Query: Analog transistor models of bacterial genetic circuits

Relevant passages:
An Introduction to Systems Biology: Design Principles of Biological Circuits <=SEP=> Bernhard Ø. Palsson Cambridge U. Press, New York, 2006. $75.00 (322 pp.). ISBN 978-0-521-85903-5 Reviewed by Nigel Goldenfeld For some of us physicists, the recent explosion of interest in biology by our colleagues is something of a mystery— perhaps even a betrayal. Biology seems to offer none of the aesthetic elegance and beauty that is the hallmark of such cherished creations as the general theory of relativity and the standard model of strong, weak, and electromagnetic interactions. Neither does biology provide the breathtaking precision with which physical experiment and theory can agree in such phenomena as quantum electrodynamics or Josephson effects. And don’t even think about summarizing all of biology on a T-shirt; biology textbooks, unlike those for physics, generally describe reactions and structures in monstrous detail, without an equation in sight. So why the allure of the subject among physicists? And what meaningful contributions can physical scientists make to the field? One answer is the emergence of a new science of biological circuits, or systems biology, which has become advanced enough, both scientifically and promotionally, that textbooks are warranted. Uri Alon’s An Introduction to Systems Biology: Design Principles of Biological Circuits and Bernhard Ø. Palsson’s Systems Biology: Properties of Reconstructed Networks are two recent offerings by leaders in this new field. These texts deserve serious attention from any quantitative scientist or physicist who hopes to learn about modern biology. Both books are well written; each has a different focus. Thus they could be used together to create an accessible course for beginners, with the instructor’s choice of topics from each book. The books are a welcome departure from the typical biology textbook. First, they emphasize quantitative modeling rather than nomenclature; second, they concentrate on essentials of the modeling rather than on exhaustive lists of components that offer no meaningful integration; and third, the approaches described in the texts make nontrivial quantitative predictions that can be and have been verified. Alon’s book is the better place for physicists to start. It assumes no prior knowledge of or even interest in biology. Yet right from chapter 1 the author succeeds in explaining in an intellectually exciting way what the cell does and what degrees of freedom enable it to function. The book proceeds with detailed discussions of some of the key network motifs, circuitelement designs that are believed to be repeated over and over again in biological systems. Those motifs include autoregulation, feed-forward loops, positive-feedback loops, and kinetic proofreading. The discussions in all cases introduce the particular motif, use simple differential equations in most cases as a way to model it, and offer plenty of comparisons with experimental data. Alon does not forget to ask a question physicists obsess over: Are any general physical principles at work in biology? Alon does not overplay that point but has included a nice chapter on robustness. He focuses on concrete examples such as chemotaxis and developmental pattern formation. He also devotes a chapter to explaining the precision with which biological processes can so accurately identify the right molecules amidst a sea of potentially confusing “wrong” targets. The basis of this process is kinetic proofreading, a concept first presented by physicist John Hopfield, and one that is based on simple nonequilibrium kinetics. Alon ends his book with an epilogue on simplicity in biology. He draws the detailed strands together into an appealing and inspiring overview of biology. Without the preceding attention to biological detail, this exercise would be vacuous. One final aspect of An Introduction to Systems Biology that must be mentioned is the wonderful set of exercises that accompany each chapter. The exercises range from elementary to advanced research areas. For example, chapter 9 contains problems on the errorminimization capabilities of the genetic code, which I and several other physicists, including Alon, are still elucidating. I would have liked to see evolution play a more central role in the text—for example, in a chapter of its own that amplifies the important comments in the epilogue about the evolution of modularity. Perhaps when it’s time for the second edition, there will be enough concrete material to further justify including the topic. Palsson’s Systems Biology presents a completely different perspective. The book focuses less on principles and more on techniques for reconstructing detailed, elaborate, and predictive circuit models of biological systems. During the past 10 years these techniques have become feasible for entire organisms, thanks to the availability of fully sequenced genomes. It is now possible to map out the metabolic networks of bacteria such as Escherichia coli and simpler eukaryotes. However, other networks in organisms control other

Ultra Low Power Bioelectronics Fundamentals , Biomedical Applications , and Bio-inspired Systems <=SEP=> This book provides, for the first time, a broad and deep treatment of the fields of both ultra low power electronics and bioelectronics. It discusses fundamental principles and circuits for ultra low power electronic design and their applications in biomedical systems. It also discusses how ultra energy-efficient cellular and neural systems in biology can inspire revolutionary low power architectures in mixed-signal and RF electronics. The book presents a unique, unifying view of ultra low power analog and digital electronics and emphasizes the use of the ultra energy-efficient subthreshold regime of transistor operation in both. Chapters on batteries, energy harvesting, and the future of energy provide an understanding of fundamental relationships between energy use and energy generation at small scales and at large scales. A wealth of insights and examples from brain implants, cochlear implants, biomolecular sensing, cardiac devices, and bio-inspired systems make the book useful and engaging for students and practicing engineers.

An analog bionic ear processor with zero-crossing detection <=SEP=> A 75 dB 251 /spl mu/W analog speech processor is described that preserves the performance, robustness, and programmability needed for deaf patients at a reduced power consumption compared to that of implementations with A/D and DSP. It also provides zero-crossing outputs for stimulation strategies that use phase information to improve performance.

Genomics of cellulosic biofuels <=SEP=> The development of alternatives to fossil fuels as an energy source is an urgent global priority. Cellulosic biomass has the potential to contribute to meeting the demand for liquid fuel, but land-use requirements and process inefficiencies represent hurdles for large-scale deployment of biomass-to-biofuel technologies. Genomic information gathered from across the biosphere, including potential energy crops and microorganisms able to break down biomass, will be vital for improving the prospects of significant cellulosic biofuel production.

A 10-nW 12-bit accurate analog storage cell with 10-aA leakage <=SEP=> Medium-term analog storage offers a compact, accurate, and low-power method of implementing temporary local memory that can be useful in adaptive circuit applications. The performance of these cells is characterized by the sampling accuracy and voltage droop that can be achieved with a given level of die area and power. Hand calculations suggest past implementations have not achieved minimum voltage droop due to uncompensated MOS leakage mechanisms. In this paper, the dominant sources of MOS leakage are experimentally characterized in a standard 1.5-/spl mu/m CMOS process using an on-chip current integration technique, focusing specifically on the 1 fA to 1 aA current range. These measurements reveal an accumulation-mode source-drain coupling mechanism that can easily dominate diode leakage under certain bias conditions and may have limited previous designs. A simple rule-of-thumb is offered for avoiding this leakage effect, leading to a novel ultra-low leakage switch topology. A differential storage cell incorporating this new switch achieves an average leakage of 10 aA at room temperature, an 8/spl times/ reduction over past designs. The cell loses one bit of voltage accuracy, 700 /spl mu/V on a 12-bit scale and 11.3 mV on an 8-bit scale, in 3.3 and 54 min, respectively. This represents a 15/spl times/ increase in hold time at these voltage accuracies over the lowest leakage cell to date, in only 92% of the area. Since the leakage is independent of amplifier bias, the cell can operate on as little as 10 nW of power. Initial measurements also indicate the switch's leakage decreases with the square of process feature size.

Electric Motor Drive Selection Issues for HEV Propulsion Systems: A Comparative Study <=SEP=> This paper describes a comparative study allowing the selection of the most appropriate electric-propulsion system for a parallel hybrid electric vehicle (HEV). This paper is based on an exhaustive review of the state of the art and on an effective comparison of the performances of the four main electric-propulsion systems, namely the dc motor, the induction motor (IM), the permanent magnet synchronous motor, and the switched reluctance motor. The main conclusion drawn by the proposed comparative study is that it is the cage IM that better fulfills the major requirements of the HEV electric propulsion

Blockchain and its uses <=SEP=> Blockchain, the technology behind most cryptocurrencies that exist today, offers a paradigm shifting technology that has the potential to transform the way that we record and verify events on the Internet. By offering a decentralized, immutable, community verified record of transactions, regardless of what these transactions represent, blockchain technology promises to transform many industries. In this paper, we provide a survey of this very important technology and discuss its possible use-cases and its effect on society. The purpose of this paper is to familiarize the reader with the current state-of-the-art in the blockchain world both in terms of technology and social impact.

ShapeNet: An Information-Rich 3D Model Repository <=SEP=> We present ShapeNet: a richly-annotated, large-scale repository of shapes represented by 3D CAD models of objects. ShapeNet contains 3D models from a multitude of semantic categories and organizes them under the WordNet taxonomy. It is a collection of datasets providing many semantic annotations for each 3D model such as consistent rigid alignments, parts and bilateral symmetry planes, physical sizes, keywords, as well as other planned annotations. Annotations are made available through a public web-based interface to enable data visualization of object attributes, promote data-driven geometric analysis, and provide a large-scale quantitative benchmark for research in computer graphics and vision. At the time of this technical report, ShapeNet has indexed more than 3,000,000 models, 220,000 models out of which are classified into 3,135 categories (WordNet synsets). In this report we describe the ShapeNet effort as a whole, provide details for all currently available datasets, and summarize future plans.

A New Aggregate Local Mobility (ALM) Clustering Algorithm for VANETs <=SEP=> We present a beacon-based clustering algorithm aimed at prolonging the cluster lifetime in VANETs. We use a new aggregate local mobility criterion to decide upon cluster re-organisation. The scheme incorporates a contention method to avoid triggering frequent re-organisations when two clusterheads encounter each other for a short period of time. Simulation results show a significant improvement of cluster lifetime and reduced node state/role changes compared to previous popular clustering algorithms.

Kinematic analysis of electroactive polymer actuators as soft and smart structures with more DoF than inputs <=SEP=> Electroactive polymer (EAP) actuators have been attracting the attention of researchers due to their muscle-like behaviour and unusual properties. Several modelling methods have been proposed to understand their mechanical, chemical, electrical behaviours or `electro-chemo-mechanical' behaviour. However, estimating the whole shape or configuration of the EAP actuators has always been challenging due to their highly non-linear bending behaviour. This paper reports on an effective method to estimate the whole shape deflection of the EAP actuators by employing a so-called backbone approach. Tri-layer configured polypyrrole (PPy) based EAP actuators were used as a soft and smart structure with more degrees of freedom than its input. After deriving the inverse kinematic model of the actuator, its complete shape is estimated by solving the inverse kinematic model with an angle optimization (AngleOPT) method. The experimental results and numerical results have demonstrated the effectiveness of the method in estimating the highly non-linear bending behaviour of the PPy actuators and applicability of this modelling approach to other EAP actuators.

A Bidirectional Bridge Modular Switched-Capacitor-Based Power Electronics Transformer <=SEP=> This paper proposes a new bridge modular switched-capacitor-based ac–ac converter, which is intended to replace conventional transformers in commercial and residential applications, especially for microgrids. The main advantages of the proposed converter lie in high efficiency and power factor, bidirectional operation, and capacitor voltage self-balancing ability. Another distinct merit is its symmetric construction, with which the voltage ripple of charge/pump capacitors can be cancelled out, and the output voltage will be smooth with significant ripple reduction. It is also noteworthy that the symmetric construction ensures that the two symmetric parts can work independently under a simplified control strategy. In addition, the modular configuration contributes to convenient voltage extension. Compared with the reported flying-capacitor switched-capacitor ac–ac converter, the proposed converter requires fewer switches and capacitors per unit of voltage conversion, thus suffering lower voltage stress. To demonstrate the performance of the converter, a prototype with 600-W 220-Vrms high-side voltage, 55-Vrms low-side voltage, and a switching frequency of 100 kHz was designed and fabricated. The relevant experimental results are reported herein. The maximum and rated power efficiency obtained were 95.9% and 94.4%, respectively.

Symbol Interdependency in Symbolic and Embodied Cognition <=SEP=> Whether computational algorithms such as latent semantic analysis (LSA) can both extract meaning from language and advance theories of human cognition has become a topic of debate in cognitive science, whereby accounts of symbolic cognition and embodied cognition are often contrasted. Albeit for different reasons, in both accounts the importance of statistical regularities in linguistic surface structure tends to be underestimated. The current article gives an overview of the symbolic and embodied cognition accounts and shows how meaning induction attributed to a specific statistical process or to activation of embodied representations should be attributed to language itself. Specifically, the performance of LSA can be attributed to the linguistic surface structure, more than special characteristics of the algorithm, and embodiment findings attributed to perceptual simulations can be explained by distributional linguistic information.

Challenges and business models for mobile location-based services and advertising <=SEP=> Mobile advertising will become more pervasive and profitable, but not before addressing key technical and business challenges.

Recognition and volume estimation of food intake using a mobile device <=SEP=> We present a system that improves accuracy of food intake assessment using computer vision techniques. Traditional dietetic method suffers from the drawback of either inaccurate assessment or complex lab measurement. Our solution is to use a mobile phone to capture images of foods, recognize food types, estimate their respective volumes and finally return quantitative nutrition information. Automated and accurate food recognition presents the following challenges. First, there exist a large variety of food types that people consume in everyday life. Second, a single category of food may contain large variations due to different ways of preparation. Also, diverse lighting conditions may lead to varying visual appearance of foods. All of these pose a challenge to the state of the art recognition approaches. Moreover, the low quality images captured using cellphones make the task of 3D reconstruction difficult. In this paper, we combine several vision techniques (visual recognition and 3D reconstruction) to achieve quantitative food intake estimation. Evaluation of both recognition and reconstruction is provided in the experimental results.

Sex differences in intrinsic aptitude for mathematics and science?: a critical review. <=SEP=> This article considers 3 claims that cognitive sex differences account for the differential representation of men and women in high-level careers in mathematics and science: (a) males are more focused on objects from the beginning of life and therefore are predisposed to better learning about mechanical systems; (b) males have a profile of spatial and numerical abilities producing greater aptitude for mathematics; and (c) males are more variable in their cognitive abilities and therefore predominate at the upper reaches of mathematical talent. Research on cognitive development in human infants, preschool children, and students at all levels fails to support these claims. Instead, it provides evidence that mathematical and scientific reasoning develop from a set of biologically based cognitive capacities that males and females share. These capacities lead men and women to develop equal talent for mathematics and science.

Inherent Resistance of Efficient ECC Designs against SCA Attacks <=SEP=> The Montgomery kP algorithm using Lopez-Dahab projective coordinates is a time and energy efficient way to perform the elliptic curve point multiplication. It even can provide resistance against simple power analysis attacks. Nevertheless, straight forward implementations of this algorithm are not resistant against differential power analysis attacks. But highly-efficient designs i.e. designs in which different functional units are operating in parallel can increase the resistance of ECC implementations against DPA. In this paper we demonstrate this fact on the examples of our 6 implementations of the Montgomery kP algorithm. We perform horizontal DPA attacks to demonstrate the fact that the resistance of the kP algorithm against side channel analysis attacks can be increased through its implementation as an efficient design.

Automatic Array Alignment in Data-Parallel Programs <=SEP=> Data-parallel languages like Fortran 90 express parallelism in the form of operations on data aggregates such as arrays. Misalignment of the operands of an array operation can reduce program performance on a distributed-memory parallel machine by requiring nonlocal data accesses. Determining array alignments that reduce communication is therefore a key issue in compiling such languages.
We present a framework for the automatic determination of array alignments in data-parallel languages such as Fortran 90. Our language model handles array sectioning, reductions, spreads, transpositions, and masked operations. We decompose alignment functions into three constituents: axis, stride, and offset. For each of these subproblems, we show how to solve the alignment problem for a basic block of code, possibly containing common subexpressions. Alignments are generated for all array objects in the code, both named program variables and intermediate results. The alignments obtained by our algorithms are more general than those provided by the “owner-computes” rule. Finally, we present some ideas for dealing with control flow, replication, and dynamic alignments that depend on loop induction variables.

Subcutaneous and visceral adipose tissue: their relation to the metabolic syndrome. <=SEP=> Methods for assessment, e.g., anthropometric indicators and imaging techniques, of several phenotypes of human obesity, with special reference to abdominal fat content, have been evaluated. The correlation of fat distribution with age, gender, total body fat, energy balance, adipose tissue lipoprotein lipase and lipolytic activity, adipose tissue receptors, and genetic characteristics are discussed. Several secreted or expressed factors in the adipocyte are evaluated in the context of fat tissue localization. The body fat distribution and the metabolic profile in nonobese and obese individuals is discussed relative to lipolysis, antilypolysis and lipogenesis, insulin sensitivity, and glucose, lipid, and protein metabolism. Finally, the endocrine regulation of abdominal visceral fat in comparison with the adipose tissue localized in other areas is presented.

The language of mental health problems in social media <=SEP=> Online social media, such as Reddit, has become an important resource to share personal experiences and communicate with others. Among other personal information, some social media users communicate about mental health problems they are experiencing, with the intention of getting advice, support or empathy from other users. Here, we investigate the language of Reddit posts specific to mental health, to define linguistic characteristics that could be helpful for further applications. The latter include attempting to identify posts that need urgent attention due to their nature, e.g. when someone announces their intentions of ending their life by suicide or harming others. Our results show that there are a variety of linguistic features that are discriminative across mental health user communities and that can be further exploited in subsequent classification tasks. Furthermore, while negative sentiment is almost uniformly expressed across the entire data set, we demonstrate that there are also condition-specific vocabularies used in social media to communicate about particular disorders. Source code and related materials are available from: https: //github.com/gkotsis/ reddit-mental-health.

A Literature Review and Classification of Recommender Systems on Academic Journals <=SEP=> Recommender systems have become an important research field since the emergence of the first paper on collaborative filtering in the mid‐1990s. In general, recommender systems are defined as the supporting systems which help users to find information, products, or services (such as books, movies, music, digital products, web sites, and TV programs) by aggregating and analyzing suggestions from other users, which mean reviews from various authorities, and user attributes. However, as academic researches on recommender systems have increased significantly over the last ten years, more researches are required to be applicable in the real world situation. Because research field on recommender systems is still wide and less mature than other research fields. Accordingly, the existing articles on recommender systems need to be reviewed toward the next generation of recommender systems. However, it would be not easy to confine the recommender system researches to specific disciplines, considering the nature of the recommender system researches. So, we reviewed all articles on recommender systems from 37 journals which were published from 2001 to 2010. The 37 journals are selected from top 125 journals of the MIS Journal Rankings. Also, the literature search was based on the descriptors “Recommender system”, “Recommendation system”, “Personalization system”, “Collaborative filtering” and “

CipherXRay: Exposing Cryptographic Operations and Transient Secrets from Monitored Binary Execution <=SEP=> Malwares are becoming increasingly stealthy, more and more malwares are using cryptographic algorithms (e.g., packing, encrypting C&C communication) to protect themselves from being analyzed. The use of cryptographic algorithms and truly transient cryptographic secrets inside the malware binary imposes a key obstacle to effective malware analysis and defense. To enable more effective malware analysis, forensics, and reverse engineering, we have developed CipherXRay - a novel binary analysis framework that can automatically identify and recover the cryptographic operations and transient secrets from the execution of potentially obfuscated binary executables. Based on the avalanche effect of cryptographic functions, CipherXRay is able to accurately pinpoint the boundary of cryptographic operation and recover truly transient cryptographic secrets that only exist in memory for one instant in between multiple nested cryptographic operations. CipherXRay can further identify certain operation modes (e.g., ECB, CBC, CFB) of the identified block cipher and tell whether the identified block cipher operation is encryption or decryption in certain cases. We have empirically validated CipherXRay with OpenSSL, popular password safe KeePassX, the ciphers used by malware Stuxnet, Kraken and Agobot, and a number of third party softwares with built-in compression and checksum. CipherXRay is able to identify various cryptographic operations and recover cryptographic secrets that exist in memory for only a few microseconds. Our results demonstrate that current software implementations of cryptographic algorithms hardly achieve any secrecy if their execution can be monitored.

DDoS: threats and mitigation <=SEP=> According to a report from Prolexic, one of the first and largest companies offering DDoS mitigation services, ⁠ attack traffic rose 66% over the course of a year (to Q3 2011). 1 Network-layer attacks accounted for 83%, the rest being application-layer attacks. The average duration was 1.4 days and the average bandwidth consumed was 1.5Gbps. The size of attacks is getting bigger, too. In July 2011, Prolexic announced it had mitigated what it believed to be the largest packet-per-second DDoS attack ever seen in Asia. Consisting of SYN and ICMP floods, the attack deployed 176,000 bots (compared to the 5,000-10,000 bots more normally seen by Prolexic) to generate 25 million packets per second. According to the company, the majority of high-end border rout-ers typically forward 70,000 packets per second. It mitigated the attack by distributing traffic among its Tier 1 carrier partners and scrubbing centres. Ben Petro, senior VP network intelligence & availability at Verisign, traces the rise of DDoS attacks back another year. He says that for years there was little awareness of the problem but that, " 2010 was a dramatic shift – not only in the size, scale and trajectory of DDoS, but also in its proliferation and the number of different types of organisation that were hit. " In the years 2006-2008, he adds, the average attack was somewhere around 40Mbps. " And then, all of a sudden, coming in 2010 we started to see 2Gbps, then 5Gbps, then 8Gbps and 15Gbps attacks, culminating in the largest that we've seen coming in at 84Gbps sustained for a week and a half. That is an incredible amount of traffic when you get down to packets or queries per second – you're over the hundreds of thousands of queries per second per location for Verisign, and we have 165 locations. So it's an enormous volume. " The rising popularity of DDoS attacks may be connected directly to their effectiveness. Paul Sop, CTO at Prolexic, says, " people get creative and they use and invent new ways and reasons to use DDoS. When an idea catches on in the industry there's a tipping point – people say, hey here's a type of attack we can launch and it's very likely we won't go to jail unless we're pretty dumb about it. " He adds: " It is like asymmetric warfare – the attackers have so much advantage in terms …

Software-defined optical networks (SDONs): a survey <=SEP=> This paper gives an overview of software-defined optical networks (SDONs). It explains the general concepts on software-defined networks (SDNs), their relationship with network function virtualization, and also about OpenFlow, which is a pioneer protocol for SDNs. It then explains the benefits and challenges of extending SDNs to multilayer optical networks, including flexible grid and elastic optical networks, and how it compares to generalized multi-protocol label switching for implementing a unified control plane. An overview on the industry and research efforts on SDON standardization and implementation is given next, to bring the reader up to speed with the current state of the art in this field. Finally, the paper outlines the benefits achieved by SDONs for network operators, and also some of the important and relevant research problems that need to be addressed.

OCR for bilingual documents using language modeling <=SEP=> Script based features are highly discriminative for text segmentation and recognition. Thus they are widely used in Optical Character Recognition(OCR) problems. But usage of script dependent features restricts the adaptation of such architectures directly for another script. With script independent systems, this problem can be solved to a certain extent for monolingual documents. But the problem aggravates in case of multilingual documents as it is very difficult for a single classifier to learn many scripts. Generally a script identification module identifies text segments and accordingly the script-dependent classifier is selected. This paper presents a unified framework of language model and multiple preprocessing hypotheses for word recognition from bilingual document images. Prior to text recognition, preprocessing steps such as binarization and segmentation are required for ease of recognition. But these steps induce huge combinatorial error propagating to final recognition accuracy. In this paper we use multiple preprocessing routines as alternate hypotheses and use a language model to verify each alternative and choose the best recognized sequence. We test this architecture for word recognition of Kannada-English and Telugu-English bilingual documents and achieved better recognition rates than single methods using same classifier.

A Use Case Identification Framework and Use Case Canvas for identifying and exploring relevant Blockchain opportunities <=SEP=> Blockchain is a new, foundational technology with a vast amount of application possibilities. However, practitioners might not be aware of which use cases in their own business model might benefit from blockchain technology. To aid them in analyzing their business regarding blockchain suitability, this paper introduces a use case identification framework for blockchain and a use case canvas. In the development process they have been evaluated with internal and external reviews in order to offer the best possible guidance. In combination they offer an analysis framework to help practitioners decide which use cases they should take into account for blockchain technology, which characteristics these blockchain implementations would have, and which specific advantages they would offer.

Neural Adaptation Layers for Cross-domain Named Entity Recognition <=SEP=> Recent research efforts have shown that neural architectures can be effective in conventional information extraction tasks such as named entity recognition, yielding state-of-the-art results on standard newswire datasets. However, despite significant resources required for training such models, the performance of a model trained on one domain typically degrades dramatically when applied to a different domain, yet extracting entities from new emerging domains such as social media can be of significant interest. In this paper, we empirically investigate effective methods for conveniently adapting an existing, well-trained neural NER model for a new domain. Unlike existing approaches, we propose lightweight yet effective methods for performing domain adaptation for neural models. Specifically, we introduce adaptation layers on top of existing neural architectures, where no re-training using the source domain data is required. We conduct extensive empirical studies and show that our approach significantly outperforms stateof-the-art methods.

Boosting Optical Character Recognition: A Super-Resolution Approach <=SEP=> Text image super-resolution is a challenging yet open research problem in the computer vision community. In particular, low-resolution images hamper the performance of typical optical character recognition (OCR) systems. In this article, we summarize our entry to the ICDAR2015 Competition on Text Image Super-Resolution. Experiments are based on the provided ICDAR2015 TextSR dataset [3] and the released Tesseract-OCR 3.02 system [1]. We report that our winning entry of text image super-resolution framework has largely improved the OCR performance with low-resolution images used as input, reaching an OCR accuracy score of 77.19%, which is comparable with that of using the original high-resolution images (78.80%).

Preventing Cell Phone Intrusion and Theft using Biometrics <=SEP=> Most cell phones use a password, PIN, or visual pattern to secure the phone. With these types of security methods being used, there is much vulnerability. Another alternative is biometric authentication. Biometric security systems have been researched for many years. Some mobile manufacturers have implemented fingerprint scanners into their phones, such as the old Fujitsu F505i [7] and the current Motorola Atrix. Since theft of cell phones is becoming more common every day, there is a real need for a security system that not only protects the data, but the phone itself. It is proposed through this research that a biometric security system be the alternative to knowledge-based and password-based authentication. Furthermore, a device dongle must be implemented into this infrastructure to establish a reliable security system that deters theft for the majority; biometrics alone is not sufficient. Cell phones need power and must be charged almost daily. A biometric phone charger that acts as a dongle with a solid state relay, will be presented as a viable solution to theft in this research. Additionally, it will be shown through the results of this research that a system dependant only on biometrics is unreliable and unsecure. Essentially, a mobile security system that combines biometrics with dongle technology is believed to be the ideal solution for limiting the black market of stolen cell phones; without the biometric charger/dongle, the stolen cell phone would be rendered useless.

Cuff-less, non-invasive and continuous blood pressure monitoring using indirect methods <=SEP=> Cuff-based methods for measuring blood pressure (BP) have shown some limitations particularly when continuous measurement is required. Moreover, the inflation of the cuff is one of the main disturbing factors as expressed among patients. In this study, a promising approach based on changes in pulse transit time (PTT) for continuous, non-invasive and indirect measurement of BP is proposed to overcome the shortcomings of cuff-based methods. The PTT can be measured using plethysmography (PPG) waveform and the QRS peak of electrocardiogram (ECG) signal and indirectly interpreted as systolic BP. Time synchronization of the two sensors plays an important role in improving the accuracy of measurement. Therefore, it is aimed to employ a tablet-based system for collecting the wireless devices' data at a specific time. It is also our objective to include a triggering mechanism option using ambient sensors in order to start the process of data collection. Bluetooth/IEEE 802.15.4 wireless technologies will be used for real-time sensing and time synchronization. We have found that the proposed indirect measurement of BP can provide continuous information of the BP in a more convenient way from the patients' point of view. Moreover, the result of our indirect measurement of BP indicates that there are some short term fluctuations in the BP.

3D printed RF passive components by liquid metal filling <=SEP=> We present three-dimensional (3D) micro-scale electrical components and systems by means of 3D printing and a liquid-metal-filling technique. The 3D supporting polymer structures with hollow channels and cavities are fabricated from inkjet printing. Liquid metals made of silver particles suspension in this demonstration are then injected into the hollow paths and solidified to form metallic elements and interconnects with high electrical conductivity. In the proof-of-concept demonstrations, various radio-frequency (RF) passive components, including 3D-shaped inductors, capacitors and resistors are fabricated and characterized. High-Q inductors and capacitors up to 1 GHz have been demonstrated. This work establishes an innovative way to construct arbitrary 3D electrical systems with efficient and labor-saving processes.