title: Visual clustering in parallel coordinates

abstract: Parallel coordinates have been widely applied to visualize high-dimensional and multivariate data, discerning patterns within the data through visual clustering. However, the effectiveness of this technique on large data is reduced by edge clutter. In this paper, we present a novel framework to reduce edge clutter, consequently improving the effectiveness of visual clustering. We exploit curved edges and optimize the arrangement of these curved edges by minimizing their curvature and maximizing the parallelism of adjacent edges. The overall visual clustering is improved by adjusting the shape of the edges while keeping their relative order. The experiments on several representative datasets demonstrate the effectiveness of our approach.


title: Artificial neural network based autoregressive modeling technique with application in voice activity detection

abstract: A new method of estimating the coefficients of an autoregressive (AR) model using real-valued neural network (RVNN) technique is presented in this paper. The coefficients of the AR model are obtained from the synaptic weights and adaptive coefficients of the activation function of a two layer RVNN while the number of neurons in the hidden layer is estimated from over-constrained system of equations. The performance of the proposed technique has been evaluated using sinusoidal data and recorded speech so as to examine the spectral resolution and line splitting as well as its ability to detect voiced and unvoiced data section from a recorded speech. Results obtained show that the method can accurately resolve closely related frequencies without experiencing spectral line splitting as well as identify the voice and unvoiced segments in a recorded speech.


Gait Partitioning Methods: A Systematic Review


title: Approximating the Minimum Spanning Tree Weight in Sublinear Time

abstract: We present a probabilistic algorithm that, given a connected graph G (represented by adjacency lists) of average degree d, with edge weights in the set{1,...,w}, and given a parameter $0<\eps<1/2$, estimates in time $O( dw \varepsilon^{-2} \log{\frac{dw}\varepsilon})$ the weight of the minimum spanning tree (MST) of G with a relative error of at most $\eps$. Note that the running time does not depend on the number of vertices in G. We also prove a nearly matching lower bound of $\Omega( dw \varepsilon^{-2} )$ on the probe and time complexity of any approximation algorithm for MST weight. ::: The essential component of our algorithm is a procedure for estimating in time $O(d\eps^{-2}\log \frac{d}\varepsilon)$ the number of connected components of an unweighted graph to within an additive error of $\varepsilon n$. (This becomes $O(\eps^{-2}\log \frac{1}\varepsilon)$ for $d=O(1)$.) The time bound is shown to be tight up to within the $\log \frac{d}\varepsilon$ factor. Our connected-components algorithm picks $O(1/\varepsilon^2)$ vertices in the graph and then grows "local spanning trees" whose sizes are specified by a stochastic process. From the local information collected in this way, the algorithm is able to infer, with high confidence, an estimate of the number of connected components. We then show how estimates on the number of components in various subgraphs of G can be used to estimate the weight of its MST.


title: The effect of different types of corrective feedback on ESL student writing

abstract: Abstract Debate about the value of providing corrective feedback on L2 writing has been prominent in recent years as a result of Truscott's [Truscott, J. (1996). The case against grammar correction in L2 writing classes. Language Learning, 46, 327–369] claim that it is both ineffective and harmful and should therefore be abandoned. A growing body of empirical research is now investigating the agenda proposed by Ferris [Ferris, D.R. (1999). The case for grammar correction in L2 writing classes. A response to Truscott (1996). Journal of Second Language Writing, 8, 1–10, Ferris, D.R. (2004). The “Grammar Correction” debate in L2 writing: Where are we, and where do we go from here? (and what do we do in the meantime…?). Journal of Second Language Writing, 13, 49–62.]. Contributing to this research base, the study reported in this article investigated whether the type of feedback (direct, explicit written feedback and student–researcher 5 minute individual conferences; direct, explicit written feedback only; no corrective feedback) given to 53 adult migrant students on three types of error (prepositions, the past simple tense, and the definite article) resulted in improved accuracy in new pieces of writing over a 12 week period. The study found a significant effect for the combination of written and conference feedback on accuracy levels in the use of the past simple tense and the definite article in new pieces of writing but no overall effect on accuracy improvement for feedback types when the three error categories were considered as a single group. Significant variations in accuracy across the four pieces of writing support earlier SLA discoveries that L2 learners, in the process of acquiring new linguistic forms, may perform them with accuracy on one occasion but fail to do so on other similar occasions.


title: Pheromonal Influences on Sociosexual Behavior in Men

abstract: This study tested whether synthesized human male pheromones increase the sociosexual behavior of men. Thirty-eight heterosexual men, ages 26-42, completed a 2-week baseline period and 6-week placebo-controlled, double-blind trial testing a pheromone "designed to improve the romance in their lives." Each subject kept daily behavioral records for 6 sociosexual behaviors: petting/affection/kissing, formal dates, informal dates, sleeping next to a romantic partner, sexual intercourse, and self-stimulation to ejaculation (masturbation) and FAXed them each week. Significantly more pheromone than placebo users increased above baseline in sexual intercourse and sleeping with a romantic partner. There was a tendency for more pheromone than placebo users to increase above baseline in petting/affection/kissing, and informal dates, but not in self-stimulation to ejaculation or in formal dates . A significantly larger proportion of pheromone than placebo users increased in ≥2 and ≥3 of the 5 sociosexual behaviors involving a female partner. Thus, there was a significant increase in male sociosexual behaviors in which a woman's sexual interest and cooperation plays a role but not in male masturbation which involves only the man. These initial data need replication but suggest that human male pheromones affected the sexual attractiveness of men to women.


title: An approach to specification-based attack detection for in-vehicle networks

abstract: An upcoming trend for automotive manufacturers is to create seamless interaction between a vehicle and fleet management to provide remote diagnostics and firmware updates over the air. To allow this, the previously isolated in-vehicle network must be connected to an external network, and can thus be exposed to a whole new range of threats known as cyber attacks. In this paper we explore the applicability of a specification-based approach to detect cyber attacks within the in-vehicle network. We derive information to create security specifications for communication and ECU behavior from the CANopen draft standard 3.01 communication protocol and object directory sections. We also provide a set of example specifications, propose a suitable location for the attack detector, and evaluate the detection using a set of attack actions.


title: Compact triple band H-shaped slotted Circular Patch Antenna

abstract: Microstrip antennas with their advantages and with the availability of tools to design were remains as a centre of research attraction. The main research aspect of the Microstrip Patch is to enhance its bandwidth. To enhance the bandwidth of the Microstrip Patch antenna several techniques were proposed. The slot on the patch, which increases the fringing fields, remains simple and effective technique. This paper provides an insight in the design of Microstrip antenna and presents a design of triple band H shaped slot Circular Patch Antenna. The design utilizes the circular patch of radius 20mm and obtains triple band at the frequencies 2.4GHz, 4.5 GHz and 6.5 GHz. The return loss was measured as −25db, −24db, −15db and the gain obtained as 7db, 5db, 4.2db in the respective frequencies. HFSS the Finite Element Method based analysis software is used to design the Patch Antenna and to simulate the results.


title: Towards Scalable and Private Industrial Blockchains

abstract: The blockchain emerges as an innovative tool that has the potential to positively impact the way we design a number of online applications today. In many ways, the blockchain technology is, however, still not mature enough to cater for industrial standards. Namely, existing Byzantine tolerant permission-based blockchain deployments can only scale to a limited number of nodes. These systems typically require that all transactions (and their order of execution) are publicly available to all nodes in the system, which comes at odds with common data sharing practices in the industry, and prevents a centralized regulator from overseeing the full blockchain system. In this paper, we propose a novel blockchain architecture devised specifically to meet industrial standards. Our proposal leverages the notion of satellite chains that can privately run different consensus protocols in parallel - thereby considerably boosting the scalability premises of the system. Our solution also accounts for a hands-off regulator that oversees the entire network, enforces specific policies by means of smart contracts, etc. We implemented our solution and integrated it with Hyperledger Fabric v0.6.


title: Text to Image Synthesis Using Generative Adversarial Networks

abstract: Generating images from natural language is one of the primary applications of recent conditional generative models. Besides testing our ability to model conditional, highly dimensional distributions, text to image synthesis has many exciting and practical applications such as photo editing or computer-aided content creation. Recent progress has been made using Generative Adversarial Networks (GANs). This material starts with a gentle introduction to these topics and discusses the existent state of the art models. Moreover, I propose Wasserstein GAN-CLS, a new model for conditional image generation based on the Wasserstein distance which offers guarantees of stability. Then, I show how the novel loss function of Wasserstein GAN-CLS can be used in a Conditional Progressive Growing GAN. In combination with the proposed loss, the model boosts by 7.07% the best Inception Score (on the Caltech birds dataset) of the models which use only the sentence-level visual semantics. The only model which performs better than the Conditional Wasserstein Progressive Growing GAN is the recently proposed AttnGAN which uses word-level visual semantics as well.


title: Statistical Data Analysis in the Computer Age

abstract: Most of our familiar statistical methods, such as hypothesis testing, linear regression, analysis of variance, and maximum likelihood estimation, were designed to be implemented on mechanical calculators. Modern electronic computation has encouraged a host of new statistical methods that require fewer distributional assumptions than their predecessors and can be applied to more complicated statistical estimators. These methods allow the scientist to explore and describe data and draw valid statistical inferences without the usual concerns for mathematical tractability. This is possible because traditional methods of mathematical analysis are replaced by specially constructed computer algorithms. Mathematics has not disappeared from statistical theory. It is the main method for deciding which algorithms are correct and efficient tools for automating statistical inference.


title: Circularly polarized equilateral triangle patch antenna for UHF RFID reader applications

abstract: A simple circularly polarized (CP) equilateral triangular patch antenna for UHF (902-928 MHz) radio identification (RFID) reader applications is proposed. In this design, good CP radiation is achieved by loading a near semi-circular notch is into the patch. Furthermore, the L-shaped probe-feed method is used for achieving good impedance matching that results in broad impedance and CP bandwidth. The experimental results show that the 3-dB AR (axial ratio) bandwidth is approximately 3% (902-929 MHz), while the 10-dB impedance bandwidth is approximately 25.4% (854-1102 MHz).


title: Surface shape from the deformation of apparent contours

abstract: The spatiotemporal analysis of deforming silhouettes (apparent contours) is here extended using the mathematics of perspective projections and tools from differential geometry. Analysis of the image motion of a silhouette or apparent contour enables computation of local surface curvature along the corresponding contour generator on the surface, assuming viewer motion is known. To perform the analysis, a spatiotemporal parameterization of image-curve motion is needed, but is underconstrained (a manifestation of the well-known aperture problem). It is shown that an epipolar parameterization is most naturally matched to the recovery of surface curvature.One immediate facility afforded by the analysis is that surface patches can be reconstructed in the vicinity of contour generators. Once surface curvature is known, it is possible to discriminate extremal contours from other fixed curves in space. Furthermore, the known robustness of parallax as a cue to depth extends to the case of surface curvature. Its derivative—rate of parallax—is shown theoretically to be a curvature cue that is robust to uncertainties in the known viewer motion. This robustness has been confirmed in experiments.Finally, the power of the new analysis for robotics applications is demonstrated. Illustrations are given of an Adept robot, equipped with a CCD camera, circumnavigating curved obstacles. When further equipped with a suction gripper the robot manipulator can pick up an object by its curved surface, under visual guidance.


title: A 32Gb/s wireline receiver with a low-frequency equalizer, CTLE and 2-tap DFE in 28nm CMOS

abstract: Standards such as OIF CEI-25G, CEI-28G and 32G-FC require transceivers operating at high data rates over imperfect channels. Equalizers are used to cancel the inter-symbol interference (ISI) caused by frequency-dependent channel losses such as skin effect and dielectric loss. The primary objective of an equalizer is to compensate for high-frequency loss, which often exceeds 30dB at fs/2. However, due to the skin effect in a PCB stripline, which starts at 10MHz or lower, we also need to compensate for a small amount of loss at low frequency (e.g., 500MHz). Figure 2.1.1 shows simulated responses of a backplane channel (42.6dB loss at fs/2 for 32Gb/s) with conventional high-frequency equalizers only (4-tap feed-forward equalizer (FFE), 1st-order continuous-time linear equalizer (CTLE) with a dominant pole at fs/4, and 1-tap DFE) and with additional low-frequency equalization. Conventional equalizers cannot compensate for the small amount of low-frequency loss because the slope of the low-frequency loss is too gentle (<;3dB/dec). The FFE and CTLE do not have a pole in the low frequency region and hence have only a steep slope of 20dB/dec above their zero. The DFE cancels only short-term ISI. Effects of such low-frequency loss have often been overlooked or neglected, because 1) the loss is small (2 to 3dB), 2) when plotted using the linear frequency axis which is commonly used to show frequency dependence of skin effect and dielectric loss, the low-frequency loss is degenerated at DC and hardly visible (Fig. 2.1.1a), and 3) the long ISI tail of the channel pulse response seems well cancelled at first glance by conventional equalizers only (Fig. 2.1.1b). However, the uncompensated low-frequency loss causes non-negligible long-term residual ISI, because the integral of the residual ISI magnitude keeps going up for several hundred UI. As shown by the eye diagrams in the inset of Fig. 2.1.1(b), the residual long-term ISI results in 0.42UI data-dependent Jitter (DDJ) that is difficult to reduce further by enhancing FFE/CTLE/DFE, but can be reduced to 0.21UI by adding a low-frequency equalizer (LFEQ). Savoj et al. also recently reported long-tail cancellation [2].


title: Pyroelectric IR sensor arrays for fall detection in the older population

abstract: Uncooled pyroelectric sensor arrays have been studied over many years for their uses in thermal imaging applications. These arrays will only detect changes in IR flux and so systems based upon them are very good at detecting movements of people in the scene without sensing the background, if they are used in staring mode. Relatively-low element count arrays (16x 16) can be used for a variety of people sensing applications, including people counting (for safety applications), queue monitoring etc. With appropriate signal processing such systems can be also be used for the detection of particular events such as a person falling over. There is a considerable need for automatic fall detection amongst older people, but there are important limitations to some of the current and emerging technologies available for this. Simple sensors, such as I or 2 element pyroelectric infra-red sensors provide crude data that is difficult to interpret; the use of devices worn on the person, such as wrist communicator and motion detectors have potential, but are reliant on the person being able and willing to wear the device; video cameras may be seen as intrusive and require considerable human resources to monitor activity while machine-interpretation of camera images is complex and may be difficult in this application area. The use of a pyroelectric thermal array sensor was seen to have a number of potential benefits. The sensor is wall-mounted and does not require the user to wear a device. It enables detailed analysis of a subject's motion to be achieved locally, within the detector, using only a modest processor. This is possible due to the relative ease with which data from the sensor can be interpreted relative to the data generated by alternative sensors such as video devices. In addition to the cost-effectiveness of this solution, it was felt that the lack of detail in the low-level data, together with the elimination of the need to transmit data outside the detector, would help to avert feelings intrusiveness on the part of the end-user. The main benefits of this type of technology would be for older people who spend time alone in unsupervised environments. This would include people living alone in ordinary housing or in sheltered accommodation (apartment complexes for older people with local warden) and non-communal areas in residential/nursing home environments (e.g. bedrooms and ensuite bathrooms and toilets). This paper will review the development of the array, the pyroelectric ceramic material upon which it is based and the system capabilities. It will present results from the Framework 5 SIMBAD project, which used the system to monitor the movements of elderly people over a considerable period of time.


title: Video Scene Parsing with Predictive Feature Learning

abstract: In this work, we address the challenging video scene parsing problem by developing effective representation learning methods given limited parsing annotations. In particular, we contribute two novel methods that constitute a unified parsing framework. (1) \textbf{Predictive feature learning}} from nearly unlimited unlabeled video data. Different from existing methods learning features from single frame parsing, we learn spatiotemporal discriminative features by enforcing a parsing network to predict future frames and their parsing maps (if available) given only historical frames. In this way, the network can effectively learn to capture video dynamics and temporal context, which are critical clues for video scene parsing, without requiring extra manual annotations. (2) \textbf{Prediction steering parsing}} architecture that effectively adapts the learned spatiotemporal features to scene parsing tasks and provides strong guidance for any off-the-shelf parsing model to achieve better video scene parsing performance. Extensive experiments over two challenging datasets, Cityscapes and Camvid, have demonstrated the effectiveness of our methods by showing significant improvement over well-established baselines.


title: 50 Years of CORDIC: Algorithms, Architectures, and Applications

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


title: Study of the antagonistic stiffness of parallel manipulators with actuation redundancy

abstract: In this paper parallel manipulators, consisting of a basic antropomorph kinematic chain and parallel chains with redundant in number linear actuators are investigated. Antagonistic stiffness, as a result of the actuation redundancy is also studied. A kinematic model of parallel manipulators and a stiffness model are created. Conditions for specification of the antagonistic stiffness are considered and the possibilities for generation of a desired stiffness matrix are investigated. Approaches for specification of a desired compliance along a given direction in the operation space and for specification of the biggest compliance in the operation space are proposed. A scheme for stiffness control of manipulators with actuation redundancy is developed on the basis of the above cited approaches. Computer experiments are performed and a graphic interpretation of the results is presented.


title: Generating Parallel Execution Plans with a Partial-order Planner

abstract: Many real-world planning problems require generating plans that maximize the parallelism inherent in a problem. There are a number of partial-order planners that generate such plans; however, in most of these planners it is unclear under what conditions the resulting plans will be correct and whether the planner can even find a plan if one exists. This paper identifies the underlying assumptions about when a partial plan can be executed in parallel, defines the classes of parallel plans that can be generated by different partial-order planners, and describes the changes required to turn UCPOP into a parallel execution planner. In addition, we describe how this planner can be applied to the problem of query access planning, where parallel execution produces substantial reductions in overall execution time.


title: Python robotics: an environment for exploring robotics beyond LEGOs

abstract: This paper describes Pyro, a robotics programming environment designed to allow inexperienced undergraduates to explore topics in advanced robotics. Pyro, which stands for Python Robotics, runs on a number of advanced robotics platforms. In addition, programs in Pyro can abstract away low-level details such that individual programs can work unchanged across very different robotics hardware. Results of using Pyro in an undergraduate course are discussed.


title: Power Supply Rejection for RF Amplifiers: Theory and Measurements

abstract: Supply noise is a significant problem in RF systems where it can mix with RF signals, degrading signal/noise ratios and potentially causing violation of spectral masks. This paper presents an analysis of the supply rejection properties of RF amplifiers. We extend a conventional Volterra-series formulation to treat multiport systems and use it to describe the mixing products between power supply noise and the RF carrier. It is shown that a multiport Volterra formulation can be used to treat weak nonlinearities in the system and that the nonsymmetric cross terms accurately predict low-order mixing phenomenon. We demonstrate the validity of our hand analysis through the design and fabrication of a power amplifier in 180-nm CMOS, operating between 900 MHz-2.4 GHz with a maximum output power of 15 dBm. Spectral regrowth of single-tone and EDGE modulation waveforms is shown to match within 1-3 dB across frequency and input signal power. Importantly, this analysis provides insight into the circuit-level mechanisms for susceptibility to power supply noise and can help designers improve the power supply rejection ratio robustness of system-on-chip wireless blocks and transmitter architectures.


title: Second-Trimester Screening for Trisomy-21 Using Prefrontal Space Ratio

abstract: OBJECTIVE ::: To investigate the potential value of prefrontal space ratio (PFSR) in second-trimester screening for trisomy-21. ::: ::: ::: METHODS ::: A retrospective study utilizing stored midsagittal two-dimensional images of fetal profiles in 240 euploid and 45 trisomy-21 pregnancies at 16(+0)-23(+6) weeks' gestation. The vertical distance between the leading edge of the skull and that of the skin (D1) and the distance between the skull and the mandibulo-maxillary line (D2) were measured and the D1:D2 ratio (PFSR) was calculated. In euploid pregnancies, regression analysis was used to determine the association between D1, D2 and PFSR with gestational age (GA). D1 and D2 were expressed as delta (Δ) values with gestational age. ΔD1, ΔD2 and PFSR in cases and controls were compared. ::: ::: ::: RESULTS ::: In trisomy-21, compared to controls, ΔD1 was increased (1.417 vs. 0.000 mm, p < 0.0001), ΔD2 was decreased (-0.842 vs. 0.000 mm, p = 0.003) and PFSR was increased (0.753 vs. 0.463, p < 0.0001). At a false-positive rate of 5%, the detection rates in screening by ΔD1, ΔD2 and PSFR were 80.0% (95% CI 65.4-90.4), 46.7% (95% CI 31.7-62.1) and 100.0% (95% CI 92.1-100.0), respectively. ::: ::: ::: CONCLUSION ::: The PFSR is an effective marker in second-trimester screening for trisomy-21.


title: Performance of a new annealing schedule

abstract: A new simulated annealing schedule has been developed; its application to the standard cell placement and the traveling salesman problems results in a two to twenty-four times speedup over annealing schedules currently available in the literature. Since it uses only statistical quantities, the annealing schedule is applicable to general combinatorial optimization problems.


title: Recurrent neural network language model adaptation for multi-genre broadcast speech recognition

abstract: Copyright © 2015 ISCA. Recurrent neural network language models (RNNLMs) have recently become increasingly popular for many applications including speech recognition. In previous research RNNLMs have normally been trained on well-matched in-domain data. The adaptation of RNNLMs remains an open research area to be explored. In this paper, genre and topic based RNNLMadaptation techniques are investigated for a multi-genre broadcast transcription task. A number of techniques including Probabilistic Latent Semantic Analysis, Latent Dirichlet Allocation and Hierarchical Dirichlet Processes are used to extract show level topic information. These were then used as additional input to the RNNLM during training, which can facilitate unsupervised test time adaptation. Experiments using a state-of-theart LVCSR system trained on 1000 hours of speech and more than 1 billion words of text showed adaptation could yield perplexity reductions of 8% relatively over the baseline RNNLM and small but consistent word error rate reductions.


title: Experimental Measures of News Personalization in Google News

abstract: Search engines and social media keep trace of profile- and behavioral-based distinct signals of their users, to provide them personalized and recommended content. Here, we focus on the level of web search personalization, to estimate the risk of trapping the user into so called Filter Bubbles. Our experimentation has been carried out on news, specifically investigating the Google News platform. Our results are in line with existing literature and call for further analyses on which kind of users are the target of specific recommendations by Google.


On the photooxidation of a high potential form of cytochromeb-559


title: Belief-State Monte Carlo Tree Search for Phantom Go

abstract: Phantom Go is a derivative of Go with imperfect information. It is challenging in AI field due to its great uncertainty of the hidden information and high game complexity inherited from Go. To deal with this imperfect information game with large game tree complexity, a general search framework named belief-state Monte Carlo tree search (BS-MCTS) is put forward in this paper. BS-MCTS incorporates belief-states into Monte Carlo Tree Search, where belief-state is a notation derived from philosophy to represent the probability that speculation is in accordance with reality. In BS-MCTS, a belief-state tree, in which each node is a belief-state, is constructed and search proceeds in accordance with beliefs. Then, Opponent Guessing and Opponent Predicting are proposed to illuminate the learning mechanism of beliefs with heuristic information. The beliefs are learned by heuristic information during search by specific methods, and we propose Opponent Guessing and Opponent Predicting to illuminate the learning mechanism. Besides, some possible improvements of the framework are investigated, such as incremental updating and all moves as first (AMAF) heuristic. Technical details are demonstrated about applying BS-MCTS to Phantom Go, especially on inference strategy. We examine the playing strength of the BS-MCTS and AMAF-BS-MCTS in Phantom Go by varying search parameters, also testify the proposed improvements.


A Systematic Review on Mobile Health Care


title: Symbiotic 4: Beyond Reachability (Competition Contribution)

abstract: The fourth version of Symbiotic brings a brand new instrumentation part, which can now instrument the analyzed program with code pieces checking various specification properties. As a consequence, Symbiotic 4 participates for the first time also in categories focused on memory safety. Further, we have ported both Symbiotic and Klee to LLVM 3.8 and added new features to the slicer which is now modular and easily extensible.


title: ARK: Augmented Reality for Kilobots

abstract: Working with large swarms of robots has challenges in calibration, sensing, tracking, and control due to the associated scalability and time requirements. Kilobots solve this through their ease of maintenance and programming, and are widely used in several research laboratories worldwide where their low cost enables large-scale swarms studies. However, the small, inexpensive nature of the Kilobots limits their range of capabilities as they are only equipped with a single sensor. In some studies, this limitation can be a source of motivation and inspiration, while in others it is an impediment. As such, we designed, implemented, and tested a novel system to communicate personalized location-and-state-based information to each robot, and receive information on each robots' state. In this way, the Kilobots can sense additional information from a virtual environment in real time; for example, a value on a gradient, a direction toward a reference point or a pheromone trail. The augmented reality for Kilobots (ARK) system implements this in flexible base control software which allows users to define varying virtual environments within a single experiment using integrated overhead tracking and control. We showcase the different functionalities of the system through three demos involving hundreds of Kilobots. The ARK provides Kilobots with additional and unique capabilities through an open-source tool which can be implemented with inexpensive, off-the-shelf hardware.


title: Age-Invariant Face Recognition

abstract: One of the challenges in automatic face recognition is to achieve temporal invariance. In other words, the goal is to come up with a representation and matching scheme that is robust to changes due to facial aging. Facial aging is a complex process that affects both the 3D shape of the face and its texture (e.g., wrinkles). These shape and texture changes degrade the performance of automatic face recognition systems. However, facial aging has not received substantial attention compared to other facial variations due to pose, lighting, and expression. We propose a 3D aging modeling technique and show how it can be used to compensate for the age variations to improve the face recognition performance. The aging modeling technique adapts view-invariant 3D face models to the given 2D face aging database. The proposed approach is evaluated on three different databases (i.g., FG-NET, MORPH, and BROWNS) using FaceVACS, a state-of-the-art commercial face recognition engine.


title: EU Climate Change Policy 2013-2020: Thoughts on Property Rights and Market Choices. ESRI WP292, April 2009

abstract: Under 2013 to 2020 European Union proposals for CO2 emission reduction, a Member State can transfer to another Member State ‘part’ of their allowed emission allocation in the non-Emission Trading Sector (“ETS”). The paper addresses three questions in relation to these Transfer Emission Units or TEUs. First, what mechanism should be used to facilitate the exchange of TEUs? The preferred mechanism is a uniform price auction, preferably EU-wide. Second, what ‘part’ of the non-ETS emission limit of a Member State should be classed as TEUs – 10%, 20% or no limit? The proportion of the non-ETS emission limit that should be traded should be maximised. Third, who should realise the value of TEUs – the State, existing polluters? The value of TEUs should accrue to the State.


title: An image steganography using pixel characteristics

abstract: This paper presents a steganographic algorithm in digital images to embed a hidden message into cover images. This method is able to provide a high quality stego image in spite of the high capacity of the concealed information. In our method, the number of insertion bits into each pixel is different according to each pixel’s characteristics. That is, the number of insertion bit is dependent on whether the pixel is an edge area or smooth area. We experimented on various images to demonstrate the effectiveness of the proposed method.


title: A Low-Noise Output Capacitorless Low-Dropout Regulator With a Switched-RC Bandgap Reference

abstract: Low-noise linear regulators are critical for power supply regulation of noise-sensitive circuits, such as ADCs, phaselocked loops, and other mixed-signal/RF system-on-a-chip designs. A low-noise low-dropout (LN-LDO) regulator using switched-RC bandgap reference and a multiloop, unconditionally stable error amplifier for output capacitorless operation is presented in this paper. A sample-and-hold switched-RC filter is developed to reduce the noise of the bandgap reference and drain-side modulated current-mode chopping technique is proposed to reduce the flicker (1/f) noise of the error amplifier. A switched capacitor notch filter is utilized to filter out the residual chopping ripple of the error amplifier. Thermal noise of the current reference circuit which is significant at such low noise levels is also reduced by using a low-area penalty passive RC filter. These techniques reduce the total integrated output noise of the LDO in the 10 Hz to 100 kHz band from 95.3 μV ::: RMS ::: down to 14.8 μV ::: RMS ::: . The LDO delivers a maximum load current of 100 mA with a dropout voltage of 230 mV and a quiescent current consumption of 40 μA. It achieves a power supply rejection of 50 dB at 10 kHz for a programmable output voltage range of 1-3.3 V. Fabricated in a 0.25 μm CMOS process, the LDO core occupies an area of 0.18 mm ::: 2 ::: .


title: FACTORS INFLUENCING FUTURE EMPLOYEES´ DECISION-MAKING TO PARTICIPATE IN A BYOD PROGRAM: DOES RISK MATTER?

abstract: As people use mobile devices (smartphones, tablets, etc.) more and more in daily life, their desire grows to use the same devices at work. In response to this demand, many firms are considering to offer BYOD programs allowing their employees to bring their own devices to work and use them for business purposes. This study analyses how employees´ perceive the benefits and risk associated with BYOD. Additionally, it is investigated whether innovativeness traits can serve as predictors of BYOD program participation. For this account, a theoretical model building on net valence approaches from decision making and perceived risk theory is proposed and tested. German students with relevant work experience and close to finishing their studies (i.e. future employees) were surveyed (n = 71). \ The study demonstrates that benefits matter more than risks, at least for the suspected drivers of IT consumerization. The results show that the intention to enrol in a BYOD program is a function of perceived risk, perceived benefits and level of personal innovativeness. Among these factors, perceived benefit most strongly affects behavioural intention, whereas only safety risks proved to inhibit an individual´s intention to use privately-owned devices at work. Knowledge acquired from this study is particularly beneficial to IT executives to guide their decision to set up or adjust BYOD initiatives.


title: Exploiting spatial sparsity for estimating channels of hybrid MIMO systems in millimeter wave communications

abstract: Hybrid multiple input multiple output (MIMO) systems consist of an analog beamformer with large antenna arrays followed by a digital MIMO processor. Channel estimation for hybrid MIMO systems in millimeter wave (mm-wave) communications is challenging because of the large antenna array and the low signal-to-noise ratio (SNR) before beamforming. In this paper, we propose an open-loop channel estimator for mm-wave hybrid MIMO systems exploiting the sparse nature of mm-wave channels. A sparse signal recovery problem is formulated for channel estimation and solved by the orthogonal matching pursuit (OMP) based methods. A modification of the OMP algorithm, called the multi-grid (MG) OMP, is proposed. It is shown that the MG-OMP can significantly reduce the computational load of the OMP method. A process for designing the training beams is also developed. Specifically, given the analog training beams the baseband processor for beam training is designed. Simulation results demonstrate the advantage of the OMP based methods over the conventional least squares (LS) method and the efficiency of the MG-OMP over the original OMP.


title: Accelerating Minibatch Stochastic Gradient Descent using Stratified Sampling

abstract: Stochastic Gradient Descent (SGD) is a popular optimization method which has been applied to many important machine learning tasks such as Support Vector Machines and Deep Neural Networks. In order to parallelize SGD, minibatch training is often employed. The standard approach is to uniformly sample a minibatch at each step, which often leads to high variance. In this paper we propose a stratified sampling strategy, which divides the whole dataset into clusters with low within-cluster variance; we then take examples from these clusters using a stratified sampling technique. It is shown that the convergence rate can be significantly improved by the algorithm. Encouraging experimental results confirm the effectiveness of the proposed method.


title: Non-iterative, fast SE(3) path smoothing

abstract: In this paper, we present a fast, non-iterative approach to smooth a noisy input on the Special Euclidean Group, SE(3) manifold. The translational part can be smoothed by a simple Gaussian convolution. We then proposed a novel approach to rotation smoothing. Unlike existing rotation smoothing methods using either iterative optimization methods or stochastic filtering methods, our method allows direct computation of the smoothing result and allows parallelization of the computation. Furthermore, we have done a comparative study on Jia and Evans's method published in 2014 [1], and shown that our method can better smooth an input rotation sequence, with shorter computational time. The smoothed camera path is then used for video stabilisation, which shows fluid and smooth camera motion.


title: Human-Inspired Neurorobotic System for Classifying Surface Textures by Touch

abstract: Giving robots the ability to classify surface textures requires appropriate sensors and algorithms. Inspired by the biology of human tactile perception, we implement a neurorobotic texture classifier with a recurrent spiking neural network, using a novel semisupervised approach for classifying dynamic stimuli. Input to the network is supplied by accelerometers mounted on a robotic arm. The sensor data are encoded by a heterogeneous population of neurons, modeled to match the spiking activity of mechanoreceptor cells. This activity is convolved by a hidden layer using bandpass filters to extract nonlinear frequency information from the spike trains. The resulting high-dimensional feature representation is then continuously classified using a neurally implemented support vector machine. We demonstrate that our system classifies 18 metal surface textures scanned in two opposite directions at a constant velocity. We also demonstrate that our approach significantly improves upon a baseline model that does not use the described feature extraction. This method can be performed in real-time using neuromorphic hardware, and can be extended to other applications that process dynamic stimuli online.


title: Theoretical and field comparison of two types of soil heat fluxmeter

abstract: Abstract Accurate measurements of soil heat flux are important for energy balance studies on bare soils. Measurements are usually made with passive transducers that transform the vertical soil heat flux into an e.m.f.. Measurement errors or bias result from differences between the calibration coefficients provided by the manufacturer and those determined in the field. These differences result from bad thermal contact between the soil and the fluxmeter and/or changes in soil thermal conductivity. New printed circuit heat fluxmeters are very thin (0.2 mm) and they provide a better thermal contact with the soil because they have an external copper layer instead of an insulating resin. We carried out a theoretical analysis to identify properties of the transducers (geometrical, thermal or electrical) most important for reducing the calibration variability. The transducer thickness was found to reduce the calibration variability due to large soil thermal conductivity variations. Transducer thermal conductivity is also important when the soil thermal conductivity is accurately known. The printed circuit transducers and classical soil heat flux transducers (thermopiles) where then compared in three different soils, a sandy loam, a loamy and a chalky soil under changing climatic conditions in spring. The outputs of both transducers were compared to reference soil heat flux measurements obtained by the heat storage method. The thermopile transducers were more sensitive (4.1 μV W −1 m 2 ) than the printed circuit transducers (1.6 μV W −1 m 2 ). Both transducers gave similar responses when the soil thermal conductivity varied over a narrow range. The total variation of the calibration coefficients of the printed circuit transducer was smaller for all three soils and for days where the soil thermal conductivity varied widely. We conclude that the printed circuit transducers should be used when field calibration is not possible, or when the calibration is not stable following large soil thermal conductivity variations. The experiment also showed that the theory does not completely describe the interaction between calibration coefficients and soil properties. We have therefore developed a new interpretation of the experimental data that takes into account the thermal contact between the soil and the transducer.


title: On the unification of line processes, outlier rejection, and robust statistics with applications in early vision

abstract: The modeling of spatial discontinuities for problems such as surface recovery, segmentation, image reconstruction, and optical flow has been intensely studied in computer vision. While “line-process” models of discontinuities have received a great deal of attention, there has been recent interest in the use of robust statistical techniques to account for discontinuities. This paper unifies the two approaches. To achieve this we generalize the notion of a “line process” to that of an analog “outlier process” and show how a problem formulated in terms of outlier processes can be viewed in terms of robust statistics. We also characterize a class of robust statistical problems for which an equivalent outlier-process formulation exists and give a straightforward method for converting a robust estimation problem into an outlier-process formulation. We show how prior assumptions about the spatial structure of outliers can be expressed as constraints on the recovered analog outlier processes and how traditional continuation methods can be extended to the explicit outlier-process formulation. These results indicate that the outlier-process approach provides a general framework which subsumes the traditional line-process approaches as well as a wide class of robust estimation problems. Examples in surface reconstruction, image segmentation, and optical flow are presented to illustrate the use of outlier processes and to show how the relationship between outlier processes and robust statistics can be exploited. An appendix provides a catalog of common robust error norms and their equivalent outlier-process formulations.


title: Fraud detections for online businesses: a perspective from blockchain technology

abstract: Abstract Background The reputation system has been designed as an effective mechanism to reduce risks associated with online shopping for customers. However, it is vulnerable to rating fraud. Some raters may inject unfairly high or low ratings to the system so as to promote their own products or demote their competitors. Method This study explores the rating fraud by differentiating the subjective fraud from objective fraud. Then it discusses the effectiveness of blockchain technology in objective fraud and its limitation in subjective fraud, especially the rating fraud. Lastly, it systematically analyzes the robustness of blockchain-based reputation systems in each type of rating fraud. Results The detection of fraudulent raters is not easy since they can behave strategically to camouflage themselves. We explore the potential strengths and limitations of blockchain-based reputation systems under two attack goals: ballot-stuffing and bad-mouthing, and various attack models including constant attack, camouflage attack, whitewashing attack and sybil attack. Blockchain-based reputation systems are more robust against bad-mouthing than ballot-stuffing fraud. Conclusions Blockchain technology provides new opportunities for redesigning the reputation system. Blockchain systems are very effective in preventing objective information fraud, such as loan application fraud, where fraudulent information is fact-based. However, their effectiveness is limited in subjective information fraud, such as rating fraud, where the ground-truth is not easily validated. Blockchain systems are effective in preventing bad mouthing and whitewashing attack, but they are limited in detecting ballot-stuffing under sybil attack, constant attacks and camouflage attack.


Pricing Barrier Options using Monte Carlo Methods


title: A literature survey on smart cities

abstract: Rapid urbanization creates new challenges and issues, and the smart city concept offers opportunities to rise to these challenges, solve urban problems and provide citizens with a better living environment. This paper presents an exhaustive literature survey of smart cities. First, it introduces the origin and main issues facing the smart city concept, and then presents the fundamentals of a smart city by analyzing its definition and application domains. Second, a data-centric view of smart city architectures and key enabling technologies is provided. Finally, a survey of recent smart city research is presented. This paper provides a reference to researchers who intend to contribute to smart city research and implementation.创新点世界范围内的快速城镇化给城市发展带来了很多新的问题和挑战, 智慧城市概念的出现, 为解决当前城市难题、提供更好的城市环境提供了有效的解决途径。论文介绍了智慧城市的起源, 总结了智慧城市领域的三个主要问题, 通过详细的综述性文献研究展开对这些问题的探讨。论文首先对智慧城市的定义和应用领域进行了归纳和分析, 然后研究了智慧城市的体系架构, 提出了智慧城市以数据为中心、多领域融合的相关特征, 并定义了以数据活化技术为核心的层次化体系架构, 并介绍了其中的关键技术, 最后选取了城市交通、城市群体行为、城市规划三个具有代表性的应用领域介绍了城市数据分析与处理的最新研究进展和存在问题。


title: Dual-Band Stacked Annular Slot/Patch Antenna for Omnidirectional Radiation

abstract: This letter presents the design of a new omnidirectional antenna, which is composed of annular slot and annular patch stacked together for dual-band operation at 2.5 and 3.5 GHz. The influence of the antenna parameters on the dual-band operation is given with simulations. A prototype of the proposed antenna was manufactured with FR4 substrates for the purpose of demonstration. The measured reflection coefficient exhibits dual-band operation at 2.32 GHz with fractional bandwidth of 19.3%, and at 3.59 GHz with fractional bandwidth of 18.6%. The stable measured omnidirectional radiation patterns can be obtained at both frequencies. The agreement between the measured and simulated patterns can be observed from the experimental results.


title: A Local Clustering Algorithm for Massive Graphs and its Application to Nearly-Linear Time Graph Partitioning

abstract: We study the design of local algorithms for massive graphs. A local algorithm is one that finds a solution containing or near a given vertex without looking at the whole graph. We present a local clustering algorithm. Our algorithm finds a good cluster--a subset of vertices whose internal connections are significantly richer than its external connections--near a given vertex. The running time of our algorithm, when it finds a non-empty local cluster, is nearly linear in the size of the cluster it outputs. Our clustering algorithm could be a useful primitive for handling massive graphs, such as social networks and web-graphs. As an application of this clustering algorithm, we present a partitioning algorithm that finds an approximate sparsest cut with nearly optimal balance. Our algorithm takes time nearly linear in the number edges of the graph. Using the partitioning algorithm of this paper, we have designed a nearly-linear time algorithm for constructing spectral sparsifiers of graphs, which we in turn use in a nearly-linear time algorithm for solving linear systems in symmetric, diagonally-dominant matrices. The linear system solver also leads to a nearly linear-time algorithm for approximating the second-smallest eigenvalue and corresponding eigenvector of the Laplacian matrix of a graph. These other results are presented in two companion papers.


title: Automatic Ontology Creation from Text for National Intelligence Priorities Framework (NIPF)

abstract: Analysts are constantly overwhelmed with large amounts of unstructured data. This holds especially true for intelligence analysts with the task of extracting useful information from large data sources. To alleviate this problem, domainspecific and general-purpose ontologies/knowledge-bases have been proposed to help automate methods for organizing data and provide access to useful information. However, problems in ontology creation and maintenance have resulted in expensive procedures for expanding/maintaining the ontology library available to support the growing and evolving needs of the Intelligence Community (IC). In this paper, we will present a semi-automatic development of an ontology library for the National Intelligence Priorities Framework (NIPF) topics. We use Jaguar-KAT, a state-of-the-art tool for knowledge acquisition and domain understanding, with minimized manual intervention to create NIPF ontologies loaded with rich semantic content. We also present evaluation results for the NIPF ontologies created using our methodology.


title: Increasing Delta-9-Tetrahydrocannabinol (?-9-THC) Content in Herbal Cannabis Over Time: Systematic Review and Meta-Analysis

abstract: AIM ::: The objective of this meta-analysis is to assess the data regarding changes in herbal cannabis potency over time (from 1970 to 2009). ::: ::: ::: METHODS ::: Systematic searches of 17 electronic scientific databases identified studies on this topic, within which 21 case series studies satisfied our inclusion criteria of reporting the mean tetrahydrocannabinol (THC) value per number of samples per year. No language, publication date, publication type or status restrictions were imposed. The study selection and data extraction processes were performed independently but uniformly by two authors, included screening, determination of eligibility and inclusion of the eligible studies in the systematic review, and a meta-analysis of the results on THC content in herbal cannabis samples. We considered papers and not monographic scientific publications, rejecting all studies that were not focused on the subject of this review. ::: ::: ::: RESULTS ::: Meta-analysis by year was performed on 21 studies containing 75 total mean THC observations from 1979 to 2009 using the random effects model. The results revealed much variability between studies. Further, there was a significant correlation between year and mean THC in herbal cannabis. The combined data indicated the correlation between year and mean THC in herbal cannabis, revealing a temporal trend of increasing potency (5% above the mean THC value in the Poisson regression analysis). ::: ::: ::: CONCLUSIONS ::: The results of the analysis suggest that there has been a recent and consistent increase in cannabis potency worldwide.


title: A novel approach to design an antenna aperture tuning circuit

abstract: In this work, a new approach to design an antenna aperture tuning circuit for mobile phone antennas is proposed. Currently in the industry, the design of such a tuning circuit is done by using antenna S-parameter measurements. This method gives limited insight into the antenna performance parameters, specifically radiation power, which is a key performance parameter for an antenna. This paper presents a new approach to design an antenna tuning circuit, which gives additional in-depth knowledge on the performance improvement of the tuned antenna system. The proposed method uses non-linear 3-Dimensional Electro-Magnetic simulations of a mobile phone antenna structure which is co-simulated with antenna tuning circuit elements to realise an antenna tuning system. The effect of antenna tuning elements on the antenna parameters can be visualized in addition to simulating the antenna radiation patterns and the Total Radiated Power (TRP). Measurement and simulation results, of a fabricated prototype antenna, are presented and a close relation is found.


title: Slumulation: An Agent-Based Modeling Approach to Slum Formations

abstract: Slums provide shelter for nearly one third of the world's urban population, most of them in the developing world. Slumulation represents an agent-based model which explores questions such as i) how slums come into existence, expand or disappear ii) where and when they emerge in a city and iii) which processes may improve housing conditions for urban poor. The model has three types of agents that influence emergence or sustenance of slums in a city: households, developers and politicians, each of them playing distinct roles. We model a multi-scale spatial environment in a stylized form that has housing units at the micro-scale and electoral wards consisting of multiple housing units at the macro-scale. Slums emerge as a result of human-environment interaction processes and inter-scale feedbacks within our model.


title: TimeLineCurator: Interactive Authoring of Visual Timelines from Unstructured Text

abstract: We present TimeLineCurator, a browser-based authoring tool that automatically extracts event data from temporal references in unstructured text documents using natural language processing and encodes them along a visual timeline. Our goal is to facilitate the timeline creation process for journalists and others who tell temporal stories online. Current solutions involve manually extracting and formatting event data from source documents, a process that tends to be tedious and error prone. With TimeLineCurator, a prospective timeline author can quickly identify the extent of time encompassed by a document, as well as the distribution of events occurring along this timeline. Authors can speculatively browse possible documents to quickly determine whether they are appropriate sources of timeline material. TimeLineCurator provides controls for curating and editing events on a timeline, the ability to combine timelines from multiple source documents, and export curated timelines for online deployment. We evaluate TimeLineCurator through a benchmark comparison of entity extraction error against a manual timeline curation process, a preliminary evaluation of the user experience of timeline authoring, a brief qualitative analysis of its visual output, and a discussion of prospective use cases suggested by members of the target author communities following its deployment.


title: DSP Implementation in the Loop of the Vector Control Drive of a Permanent Magnet Synchronous Machine

abstract: The aim of this work is to design and implement the FOC (Field Oriented Control) of the permanent magnet synchronous machine (PMSM) on DSP in Hardware In the Loop (HIL). The MATLAB /Simulink, the IDE Code Composer Studio and the DSP TMS320F28335 platform will be used to perform the simulation, the code generation and the HIL. The obtained performances of this command (a speed response time of 10 ms and a zero static error vis-a-vis the setpoint and disruption) converge to those obtained with conventional simulation on SIMULINK


title: BatchDB: Efficient Isolated Execution of Hybrid OLTP+OLAP Workloads for Interactive Applications

abstract: In this paper we present BatchDB, an in-memory database engine designed for hybrid OLTP and OLAP workloads. BatchDB achieves good performance, provides a high level of data freshness, and minimizes load interaction between the transactional and analytical engines, thus enabling real time analysis over fresh data under tight SLAs for both OLTP and OLAP workloads. BatchDB relies on primary-secondary replication with dedicated replicas, each optimized for a particular workload type (OLTP, OLAP), and a light-weight propagation of transactional updates. The evaluation shows that for standard TPC-C and TPC-H benchmarks, BatchDB can achieve competitive performance to specialized engines for the corresponding transactional and analytical workloads, while providing a level of performance isolation and predictable runtime for hybrid workload mixes (OLTP+OLAP) otherwise unmet by existing solutions.


title: Author's personal copy Review Socioeconomic status and the developing brain

abstract: Childhood socioeconomic status (SES) is associated with cognitive achievement throughout life. How does SES relate to brain development, and what are the mechanisms by which SES might exert its influence? We review studies in which behavioral, electrophysiological and neuroimaging methods have been used to characterize SES disparities in neurocognitive function. These studies indicate that SES is an important predictor of neurocognitive performance, particularly of language and executive function, and that SES differences are found in neural processing even when performance levels are equal. Implications for basic cognitive neuroscience and for understanding and ameliorating the problems related to childhood poverty are discussed.


title: Pattern Recognition in Latin America in the "Big Data" Era

abstract: The "Big Data" era has arisen, driven by the increasing availability of data from multiple sources such as social media, online transactions, network sensors or mobile devices. This is currently a focus of interest among public and private organizations, governments, research institutes and companies operating in diverse fields as health, security, commercial recommendations, detection of anomalies and future trends among others. In this problem, the main objective is to recognize and extract meaningful information (patterns, structure, underlying relationships, etc.) from huge amounts of heterogeneous data. This task is complicated by new, significant storage and processing requirements due to unprecedented volumes of data. In this scenario, new algorithms in Pattern Recognition and related fields are being devised, while well known techniques are revisited and adapted to these new challenges. Latin American research in the "Big Data" problem is still incipient, but there is a significant body of recent works in the subjects of Pattern Recognition and related fields that indirectly addresses the problem. This paper reviews Latin American contributions in Pattern Recognition and related fields in the last lustrum. The focus is set on-but not restricted to-applications in the fields of Computer Vision and Image Analysis with large scale characteristics. HighlightsContributions on Pattern Recognition and related fields in Latin America are explored.Large scale characteristic applications in Computer Vision are presented.Collaboration relationships of Latin American countries are analyzed.


title: Prefrontal direct current stimulation modulates resting EEG and event-related potentials in healthy subjects: A standardized low resolution tomography (sLORETA) study

abstract: Abstract Prefrontal transcranial direct current stimulation (tDCS) with the anode placed on the left dorsolateral prefrontal cortex (DLPFC) has been reported to enhance working memory in healthy subjects and to improve mood in major depression. However, its putative antidepressant, cognitive and behavior action is not well understood. Here, we evaluated the distribution of neuronal electrical activity changes after anodal tDCS of the left DLPFC and cathodal tDCS of the right supraorbital region using spectral power analysis and standardized low resolution tomography (sLORETA). Ten healthy subjects underwent real and sham tDCS on separate days in a double-blind, placebo-controlled cross-over trial. Anodal tDCS was applied for 20 min at 2 mA intensity over the left DLPFC, while the cathode was positioned over the contralateral supraorbital region. After tDCS, EEG was recorded during an eyes-closed resting state followed by a working memory (n-back) task. Statistical non-parametric mapping showed reduced left frontal delta activity in the real tDCS condition. Specifically, a significant reduction of mean current densities (sLORETA) for the delta band was detected in the left subgenual PFC, the anterior cingulate and in the left medial frontal gyrus. Moreover, the effect was strongest for the first 5 min (p


title: A Field Study of Run-Time Location Access Disclosures on Android Smartphones

abstract: Smartphone users are increasingly using apps that can access their location. Often these accesses can be without users knowledge and consent. For example, recent research has shown that installation-time capability disclosures are ineffective in informing people about their apps’ location access. In this paper, we present a four-week field study (N=22) on run-time location access disclosures. Towards this end, we implemented a novel method to disclose location accesses by location-enabled apps on participants’ smartphones. In particular, the method did not need any changes to participants’ phones beyond installing our study app. We randomly divided our participants to two groups: a Disclosure group (N=13), who received our disclosures and a No Disclosure group (N=9) who received no disclosures from us. Our results confirm that the Android platform’s location access disclosure method does not inform participants effectively. Almost all participants pointed out that their location was accessed by several apps they would have not expected to access their location. Further, several apps accessed their location more frequently than they expected. We conclude that our participants appreciated the transparency brought by our run-time disclosures and that because of the disclosures most of them had taken actions to manage their apps’ location access.


title: Hierarchical context supplementation for consecutive question answering

abstract: Question-answering (QA) systems have recently shown impressive results in terms of accurately answering user questions in such situations as domain specific user questions. However, we have identified many real situations where QA systems must cope with not a single question-answering situation but rather a sequence of consecutive questions. In such cases, users often ask questions on the basis of the previous answer they have received, so the context of the questions changes on a certain level. The commonly used method to handle this problem when using a QA system is to append the current question to the previous question (append method). However, the append method is not designed to detect such context changes. To deal with such context changes, we have designed a hierarchical context supplementation QA System (HCSQ). The HCSQ handles consecutive questions by matching the current question with the hierarchical domain knowledge database structure of the previous answer and then supplements the context of the current question with the required keywords. We also show that our method can be further applied to the initial question to supplement omitted context. Experimental results show that our method substantially outperforms the state-of-the-art methods.


title: Conundrums in Noun Phrase Coreference Resolution: Making Sense of the State-of-the-Art

abstract: We aim to shed light on the state-of-the-art in NP coreference resolution by teasing apart the differences in the MUC and ACE task definitions, the assumptions made in evaluation methodologies, and inherent differences in text corpora. First, we examine three subproblems that play a role in coreference resolution: named entity recognition, anaphoricity determination, and coreference element detection. We measure the impact of each subproblem on coreference resolution and confirm that certain assumptions regarding these subproblems in the evaluation methodology can dramatically simplify the overall task. Second, we measure the performance of a state-of-the-art coreference resolver on several classes of anaphora and use these results to develop a quantitative measure for estimating coreference resolution performance on new data sets.


title: Semi-Supervised Learning With Deep Embedded Clustering for Image Classification and Segmentation

abstract: Deep neural networks usually require large labeled datasets to construct accurate models; however, in many real-world scenarios, such as medical image segmentation, labeling data are a time-consuming and costly human (expert) intelligent task. Semi-supervised methods leverage this issue by making use of a small labeled dataset and a larger set of unlabeled data. In this paper, we present a flexible framework for semi-supervised learning that combines the power of supervised methods that learn feature representations using state-of-the-art deep convolutional neural networks with the deeply embedded clustering algorithm that assigns data points to clusters based on their probability distributions and feature representations learned by the networks. Our proposed semi-supervised learning algorithm based on deeply embedded clustering (SSLDEC) learns feature representations via iterations by alternatively using labeled and unlabeled data points and computing target distributions from predictions. During this iterative procedure, the algorithm uses labeled samples to keep the model consistent and tuned with labeling, as it simultaneously learns to improve feature representation and predictions. The SSLDEC requires a few hyper-parameters and thus does not need large labeled validation sets, which addresses one of the main limitations of many semi-supervised learning algorithms. It is also flexible and can be used with many state-of-the-art deep neural network configurations for image classification and segmentation tasks. To this end, we implemented and tested our approach on benchmark image classification tasks as well as in a challenging medical image segmentation scenario. In benchmark classification tasks, the SSLDEC outperformed several state-of-the-art semi-supervised learning methods, achieving 0.46% error on MNIST with 1000 labeled points and 4.43% error on SVHN with 500 labeled points. In the iso-intense infant brain MRI tissue segmentation task, we implemented SSLDEC on a 3D densely connected fully convolutional neural network where we achieved significant improvement over supervised-only training as well as a semi-supervised method based on pseudo-labeling. Our results show that the SSLDEC can be effectively used to reduce the need for costly expert annotations, enhancing applications, such as automatic medical image segmentation.


title: A Novel Deeper One-Dimensional CNN With Residual Learning for Fault Diagnosis of Wheelset Bearings in High-Speed Trains

abstract: The health condition of a wheelset bearing, the key component of a railway bogie, has a considerable impact on the safety of a train. Traditional bearing fault diagnosis techniques generally extract signals manually and then diagnose the bearing health conditions through the classifier. However, high-speed trains (HSTs) are usually faced with variable loads, variable speeds, and strong environmental noise, which pose a huge challenge to the application of the traditional bearing fault diagnosis methods in wheelset bearing fault diagnosis. Therefore, this paper proposes a 1D residual block, and based on the block, a novel deeper 1D convolutional neural network (Der-1DCNN) is proposed. The framework includes the idea of residual learning and can effectively learn high-level and abstract features while effectively alleviating the problem of training difficulty and the performance degradation of a deeper network. Additionally, for the first time, we fully use the wide convolution kernel and dropout technology to improve the model's ability to learn low-frequency signal features related to the fault components and to enhance the network's generalization performance. By constructing a deep residual learning network, Der-1DCNN can adaptively learn the deep fault features of the original vibration signal. This method not only achieves very high diagnostic accuracy for the fault diagnosis task of wheelset bearings in HSTs under strong noise environment, but also its performance is quite superior when the train's working load changes without any domain adaptation algorithm processing. The proposed Der-1DCNN is evaluated on the dataset of the multi-operating conditions of the wheelset bearings of HSTs. Experiments show that this method shows a better diagnostic performance compared with the state-of-the-art deep learning methods of bearing fault diagnosis, which proves the method's effectiveness and superiority.


title: Hip sonography update. Quality-management, catastrophes – tips and tricks

abstract: Aim: Hip sonography is today considered to be the diagnostic standard tool for developmental dysplasia of the hip (DDH) diagnosis. In Germany special commissions control the quality of the sonograms according to checklists to keep the standard high and to avoid over- and under - treatment. This paper lists tips and tricks to avoid typical mistakes according to these results. Material and method: In 8 German countries the quality of sonograms used to diagnose DDH was checked according to special checklists. An additional 250 medical doctors (pediatricians, radiologists, orthopaedic surgeons) were asked to classify 4 sonograms by measuring and typing. From the same group the projection (standing left, standing right, horizontal-cranial left, horizontal-cranial right) was checked according to the correct diagnosis in the shortest time. Results: In 1.6 % – 43.7% the licence for hip sonography was withdrawn by the German commission. The best projection with the lowest rate of wrong interpretation was the “standing right”-projection. Most of the mistakes were made because of a wrong anatomical identification and usability check. Conclusion: Hip sonography must be trained by authorized teachers. The quality of the sonograms must be controlled according to checklists. The bedside teaching without control leads to a systematic teaching of mistakes and finally catastrophes.


title: A general approach to sizing and power density equations for comparison of electrical machines

abstract: Whenever an electrical machine is meant to be fed by a power converter, the design should be approached as a system optimization, more than a simple machine sizing. A great variety of electrical machines is available to accomplish this goal, and the task of comparing the different options can be very difficult. A general purpose sizing equation, easily adjustable for every topology, that could take into account different waveforms and machine characteristics, would be a very desirable tool. In this paper, a general approach is presented to develop and to discuss such an equation. Sample applications of the sizing and power density equations are utilized to compare the induction machine and the doubly salient permanent magnet (DSPM) machine.


title: Prevalence of depression and anxiety among undergraduate university students in low- and middle-income countries: a systematic review protocol

abstract: BACKGROUND ::: Depression and anxiety symptoms are reported to be common among university students in many regions of the world and impact on quality of life and academic attainment. The extent of the problem of depression and anxiety among students in low- and middle-income countries (LMICs) is largely unknown. This paper details methods for a systematic review that will be conducted to explore the prevalence, antecedents, consequences, and treatments for depression and anxiety among undergraduate university students in LMICs. ::: ::: ::: METHODS ::: Studies reporting primary data on common mental disorders among students in universities and colleges within LMICs will be included. Quality assessment of retrieved articles will be conducted using four Joanna Briggs critical appraisal checklists for prevalence, randomized control/pseudo-randomized trials, descriptive case series, and comparable cohort/case control. Meta-analysis of the prevalence of depression and anxiety will be conducted using a random effects model which will generate pooled prevalence with their respective 95% confidence intervals. ::: ::: ::: DISCUSSION ::: The results from this systematic review will help in informing and guiding healthcare practitioners, planners, and policymakers on the burden of common mental disorders in university students in LMICs and of appropriate and feasible interventions aimed at reducing the burden of psychological morbidity among them. The results will also point to gaps in research and help set priorities for future enquiries. ::: ::: ::: SYSTEMATIC REVIEW REGISTRATION ::: PROSPERO CRD42017064148.


title: Exploring the network dynamics underlying brain activity during rest

abstract: Abstract Since the mid 1990s, the intriguing dynamics of the brain at rest has been attracting a growing body of research in neuroscience. Neuroimaging studies have revealed distinct functional networks that slowly activate and deactivate, pointing to the existence of an underlying network dynamics emerging spontaneously during rest, with specific spatial, temporal and spectral characteristics. Several theoretical scenarios have been proposed and tested with the use of large-scale computational models of coupled brain areas. However, a mechanistic explanation that encompasses all the phenomena observed in the brain during rest is still to come. In this review, we provide an overview of the key findings of resting-state activity covering a range of neuroimaging modalities including fMRI, EEG and MEG. We describe how to best define and analyze anatomical and functional brain networks and how unbalancing these networks may lead to problems with mental health. Finally, we review existing large-scale models of resting-state dynamics in health and disease. An important common feature of resting-state models is that the emergence of resting-state functional networks is obtained when the model parameters are such that the system operates at the edge of a bifurcation. At this critical working point, the global network dynamics reveals correlation patterns that are spatially shaped by the underlying anatomical structure, leading to an optimal fit with the empirical BOLD functional connectivity. However, new insights coming from recent studies, including faster oscillatory dynamics and non-stationary functional connectivity, must be taken into account in future models to fully understand the network mechanisms leading to the resting-state activity.


title: Distributed Semantic Analytics Using the SANSA Stack

abstract: A major research challenge is to perform scalable analysis of large-scale knowledge graphs to facilitate applications like link prediction, knowledge base completion and reasoning. Analytics methods which exploit expressive structures usually do not scale well to very large knowledge bases, and most analytics approaches which do scale horizontally (i.e., can be executed in a distributed environment) work on simple feature-vector-based input. This software framework paper describes the ongoing Semantic Analytics Stack (SANSA) project, which supports expressive and scalable semantic analytics by providing functionality for distributed computing on RDF data.


title: A 3D printed monolithic soft gripper with adjustable stiffness

abstract: Soft robotics has recently gained a significant momentum as a newly emerging field in robotics that focuses on biomimicry, compliancy and conformability with safety in near-human environments. Beside conventional fabrication methods, additive manufacturing is a primary technique to employ to fabricate soft robotic devices. We developed a monolithic soft gripper, with variable stiffness fingers, that was fabricated as a one-piece device. Negative pressure was used for the actuation of the gripper while positive pressure was used to vary the stiffness of the fingers of the gripper. Finger bending and gripping capabilities of the monolithic soft gripper were experimentally tested. Finite element simulation and experimental results demonstrate that the proposed monolithic soft gripper is fully compliant, low cost and requires an actuation pressure below −100 kPa.


title: Mutual coupling compensation in small phased array antennas

abstract: A new technique to compensate for the mutual coupling effect in small phased array antennas is presented. This method is a modification to the classical approach for correcting the array output vector by multiplication of a decoupling matrix to achieve a less unperturbed array response. Two different methods of calculating coupling coefficients between array elements are presented. The performance is demonstrated by a simulation based on a numerical analysis with the finite element method (FEM) and a practical application to a digital beamforming (DBF) array.


title: Active-area-segmentation (AAS) technique for compact, ESD robust, fully silicided NMOS design

abstract: This paper describes a layout technique to optimize the ESD performance per area for fully silicided NMOS devices by segmenting the active area of drain and source regions. Efficient multi finger triggering is achieved by intrinsic inter-finger-coupling through the bulk enabled by compact finger design. The technique is successfully applied in a 0.13 um and a 0.18 um CMOS technology obtaining HBM ESD capability of up to 8.6 V/um2.


title: First in-field experiments with a “bilingual” underwater acoustic modem supporting the JANUS standard

abstract: This paper presents the design, implementation, and in-field experimentation of a “bilingual” underwater acoustic modem with multi-hop networking capabilities. The designed system supports the use of the JANUS physical coding scheme and of a proprietary one. JANUS is an open, simple and robust digital coding technology currently in process to become a NATO standard. The Applicon SeaModem has been selected as the communication hardware to use and JANUS has been integrated into it. The designed system has also been interfaced with the SUNSET system which provides ad-hoc networking capabilities and the support for distributed cooperation. Additionally, SUNSET has been extended with a policy module allowing to switch between the different available communication schemes according to the network needs. In-lab experiments and in-field tests have been conducted to validate and evaluate the proposed system. A network of 4 underwater devices (three static nodes and one surface vehicle) was deployed and JANUS was used for initial contact and parameters negotiation to then switch to the proprietary communication scheme. Promising results were collected and several lessons were learnt. After the experiments a more efficient policy module has been designed and implemented and it will be tested in the next at-sea trial.


Probabilistic outputs for support vector machines and comparisons to regularized likelihood methods


title: Accuracy of full-arch scans using intraoral scanners

abstract: OBJECTIVES ::: This study aimed to evaluate the accuracy of intraoral scanners in full-arch scans. ::: ::: ::: MATERIALS AND METHODS ::: A representative model with 14 prepared abutments was digitized using an industrial scanner (reference scanner) as well as four intraoral scanners (iTero, CEREC AC Bluecam, Lava C.O.S., and Zfx IntraScan). Datasets obtained from different scans were loaded into 3D evaluation software, superimposed, and compared for accuracy. One-way analysis of variance (ANOVA) was implemented to compute differences within groups (precision) as well as comparisons with the reference scan (trueness). A level of statistical significance of p < 0.05 was set. ::: ::: ::: RESULTS ::: Mean trueness values ranged from 38 to 332.9 μm. Data analysis yielded statistically significant differences between CEREC AC Bluecam and other scanners as well as between Zfx IntraScan and Lava C.O.S. Mean precision values ranged from 37.9 to 99.1 μm. Statistically significant differences were found between CEREC AC Bluecam and Lava C.O.S., CEREC AC Bluecam and iTero, Zfx Intra Scan and Lava C.O.S., and Zfx Intra Scan and iTero (p < 0.05). ::: ::: ::: CONCLUSIONS ::: Except for one intraoral scanner system, all tested systems showed a comparable level of accuracy for full-arch scans of prepared teeth. Further studies are needed to validate the accuracy of these scanners under clinical conditions. ::: ::: ::: CLINICAL RELEVANCE ::: Despite excellent accuracy in single-unit scans having been demonstrated, little is known about the accuracy of intraoral scanners in simultaneous scans of multiple abutments. Although most of the tested scanners showed comparable values, the results suggest that the inaccuracies of the obtained datasets may contribute to inaccuracies in the final restorations.


title: Near-Optimal Regret Bounds for Thompson Sampling

abstract: Thompson Sampling (TS) is one of the oldest heuristics for multiarmed bandit problems. It is a randomized algorithm based on Bayesian ideas and has recently generated significant interest after several studies demonstrated that it has favorable empirical performance compared to the state-of-the-art methods. In this article, a novel and almost tight martingale-based regret analysis for Thompson Sampling is presented. Our technique simultaneously yields both problem-dependent and problem-independent bounds: (1) the first near-optimal problem-independent bound of O(s NT ln T) on the expected regret and (2) the optimal problem-dependent bound of (1 + e)∑i fln T d(μi,μ1) + O(fNe2) on the expected regret (this bound was first proven by Kaufmann et al. (2012b)). Our technique is conceptually simple and easily extends to distributions other than the Beta distribution used in the original TS algorithm. For the version of TS that uses Gaussian priors, we prove a problem-independent bound of O(s NT ln N) on the expected regret and show the optimality of this bound by providing a matching lower bound. This is the first lower bound on the performance of a natural version of Thompson Sampling that is away from the general lower bound of Ω (s NT) for the multiarmed bandit problem.


title: Initial results in underwater single image dehazing

abstract: As light is transmitted from subject to observer it is absorbed and scattered by the medium it passes through. In mediums with large suspended particles, such as fog or turbid water, the effect of scattering can drastically decrease the quality of images. In this paper we present an algorithm for removing the effects of light scattering, referred to as dehazing, in underwater images. Our key contribution is to propose a simple, yet effective, prior that exploits the strong difference in attenuation between the three image color channels in water to estimate the depth of the scene. We then use this estimate to reduce the spatially varying effect of haze in the image. Our method works with a single image and does not require any specialized hardware or prior knowledge of the scene. As a by-product of the dehazing process, an up-to-scale depth map of the scene is produced. We present results over multiple real underwater images and over a controlled test set where the target distance and true colors are known.


title: Potentials and Implications of Dedicated Highway Lanes for Autonomous Vehicles

abstract: The introduction of autonomous vehicles (AVs) will have far-reaching effects on road traffic in cities and on highways.The implementation of automated highway system (AHS), possibly with a dedicated lane only for AVs, is believed to be a requirement to maximise the benefit from the advantages of AVs. We study the ramifications of an increasing percentage of AVs on the traffic system with and without the introduction of a dedicated AV lane on highways. We conduct an analytical evaluation of a simplified scenario and a macroscopic simulation of the city of Singapore under user equilibrium conditions with a realistic traffic demand. We present findings regarding average travel time, fuel consumption, throughput and road usage. Instead of only considering the highways, we also focus on the effects on the remaining road network. Our results show a reduction of average travel time and fuel consumption as a result of increasing the portion of AVs in the system. We show that the introduction of an AV lane is not beneficial in terms of average commute time. Examining the effects of the AV population only, however, the AV lane provides a considerable reduction of travel time (approx. 25%) at the price of delaying conventional vehicles (approx. 7%). Furthermore a notable shift of travel demand away from the highways towards major and small roads is noticed in early stages of AV penetration of the system. Finally, our findings show that after a certain threshold percentage of AVs the differences between AV and no AV lane scenarios become negligible.


title: Cards, Money and Two Hacking Forums: An Analysis of Online Money Laundering Schemes

abstract: The emergence of the internet as a global, borderless communication platform afforded a wide range ofsocial and economic opportunities to people throughout theworld. Criminals have exploited the ability to communicateinstantaneously around the globe to facilitate crossjurisdictionalcyber-fraud and subsequently, online moneylaundering. Coordinating international fraud and moneylaundering schemes requires a medium of communication, suchas online hacking and carding forums, where offenders meet toexchange information and to engage in their illegal business. Forthe study presented in this paper, publicly available onlinecarding and hacking forums were downloaded and keywords ofinterest pertaining to online money laundering were extracted. This study undertakes an analysis of two large Russian-speakinghacking and carding forums by qualitatively analyzing andquantifying contexts of keyword usage. Findings indicate thatcyber-fraudsters are primarily interested in cashing outdigitally stolen funds and do so mainly by resorting to theservices of money mules and virtual casinos.


Amelanotic melanoma mimicking keratoacanthoma: the diagnostic role of dermoscopy


title: Methods for Sentence Compression

abstract: Sentence compression is the task of producing a summary of a single sentence. The compressed sentence should be shorter, contain the important content from the original, and itself be grammatical. The three papers discussed here take different approaches to identifying important content, determining which sentences are grammatical, and jointly optimizing these objectives. One family of approaches we will discuss is those that are tree-based, which create a compressed sentence by making edits to the syntactic tree of the original sentence. A second type of approach is sentence-based, which generates strings directly. Orthogonal to either of these two approaches is whether sentences are treated in isolation or if the surrounding discourse affects compressions. We compare a tree-based, a sentence-based, and a discourse-based approach and conclude with ideas for future work in this area. Comments University of Pennsylvania Department of Computer and Information Science Technical Report No. MSCIS-10-20. This technical report is available at ScholarlyCommons: http://repository.upenn.edu/cis_reports/929 Methods for Sentence Compression


Multi-access Edge Computing: A Survey


title: Human-Aware Robotic Assistant for Collaborative Assembly: Integrating Human Motion Prediction With Planning in Time

abstract: Introducing mobile robots into the collaborative assembly process poses unique challenges for ensuring efficient and safe human-robot interaction. Current human-robot work cells require the robot to cease operating completely whenever a human enters a shared region of the given cell, and the robots do not explicitly model or adapt to the behavior of the human. In this work, we present a human-aware robotic system with single-axis mobility that incorporates both predictions of human motion and planning in time to execute efficient and safe motions during automotive final assembly. We evaluate our system in simulation against three alternative methods, including a baseline approach emulating the behavior of standard safety systems in factories today. We also assess the system within a factory test environment. Through both live demonstration and results from simulated experiments, we show that our approach produces statistically significant improvements in quantitative measures of safety and fluency of interaction.


title: Understanding Mental States in Natural Language

abstract: Understanding mental states in narratives is an important aspect of human language comprehension. By "mental states" we refer to beliefs, states of knowledge, points of view, and suppositions, all of which may change over time. In this paper, we propose an approach for automatically extracting and understanding multiple mental states in stories. Our model consists of two parts: (1) a parser that takes an English sentence and translates it to some semantic operations; (2) a mental-state inference engine that reads in the semantic operations and produces a situation model that represents the meaning of the sentence. We present the performance of the system on a corpus of children stories containing both fictional and non-fictional texts.


title: COMMENTARY The Hippocampal Indexing Theory and Episodic Memory: Updating the Index

abstract: A little over 20 years ago, (Teyler and DiScenna, 1986; Behav Neurosci 100:147-152) proposed the hippocampal memory index theory. It offered an account of episodic memory based on the intrinsic organization of the hippocampus, its synaptic physiology and its ana- tomical relationship to other regions of the brain. The essence of their idea was that the hippocampus was functionally designed and anatomi- cally situated to capture information about neocortical activity gener- ated by the individual features of behavioral episode. Moreover, because the hippocampus projects back to these neocortical regions the information it stored could serve as an index to the pattern of neocorti- cal activity produced by the episode. Consequently, a partial cue that activated the index could activate the neocortical patterns and thus retrieve the memory of the episode. In this article we revisit and update indexing theory. Our conclusion is that it has aged very well. Its core ideas can be seen in many contemporary theories and there is a wealth of data that support this conceptual framework. V C 2007 Wiley-Liss, Inc.


Design Science Research Contributions: Finding a Balance between Artifact and Theory


title: FBI-Pose: Towards Bridging the Gap between 2D Images and 3D Human Poses using Forward-or-Backward Information

abstract: Although significant advances have been made in the area of human poses estimation from images using deep Convolutional Neural Network (ConvNet), it remains a big challenge to perform 3D pose inference in-the-wild. This is due to the difficulty to obtain 3D pose groundtruth for outdoor environments. In this paper, we propose a novel framework to tackle this problem by exploiting the information of each bone indicating if it is forward or backward with respect to the view of the camera(we term it Forwardor-Backward Information abbreviated as FBI). Our method firstly trains a ConvNet with two branches which maps an image of a human to both the 2D joint locations and the FBI of bones. These information is further fed into a deep regression network to predict the 3D positions of joints. To support the training, we also develop an annotation user interface and labeled such FBI for around 12K in-the-wild images which are randomly selected from MPII (a public dataset of 2D pose annotation). Our experimental results on the standard benchmarks demonstrate that our approach outperforms state-of-the-art methods both qualitatively and quantitatively.


title: Performance Improvement of Multiphase Multilevel Inverter Using Hybrid Carrier Based Space Vector Modulation

abstract: This paper proposes a hybrid carrier based space vector modulation suitable for multiphase multilevel inverters. Multiphase multilevel inverters are controlled by this hybrid modulation to provide multiphase variable voltage and variable frequency supply. The proposed modulation inherits the features of fundamental frequency modulation and carrier based space vector modulation strategies. The main characteristics of this hybrid modulation are the reduction in power losses, and effectively improve harmonic performance. This algorithm can be applied to cascaded multilevel inverter topologies; it has low computational complexity and it is suitable for hardware implementations. Theoretical considerations are detailed using a five phase multilevel inverter. The performance of this hybrid modulation is analyzed based on power loss, weighted total harmonic distortion, the linearity and it is compared with standard modulation strategies. Simulation and experiment results confirm the good performance of the proposed modulation scheme.


title: A Distributed Redis Framework for Use in the UCWW

abstract: The performance of data access plays an important role for the applications of the emerging ubiquitous consumer wireless world (UCWW). As a 'Not only SQL' (NoSQL) database, Redis has been deployed in the UCWW cloud as an open-source key value store acting as the key component in the system. Given the limited performance of a single Redis node, to improve the system's performance and handle large amounts of requests from the web applications in the UCWW system, a distributed Redis framework has been designed and is proposed in this paper. Considering the complex management of the Redis cluster, in the distributed Redis framework the ZooKeeper is used to manage the Redis nodes at the database layer and service governance is utilized at the service layer. With this layered design, the resultant framework is flexible and scalable, and could be easily integrated into the UCWW cloud.


title: Information-sharing in public organizations: A literature review of interpersonal, intra-organizational and inter-organizational success factors

abstract: Abstract Information sharing is considered an important approach to increasing organizational efficiency and performance. With advances in information and communication technology, sharing information across organizations has become more feasible. In the public sector, government agencies are also aware of the importance of information sharing for addressing policy issues such as anti-terrorism and public health. However, information sharing can be a complex task. Identifying factors that influence information sharing is critical. In the literature, research in information sharing focuses on the interpersonal, intra-organizational, and inter-organizational levels. This paper reviews the current information-sharing research, discusses the factors affecting information sharing at the three levels, and provides summative frameworks. These frameworks provide a means to discover future research opportunities, and a systematic way for practitioners to identify key factors involved in successful information sharing.