Query: Speech Emotion Recognition with Emotion-Pair Based Framework Considering Emotion Distribution Information in Dimensional Emotion Space

Relevant passages:
Reducing Multiclass to Binary: A Unifying Approach for Margin Classifiers <=SEP=> We present a unifying framework for studying the solution of multiclass categorization problems by reducing them to multiple binary problems that are then solved using a margin-based binary learning algorithm. The proposed framework unifies some of the most popular approaches in which each class is compared against all others, or in which all pairs of classes are compared to each other, or in which output codes with error-correcting properties are used. We propose a general method for combining the classifiers generated on the binary problems, and we prove a general empirical multiclass loss bound given the empirical loss of the individual binary learning algorithms. The scheme and the corresponding bounds apply to many popular classification learning algorithms including support-vector machines, AdaBoost, regression, logistic regression and decision-tree algorithms. We also give a multiclass generalization error analysis for general output codes with AdaBoost as the binary learner. Experimental results with SVM and AdaBoost show that our scheme provides a viable alternative to the most commonly used multiclass algorithms.

Analysis of Emotionally Salient Aspects of Fundamental Frequency for Emotion Detection <=SEP=> During expressive speech, the voice is enriched to convey not only the intended semantic message but also the emotional state of the speaker. The pitch contour is one of the important properties of speech that is affected by this emotional modulation. Although pitch features have been commonly used to recognize emotions, it is not clear what aspects of the pitch contour are the most emotionally salient. This paper presents an analysis of the statistics derived from the pitch contour. First, pitch features derived from emotional speech samples are compared with the ones derived from neutral speech, by using symmetric Kullback-Leibler distance. Then, the emotionally discriminative power of the pitch features is quantified by comparing nested logistic regression models. The results indicate that gross pitch contour statistics such as mean, maximum, minimum, and range are more emotionally prominent than features describing the pitch shape. Also, analyzing the pitch statistics at the utterance level is found to be more accurate and robust than analyzing the pitch statistics for shorter speech regions (e.g., voiced segments). Finally, the best features are selected to build a binary emotion detection system for distinguishing between emotional versus neutral speech. A new two-step approach is proposed. In the first step, reference models for the pitch features are trained with neutral speech, and the input features are contrasted with the neutral model. In the second step, a fitness measure is used to assess whether the input speech is similar to, in the case of neutral speech, or different from, in the case of emotional speech, the reference models. The proposed approach is tested with four acted emotional databases spanning different emotional categories, recording settings, speakers and languages. The results show that the recognition accuracy of the system is over 77% just with the pitch features (baseline 50%). When compared to conventional classification schemes, the proposed approach performs better in terms of both accuracy and robustness.

The role of voice quality in communicating emotion, mood and attitude <=SEP=> This paper explores the role of voice quality in the communication of emotions, moods and attitudes. Listeners reactions to an utterance synthesised with seven different voice qualities were elicited in terms of pairs of opposing affective attributes. The voice qualities included harsh voice, tense voice, modal voice, breathy voice, whispery voice, creaky voice and lax–creaky voice. These were synthesised using a formant synthesiser, and the voice source parameter settings were guided by prior analytic studies as well as auditory judgements. Results offer support for some past observations on the association of voice quality and affect, and suggest a number of refinements in some cases. Listeners ratings further suggest that these qualities are considerably more effective in signalling milder affective states than the strong emotions. It is clear that there is no one-to-one mapping between voice quality and affect: rather a given quality tends to be associated with a cluster of affective attributes. 2002 Elsevier Science B.V. All rights reserved.

Emotion recognition in human-computer interaction <=SEP=> In this paper, we outline the approach we have developed to construct an emotion-recognising system. It is based on guidance from psychological studies of emotion, as well as from the nature of emotion in its interaction with attention. A neural network architecture is constructed to be able to handle the fusion of different modalities (facial features, prosody and lexical content in speech). Results from the network are given and their implications discussed, as are implications for future direction for the research.

New Support Vector Algorithms <=SEP=> We propose a new class of support vector algorithms for regression and classification. In these algorithms, a parameter lets one effectively control the number of support vectors. While this can be useful in its own right, the parameterization has the additional benefit of enabling us to eliminate one of the other free parameters of the algorithm: the accuracy parameter in the regression case, and the regularization constant C in the classification case. We describe the algorithms, give some theoretical results concerning the meaning and the choice of , and report experimental results.

RNN-based sequence prediction as an alternative or complement to traditional recommender systems <=SEP=> The recurrent neural networks have the ability to grasp the temporal patterns within the data. This is a property that can be used in order to help a recommender system better taking into account the user past history. Still the dimensionality problem that raises within the recommender system field also raises here as the number of items the system have to be aware of is susceptibility high. Recent research have studied the use of such neural networks at a user’s session level. This thesis rather examines the use of this technique at a whole user’s past history level associated with techniques such as embeddings and softmax sampling in order to accommodate with the high dimensionality. The proposed method results in a sequence prediction model that can be used as is for the recommender task or as a feature within a more complex system.

Developing multiple hypotheses in behavioral ecology <=SEP=> Researchers in behavioral ecology are increasingly turning to research methods that allow the simultaneous evaluation of hypotheses. This approach has great potential to increase our scientific understanding, but researchers interested in the approach should be aware of its long and somewhat contentious history. Also, prior to implementing multiple hypothesis evaluation, researchers should be aware of the importance of clearly specifying a priori hypotheses. This is one of the more difficult aspects of research based on multiple hypothesis evaluation, and we outline and provide examples of three approaches for doing so. Finally, multiple hypothesis evaluation has some limitations important to behavioral ecologists; we discuss two practical issues behavioral ecologists are likely to face.

The Sixth PASCAL Recognizing Textual Entailment Challenge <=SEP=> This paper presents the Fifth Recognizing Textual Entailment Challenge (RTE5). Following the positive experience of the last campaign, RTE-5 has been proposed for the second time as a track at the Text Analysis Conference (TAC). The structure of the RTE-5 Main Task remained unchanged, offering both the traditional two-way task and the threeway task introduced in the previous campaign. Moreover, a pilot Search Task was set up, consisting of finding all the sentences in a set of documents that entail a given hypothesis. 21 teams participated in the campaign, among which 20 in the Main Task (for a total of 54 runs) and 8 in the Pilot Task (for a total of 20 runs). Another important innovation introduced in this campaign was mandatory ablation tests that participants had to perform for all major knowledge resources employed by their systems.

Mindfulness-Based Cognitive Therapy and the Adult ADHD Brain: A Neuropsychotherapeutic Perspective <=SEP=> Attention-deficit/hyperactivity disorder (ADHD) is a recognized serious mental disorder that often persists into adulthood. The symptoms and impairments associated with ADHD often cause significant mental suffering in affected individuals. ADHD has been associated with abnormal neuronal activity in various neuronal circuits, such as the dorsofrontostriatal, orbitofrontostriatal, and frontocerebellar circuits. Psychopharmacological treatment with methylphenidate hydrochloride is recommended as the first-line treatment for ADHD. It is assumed that medication ameliorates ADHD symptoms by improving the functioning of the brain areas affected in the condition. However, side effects, contraindications, or non-response can limit the effectiveness of a psychopharmacological treatment for ADHD. It is therefore necessary to develop non-pharmacological interventions that target neuronal mechanisms associated with the condition in the same way as pharmacological treatment. We think that mindfulness meditation employed as a neuropsychotherapeutic intervention could help patients with ADHD to regulate impaired brain functioning and thereby reduce ADHD symptoms. In this paper, we highlight the mechanisms of such mindfulness meditation, and thus provide a rationale for further research and treatment development from a neuropsychotherapeutic perspective. We conclude that mindfulness meditation employed as a neuropsychotherapeutic intervention in therapy is a promising treatment approach in ADHD.

Image-based reconstruction of wire art <=SEP=> Objects created by connecting and bending wires are common in furniture design, metal sculpting, wire jewelry, etc. Reconstructing such objects with traditional depth and image based methods is extremely difficult due to their unique characteristics such as lack of features, thin elements, and severe self-occlusions. We present a novel image-based method that reconstructs a set of continuous 3D wires used to create such an object, where each wire is composed of an ordered set of 3D curve segments. Our method exploits two main observations: simplicity - wire objects are often created using only a small number of wires, and smoothness - each wire is primarily smoothly bent with sharp features appearing only at joints or isolated points. In light of these observations, we tackle the challenging image correspondence problem across featureless wires by first generating multiple candidate 3D curve segments and then solving a global selection problem that balances between image and smoothness cues to identify the correct 3D curves. Next, we recover a decomposition of such curves into a set of distinct and continuous wires by formulating a multiple traveling salesman problem, which finds smooth paths, i.e., wires, connecting the curves. We demonstrate our method on a wide set of real examples with varying complexity and present high-fidelity results using only 3 images for each object. We provide the source code and data for our work in the project website.

On the Semantics of Self-Unpacking Malware Code ∗ <=SEP=> The rapid increase in attacks on software systems via malware such as viruses, worms, trojans, etc., has made it imperative to develop effective techniques for detecting and analyzing malware binaries. Such binaries are usually transmitted in packed or encrypted form, with the executable payload decrypted dynamically and then executed. In order to reason formally about their execution behavior, therefore, we need semantic descriptions that can capture this self-modifying aspect of their code. However, current approaches to the semantics of programs usually assume that the program code is immutable, which makes them inapplicable to self-unpacking malware code. This paper takes a step towards addressing this problem by describing a formal semantics for self-modifying code. We use our semantics to show how the execution of self-unpacking code can be divided naturally into a sequence of phases, and uses this to show how the behavior of a program can be characterized statically in terms of a program evolution graph. We discuss several applications of our work, including static unpacking and deobfuscation of encrypted malware and static cross-phase code analysis.

An Information Retrieval Approach For Automatically Constructing Software Libraries <=SEP=> Although software reuse presents clear advantages for programmer productivit.y and code reliability, it is not practiced enough. One of the reasons for the only moderate success of reuse is the lack of software libr'lries that facilitate the actual locating and understanding of reusable components. This paper dpscrihes II technology for automatically I\Ssembling large softwar~ libraries that promote softwarp rpuse by helping the user locate the components closest to hfO'r/his neeels Softwarp libraries are aut.omatically assemblfO'd from a set. of Ilnorganizpd component.s by using informat.ion rptripval techniques. The constrllction of the library is done in !.wo steps. First, attribut.es ;up alJtornal.ically pxtracted from nat.urlll language docllmpntat.ion by IIsing a npIV inJexing scheme ba~fO'd an t.he nntinns of lexical affinities anci quantity of inforrnllt.ion. Then, a hierarchy for browsing is alJtomat.iclllly generaterl using a clustering techniq1le that draws only nn the informlltion provided by the attribulps. Thanks to the frfO'p-!.pxt inrlexing se-heme, tools following this approach can accept free-style nat'Jral language 'luprips. This tpChllOlogy h1\.S bfO'en impll"ment .. d in the GURU ~ystpm, whirh h<l5 bpen applied 1.0 construct an organized library of Alx utilities. An exppriment. was rondllrtpd in orrlpr to pvalullte the n·t.rievll\ effectivl"nfO'ss of GURU 1\.5 compl\red to INFOExPLORER a hypprt.pxt lihrary syslplll for Alx 3 on the IBM RISe System/6000 series. We followpr\ Ihe usual evaluation prOf"pr\lJr!' us .. .! in informat.ion rptrifO'vl\l, hased upon recall and precision ml"a5IJrPS, and d"t.erminpd t 1111 I. nllr syst.f'Tll pr>rforms l!i% better on a random test set, while being milch le~s pxpensive to build than INFOEXl'LORF.R.

NOSEP: Nonoverlapping Sequence Pattern Mining With Gap Constraints <=SEP=> Sequence pattern mining aims to discover frequent subsequences as patterns in a single sequence or a sequence database. By combining gap constraints (or flexible wildcards), users can specify special characteristics of the patterns and discover meaningful subsequences suitable for their own application domains, such as finding gene transcription sites from DNA sequences or discovering patterns for time series data classification. Due to the inherent complexity of sequence patterns, including the exponential candidate space with respect to pattern letters and gap constraints, to date, existing sequence pattern mining methods are either incomplete or do not support the Apriori property because the support ratio of a pattern may be greater than that of its subpatterns. Most importantly, patterns discovered by these methods are either too restrictive or too general and cannot represent underlying meaningful knowledge in the sequences. In this paper, we focus on a nonoverlapping sequence pattern mining task with gap constraints, where a nonoverlapping sequence pattern allows sequence letters to be flexibly and maximally utilized for pattern discovery. A new Apriori-based nonoverlapping sequence pattern mining algorithm, NOSEP, is proposed. NOSEP is a complete pattern mining algorithm, which uses a specially designed data structure, Nettree, to calculate the exact occurrence of a pattern in the sequence. Experimental results and comparisons on biology DNA sequences, time series data, and Gazelle datasets demonstrate the efficiency of the proposed algorithm and the uniqueness of nonoverlapping sequence patterns compared to other methods.

A CMOS Transceiver for a Multistandard 13.56-MHz RFID Reader SoC <=SEP=> A CMOS transceiver for a multistandard 13.56-MHz radio-frequency identification reader system-on-a-chip (SoC) is designed and fabricated. The SoC consists of an RF/analog part for modulation/demodulation and a digital part for controlling the transceiver functionality. Prior to designing the integrated circuit, pre-experiments using discrete components and commercial tags are performed. With the results, overall functions and specifications are determined. For supporting multistandard, several blocks are designed with digital controls according to the standards. In the transmitter, a digitally controlled amplitude modulator for various modulation indexes and a power control circuit are adopted. In the receiver, a variable gain amplifier and a level-controllable comparator, which are also controlled digitally according to the standard, are introduced. The full transceiver SoC is implemented in the Chartered 0.18-¿m CMOS technology. The measurement results of the implemented chip indicate that the designed transceiver operates in a multistandard mode.

The contagious leader: impact of the leader's mood on the mood of group members, group affective tone, and group processes. <=SEP=> The present study examined the effects of leaders' mood on (a) the mood of individual group members, (b) the affective tone of groups, and (c) 3 group processes: coordination, effort expenditure, and task strategy. On the basis of a mood contagion model, the authors found that when leaders were in a positive mood, in comparison to a negative mood, (a) individual group members experienced more positive and less negative mood, and (b) groups had a more positive and a less negative affective tone. The authors also found that groups with leaders in a positive mood exhibited more coordination and expended less effort than did groups with leaders in a negative mood. Applied implications of the results are discussed.

A 3-Month, Randomized, Double-Blind, Placebo-Controlled Study Evaluating the Ability of an Extra-Strength Marine Protein Supplement to Promote Hair Growth and Decrease Shedding in Women with Self-Perceived Thinning Hair <=SEP=> An oral marine protein supplement (MPS) is designed to promote hair growth in women with temporary thinning hair (Viviscal Extra Strength; Lifes2good, Inc., Chicago, IL). This double-blind, placebo-controlled study assessed the ability of MPS to promote terminal hair growth in adult women with self-perceived thinning hair associated with poor diet, stress, hormonal influences, or abnormal menstrual cycles. Adult women with thinning hair were randomized to receive MPS (N = 30) or placebo (N = 30) twice daily for 90 days. Digital images were obtained from a 4 cm(2) area scalp target area. Each subject's hair was washed and shed hairs were collected and counted. After 90 days, these measures were repeated and subjects completed Quality of Life and Self-Assessment Questionnaires. MPS-treated subjects achieved a significant increase in the number of terminal hairs within the target area (P < 0.0001) which was significantly greater than placebo (P < 0.0001). MPS use also resulted in significantly less hair shedding (P = 0.002) and higher total Self-Assessment (P = 0.006) and Quality of Life Questionnaires scores (P = 0.035). There were no reported adverse events. MPS promotes hair growth and decreases hair loss in women suffering from temporary thinning hair. This trial is registered with ClinicalTrials.gov Identifier: NCT02297360.

Digital Advertising: An Information Scientist's Perspective <=SEP=> Digital online advertising is a form of promotion that uses the Internet and World Wide Web for the express purpose of delivering marketing messages to attract customers. Examples of online advertising include text ads that appear on search engine results pages, banner ads, in-text ads, or Rich Media ads that appear on regular web pages, portals, or applications. Over the past 15 years online advertising, a $65 billion industry worldwide in 2009, has been pivotal to the success of the World Wide Web. That being said, the field of advertising has been equally revolutionized by the Internet, World Wide Web, and more recently, by the emergence of the social web, and mobile devices. This success has arisen largely from the transformation of the advertising industry from a low-tech, human intensive, “Mad Men” way of doing work to highly optimized, quantitative, mathematical, computerand data-centric processes that enable highly targeted, personalized, performance based advertising. This chapter provides a clear and detailed overview of the technologies and business models that are transforming the field of online advertising primarily from statistical machine learning and information science perspectives.

Design on the low-leakage diode string for using in the power-rail ESD clamp circuits in a 0.35-/spl mu/m silicide CMOS process <=SEP=> A new design of the diode string with very low leakage current is proposed for use in the ESD clamp circuits across the power rails. By adding an NMOS-controlled lateral SCR (NCLSCR) device into the stacked diode string, the leakage current of this new diode string with six stacked diodes at 5 V (3.3 V) forward bias can be reduced to only 2.1 (1.07) nA at a temperature of 125/spl deg/C in a 0.35 /spl mu/m silicide CMOS process, whereas the previous designs have a leakage current in the order of mA. The total blocking voltage of this new design with NCLSCR can be linearly adjusted by changing the number of the stacked diodes in the diode string without causing latch-up danger across the power rails. From the experimental results, the human-body-model ESD level of the ESD clamp circuit with the proposed low-leakage diode string is greater than 8 kV in a 0.35 /spl mu/m silicide CMOS process by using neither ESD implantation nor the silicide-blocking process modifications.

Zero-bias autoencoders and the benefits of co-adapting features <=SEP=> Regularized training of an autoencoder typically results in hidden unit biases that take on large negative values. We show that negative biases are a natural result of using a hidden layer whose responsibility is to both represent the input data and act as a selection mechanism that ensures sparsity of the representation. We then show that negative biases impede the learning of data distributions whose intrinsic dimensionality is high. We also propose a new activation function that decouples the two roles of the hidden layer and that allows us to learn representations on data with very high intrinsic dimensionality, where standard autoencoders typically fail. Since the decoupled activation function acts like an implicit regularizer, the model can be trained by minimizing the reconstruction error of training data, without requiring any additional regularization.

Global prevalence of glaucoma and projections of glaucoma burden through 2040: a systematic review and meta-analysis. <=SEP=> PURPOSE
Glaucoma is the leading cause of global irreversible blindness. Present estimates of global glaucoma prevalence are not up-to-date and focused mainly on European ancestry populations. We systematically examined the global prevalence of primary open-angle glaucoma (POAG) and primary angle-closure glaucoma (PACG), and projected the number of affected people in 2020 and 2040.


DESIGN
Systematic review and meta-analysis.


PARTICIPANTS
Data from 50 population-based studies (3770 POAG cases among 140,496 examined individuals and 786 PACG cases among 112 398 examined individuals).


METHODS
We searched PubMed, Medline, and Web of Science for population-based studies of glaucoma prevalence published up to March 25, 2013. Hierarchical Bayesian approach was used to estimate the pooled glaucoma prevalence of the population aged 40-80 years along with 95% credible intervals (CrIs). Projections of glaucoma were estimated based on the United Nations World Population Prospects. Bayesian meta-regression models were performed to assess the association between the prevalence of POAG and the relevant factors.


MAIN OUTCOME MEASURES
Prevalence and projection numbers of glaucoma cases.


RESULTS
The global prevalence of glaucoma for population aged 40-80 years is 3.54% (95% CrI, 2.09-5.82). The prevalence of POAG is highest in Africa (4.20%; 95% CrI, 2.08-7.35), and the prevalence of PACG is highest in Asia (1.09%; 95% CrI, 0.43-2.32). In 2013, the number of people (aged 40-80 years) with glaucoma worldwide was estimated to be 64.3 million, increasing to 76.0 million in 2020 and 111.8 million in 2040. In the Bayesian meta-regression model, men were more likely to have POAG than women (odds ratio [OR], 1.36; 95% CrI, 1.23-1.52), and after adjusting for age, gender, habitation type, response rate, and year of study, people of African ancestry were more likely to have POAG than people of European ancestry (OR, 2.80; 95% CrI, 1.83-4.06), and people living in urban areas were more likely to have POAG than those in rural areas (OR, 1.58; 95% CrI, 1.19-2.04).


CONCLUSIONS
The number of people with glaucoma worldwide will increase to 111.8 million in 2040, disproportionally affecting people residing in Asia and Africa. These estimates are important in guiding the designs of glaucoma screening, treatment, and related public health strategies.

Fuzzy Logic Based-Map Matching Algorithm for Vehicle Navigation System in Urban Canyons <=SEP=> With the rapid progress in the development of wireless technology, Global Positioning System (GPS) based vehicle navigation systems are being widely deployed in automobiles to serve the location-based needs of users and for efficient traffic management. An essential process in vehicle navigation is to map match the position obtained from GPS (or/and other sensors) on a road network map. This process of map matching in turn helps in mitigating errors from navigation solution. GPS based vehicle navigation systems have difficulties in tracking vehicles in urban canyons due to poor satellite availability. High Sensitivity GPS (HS GPS) receivers can alleviate this problem by acquiring and tracking weak signals (and increasing the availability), but at the cost of high measurement noise and errors due to multipath and cross correlation. Position and velocity results in such conditions are typically biased and have unknown distributions. Thus filtering and other statistical methods are difficult to implement. Soft computing has replaced classical computing on many fronts where uncertainties are difficult to model. Fuzzy logic, based on fuzzy reasoning concepts, is one of the most widely used soft computational methods. In many circumstances, it can take noisy, imprecise input, to yield crisp (i.e. numerically accurate) output. Fuzzy logic can be applied effectively to map match the output from a HS GPS receiver in urban canyons because of its inherent tolerance to imprecise inputs. This paper describes a map matching algorithm based on fuzzy logic. The input of the system comes from a SiRF HS XTrac GPS receiver and a low cost gyro (Murata ENV-05G). The results show an improvement in tracking the vehicle in urban canyon conditions.

Automatic design of low power CMOS buffer-chain circuit using differential evolutionary algorithm and particle swarm optimization <=SEP=> PSO and DE algorithms and its variants are used for the optimization of a buffer-chain circuit and the results of all the algorithms are compared in this literature. By testing these algorithms on different mathematical benchmark functions the best parameter values of buffer chain circuit are obtained in such a way that it reduces the error between simulated output and optimized output, hence giving the best circuit performance. Evolutionary algorithms are better in performance and speed than the classical methods. 130nm CMOS technology has been used in this work. With the help of these parameter values the circuit simulator gives the values of power consumption, symmetry, rise time and fall time, which are almost closer to the desired specification of the buffer chain circuit.

Memory Interference as a Determinant of Language Comprehension <=SEP=> The parameters of the human memory system constrain the operation of language comprehension processes. In the memory literature, both decay and interference have been proposed as causes of forgetting; however, while there is a long history of research establishing the nature of interference effects in memory, the effects of decay are much more poorly supported. Nevertheless, research investigating the limitations of the human sentence processing mechanism typically focus on decay-based explanations, emphasizing the role of capacity, while the role of interference has received comparatively little attention. This paper reviews both accounts of difficulty in language comprehension by drawing direct connections to research in the memory domain. Capacity-based accounts are found to be untenable, diverging substantially from what is known about the operation of the human memory system. In contrast, recent research investigating comprehension difficulty using a retrieval-interference paradigm is shown to be wholly consistent with both behavioral and neuropsychological memory phenomena. The implications of adopting a retrieval-interference approach to investigating individual variation in language comprehension are discussed.

Sentiment Classification through Semantic Orientation Using SentiWordNet <=SEP=> Sentiment analysis is the procedure by which information is extracted from the opinions, appraisals and emotions of people in regards to entities, events and their attributes. In decision making, the opinions of others have a significant effect on customers ease in making choices regards to online shopping, choosing events, products, entities. In this paper, a rule based domain independent sentiment analysis method is proposed. The proposed method classifies subjective and objective sentences from reviews and blog comments. The semantic score of subjective sentences is extracted from SentiWordNet to calculate their polarity as positive, negative or neutral based on the contextual sentence structure. The results show the effectiveness of the proposed method and it outperforms the machine learning methods. The proposed method achieves an accuracy of 87% at the feedback level and 83% at the sentence level for comments. [Aurangzeb khan, Muhammad Zubair Asghar, Shakeel Ahmad, Fazal Masud Kundi, Maria Qasim, Furqan. Sentiment Classification through Semantic Orientation Using SentiWordNet. Life Sci J 2014; 11(10):309-315] (ISSN: 1097-8135). http://www.lifesciencesite.com. 44

Radar Signal Processing for Jointly Estimating Tracks and Micro-Doppler Signatures <=SEP=> The aim of the radar systems is to collect information about their surroundings. In many scenarios besides static targets there are numerous moving objects with very different characteristics, such as extent, movement behavior or micro-Doppler spread. It would be most desirable to have algorithms that extract all information on static and moving object automatically, without a system operator. In this paper, we present measurements conducted with a commercially available high-resolution multi-channel linear frequency-modulated continuous-wave radar and algorithms that do not only produce radar images but a description of the scenario on a higher level. After conventional spectrum estimation and thresholding, we present a clustering stage that combines individual detections and generates representations of each target individually. This stage is followed by a Kalman filter based multi-target tracking block. The tracker allows us to follow each target and collect its properties over time. With this method of jointly estimating tracks and characteristics of each individual target in a scenario, inputs for classifiers can be generated. Which, in turn, will be able to generate information that could be used for driver assistance or alarm trigger systems.

The medial patellofemoral ligament: location of femoral attachment and length change patterns resulting from anatomic and nonanatomic attachments. <=SEP=> BACKGROUND
Incompetence of the medial patellofemoral ligament (MPFL) is an integral factor in patellofemoral instability. Reconstruction of this structure is gaining increasing popularity. However, the natural behavior of the ligament is still not fully understood, and crucially, the correct landmark for femoral attachment of the MPFL at surgery is poorly defined.


PURPOSE
To determine the length change pattern of the native MPFL, investigate the effect of nonanatomic femoral and differing patellar attachment sites on length changes, and recommend a reproducible femoral attachment site for undertaking anatomic MPFL reconstruction.


STUDY DESIGN
Descriptive laboratory study.


METHODS
Eight cadaveric knees were dissected of skin and subcutaneous fat and mounted in a kinematics rig with the quadriceps tensioned. The MPFL length change patterns were measured for combinations of patellar and femoral attachments using a suture and displacement transducer. Three attachments were along the superomedial border of the patella, and 5 femoral attachments were at the MPFL center and 5 mm proximal, distal, anterior, and posterior to this point. Reproducibility of attachment sites was validated radiographically.


RESULTS
The femoral attachment point, taking the anterior-posterior medial femoral condyle diameter to be 100%, was identified 40% from the posterior, 50% from the distal, and 60% from the anterior border of the medial femoral condyle. This point was most isometric, with a mean maximal length change to the central patellar attachment of 2.1 mm from 0° to 110° of knee flexion. The proximal femoral attachment resulted in up to 6.4 mm mean lengthening and the distal attachment up to 9.1 mm mean shortening through 0° to 110° of knee flexion, resulting in a significantly nonisometric graft (P < .05).


CONCLUSION
We report the anatomic femoral and patellar MPFL graft attachments, with confirmation of the reproducibility of their location and resulting kinematic behavior. Nonanatomic attachments caused significant loss of isometry.


CLINICAL RELEVANCE
The importance of an anatomically positioned MPFL reconstruction is highlighted, and an identifiable radiographic point for femoral tunnel position is suggested for use intraoperatively.

The Spatial Orienting paradigm: How to design and interpret spatial attention experiments <=SEP=> This paper is conceived as a guide that will describe the very well known Spatial Orienting paradigm, used to explore attentional processes in healthy individuals as well as in people suffering from psychiatric disorders and brain-damaged patients. The paradigm was developed in the late 1970s, and since then, it has been used in thousands of attentional studies. In this review, we attempt to describe, the paradigm for the naïf reader, and explain in detail when is it used, which variables are usually manipulated, how to interpret its results, and how can it be adapted to different populations and methodologies. The main goal of this review is to provide a practical guide to researchers who have never used the paradigm that will help them design their experiments, as a function of their theoretical and experimental needs. We also focus on how to adapt the paradigm to different technologies (such as event-related potentials, functional resonance imaging, or transcranial magnetic stimulation), and to different populations by presenting an example of its use in brain-damaged patients.

A gesture-free geometric approach for mid-air expression of design intent in 3D virtual pottery <=SEP=> The advent of depth cameras has enabled mid-air interactions for shape modeling with bare hands. Typically, these interactions employ a finite set of pre-defined hand gestures to allow users to specify modeling operations in virtual space. However, human interactions in real world shaping processes (such as pottery or sculpting) are complex, iterative, and continuous. In this paper, we show that the expression of user intent in shaping processes can be derived from the geometry of contact between the hand and the manipulated object. Specifically, we describe the design and evaluation of a geometric interaction technique for bare-hand mid-air virtual pottery. We model the shaping of a pot as a gradual and progressive convergence of the pot’s profile to the shape of the user’s hand represented as a point-cloud (PCL). Thus, a user does not need to learn, know, or remember any gestures to interact with our system. Our choice of pottery simplifies the geometric representation, allowing us to systematically study how users use their hands and fingers to express the intent of deformation during a shaping process. Our evaluations demonstrate that it is possible to enable users to express their intent for shape deformation without the need for a fixed set of gestures for clutching and deforming a shape.

A comparative study of differential evolution variants for global optimization <=SEP=> In this paper, we present an empirical comparison of some Differential Evolution variants to solve global optimization problems. The aim is to identify which one of them is more suitable to solve an optimization problem, depending on the problem's features and also to identify the variant with the best performance, regardless of the features of the problem to be solved. Eight variants were implemented and tested on 13 benchmark problems taken from the specialized literature. These variants vary in the type of recombination operator used and also in the way in which the mutation is computed. A set of statistical tests were performed in order to obtain more confidence on the validity of the results and to reinforce our discussion. The main aim is that this study can help both researchers and practitioners interested in using differential evolution as a global optimizer, since we expect that our conclusions can provide some insights regarding the advantages or limitations of each of the variants studied.

An AES Smart Card Implementation Resistant to Power Analysis Attacks <=SEP=> In this article we describe an efficient AES software implementation that is well suited for 8-bit smart cards and resistant against power analysis attacks. Our implementation masks the intermediate results and randomizes the sequence of operations at the beginning and the end of the AES execution. Because of the masking, it is secure against simple power analysis attacks, template attacks and first-order DPA attacks. Due to the combination of masking and randomization, it is resistant against higher-order DPA attacks. Resistant means that a large number of measurements is required for a successful attack. This expected number of measurements is tunable. The designer can choose the amount of randomization and thereby increase the number of measurements. This article also includes a practical evaluation of the countermeasures. The results prove the theoretical assessment of the countermeasures to be correct.