Query: Full-Duplex Cooperative Non-Orthogonal Multiple Access With Beamforming and Energy Harvesting

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Introduction to Algorithms <=SEP=> problems To understand the class of polynomial-time solvable proble ms, we must first have a formal notion of what a “problem” is. We define anbstract problemQ to be a binary relation on a set I of probleminstancesand a setS of problemsolutions. For example, an instance for SHORTEST-PATH is a triple consi sting of a graph and two vertices. A solution is a sequence of vertices in the g raph, with perhaps the empty sequence denoting that no path exists. The problem SHORTEST-PATH itself is the relation that associates each instance of a gra ph and two vertices with a shortest path in the graph that connects the two vertices. S ince shortest paths are not necessarily unique, a given problem instance may have mo r than one solution. This formulation of an abstract problem is more general than is required for our purposes. As we saw above, the theory of NP-completeness res tricts attention to decision problems : those having a yes/no solution. In this case, we can view an abstract decision problem as a function that maps the instan ce setI to the solution set {0, 1}. For example, a decision problem related to SHORTEST-PATH i s the problem PATH that we saw earlier. If i = 〈G,u, v,k〉 is an instance of the decision problem PATH, then PATH(i ) = 1 (yes) if a shortest path fromu to v has at mostk edges, and PATH (i ) = 0 (no) otherwise. Many abstract problems are not decision problems, but rather optimization problems , in which some value must be minimized or maximized. As we saw above, however, it is usual ly a simple matter to recast an optimization problem as a decision problem that is no harder. 1See Hopcroft and Ullman [156] or Lewis and Papadimitriou [20 4] for a thorough treatment of the Turing-machine model. 34.1 Polynomial time 973

Passive Self-Interference Suppression for Full-Duplex Infrastructure Nodes <=SEP=> Recent research results have demonstrated the feasibility of full-duplex wireless communication for short-range links. Although the focus of the previous works has been active cancellation of the self-interference signal, a majority of the overall self-interference suppression is often due to passive suppression, i.e., isolation of the transmit and receive antennas. We present a measurement-based study of the capabilities and limitations of three key mechanisms for passive self-interference suppression: directional isolation, absorptive shielding, and cross-polarization. The study demonstrates that more than 70 dB of passive suppression can be achieved in certain environments, but also establishes two results on the limitations of passive suppression: (1) environmental reflections limit the amount of passive suppression that can be achieved, and (2) passive suppression, in general, increases the frequency selectivity of the residual self-interference signal. These results suggest two design implications: (1) deployments of full-duplex infrastructure nodes should minimize near-antenna reflectors, and (2) active cancellation in concatenation with passive suppression should employ higher-order filters or per-subcarrier cancellation.

System-level performance evaluation of downlink non-orthogonal multiple access (NOMA) <=SEP=> As a promising downlink multiple access scheme for further LTE enhancement and future radio access (FRA), this paper investigates the system-level performance of non-orthogonal multiple access (NOMA) with a successive interference canceller (SIC) on the receiver side. The goal is to clarify the potential gains of NOMA over orthogonal multiple access (OMA) such as OFDMA, taking into account key link adaptation functionalities of the LTE radio interface such as adaptive modulation and coding (AMC), hybrid automatic repeat request (HARQ), time/frequency-domain scheduling, and outer loop link adaptation (OLLA), in addition to NOMA specific functionalities such as dynamic multi-user power allocation. Based on computer simulations, we show under multiple configurations that the system-level performance achieved by NOMA is superior to that for OMA.

Non-Orthogonal Multiple Access With Cooperative Full-Duplex Relaying <=SEP=> We propose a full-duplex (FD) cooperative non-orthogonal multiple access (NOMA) system with dual users, where a dedicated FD relay assists the information transmission to the user with weak channel condition. Under the realistic assumption of imperfect self-interference cancellation, the achievable outage probability of both users and ergodic sum capacity are investigated, and exact analytical expressions are derived. Simulation results demonstrate that the proposed FD cooperative NOMA system attains better performance than the half-duplex cooperative NOMA system in the moderate signal-to-noise ratio regime.

An Analysis of Several Heuristics for the Traveling Salesman Problem <=SEP=> Several polynomial time algorithms finding "good," but not necessarily optimal, tours for the traveling salesman problem are considered. We measure the closeness of a tour by the ratio of the obtained tour length to the minimal tour length. For the nearest neighbor method, we show the ratio is bounded above by a logarithmic function of the number of nodes. We also provide a logarithmic lower bound on the worst case. A class of approximation methods we call insertion methods are studied, and these are also shown to have a logarithmic upper bound. For two specific insertion methods, which we call nearest insertion and cheapest insertion, the ratio is shown to have a constant upper bound of 2, and examples are provided that come arbitrarily close to this upper bound. It is also shown that for any n => 8, there are traveling salesman problems with n nodes having tours which cannot be improved by making n/4 edge changes, but for which the ratio is 2(1l/n). Key words, traveling salesman problem, approximation algorithm, k-optimal, minimal spanning tree, triangle inequality

A survey of vertical handover decision algorithms in Fourth Generation heterogeneous wireless networks <=SEP=> 1389-1286/$ see front matter 2010 Elsevier B.V doi:10.1016/j.comnet.2010.02.006 * Corresponding author. Tel.: +61 3 99053503; fa E-mail address: ASekerci@ieee.org (Y. Ahmet S ek Vertical handover decision (VHD) algorithms are essential components of the architecture of the forthcoming Fourth Generation (4G) heterogeneous wireless networks. These algorithms need to be designed to provide the required Quality of Service (QoS) to a wide range of applications while allowing seamless roaming among a multitude of access network technologies. In this paper, we present a comprehensive survey of the VHD algorithms designed to satisfy these requirements. To offer a systematic comparison, we categorize the algorithms into four groups based on the main handover decision criterion used. Also, to evaluate tradeoffs between their complexity of implementation and efficiency, we discuss three representative VHD algorithms in each group. 2010 Elsevier B.V. All rights reserved.

Animal Navigation: Path Integration, Visual Landmarks and Cognitive Maps <=SEP=> Animals typically have several navigational strategies available to them. Interactions between these strategies can reduce navigational errors and may lead to the emergence of new capacities.

A Survey of Model Comparison Approaches and Applications <=SEP=> This survey paper presents the current state of model comparison as it applies to Model-Driven Engineering. We look specifically at how model matching is accomplished, the application of the approaches, and the types of models that approaches are intended to work with. Our paper also indicates future trends and directions. We find that many of the latest model comparison techniques are geared towards facilitating arbitrary meta models and use similarity-based matching. Thus far, model versioning is the most prevalent application of model comparison. Recently, however, work on comparison for versioning has begun to stagnate, giving way to other applications. Lastly, there is wide variance among the tools in the amount of user effort required to perform model comparison, as some require more effort to facilitate more generality and expressive power.

A topological hierarchy for functions on triangulated surfaces <=SEP=> We combine topological and geometric methods to construct a multiresolution representation for a function over a two-dimensional domain. In a preprocessing stage, we create the Morse-Smale complex of the function and progressively simplify its topology by cancelling pairs of critical points. Based on a simple notion of dependency among these cancellations, we construct a hierarchical data structure supporting traversal and reconstruction operations similarly to traditional geometry-based representations. We use this data structure to extract topologically valid approximations that satisfy error bounds provided at runtime.

CampusSense — A smart vehicle parking monitoring and management system using ANPR cameras and android phones <=SEP=> Vehicle parking monitoring and management has become a big challenge for educational institutions with increasing enrollments, high percentage of vehicle ownership and decreasing parking supply which in result triggering blockage of vehicle, congestion, wastage of time and money. In university campuses particularly in Kingdom of Saudi Arabia, vehicle parking monitoring and management problem is getting worse and more frustrating due to the fact that majority of students, faculty and staff members own cars and drive through them to the university campuses. These common problems include finding out people (evidence) who are responsible for the damages (hitting, scraping, scratching and dents) to other cars and the blockage of car due to wrong car parking which takes much time to locate the owner of the car. Moreover, locating or forgetting their car park location another difficulty that is often faced by the students, faculty and staff members. The existing cameras located at the parking lots are only for video surveillance and cannot help in such situations as there is a lack of proper vehicle parking monitoring and management system. To cope with above mentioned problems and to ensure a better parking experience by accommodating increasing number of vehicles in a proper convenient manner, we propose a smart vehicle parking monitoring and management system called CampusSense. In CampusSense, Automatic Number Plate Recognition (ANPR) cameras and android based mobile application is developed to efficiently monitor, manage and protect the parking facilities at university campuses. Parking problems around the university campus faced by the students, faculty and staff members are analyzed by conducting a survey.

Angry, disgusted, or afraid? Studies on the malleability of emotion perception. <=SEP=> Current theories of emotion perception posit that basic facial expressions signal categorically discrete emotions or affective dimensions of valence and arousal. In both cases, the information is thought to be directly "read out" from the face in a way that is largely immune to context. In contrast, the three studies reported here demonstrated that identical facial configurations convey strikingly different emotions and dimensional values depending on the affective context in which they are embedded. This effect is modulated by the similarity between the target facial expression and the facial expression typically associated with the context. Moreover, by monitoring eye movements, we demonstrated that characteristic fixation patterns previously thought to be determined solely by the facial expression are systematically modulated by emotional context already at very early stages of visual processing, even by the first time the face is fixated. Our results indicate that the perception of basic facial expressions is not context invariant and can be categorically altered by context at early perceptual levels.

Simulator sickness in virtual display gaming: a comparison of stereoscopic and non-stereoscopic situations <=SEP=> In this paper we compare simulator sickness symptoms produced by racing game in three different conditions. In the first experiment the participants played the Need for Speed car racing game with an ordinary 17" display and in the second and third experiments they used a head-worn virtual display for the game playing. The difference between experiments 2 and 3 was in the use of stereoscopy, as in the third experiment the car racing game was seen in stereoscopic three-dimensions. Our results indicated that there were no significant differences in sickness symptoms when we compared the ordinary display and the virtual display in non-stereoscopic mode. In stereoscopic condition the eye strain and disorientation symptoms were significantly elevated compared to the ordinary display. We conclude that using a virtual display as an accessory in a mobile device is a viable alternative, because the non-stereoscopic virtual display did not produce significantly more sickness symptoms compared to ordinary game playing.

Assessment of lexical semantic judgment abilities in alcohol-dependent subjects: An fMRI study <=SEP=> Neuropsychological studies have shown that alcohol dependence is associated with neurocognitive deficits in tasks requiring memory, perceptual motor skills, abstraction and problem solving, whereas language skills are relatively spared in alcoholics despite structural abnormalities in the language-related brain regions. To investigate the preserved mechanisms of language processing in alcohol-dependents, functional brain imaging was undertaken in healthy controls (n=18) and alcohol-dependents (n=16) while completing a lexical semantic judgment task in a 3 T MR scanner. Behavioural data indicated that alcohol-dependents took more time than controls for performing the task but there was no significant difference in their response accuracy. fMRI data analysis revealed that while performing the task, the alcoholics showed enhanced activations in left supramarginal gyrus, precuneus bilaterally, left angular gyrus, and left middle temporal gyrus as compared to control subjects. The extensive activations observed in alcoholics as compared to controls suggest that alcoholics recruit additional brain areas to meet the behavioural demands for equivalent task performance. The results are consistent with previous fMRI studies suggesting compensatory mechanisms for the execution of task for showing an equivalent performance or decreased neural efficiency of relevant brain networks. However, on direct comparison of the two groups, the results did not survive correction for multiple comparisons; therefore, the present findings need further exploration.

Markov Random Field model for single image defogging <=SEP=> Fog reduces contrast and thus the visibility of vehicles and obstacles for drivers. Each year, this causes traffic accidents. Fog is caused by a high concentration of very fine water droplets in the air. When light hits these droplets, it is scattered and this results in a dense white background, called the atmospheric veil. As pointed in [1], Advanced Driver Assistance Systems (ADAS) based on the display of defogged images from a camera may help the driver by improving objects visibility in the image and thus may lead to a decrease of fatality and injury rates. In the last few years, the problem of single image defogging has attracted attention in the image processing community. Being an ill-posed problem, several methods have been proposed. However, a few among of these methods are dedicated to the processing of road images. One of the first exception is the method in [2], [1] where a planar constraint is introduced to improve the restoration of the road area, assuming an approximately flat road. The single image defogging problem being ill-posed, the choice of the Bayesian approach seems adequate to set this problem as an inference problem. A first Markov Random Field (MRF) approach of the problem has been proposed recently in [3]. However, this method is not dedicated to road images. In this paper, we propose a novel MRF model of the single image defogging problem which applies to all kinds of images but can also easily be refined to obtain better results on road images using the planar constraint. A comparative study and quantitative evaluation with several state-of-the-art algorithms is presented. This evaluation demonstrates that the proposed MRF model allows to derive a new algorithm which produces better quality results, in particular in case of a noisy input image.

Log-Euclidean Metric Learning on Symmetric Positive Definite Manifold with Application to Image Set Classification <=SEP=> The manifold of Symmetric Positive Definite (SPD) matrices has been successfully used for data representation in image set classification. By endowing the SPD manifold with LogEuclidean Metric, existing methods typically work on vector-forms of SPD matrix logarithms. This however not only inevitably distorts the geometrical structure of the space of SPD matrix logarithms but also brings low efficiency especially when the dimensionality of SPD matrix is high. To overcome this limitation, we propose a novel metric learning approach to work directly on logarithms of SPD matrices. Specifically, our method aims to learn a tangent map that can directly transform the matrix logarithms from the original tangent space to a new tangent space of more discriminability. Under the tangent map framework, the novel metric learning can then be formulated as an optimization problem of seeking a Mahalanobis-like matrix, which can take the advantage of traditional metric learning techniques. Extensive evaluations on several image set classification tasks demonstrate the effectiveness of our proposed metric learning method.

Facial expression recognition in peripheral versus central vision: role of the eyes and the mouth. <=SEP=> This study investigated facial expression recognition in peripheral relative to central vision, and the factors accounting for the recognition advantage of some expressions in the visual periphery. Whole faces or only the eyes or the mouth regions were presented for 150 ms, either at fixation or extrafoveally (2.5° or 6°), followed by a backward mask and a probe word. Results indicated that (a) all the basic expressions were recognized above chance level, although performance in peripheral vision was less impaired for happy than for non-happy expressions, (b) the happy face advantage remained when only the mouth region was presented, and (c) the smiling mouth was the most visually salient and most distinctive facial feature of all expressions. This suggests that the saliency and the diagnostic value of the smile account for the advantage in happy face recognition in peripheral vision. Because of saliency, the smiling mouth accrues sensory gain and becomes resistant to visual degradation due to stimulus eccentricity, thus remaining accessible extrafoveally. Because of diagnostic value, the smile provides a distinctive single cue of facial happiness, thus bypassing integration of face parts and reducing susceptibility to breakdown of configural processing in peripheral vision.

Classifying streaming of Twitter data based on sentiment analysis using hybridization <=SEP=> Twitter is a social media that developed rapidly in today’s modern world. As millions of Twitter messages are sent day by day, the value and importance of developing a new technique for detecting spammers become significant. Moreover, legitimate users are affected by means of spams in the form of unwanted URLs, irrelevant messages, etc. Another hot topic of research is sentiment analysis that is based on each tweet sent by the user and opinion mining of the customer reviews. Most commonly natural language processing is used for sentiment analysis. The text is collected from user’s tweets by opinion mining and automatic sentiment analysis that are oriented with ternary classifications, such as “positive,” “neutral,” and “negative.” Due to limited size, unstructured nature, misspells, slangs, and abbreviations, it is more challenging for researchers to find sentiments for Twitter data. In this paper, we collected 600 million public tweets using URL-based security tool and feature generation is applied for sentiment analysis. The ternary classification is processed based on preprocessing technique, and the results of tweets sent by the users are obtained. We use a hybridization technique using two optimization algorithms and one machine learning classifier, namely particle swarm optimization and genetic algorithm and decision tree for classification accuracy by sentiment analysis. The results are compared with previous works, and our proposed method shows a better analysis than that of other classifiers.

Semi-autonomous flying robot for physical interaction with environment <=SEP=> This contribution presents the first results of the development of an unmanned aerial vehicle (UAV) which is capable of applying force to a wall while maintaining flight stability. This is a novel idea since UAVs are used so far only for tasks without physical contact to the surrounding objects. The basis for the work presented is a quadrotor system which is stabilized with an inertial measurement unit. As a new approach an additional actuator was added to generate forces in physical contact while the UAV stays horizontal. A control architecture based on ultrasonic distance sensors and a CMOS-camera is proposed. The performance of the system was proved by several flight tests. Potential applications of the system can be physical tasks at high places like cleaning windows or walls as well as rescue or maintenance tasks.

Bi-Modal DRAM Cache: Improving Hit Rate, Hit Latency and Bandwidth <=SEP=> In this paper, we present Bi-Modal Cache - a flexible stacked DRAM cache organization which simultaneously achieves several objectives: (i) improved cache hit ratio, (ii) moving the tag storage overhead to DRAM, (iii) lower cache hit latency than tags-in-SRAM, and (iv) reduction in off-chip bandwidth wastage. The Bi-Modal Cache addresses the miss rate versus off-chip bandwidth dilemma by organizing the data in a bi-modal fashion - blocks with high spatial locality are organized as large blocks and those with little spatial locality as small blocks. By adaptively selecting the right granularity of storage for individual blocks at run-time, the proposed DRAM cache organization is able to make judicious use of the available DRAM cache capacity as well as reduce the off-chip memory bandwidth consumption. The Bi-Modal Cache improves cache hit latency despite moving the metadata to DRAM by means of a small SRAM based Way Locator. Further by leveraging the tremendous internal bandwidth and capacity that stacked DRAM organizations provide, the Bi-Modal Cache enables efficient concurrent accesses to tags and data to reduce hit time. Through detailed simulations, we demonstrate that the Bi-Modal Cache achieves overall performance improvement (in terms of Average Normalized Turnaround Time (ANTT)) of 10.8%, 13.8% and 14.0% in 4-core, 8-core and 16-core workloads respectively.

Intangible benefits valuation in ERP projects <=SEP=> The development, implementation and ownership of information systems, especially large-scale systems such as enterprise resource planning (ERP), has become progressively longer in duration and more cost intensive. As a result, IS managers are being required to justify projects financially based on their return. Historically, information systems have been difficult to quantify in monetary terms because of the intangible nature of many of the derived benefits, e.g. improved customer service. Using the case study methodology, this paper examines an attempt by a large computer manufacturer to incorporate intangibles into traditional cost–benefit analysis in an ERP project. The paper reviews the importance of intangibles, lists intangible benefits that are important in ERP projects and demonstrates the use of a scheme through which they can be incorporated into traditional evaluation techniques.

Modeling of electric vehicle loads for power flow analysis based on PSAT <=SEP=> This paper proposes the modeling of electric vehicle(EV) loads for power flow analysis based on User Define Models (UDMs) in power system analysis toolbox (PSAT) programming, According to the development of EV technology especially motor controller and battery, the EV has totally designed and made for using in city area as small city cars. To study the performance of EV, this aims to present the model of EV loads for using to solve power flow analysis in the real power system. EV load is modeled as the function box equivalent on PSAT that can connect to the single line diagram of power system model. The IEEE 14 bus system is selected for simulating the performance of EV and charging station which compared between PQ load base case and EV load. The simulation result showed that the EV load was installed at bus No.14. The rated power of EV load was increased from 5.0 p.u. to 79 p.u. This proposed EV load model can be used to solve the power flow analysis with continuation power flow (CPF) method. The EV load model is directly effected to voltage stability margin when the EV load increased. This study can be verified that proposed EV load can use to study the EV load in the future works.

Modular equalization architecture using inter-module and switchless intra-module equalizer for energy storage system <=SEP=> This paper proposes a novel modular equalization architecture using inter-module and intra-module equalizers for energy storage systems comprising multiple cells/modules connected in series. In the proposed equalization architecture, cells in a module is equalized by a series-resonant voltage multiplier (SRVM)-based intra-module equalizer while module voltages are unified by a switched capacitor converter (SCC)-based inter-module equalizer. A square wave voltage generated at a switching node of the SCC-based inter-module equalizer is utilized to drive the SRVM-based intra-module equalizer so that the SRVM-based intra-module equalizer can be totally switchless topology. The required switch count of the proposed equalization architecture can be dramatically reduced compared to conventional architectures, allowing simplified circuitry. The proposed equalization architecture is modular and allows different equalizer topologies to be used for inter- and intra-module equalizers, offering good modularity and design flexibility. The derivation procedure of the proposed equalization architecture is explained, followed by separate analyses for the SCC-based inter-module equalizer and SRVM-based intra-module equalizer. An experimental equalization test for three supercapacitor (SC) modules, each consisting of four cells in series, was performed from an initially voltage-imbalanced condition. Module and cell voltages were equalized at different rates, and the equalization performance of the proposed modular equalization architecture was successfully demonstrated.

Nonnegative Matrix Factorization with the Itakura-Saito Divergence: With Application to Music Analysis <=SEP=> This letter presents theoretical, algorithmic, and experimental results about nonnegative matrix factorization (NMF) with the Itakura-Saito (IS) divergence. We describe how IS-NMF is underlaid by a well-defined statistical model of superimposed gaussian components and is equivalent to maximum likelihood estimation of variance parameters. This setting can accommodate regularization constraints on the factors through Bayesian priors. In particular, inverse-gamma and gamma Markov chain priors are considered in this work. Estimation can be carried out using a space-alternating generalized expectation-maximization (SAGE) algorithm; this leads to a novel type of NMF algorithm, whose convergence to a stationary point of the IS cost function is guaranteed. We also discuss the links between the IS divergence and other cost functions used in NMF, in particular, the Euclidean distance and the generalized Kullback-Leibler (KL) divergence. As such, we describe how IS-NMF can also be performed using a gradient multiplicative algorithm (a standard algorithm structure in NMF) whose convergence is observed in practice, though not proven. Finally, we report a furnished experimental comparative study of Euclidean-NMF, KL-NMF, and IS-NMF algorithms applied to the power spectrogram of a short piano sequence recorded in real conditions, with various initializations and model orders. Then we show how IS-NMF can successfully be employed for denoising and upmix (mono to stereo conversion) of an original piece of early jazz music. These experiments indicate that IS-NMF correctly captures the semantics of audio and is better suited to the representation of music signals than NMF with the usual Euclidean and KL costs.

The Life Satisfaction Advantage of Being Married and Gender Specialization <=SEP=> This investigation examined whether the life satisfaction advantage of married over unmarried persons decreased over the last three decades, and whether the changes in the contextual gender specialization explained this trend. The author used representative data from the World Values Survey–European Values Study (WVS–EVS)-integrated data set for 87 countries (N = 292,525) covering a period of 29 years. Results showed that the life satisfaction advantage of being married decreased among men but not among women. The analysis did not support the hypothesis that contextual gender specialization shaped the observed trend. Only in developed countries the declining contextual specialization correlated with smaller life satisfaction advantage of being married. This evidence suggests that the advantages of marriage are greater under conditions that support freedom of choice rather than economic necessity. (130 words)

Characterizing the usability of interactive applications through query log analysis <=SEP=> People routinely rely on Internet search engines to support their use of interactive systems: they issue queries to learn how to accomplish tasks, troubleshoot problems, and otherwise educate themselves on products. Given this common behavior, we argue that search query logs can usefully augment traditional usability methods by revealing the primary tasks and needs of a product's user population. We term this use of search query logs CUTS - characterizing usability through search. In this paper, we introduce CUTS and describe an automated process for harvesting, ordering, labeling, filtering, and grouping search queries related to a given product. Importantly, this data set can be assembled in minutes, is timely, has a high degree of ecological validity, and is arguably less prone to self-selection bias than data gathered via traditional usability methods. We demonstrate the utility of this approach by applying it to a number of popular software and hardware systems.

Hierarchical classification of Web content <=SEP=> This paper explores the use of hierarchical structure for classifying a large, heterogeneous collection of web content. The hierarchical structure is initially used to train different second-level classifiers. In the hierarchical case, a model is learned to distinguish a second-level category from other categories within the same top level. In the flat non-hierarchical case, a model distinguishes a second-level category from all other second-level categories. Scoring rules can further take advantage of the hierarchy by considering only second-level categories that exceed a threshold at the top level.
We use support vector machine (SVM) classifiers, which have been shown to be efficient and effective for classification, but not previously explored in the context of hierarchical classification. We found small advantages in accuracy for hierarchical models over flat models. For the hierarchical approach, we found the same accuracy using a sequential Boolean decision rule and a multiplicative decision rule. Since the sequential approach is much more efficient, requiring only 14%-16% of the comparisons used in the other approaches, we find it to be a good choice for classifying text into large hierarchical structures.

UFMC system performance analysis for discrete narrow-band private networks <=SEP=> In this paper, the performance of universal-filtered multi-carrier (UFMC) system is analyzed. Specifically, the UFMC signals are generated with Dolph-Chebyshev, Hamming and Hanning filtering. The characteristics of UFMC signals are also compared with OFDM signal, in both software and hardware-in-the-loop simulations. Experimental results show that UFMC signals have better performance than OFDM signal, by means of side-lobe attenuation, bit-error-ratio (BER) and Error Vector Magnitude (EVM). The results indicate that the UFMC signal is more suitable than OFDM signal for discrete narrow-band private networks. The results can provide useful information on the design of multi-carrier radio systems.

Following My Head and My Heart: Integrating Preschoolers' Empathy, Theory of Mind, and Moral Judgments. <=SEP=> Associations among hypothetical, prototypic moral, and conventional judgments; theory of mind (ToM); empathy; and personal distress were examined in 108 socioeconomically diverse preschoolers (Mage  = 42.94 months, SD = 1.42). Repeated measures analysis of covariance with empathy, false beliefs, and their interaction as covariates indicated that empathy was significantly associated with judgments of greater moral but not conventional transgression severity, particularly for psychological harm, and with deserved punishment for unfairness. False beliefs were associated with (combined) moral criterion judgments of rule and authority independence and inalterability. Empathy also was positively associated with criterion judgments but only for children low in ToM. Personal distress was unrelated to judgments. Results demonstrate the importance of both affective and cognitive processes in preschoolers' moral judgments.

A 5-MHz 91% Peak-Power-Efficiency Buck Regulator With Auto-Selectable Peak- and Valley-Current Control <=SEP=> This paper presents a multi-MHz buck regulator for portable applications using an auto-selectable peak- and valley-current control (ASPVCC) scheme. The proposed ASPVCC scheme can enable the current-mode buck regulator to reduce the settling-time requirement of the current sensing by two times. In addition, the dynamically biased shunt feedback technique is employed to improve the sensing speed and the sensing accuracy of both the peak and valley current sensors. With both ASPVCC scheme and advanced current sensors, the buck regulator can thus operate at high switching frequencies with a wide range of duty ratios for reducing the required off-chip inductance. The proposed current-mode buck regulator was fabricated in a standard 0.35-μm CMOS process and occupies a small chip area of 0.54 mm2. Measurement results show that the buck regulator can deliver a maximum output current of 500 mA, operate at 5 MHz with a wide duty-ratio range of about 0.6, use a small-value off-chip inductor of 1 μH, and achieve the peak power efficiency of 91%.

Low-Quality Product Review Detection in Opinion Summarization <=SEP=> Product reviews posted at online shopping sites vary greatly in quality. This paper addresses the problem of detecting lowquality product reviews. Three types of biases in the existing evaluation standard of product reviews are discovered. To assess the quality of product reviews, a set of specifications for judging the quality of reviews is first defined. A classificationbased approach is proposed to detect the low-quality reviews. We apply the proposed approach to enhance opinion summarization in a two-stage framework. Experimental results show that the proposed approach effectively (1) discriminates lowquality reviews from high-quality ones and (2) enhances the task of opinion summarization by detecting and filtering lowquality reviews.