extracted digitally for each heartbeat. From the fiducial points, stable features were computed that characterize the uniqueness of an individual. The tests show that the extracted features are independent of sensor location, invariant to the individual’s state of anxiety, and unique to an individual. 2004 Pattern Recognition Society. Published by Elsevier Ltd. All rights reserved.

ECG analysis: a new approach in human identification <=SEP=> In this paper, a new approach in human identification is investigated. For this purpose, a standard 12-lead electrocardiogram (ECG) recorded during rest is used. Selected features extracted from the ECG are used to identify a person in a predetermined group. Multivariate analysis is used for the identification task. Experiments show that it is possible to identify a person by features extracted from one lead only. Hence, only three electrodes have to be attached on the person to be identified. This makes the method applicable without too much effort.

Development of an Airborne Ground Penetrating Radar System: Antenna Design, Laboratory Experiment, and Numerical Simulation <=SEP=> A stepped-frequency continuous wave (SFCW) airborne ground penetrating radar (GPR) system was built using a vector network analyzer (VNA), an optical-to-electric ( \mmb O/\mmb E) converter, an electric-to-optical ( \mmb E/\mmb O) converter, and the resistively loaded planer dipole antennas. The resistively loaded antennas are based on the Altshuler discrete resistive loading approach. The distance from the loading point to the feeding point and the resistance has been optimized; in addition, a balun at the feeding point was introduced to convert the unbalanced signal from the coax to balanced signal. Test results show that the manufactured antennas have a wide bandwidth frequency range from 55 to 275 MHz. A laboratory experiment using the developed system was conducted in a building with high ceilings. The results registered all basic features including the ground, sub-ground surface, and the lamp hanging from the ceiling. Numerical modeling by finite-difference time-domain (FDTD) method using two-dimensional (2-D) transverse electric (TE) verifies the presence of these registered features in the measured airborne data. A bedrock outcrop in ice sheet model is reconstructed based on a piece of real airborne GPR data, the modeling profile results show excellent consistent with the observed data. The capability of airborne GPR detection of subsurface features is clearly validated.

perspectives on Bitcoin and second-generation cryptocurrencies <=SEP=> Bitcoin has emerged as the most successful cryptographic currency in history. Within two years of its quiet launch in 2009, Bitcoin grew to comprise billions of dollars of economic value, even while the body of published research and security analysis justifying the system’s design was negligible. In the ensuing years, a growing literature has identified hidden-butimportant properties of the system, discovered attacks, proposed promising alternatives, and singled out difficult future challenges. This interest has been complemented by a large and vibrant community of open-source developers who steward the system, while proposing and deploying numerous modifications and extensions. We provide the first systematic exposition of the second generation of cryptocurrencies, including Bitcoin and the many alternatives that have been implemented as alternate protocols or “altcoins.” Drawing from a scattered body of knowledge, we put forward three key components of Bitcoin’s design that can be decoupled, enabling a more insightful analysis of Bitcoin’s properties and its proposed modifications and extensions. We contextualize the literature into five central properties capturing blockchain stability. We map the design space for numerous proposed modification, providing comparative analyses for alternative consensus mechanisms, currency allocation mechanisms, computational puzzles, and key management tools. We focus on anonymity issues in Bitcoin and provide an evaluation framework for analyzing a variety of proposals for enhancing unlinkability. Finally we provide new insights on a what we term disintermediation protocols, which absolve the need for trusted intermediaries in an interesting set of applications. We identify three general disintermediation strategies and provide a detailed comparative cost analysis. I. WHY BITCOIN IS WORTHY OF RESEARCH Consider two opposing viewpoints on Bitcoin in straw-man form. The first is that “Bitcoin works in practice, but not in theory.” At times devoted members of the Bitcoin community espouse this philosophy and criticize the security research community for failing to discover Bitcoin, not immediately recognizing its novelty, and still today dismissing its importance due to a lack of rigorous theoretical foundation. A second viewpoint is that Bitcoin hopelessly relies on an unknown combination of socio-economic factors for its current stability which are intractable to model with sufficient precision, failing to yield a convincing argument for the system’s soundness. Given these difficulties, experienced security researchers may avoid Bitcoin as a topic of study, considering it prudent security engineering to only design systems with precise threat models that admit formal security proofs. We strongly dismiss both of these simplistic approaches and show where each viewpoint fails, forwarding new insights based on multiple examples of existing knowledge. To the first, we contend that while Bitcoin has worked surprisingly well in practice so far, there is an important role for research to play in identifying precisely why this has been possible, moving beyond a blind acceptance of the informal arguments presented with the system’s initial proposal. Furthermore, it is crucial to understand whether Bitcoin will still “work in practice” as practices change. We expect external political and economic factors to evolve, and the system must change if and when transaction volume scales, and the nature of the monetary rewards for Bitcoin miners will change over time as part of the system design. It is not enough to argue that Bitcoin has worked from 2009–2014 and will therefore continue likewise. We do not yet have sufficient understanding to conclude with confidence that Bitcoin will continue to work well in practice, and that is a crucial research challenge that requires insight from computer science theory. To the second viewpoint, we contend that Bitcoin is filling an important niche by providing a virtual currency system without any trusted parties and without pre-assumed identities among the participants. Within these constraints, the general problem of consensus in a distributed system is impossible [5], [81] without further assumptions like Bitcoin’s premise that rational (greedy) behavior can be modeled and incentives can be aligned to ensure secure operation of the consensus algorithm. Yet these constraints matter in practice, both philosophically and technically, and Bitcoin’s approach to consensus within this model is deeply surprising and a fundamental contribution. Bitcoin’s core consensus protocol also has profound implications for many other computer security problems beyond currency1 such as distributed naming, secure timestamping and commitment, generation of public randomness, as well as many financial problems such as self-enforcing (“smart”) contracts, decentralized markets and order books, and distributed autonomous agents. In short, even though Bitcoin is not easy to model, it is worthy of considerable research attention as it may form the basis for practical solutions to exceedingly difficult and important problems. II. OVERVIEW OF BITCOIN A. A Contextualized History We refer the interested reader to existing surveys on the “first wave” of cryptocurrency research [13], [82]. In short, cryptographic currencies date back to Chaum’s proposal for 1As we shall see, it may not be possible to remove the currency functionality and still have a working consensus system. “untraceable payments” in 1983 [22], a system involving bankissued cash in the form of blindly signed coins. Unblinded coins are transferred between users and merchants, and redeemable after the bank verifies they have not been previously redeemed. Blind signatures prevent the bank from linking users to coins, providing unlinkability akin to cash. Throughout the 1990s, many variations and extensions of this scheme were proposed. Significant contributions include: removing the need for the bank to be online at purchase time [23], allowing coins to be divided into smaller units [80] and improving efficiency [21]. Several startup companies including DigiCash [95] and Peppercoin [87] attempted to bring electronic cash protocols into practice but ultimately failed in the market. In fact, no schemes from this “first wave” of cryptocurrency research achieved significant deployment. Moderately hard “proof-of-work” puzzles were proposed in the early 1990s for combatting email spam [34] (although it was never widely deployed for this purpose [59]). Many other applications followed, including proposals for a fair lottery [41], minting coins for micropayments [88], and preventing various forms of denial-of-service and abuse in anonymous networks [8]. The latter, Hashcash, was an alternative to using digital micropayments (e.g., NetBill [98] and Karma [107]). Proof of work was also used to detect sybil nodes in distributed peer-to-peer consensus protocols [5], and is used in Bitcoin consensus for a similar reason. Another essential element of Bitcoin is the public ledger, which makes double-spending detectable. In auditable ecash [93], [94], proposed in the late 1990s, the bank maintains a public database to detect double-spending and ensure the validity of coins, however the notion of publishing the entire set of valid coins was dismissed as impractical (only a Merkle root was published instead). B-money [29], proposed in 1998, appears to be the first system where all transactions are publicly (anonymously) broadcast and stored. Proposed on the Cypherpunks mailing list, b-money received minimal attention from the academic research community. Smart contracts [102], proposed in the early 1990s, enable parties to formally specify an enforceable agreement using cryptography and scripts. This idea portends Bitcoin’s scripting capabilities. In 2008, Bitcoin was announced and a white paper penned under the pseudonym Satoshi Nakamoto was posted to the Cypherpunks mailing list [77], followed quickly the source code of the original reference client. Bitcoin’s genesis block was mined on or around January 3, 2009.2 The first use of Bitcoin as a currency is thought to be a transaction in May 2010, where one user ordered pizza delivery for another in exchange for 10 000 bitcoins. Since then, increasing number of merchants and services have incorporated Bitcoin in some way, and the price has generally risen, reaching a peak of approximately $1400USD per coin in July 2013. Bitcoin’s history has also been colored by association with 2Famously, the first block contains the string “The Times 03/Jan/2009 Chancellor on brink of second bailout for banks.” crime. Bitcoin was famously used in a black market website, Silk Road [24], which operated from Feb. 2011 until Oct. 2013 when it was seized and shut down by the FBI. Botnets have found Bitcoin mining to be a supplemental source of income [46]. A current US federal court case involves a large Bitcoin-based Ponzi scheme [97]. In 2014, a computer virus called CryptoLocker extorted millions of dollars from victims by encrypting their files and demanding a Bitcoin ransom to release the decryption key [38]. Many users’ Bitcoins have been lost due to theft [33] and collapsed exchanges [75]. B. A Technical Overview We present Bitcoin’s current operation through its three main technical components: transactions (including scripts), the consensus protocol, and the communication network. Bitcoin is exceedingly complex—our goal is to present the system with sufficient technical depth, so the extant literature on Bitcoin, reviewed and evaluated in later sections of this paper, becomes understandable. In particular, a key benefit of our three-component breakdown is that it makes evaluating and systematizing proposed changes (Sections V & VIII) insightful by “decoupling” concepts that may be changed independently. Sources of information on Bitcoin. Bitcoin can be difficult to define as there is no formal

Intrusion Detection in the RPL-connected 6LoWPAN Networks <=SEP=> The interconnectivity of 6LoWPAN networks with the Internet raises serious security concerns, as constrained 6LoWPAN devices are accessible anywhere from the untrusted global Internet. Also, 6LoWPAN devices are mostly deployed in unattended environments, hence easy to capture and clone. Despite that state of the art crypto solutions provide information security, IPv6 enabled smart objects are vulnerable to attacks from outside and inside 6LoWPAN networks that are aimed to disrupt networks. This paper attempts to identify intrusions aimed to disrupt the Routing Protocol for Low-Power and Lossy Networks (RPL).In order to improve the security within 6LoWPAN networks, we extend SVELTE, an intrusion detection system for the Internet of Things, with an intrusion detection module that uses the ETX (Expected Transmissions) metric. In RPL, ETX is a link reliability metric and monitoring the ETX value can prevent an intruder from actively engaging 6LoWPAN nodes in malicious activities. We also propose geographic hints to identify malicious nodes that conduct attacks against ETX-based networks. We implement these extensions in the Contiki OS and evaluate them using the Cooja simulator.

Shrinkable, stiffness-controllable soft manipulator based on a bio-inspired antagonistic actuation principle <=SEP=> This paper explores a new hybrid actuation principle combining pneumatic and tendon-driven actuators for a soft robotic manipulator. The fusion of these two actuation principles leads to an overall antagonistic actuation mechanism whereby pneumatic actuation opposes tendon actuation - a mechanism commonly found in animals where muscles can oppose each other to vary joint stiffness. We are taking especially inspiration from the octopus who belongs to the class of Cephalopoda; the octopus uses its longitudinal and transversal muscles in its arms to achieve varied motion patterns; activating both sets of muscles, the octopus can control the arm stiffness over a wide range. Our approach mimics this behavior and achieves comparable motion patterns, including bending, elongation and stiffening. The proposed method combines the advantages of tendon-driven and pneumatic actuated systems and goes beyond what current soft, flexible robots can achieve: because the new robot structure is effectively an inflatable, sleeve, it can be pumped up to its fully inflated volume and, also, completely deflated and shrunk. Since, in the deflated state, it comprises just its outer “skin” and tendons, the robot can be compressed to a very small size, many times smaller when compared to its fully-inflated state. In this paper, we describe the mechanical structure of the soft manipulator. Proof-of-concept experiments focus on the robot's ability to bend, to morph from completely shrunk to entirely inflated as well as to vary its stiffness.

Design Considerations and Performance Evaluation of Single-Stage TAIPEI Rectifier for HVDC Distribution Applications <=SEP=> Design considerations and performance evaluations of a three-phase, four-switch, single-stage, isolated zero-voltage-switching (ZVS) rectifier are presented. The circuit is obtained by integrating the three-phase, two-switch, ZVS, discontinuous-current-mode (DCM), boost power-factorcorrection (PFC) rectifier, named for short the TAIPEI rectifier, with the ZVS full-bridge (FB) phase-shift dc/dc converter. The performance was evaluated on a three-phase 2.7-kW prototype designed for HVDC distribution applications with the line-toline voltage range from 180 VRMS to 264 VRMS and with a tightly regulated variable dc output voltage from 200 V to 300 V. The prototype operates with ZVS over the entire input-voltage and load-current range and achieves less than 5% input-current THD with the efficiency in the 95% range.

Fast and Accurate Crop and Weed Identification with Summarized Train Sets for Precision Agriculture <=SEP=> In this paper we present a perception system for agriculture robotics that enables an unmanned ground vehicle (UGV) equipped with a multi spectral camera to automatically perform the crop/weed detection and classification tasks in real-time. Our approach exploits a pipeline that includes two different convolutional neural networks (CNNs) applied to the input RGB+near infra-red (NIR) images. A lightweight CNN is used to perform a fast and robust, pixelwise, binary image segmentation, in order to extract the pixels that represent projections of 3D points that belong to green vegetation. A deeper CNN is then used to classify the extracted pixels between the crop and weed classes. A further important contribution of this work is a novel unsupervised dataset summarization algorithm that automatically selects from a large dataset the most informative subsets that better describe the original one. This enables to streamline and speed-up the manual dataset labeling process, otherwise extremely time consuming, while preserving good classification performances. Experiments performed on different datasets taken from a real farm robot confirm the effectiveness of our approach.

Osmotic Heat Engine Using Thermally Responsive Ionic Liquids. <=SEP=> The osmotic heat engine (OHE) is a promising technology for converting low grade heat to electricity. Most of the existing studies have focused on thermolytic salt systems. Herein, for the first time, we proposed to use thermally responsive ionic liquids (TRIL) that have either an upper critical solution temperature (UCST) or lower critical solution temperature (LCST) type of phase behavior as novel thermolytic osmotic agents. Closed-loop TRIL-OHEs were designed based on these unique phase behaviors to convert low grade heat to work or electricity. Experimental studies using two UCST-type TRILs, protonated betaine bis(trifluoromethyl sulfonyl)imide ([Hbet][Tf2N]) and choline bis(trifluoromethylsulfonyl)imide ([choline][Tf2N]) showed that (1) the specific energy of the TRIL-OHE system could reach as high as 4.0 times that of the seawater and river water system, (2) the power density measured from a commercial FO membrane reached up to 2.3 W/m2, and (3) the overall energy efficiency reached up to 2.6% or 18% of the Carnot efficiency at no heat recovery and up to 10.5% or 71% of the Carnet efficiency at 70% heat recovery. All of these results clearly demonstrated the great potential of using TRILs as novel osmotic agents to design high efficient OHEs for recovery of low grade thermal energy to work or electricity.

Study of Viola-Jones Real Time Face Detector <=SEP=> Face detection has been one of the most studied topics in computer vision literature. Given an arbitrary image, the goal of face detection is to determine whether or not there are any faces in the image and, if present, return the image location and extent of each face. While this appears to be a trivial task for human beings, it is a very challenging task for computers. The difficulty associated with face detection can be attributed to many variations in scale, location, view point, illumination, occlusions, etc. Although there have been hundreds of reported approaches to face detection, if one were asked to name a single face detection algorithm that has the most impact in recent decades, it will most likely be the Viola and Jones face detection, which is capable of processing images extremely rapidly and achieve high detection rates. This project is going to study and understand the Viola-Jones algorithm by implementing the whole detection framework and based on the implementation, conduct experiment to hopefully further improve the performance.

Parameterized Models for Facial Animation <=SEP=> Parameterized models can produce realistic, manipulable images of human faces&mdash; with a surprisingly small number of parameters.

Personal Safety is More Important Than Cost of Damage During Robot Failure <=SEP=> As robots become more common in everyday life it will be increasingly important to understand how non-experts will view robot failure. In this study, we found that severity of failure seems to be tightly coupled with perceived risk to self rather than risk to the robot's task and object. We initially thought perceived severity would be tied to the cost of damage. Instead, participants placed falling drinking glasses above a laptop when rating the severity of the failure. Related results reinforce the primacy of personal safety over the financial cost of damage and suggest the results were tied to proximity to breaking glass.

Augmented Reality through Wearable Computing <=SEP=> Wearable computing moves computation from the desktop to the user. We are forming a community of networked, wearable-computer users to explore, over a long period, the augmented realities that these systems can provide. By adapting its behavior to the user's changing environment, a body-worn computer can assist the user more intelligently, consistently, and continuously than a desktop system. A text-based augmented reality, the Remembrance Agent, is presented to illustrate this approach. Video cameras are used both to warp the visual input (mediated reality) and to sense the user's world for graphical overlay. With a camera, the computer could track the user's finger to act as the system's mouse; perform face recognition; and detect passive objects to overlay 2.5D and 3D graphics onto the real world. Additional apparatus such as audio systems, infrared beacons for sensing location, and biosensors for learning about the wearer's affect are described. With the use of input from these interface devices and sensors, a long-term goal of this project is to model the user's actions, anticipate his or her needs, and perform a seamless interaction between the virtual and physical environments.

Visual-Interactive Preprocessing of Time Series Data <=SEP=> Time series data is an important data type in many different application scenarios. Consequently, there are a great variety of approaches for analyzing time series data. Within these approaches different strategies for cleaning, segmenting, representing, normalizing, comparing, and aggregating time series data can be found. When combining these operations, the time series analysis preprocessing workflow has many degrees of freedom. To define an appropriate preprocessing pipeline, the knowledge of experts coming from the application domain has to be included into the design process. Unfortunately, these experts often cannot estimate the effects of the chosen preprocessing algorithms and their parameterizations on the time series. We introduce a system for the visual-interactive exploitation of the preprocessing parameter space. In contrast to ‘black box’-driven approaches designed by computer scientists based on the requirements of domain experts, our system allows these experts to visual-interactively compose time series preprocessing pipelines by themselves. Visual support is provided to choose the right order and parameterization of the preprocessing steps. We demonstrate the usability of our approach with a case study from the digital library domain, in which time-oriented scientific research data has to be preprocessed to realize a visual search and analysis application.

Design of fully printable chipless RFID tag on flexible substrate for secure banknote applications <=SEP=> A fully printable, passive and planar chipless RFID tag on thin flexible substrate is presented. The chipless tag encodes data into the spectral signature using a multiresonating circuit. Both amplitude and phase components of the spectral signature are used for data encoding. The tag comprises of a microstrip multiresonating circuit with 6 multi-spiral resonators and two cross-polarized UWB disc loaded monopole transmitting and receiving antennas. The chipless tag is designed to be printed on the Australian banknote and provide an extra layer of security against counterfeiting.

Active Antennas : The Next Step in Radio and Antenna Evolution <=SEP=> 

Computational Creativity <=SEP=> Creative thinking is one of the hallmarks of human-level competence. Although it is still a poorly understood subject speculative ideas about brain processes involved in creative thinking may be implemented in computational models. A review of different approaches to creativity, insight and intuition is presented. Two factors are essential for creativity: imagination and selection or filtering. Imagination should be constrained by experience, while filtering in the case of creative use of words may be based on semantic and phonological associations. Analysis of brain processes involved in invention of new words leads to practical algorithms that create many interesting and novel names associated with a set of keywords.

Robust Speaker-Adaptive HMM-Based Text-to-Speech Synthesis <=SEP=> This paper describes a speaker-adaptive HMM-based speech synthesis system. The new system, called ldquoHTS-2007,rdquo employs speaker adaptation (CSMAPLR+MAP), feature-space adaptive training, mixed-gender modeling, and full-covariance modeling using CSMAPLR transforms, in addition to several other techniques that have proved effective in our previous systems. Subjective evaluation results show that the new system generates significantly better quality synthetic speech than speaker-dependent approaches with realistic amounts of speech data, and that it bears comparison with speaker-dependent approaches even when large amounts of speech data are available. In addition, a comparison study with several speech synthesis techniques shows the new system is very robust: It is able to build voices from less-than-ideal speech data and synthesize good-quality speech even for out-of-domain sentences.

Dermoscopic findings in Laugier-Hunziker syndrome. <=SEP=> BACKGROUND
Laugier-Hunziker syndrome (LHS) is a rare, acquired mucocutaneous hyperpigmentation often associated with longitudinal melanonychia. The clinical behavior of mucocutaneous pigmented lesions ranges from benign to highly malignant. Therefore, in most cases, the clinical diagnosis should be confirmed by further diagnostic methods. Dermoscopy is a noninvasive technique that has been used to make more accurate diagnoses of pigmented skin lesions. Nevertheless, to our knowledge, the dermoscopic features of the pigmented lesions in LHS have not been described previously. Herein, we report a case of LHS together with its dermoscopic features.


OBSERVATIONS
The clinical examination revealed macular hyperpigmentation on the oral and genital mucosa, conjunctiva, and palmoplantar region together with longitudinal melanonychia. Dermoscopic examination of mucosal lesions on the patient's lips and vulva revealed a parallel pattern. Longitudinal homogeneous pigmentation was observed on the toenails. The pigmented macules on the palms and the sole showed a parallel furrow pattern. A skin biopsy sample taken from the labial lesion was compatible with a diagnosis of mucosal melanosis.


CONCLUSIONS
By means of this case report, the dermoscopic features of the pigmented lesions in LHS are described for the first time, which facilitates diagnosis with a noninvasive technique. Future reports highlighting the dermoscopic features of this syndrome may simplify the diagnosis of LHS, which is thought to be underdiagnosed.

Current Methods in the Automatic Tissue Segmentation of 3D Magnetic Resonance Brain Images <=SEP=> Accurate segmentation of magnetic resonance (MR) images of the brain is of interest in the study of many brain disorders. In this paper, we provide a review of some of the current approaches in the tissue segmentation of MR brain images. We broadly divided current MR brain image segmentation algorithms into three categories: classificationbased, region-based, and contour-based, and discuss the advantages and disadvantages of these approaches. We also briefly review our recent work in this area. We show that by incorporating two key ideas into the conventional fuzzy cmeans clustering algorithm, we are able to take into account the local spatial context and compensate for the intensity nonuniformity (INU) artifact during the clustering process. We conclude this review by pointing to some possible future directions in this area.

Generalised spatial modulation with multiple active transmit antennas <=SEP=> We propose a new generalised spatial modulation (GSM) technique, which can be considered as a generalisation of the recently proposed spatial modulation (SM) technique. SM can be seen as a special case of GSM with only one active transmit antenna. In contrast to SM, GSM uses the indices of multiple transmit antennas to map information bits, and is thus able to achieve substantially increased spectral efficiency. Furthermore, selecting multiple active transmit antennas enables GSM to harvest significant transmit diversity gains in comparison to SM, because all the active antennas transmit the same information. On the other hand, inter-channel interference (ICI) is completely avoided by transmitting the same symbols through these active antennas. We present theoretical analysis using order statistics for the symbol error rate (SER) performance of GSM. The analytical results are in close agreement with our simulation results. The bit error rate performance of GSM and SM is simulated and compared, which demonstrates the superiority of GSM. Moreover, GSM systems with configurations of different transmit and receive antennas are studied. Our results suggest that using a less number of transmit antennas with a higher modulation order will lead to better BER performance.

Accelerometer based wireless air mouse using Arduino micro-controller board <=SEP=> With the day to day advancements in technology, the interaction between the human and the digital world is diminishing. Lot of improvement has taken place in the mobile technology from button keypads to touch screens. However the current PCs still need a pad to operate its mouse and are wired most of the time. The idea is to develop a wireless mouse which works on the hand gestures of the user without the need of a pad making an effortless interaction between the human and the computer. The implementation is done using a sensor named accelerometer to sense the hand gestures. Accelerometer is a motion sensor which sense changes in motion in any of the three axes. In here the accelerometer will be at the users side, attached to the hand to sense the movement and gives the output to a micro-controller to process it. Necessary modifications are done by the microcontroller to these values and are transmitted through a RF module to the PC. At the receiving end a mouse control program which contains functions to control the mouse reads these values and performs the necessary action.

Safety in shipping: the human element. <=SEP=> INTRODUCTION
There are numerous diverse papers that have addressed issues within maritime safety; to date there has been no comprehensive review of this literature to aggregate the causal factors within accidents in shipping and surmise current knowledge.


METHODS
This paper reviewed the literature on safety in three key areas: common themes of accidents, the influence of human error, and interventions to make shipping safer. The review included 20 studies of seafaring across the following areas: fatigue, stress, health, situation awareness, teamwork, decision-making, communication, automation, and safety culture.


RESULTS
The review identifies the relative contributions of individual and organizational factors in shipping accidents, and also presents the methodological issues with previous research.


CONCLUSIONS
The paper concludes that monitoring and modifying the human factors issues presented in this paper could contribute to maritime safety performance.


IMPACT ON INDUSTRY
This review illustrates which human factors issues are prevalent in incidents therefore this gives shipping practitioners a focus for interventions.

Ranging RFID Tags With Ultrasound <=SEP=> Indoor localization and tracking of persons and assets with centimeter-level accuracy for inventory, security, medical monitoring, and training, as well as gesture interfaces for domotics, is highly desirable in the framework of the emerging IoT paradigm. Low cost, tiny, battery, or batteryless operated position sensors are required. 3-D localization can be computed by combining three or more distance measurements between sensor and reference points. Our aim is to give the capability of measuring the distance from a reference point to radio frequency identification (RFID) tags. The main challenge is in the estimation of the distances with millimeter accuracy in presence of both size and power supply strict constraints, and thus with very limited computational power. An accurate ranging technique using cross-correlation and small RFID-based sensors is proposed. Its originality resides in moving the main computational efforts from the sensor to an external processing unit with sufficient computational and supply power, thus overcoming the sensor limits. The system is composed of a beacon that emits ultrasound chirps and RF sync signals, a RFID-based distance sensor, a commercial RFID reader, and a processing unit. Main advantages are the high miniaturization and low power consumption of the remote sensor, and its compatibility with existing RFID standards.

Discriminant validity of well-being measures. <=SEP=> The convergent and discriminant validities of well-being concepts were examined using multitrait-multimethod matrix analyses (D. T. Campbell & D. W. Fiske, 1959) on 3 sets of data. In Study 1, participants completed measures of life satisfaction, positive affect, negative affect, self-esteem, and optimism on 2 occasions 4 weeks apart and also obtained 3 informant ratings. In Study 2, participants completed each of the 5 measures on 2 occasions 2 years apart and collected informant reports at Time 2. In Study 3, participants completed 2 different scales for each of the 5 constructs. Analyses showed that (a) life satisfaction is discriminable from positive and negative affect, (b) positive affect is discriminable from negative affect, (c) life satisfaction is discriminable from optimism and self-esteem, and (d) optimism is separable from trait measures of negative affect.

Fusing Similarity Models with Markov Chains for Sparse Sequential Recommendation <=SEP=> Predicting personalized sequential behavior is a key task for recommender systems. In order to predict user actions such as the next product to purchase, movie to watch, or place to visit, it is essential to take into account both long-term user preferences and sequential patterns (i.e., short-term dynamics). Matrix Factorization and Markov Chain methods have emerged as two separate but powerful paradigms for modeling the two respectively. Combining these ideas has led to unified methods that accommodate long-and short-term dynamics simultaneously by modeling pairwise user-item and item-item interactions. In spite of the success of such methods for tackling dense data, they are challenged by sparsity issues, which are prevalent in real-world datasets. In recent years, similarity-based methods have been proposed for (sequentially-unaware) item recommendation with promising results on sparse datasets. In this paper, we propose to fuse such methods with Markov Chains to make personalized sequential recommendations. We evaluate our method, Fossil, on a variety of large, real-world datasets. We show quantitatively that Fossil outperforms alternative algorithms, especially on sparse datasets, and qualitatively that it captures personalized dynamics and is able to make meaningful recommendations.

A New Approach for Image Steganography Using Edge Detection Method for Hiding Text in Color Images Using HSI Color Model <=SEP=> The objective of the present project is to uses a new techniques for steganography in a HSI color cover images, which hides secret message in the edges of the carrier images using 2-bit LSB substitution for embedding. To get true edges, canny edge detection technique has been used. Amount of data to be embedded plays an important role on the selection of edges. The main advantage of using HIS color mode is that it produces a image with a significantly larg file size hence we hide large amount of secrete message Experimental results have shown that the proposed technique performs better and higher embedding capacity.