Query: Power-efficient beam sweeping for initial synchronization in mm-Wave wireless networks

Relevant passages:
A Tractable Approach to Coverage and Rate in Cellular Networks <=SEP=> Cellular networks are usually modeled by placing the base stations on a grid, with mobile users either randomly scattered or placed deterministically. These models have been used extensively but suffer from being both highly idealized and not very tractable, so complex system-level simulations are used to evaluate coverage/outage probability and rate. More tractable models have long been desirable. We develop new general models for the multi-cell signal-to-interference-plus-noise ratio (SINR) using stochastic geometry. Under very general assumptions, the resulting expressions for the downlink SINR CCDF (equivalent to the coverage probability) involve quickly computable integrals, and in some practical special cases can be simplified to common integrals (e.g., the Q-function) or even to simple closed-form expressions. We also derive the mean rate, and then the coverage gain (and mean rate loss) from static frequency reuse. We compare our coverage predictions to the grid model and an actual base station deployment, and observe that the proposed model is pessimistic (a lower bound on coverage) whereas the grid model is optimistic, and that both are about equally accurate. In addition to being more tractable, the proposed model may better capture the increasingly opportunistic and dense placement of base stations in future networks.

Channel Estimation and Hybrid Precoding for Millimeter Wave Cellular Systems <=SEP=> Millimeter wave (mmWave) cellular systems will enable gigabit-per-second data rates thanks to the large bandwidth available at mmWave frequencies. To realize sufficient link margin, mmWave systems will employ directional beamforming with large antenna arrays at both the transmitter and receiver. Due to the high cost and power consumption of gigasample mixed-signal devices, mmWave precoding will likely be divided among the analog and digital domains. The large number of antennas and the presence of analog beamforming requires the development of mmWave-specific channel estimation and precoding algorithms. This paper develops an adaptive algorithm to estimate the mmWave channel parameters that exploits the poor scattering nature of the channel. To enable the efficient operation of this algorithm, a novel hierarchical multi-resolution codebook is designed to construct training beamforming vectors with different beamwidths. For single-path channels, an upper bound on the estimation error probability using the proposed algorithm is derived, and some insights into the efficient allocation of the training power among the adaptive stages of the algorithm are obtained. The adaptive channel estimation algorithm is then extended to the multi-path case relying on the sparse nature of the channel. Using the estimated channel, this paper proposes a new hybrid analog/digital precoding algorithm that overcomes the hardware constraints on the analog-only beamforming, and approaches the performance of digital solutions. Simulation results show that the proposed low-complexity channel estimation algorithm achieves comparable precoding gains compared to exhaustive channel training algorithms. The results illustrate that the proposed channel estimation and precoding algorithms can approach the coverage probability achieved by perfect channel knowledge even in the presence of interference.

Spatially Sparse Precoding in Millimeter Wave MIMO Systems <=SEP=> Millimeter wave (mmWave) signals experience orders-of-magnitude more pathloss than the microwave signals currently used in most wireless applications and all cellular systems. MmWave systems must therefore leverage large antenna arrays, made possible by the decrease in wavelength, to combat pathloss with beamforming gain. Beamforming with multiple data streams, known as precoding, can be used to further improve mmWave spectral efficiency. Both beamforming and precoding are done digitally at baseband in traditional multi-antenna systems. The high cost and power consumption of mixed-signal devices in mmWave systems, however, make analog processing in the RF domain more attractive. This hardware limitation restricts the feasible set of precoders and combiners that can be applied by practical mmWave transceivers. In this paper, we consider transmit precoding and receiver combining in mmWave systems with large antenna arrays. We exploit the spatial structure of mmWave channels to formulate the precoding/combining problem as a sparse reconstruction problem. Using the principle of basis pursuit, we develop algorithms that accurately approximate optimal unconstrained precoders and combiners such that they can be implemented in low-cost RF hardware. We present numerical results on the performance of the proposed algorithms and show that they allow mmWave systems to approach their unconstrained performance limits, even when transceiver hardware constraints are considered.

An introduction to millimeter-wave mobile broadband systems <=SEP=> Almost all mobile communication systems today use spectrum in the range of 300 MHz-3 GHz. In this article, we reason why the wireless community should start looking at the 3-300 GHz spectrum for mobile broadband applications. We discuss propagation and device technology challenges associated with this band as well as its unique advantages for mobile communication. We introduce a millimeter-wave mobile broadband (MMB) system as a candidate next generation mobile communication system. We demonstrate the feasibility for MMB to achieve gigabit-per-second data rates at a distance up to 1 km in an urban mobile environment. A few key concepts in MMB network architecture such as the MMB base station grid, MMB interBS backhaul link, and a hybrid MMB + 4G system are described. We also discuss beamforming techniques and the frame structure of the MMB air interface.

Millimeter Wave Mobile Communications for 5 G Cellular : It Will Work ! <=SEP=> The global bandwidth shortage facing wireless carriers has motivated the exploration of the underutilized millimeter wave (mm-wave) frequency spectrum for future broadband cellular communication networks. There is, however, little knowledge about cellular mm-wave propagation in densely populated indoor and outdoor environments. Obtaining this information is vital for the design and operation of future fifth generation cellular networks that use the mm-wave spectrum. In this paper, we present the motivation for new mm-wave cellular systems, methodology, and hardware for measurements and offer a variety of measurement results that show 28 and 38 GHz frequencies can be used when employing steerable directional antennas at base stations and mobile devices. INDEX TERMS 28GHz, 38GHz, millimeter wave propagation measurements, directional antennas, channel models, 5G, cellular, mobile communications, MIMO.

Towards automatic generation of vulnerability-based signatures <=SEP=> In this paper we explore the problem of creating vulnerability signatures. A vulnerability signature matches all exploits of a given vulnerability, even polymorphic or metamorphic variants. Our work departs from previous approaches by focusing on the semantics of the program and vulnerability exercised by a sample exploit instead of the semantics or syntax of the exploit itself. We show the semantics of a vulnerability define a language which contains all and only those inputs that exploit the vulnerability. A vulnerability signature is a representation (e.g., a regular expression) of the vulnerability language. Unlike exploit-based signatures whose error rate can only be empirically measured for known test cases, the quality of a vulnerability signature can be formally quantified for all possible inputs. We provide a formal definition of a vulnerability signature and investigate the computational complexity of creating and matching vulnerability signatures. We also systematically explore the design space of vulnerability signatures. We identify three central issues in vulnerability-signature creation: how a vulnerability signature represents the set of inputs that may exercise a vulnerability, the vulnerability coverage (i.e., number of vulnerable program paths) that is subject to our analysis during signature creation, and how a vulnerability signature is then created for a given representation and coverage. We propose new data-flow analysis and novel adoption of existing techniques such as constraint solving for automatically generating vulnerability signatures. We have built a prototype system to test our techniques. Our experiments show that we can automatically generate a vulnerability signature using a single exploit which is of much higher quality than previous exploit-based signatures. In addition, our techniques have several other security applications, and thus may be of independent interest

A novel explicit multi-focus image fusion method <=SEP=> We propose a multi-focus image fusion method. The energy of Laplacian of input images is obtained to decide which portions of the input images are in better focus, and the majority filter offers a means of spreading the focused regions to neighborhood. The edge-preserving guided image filter is applied to reduce the block effect. We conduct several experiments which demonstrate that it provided a better performance than the state of the art fusion methods in visual and quantitative evaluations.

How do Retailers Adjust Prices?: Evidence from Store-Level Data <=SEP=> Recent theoretical work on retail pricing dynamics suggests that retailers periodically hold sales periodic, temporary reductions in price, -even when their costs are unchanged. In this paper we extend existing theory to predict which items will go on sale, and use a new data set from the BLS to document the frequency of sales across a wide range of goods and geographic areas. We find a number of pricing regularities for the 20 categories of goods we examine. First, retailers seem to have a “regular” price, and most deviations from that price are downward. Second, there is considerable heterogeneity in sale behavior across goods within a category (e.g. cereal); the same items are regularly put on sale, while other items rarely are on sale. Third, items are more likely to go on sale when demand is highest. Fourth, for a limited number of items for which we know market shares, products with larger market shares go on sale more often. These final three observations are consistent with our theoretical result that popular products are most likely to be placed on sale.

Combined ivermectin and doxycycline treatment has microfilaricidal and adulticidal activity against Dirofilaria immitis in experimentally infected dogs. <=SEP=> There is still a pressing need for effective adulticide treatment for human and animal filarial infections. Like many filarial nematodes, Dirofilaria immitis, the causative agent of canine heartworm disease, harbours the bacterial endosymbiont Wolbachia, which has been shown to be essential for worm development, fecundity and survival. Here the authors report the effect of different treatment regimens in dogs experimentally infected with adult D. immitis on microfilariemia, antigenemia, worm recovery and Wolbachia content. Treatment with ivermectin (IVM; 6 microg/kg per os weekly) combined with doxycycline (DOXY; 10 mg/kg/day orally from Weeks 0-6, 10-12, 16-18, 22-26 and 28-34) resulted in a significantly faster decrease of circulating microfilariae and higher adulticidal activity compared with either IVM or DOXY alone. Quantitative PCR analysis of ftsZ (Wolbachia DNA) and 18S rDNA (nematode DNA) absolute copy numbers showed significant decreases in Wolbachia content compared with controls in worms recovered from DOXY-treated dogs that were not, however, associated with worm death. Worms from IVM/DOXY-treated dogs, on the other hand, had Wolbachia/nematode DNA ratios similar to those of control worms, suggesting a loss of both Wolbachia and nematode DNA as indicated by absolute copy number values. Histology and transmission electron microscopy of worms recovered from the IVM/DOXY combination group showed complete loss of uterine content in females and immunohistochemistry for Wolbachia was negative. Results indicate that the combination of these two drugs causes adult worm death. This could have important implications for control of human and animal filarial infections.

Landing Strategies in Honeybees and Applications to Uninhabited Airborne Vehicles <=SEP=> An application of insect visuomotor behavior to automatic control of landing is explored. Insects, being perhaps more reliant on image motion cues than mammals or higher vertebrates, are proving to be an excellent organism in which to investigate how information on optic flow is exploited to guide locomotion and navigation. We have observed how bees perform grazing landings on a flat surface and have deduced the algorithmic basis for the behavior. A smooth landing is achieved by a surprisingly simple and elegant strategy: image velocity is held constant as the surface is approached, thus automatically ensuring that flight speed is close to zero at touchdown. No explicit knowledge of flight speed or height above the ground is necessary. The feasibility of this landing strategy was tested by implementation in a robotic gantry. We also outline our current efforts at exploring the applicability of this and related techniques to the guidance of uninhabited airborne vehicles (UAVs). Aspects of the algorithm were tested on a small UAV using real imagery to control

A New Approach for Resource Scheduling with Deep Reinforcement Learning <=SEP=> With the rapid development of deep learning, deep reinforcement learning (DRL) began to appear in the field of resource scheduling in recent years. Based on the previous research on DRL in the literature, we introduce online resource scheduling algorithm DeepRM2 and the offline resource scheduling algorithm DeepRM_Off. Compared with the state-of-the-art DRL algorithm DeepRM and heuristic algorithms, our proposed algorithms have faster convergence speed and better scheduling efficiency with regarding to average slowdown time, job completion time and rewards.

COTS-based software development: Processes and open issues <=SEP=> The work described in this paper is an investigation of COTS-based software development within a particular NASA environment, with an emphasis on the processes used. Fifteen projects using a COTS-based approach were studied and their actual process was documented. This process is evaluated to identify essential differences in comparison to traditional software development. The main differences, and the activities for which projects require more guidance, are requirements definition and COTS selection, high level design, integration and testing. Starting from these empirical observations, a new process and set of guidelines for COTS-based development are developed and briefly presented.

' s personal copy A comparative study on feature reduction approaches in Hindi and Bengali named entity recognition <=SEP=> Features used for named entity recognition (NER) are often high dimensional in nature. These cause overfitting when training data is not sufficient. Dimensionality reduction leads to performance enhancement in such situations. There are a number of approaches for dimensionality reduction based on feature selection and feature extraction. In this paper we perform a comprehensive and comparative study on different dimensionality reduction approaches applied to the NER task. To compare the performance of the various approaches we consider two Indian languages namely Hindi and Bengali. NER accuracies achieved in these languages are comparatively poor as yet, primarily due to scarcity of annotated corpus. For both the languages dimensionality reduction is found to improve performance of the classifiers. A Comparative study of the effectiveness of several dimensionality reduction techniques is presented in detail in this paper. 2011 Elsevier B.V. All rights reserved.

UML CLASS DIAGRAM OR ENTITY RELATIONSHIP DIAGRAM? AN OBJECT-RELATIONAL CONCEPTUAL IMPEDANCE MISMATCH <=SEP=> It is now nearly 30 years since Peter Chen’s watershed paper “The Entity-Relationship Model – towards a Unified View of Data”. [1] The entity relationship model and variations and extensions to it have been taught in colleges and universities for many years. In his original paper Peter Chen looked at converting his new ER model to the then existing data structure diagrams for the Network model. In recent years there has been a tendency to use a Unified Modelling Language (UML) class diagram for conceptual modeling for relational databases, and several popular course text books use UML notation to some degree [2] [3]. However Object and Relational technology are based on different paradigms. In the paper we argue that the UML class diagram is more of a logical model (implementation specific). ER Diagrams on the other hand, are at a conceptual level of database design dealing with the main items and their relationships and not with implementation specific detail. UML focuses on OOAD (Object Oriented Analysis and Design) and is navigational and program dependent whereas the relational model is set based and exhibits data independence. The ER model provides a well-established set of mapping rules for mapping to a relational model. In this paper we look specifically at the areas which can cause problems for the novice database designer due to this conceptual mismatch of two different paradigms. Firstly, transferring the mapping of a weak entity from an Entity Relationship model to UML and secondly the representation of structural constraints between objects. We look at the mixture of notations which students mistakenly use when modeling. This is often the result of different notations being used on different courses throughout their degree. Several of the popular text books at the moment use either a variation of ER, UML, or both for teaching database modeling. At the moment if a student picks up a text book they could be faced with either; one of the many ER variations, UML, UML and a variation of ER both covered separately, or UML and ER merged together. We regard this problem as a conceptual impedance mismatch. This problem is documented in [21] who have produced a catalogue of impedance mismatch problems between object-relational and relational paradigms. We regard the problems of using UML class diagrams for relational database design as a conceptual impedance mismatch as the Entity Relationship model does not have the structures in the model to deal with Object Oriented concepts

Controlling Physically Based Virtual Musical Instruments Using The Gloves <=SEP=> In this paper we propose an empirical method to develop mapping strategies between a gestural-based interface (the Gloves) and physically based sound synthesis models. An experiment was conducted to investigate which gestures listeners associate with sounds synthesised using physical models, corresponding to three categories of sound: sustained, iterative and impulsive. The results of the experiment show that listeners perform similar gestures when controlling sounds from the different categories. We used such gestures in order to create the mapping strategy between the Gloves and the physically based synthesis engine.

Conservative treatment of fractures of the thoracolumbar spine <=SEP=> We reviewed 48 patients with thoracolumbar fractures treated conservatively between 1988 and 1999. The average follow-up was 77.5 (31–137) months and average patient age (23 women, 25 men) was 46 (18–76) years. Twenty-nine patients suffered a fall from a height and 13 patients were injured in traffic accidents. Thirty-two patients had compression-type fractures and 16 burst-type fractures. There were no neurological deficits. Twenty-nine patients were treated by orthosis, 13 by body cast and six by bed rest. In addition to pain and functional scoring, we measured a number of radiographic parameters at the time of admission and at latest follow-up and compared the values. In patients with compression fractures there were significant changes in scoliosis angle and wedging index (p<0.05). The mean pain score was 1.66 and mean functional score 1.03. In patients with burst fractures, vertebral index, wedging index and height loss increased after treatment (p<0.05). The mean pain score was 1.26 and functional score 0.93. Compression fractures with kyphosis angle <30° are supposed to be stable and can be treated conservatively. If the kyphosis angle is more than 30°, magnetic resonance imaging (MRI) should be performed, and if the posterior ligamentous complex is damaged, surgery should be considered. In burst fractures, MRI should always be performed and conservative treatment should only be considered if there is no neurological deficit and the ligaments are intact. Nous avons examiné 48 malades avec une fracture dorsolombaire traitée d’une manière conservatrice entre 1988 et 1999. Le suivi moyen était de 77,5 (31–137) mois et l’âge moyen des malades (23 femmes, 25 hommes) était de 46 (18–76) ans. Vingt-neuf malades avaient fait une chute de grande hauteur et 13 malades ont été blessés dans un accident de la circulation. Trente-deux malades avaient des fractures du type compression et 16 fractures du type explosion. Il n’y avait pas de déficit neurologique. Vingt-neuf malades ont été traités par orthèse, 13 par corset plâtré et six par repos au lit. En plus des scores douleur et des scores fonctionnels, nous avons comparé plusieurs paramètres radiographiques entre l’admission et le plus long recul. Chez les malades avec fracture-compression il y avait des changements significatifs dans l’angle de la scoliose et l’index angulaire (p<0.05). Le score moyen de la douleur était 1.66 et le score fonctionnel moyen 1.03. Chez les malades avec fracture-explosion, l’index vertébral, l’index angulaire, et la perte de hauteur ont augmenté après traitement (p<0.05). Le score moyen de la douleur était 1.26 et le score fonctionnel 0.93. Les fractures de type de compression avec angle de cyphose <30° sont supposés être stables et sont traités d’une manière conservatrice. Si l’angle de la cyphose est de plus de 30°, une IRM devrait être exécutée et si le complexe ligamentaire postérieur est endommagé, la chirurgie devrait être envisagée. Dans les fractures du type de explosion, une IMR devrait toujours être exécutée et le traitement conservateur devrait être retenu seulement s’il n’y a aucun déficit neurologique et si les ligaments sont intacts.

The role of rumination in depressive disorders and mixed anxiety/depressive symptoms. <=SEP=> Several studies have shown that people who engage in ruminative responses to depressive symptoms have higher levels of depressive symptoms over time, after accounting for baseline levels of depressive symptoms. The analyses reported here showed that rumination also predicted depressive disorders, including new onsets of depressive episodes. Rumination predicted chronicity of depressive disorders before accounting for the effects of baseline depressive symptoms but not after accounting for the effects of baseline depressive symptoms. Rumination also predicted anxiety symptoms and may be particularly characteristic of people with mixed anxiety/depressive symptoms.

A direct approach to estimating surfaces in tomographic data <=SEP=> Under ideal circumstances, the inverse of the radon transform is computable, and sequences of measured projections are sufficient to obtain accurate estimates of volume densities. In situations where the sinogram data is incomplete, the radon transform is noninvertable, and attempts to reconstruct greyscale density values result in reconstruction artifacts that can undermine the effectiveness of subsequent processing. This paper presents a direct approach to the segmentation of incomplete tomographic data. The strategy is to impose a fairly simple model on the data, and treat segmentation as a problem of estimating the interface between two substances of somewhat homogeneous density. The segmentation is achieved by simultaneously deforming a surface model and updating density parameters in order to achieve a best fit between the projected model and the measured sinograms. The deformation is implemented with level-set surface models, calculated at the resolution of the input data. Relative to previous work, this paper makes several contributions. First is a proper derivation of the deformation of surface models that move according to a gradient descent on a likelihood measure. We also present a series of computational innovations that make this direct surface-fitting approach feasible with state-of-the-art computers. Another contribution is the demonstration of the effectiveness of this approach on under-constrained tomographic problems, using both simulated and real datasets.

Adaptive Simulation-based Training of AI Decision-makers using Bayesian Optimization <=SEP=> This work studies how an AI-controlled dog-fighting agent with tunable decisionmaking parameters can learn to optimize performance against an intelligent adversary, as measured by a stochastic objective function evaluated on simulated combat engagements. Gaussian process Bayesian optimization (GPBO) techniques are developed to automatically learn global Gaussian Process (GP) surrogate models, which provide statistical performance predictions in both explored and unexplored areas of the parameter space. This allows a learning engine to sample full-combat simulations at parameter values that are most likely to optimize performance and also provide highly informative data points for improving future predictions. However, standard GPBO methods do not provide a reliable surrogate model for the highly volatile objective functions found in aerial combat, and thus do not reliably identify global maxima. These issues are addressed by novel Repeat Sampling (RS) and Hybrid Repeat/Multipoint Sampling (HRMS) techniques. Simulation studies show that HRMS improves the accuracy of GP surrogate models, allowing AI decision-makers to more accurately predict performance and efficiently tune parameters.

Folded cascode OTA design for wide band applications <=SEP=> This paper deals with design and optimization of a folded cascode operational transconductance amplifier. First, a detailed description of an optimum OTA topology is done in order to optimize MOS transistor sizing. Second, the design of folded cascode OTA, which works for frequencies that lead to a base band circuit design for RF application, is based on transistor sizing methodology. Third, folded cascode OTAs generally find several applications that are well developed. Simulation results are performed using SPICE software and BSIM3V3 model for CMOS 0.35mum process, show that the designed folded cascode OTA has a 85dB DC gain and provides a gain bandwidth product of around 332MHz

On visual similarity based 2D drawing retrieval <=SEP=> A large amount of 2D drawings have been produced in engineering fields. To reuse and share the available drawings efficiently, we propose two methods in this paper, namely 2.5D spherical harmonics transformation and 2D shape histogram, to retrieve 2D drawings by measuring their shape similarity. The first approach represents a drawing as a spherical function by transforming it from a 2D space into a 3D space. Then a fast spherical harmonics transformation is employed to get a rotation invariant descriptor. The second statistics-based approach represents the shape of a 2D drawing using a distance distribution between two randomly sampled points. To allow users to interactively emphasize certain local shapes that they are interested in, we have adopted a flexible sampling strategy by specifying a bias sampling density upon these local shapes. The two proposed methods have many valuable properties, including transform invariance, efficiency, and robustness. In addition, their insensitivity to noise allows for the user’s causal input, thus supporting a freehand sketch-based retrieval user interface. Experiments show that a better performance can be achieved by combining them together using weights. q 2005 Elsevier Ltd. All rights reserved.

Memory versus non-linearity in reservoirs <=SEP=> Reservoir Computing (RC) is increasingly being used as a conceptually simple yet powerful method for using the temporal processing of recurrent neural networks (RNN). However, because fundamental insight in the exact functionality of the reservoir is as yet still lacking, in practice there is still a lot of manual parameter tweaking or brute-force searching involved in optimizing these systems. In this contribution we aim to enhance the insights into reservoir operation, by experimentally studying the interplay of the two crucial reservoir properties, memory and non-linear mapping. For this, we introduce a novel metric which measures the deviation of the reservoir from a linear regime and use it to define different regions of dynamical behaviour. Next, we study the relationship of two important reservoir parameters, input scaling and spectral radius, on two properties of an artificial task, namely memory and non-linearity.

Dual-Transfer Face Sketch–Photo Synthesis <=SEP=> Recognizing the identity of a sketched face from a face photograph dataset is a critical yet challenging task in many applications, not least law enforcement and criminal investigations. An intelligent sketched face identification system would rely on automatic face sketch synthesis from photographs, thereby avoiding the cost of artists manually drawing sketches. However, conventional face sketch–photo synthesis methods tend to generate sketches that are consistent with the artists’drawing styles. Identity-specific information is often overlooked, leading to unsatisfactory identity verification and recognition performance. In this paper, we discuss the reasons why conventional methods fail to recover identity-specific information. Then, we propose a novel dual-transfer face sketch–photo synthesis framework composed of an inter-domain transfer process and an intra-domain transfer process. In the inter-domain transfer, a regressor of the test photograph with respect to the training photographs is learned and transferred to the sketch domain, ensuring the recovery of common facial structures during synthesis. In the intra-domain transfer, a mapping characterizing the relationship between photographs and sketches is learned and transferred across different identities, such that the loss of identity-specific information is suppressed during synthesis. The fusion of information recovered by the two processes is straightforward by virtue of an ad hoc information splitting strategy. We employ both linear and nonlinear formulations to instantiate the proposed framework. Experiments on The Chinese University of Hong Kong face sketch database demonstrate that compared to the current state-of-the-art the proposed framework produces more identifiable facial structures and yields higher face recognition performance in both the photo and sketch domains.

An improved LLC resonant inverter for induction heating with asymmetrical control <=SEP=> This paper proposes a modified LLC resonant load configuration of a full-bridge inverter for induction heating applications by using asymmetrical voltage cancellation control. The proposed control method is implemented in a full-bridge inverter topology. With the use of a phase-locked loop control, the operating frequency is automatically adjusted to maintain a small constant lagging phase angle under load parameter variation. The output power is controlled using the asymmetrical voltage cancellation technique. The LLC resonant tank is designed with a matching transformer in between the series inductor and paralleled LC resonant tank for short circuit protection capability of the matching transformer and the induction coil. The validity of the proposed method is verified through computer simulation and hardware experiment at the operating frequency of 108.7 to 110.6 kHz.

Paraphrasing for Style <=SEP=> We present initial investigation into the task of paraphrasing language while targeting a particular writing style. The plays of William Shakespeare and their modern translations are used as a testbed for evaluating paraphrase systems targeting a specific style of writing. We show that even with a relatively small amount of parallel training data, it is possible to learn paraphrase models which capture stylistic phenomena, and these models outperform baselines based on dictionaries and out-of-domain parallel text. In addition we present an initial investigation into automatic evaluation metrics for paraphrasing writing style. To the best of our knowledge this is the first work to investigate the task of paraphrasing text with the goal of targeting a specific style of writing.

Measurements and Modelling of Base Station Power Consumption under Real Traffic Loads † <=SEP=> Base stations represent the main contributor to the energy consumption of a mobile cellular network. Since traffic load in mobile networks significantly varies during a working or weekend day, it is important to quantify the influence of these variations on the base station power consumption. Therefore, this paper investigates changes in the instantaneous power consumption of GSM (Global System for Mobile Communications) and UMTS (Universal Mobile Telecommunications System) base stations according to their respective traffic load. The real data in terms of the power consumption and traffic load have been obtained from continuous measurements performed on a fully operated base station site. Measurements show the existence of a direct relationship between base station traffic load and power consumption. According to this relationship, we develop a linear power consumption model for base stations of both technologies. This paper also gives an overview of the most important concepts which are being proposed to make cellular networks more energy-efficient.

Routing questions to appropriate answerers in community question answering services <=SEP=> Community Question Answering (CQA) service provides a platform for increasing number of users to ask and answer for their own needs but unanswered questions still exist within a fixed period. To address this, the paper aims to route questions to the right answerers who have a top rank in accordance of their previous answering performance. In order to rank the answerers, we propose a framework called Question Routing (QR) which consists of four phases: (1) performance profiling, (2) expertise estimation, (3) availability estimation, and (4) answerer ranking. Applying the framework, we conduct experiments with Yahoo! Answers dataset and the results demonstrate that on average each of 1,713 testing questions obtains at least one answer if it is routed to the top 20 ranked answerers.

Punctuation Prediction with Transition-based Parsing <=SEP=> Punctuations are not available in automatic speech recognition outputs, which could create barriers to many subsequent text processing tasks. This paper proposes a novel method to predict punctuation symbols for the stream of words in transcribed speech texts. Our method jointly performs parsing and punctuation prediction by integrating a rich set of syntactic features when processing words from left to right. It can exploit a global view to capture long-range dependencies for punctuation prediction with linear complexity. The experimental results on the test data sets of IWSLT and TDT4 show that our method can achieve high-level performance in punctuation prediction over the stream of words in transcribed speech text.

SRFeat: Single Image Super-Resolution with Feature Discrimination <=SEP=> Generative adversarial networks (GANs) have recently been adopted to single image super-resolution (SISR) and showed impressive results with realistically synthesized high-frequency textures. However, the results of such GAN-based approaches tend to include less meaningful high-frequency noise that is irrelevant to the input image. In this paper, we propose a novel GAN-based SISR method that overcomes the limitation and produces more realistic results by attaching an additional discriminator that works in the feature domain. Our additional discriminator encourages the generator to produce structural high-frequency features rather than noisy artifacts as it distinguishes synthetic and real images in terms of features. We also design a new generator that utilizes long-range skip connections so that information between distant layers can be transferred more effectively. Experiments show that our method achieves the state-of-the-art performance in terms of both PSNR and perceptual quality compared to recent GAN-based methods.

Bias and causal associations in observational research <=SEP=> Readers of medical literature need to consider two types of validity, internal and external. Internal validity means that the study measured what it set out to; external validity is the ability to generalise from the study to the reader's patients. With respect to internal validity, selection bias, information bias, and confounding are present to some degree in all observational research. Selection bias stems from an absence of comparability between groups being studied. Information bias results from incorrect determination of exposure, outcome, or both. The effect of information bias depends on its type. If information is gathered differently for one group than for another, bias results. By contrast, non-differential misclassification tends to obscure real differences. Confounding is a mixing or blurring of effects: a researcher attempts to relate an exposure to an outcome but actually measures the effect of a third factor (the confounding variable). Confounding can be controlled in several ways: restriction, matching, stratification, and more sophisticated multivariate techniques. If a reader cannot explain away study results on the basis of selection, information, or confounding bias, then chance might be another explanation. Chance should be examined last, however, since these biases can account for highly significant, though bogus results. Differentiation between spurious, indirect, and causal associations can be difficult. Criteria such as temporal sequence, strength and consistency of an association, and evidence of a dose-response effect lend support to a causal link.