Query: FastFlow: High-level and Efficient Streaming on Multi-core

Relevant passages:
Wait-Free Synchronization <=SEP=> A wait-free implementation of a concurrent data object is one that guarantees that any process can complete any operation in a finite number of steps, regardless of the execution speeds of the other processes. The problem of constructing a wait-free implementation of one data object from another lies at the heart of much recent work in concurrent algorithms, concurrent data structures, and multiprocessor architectures. First, we introduce a simple and general technique, based on reduction to a concensus protocol, for proving statements of the form, “there is no wait-free implementation of X by Y.” We derive a hierarchy of objects such that no object at one level has a wait-free implementation in terms of objects at lower levels. In particular, we show that atomic read/write registers, which have been the focus of much recent attention, are at the bottom of the hierarchy: thay cannot be used to construct wait-free implementations of many simple and familiar data types. Moreover, classical synchronization primitives such astest&set and fetch&add, while more powerful than read and write, are also computationally weak, as are the standard message-passing primitives. Second, nevertheless, we show that there do exist simple universal objects from which one can construct a wait-free implementation of any sequential object.

MapReduce: Simplified Data Processing on Large Clusters <=SEP=> MapReduce is a programming model and an associated implementation for processing and generating large datasets that is amenable to a broad variety of real-world tasks. Users specify the computation in terms of a map and a reduce function, and the underlying runtime system automatically parallelizes the computation across large-scale clusters of machines, handles machine failures, and schedules inter-machine communication to make efficient use of the network and disks. Programmers find the system easy to use: more than ten thousand distinct MapReduce programs have been implemented internally at Google over the past four years, and an average of one hundred thousand MapReduce jobs are executed on Google's clusters every day, processing a total of more than twenty petabytes of data per day.

Salt-and-pepper noise removal by median-type noise detectors and detail-preserving regularization <=SEP=> This paper proposes a two-phase scheme for removing salt-and-pepper impulse noise. In the first phase, an adaptive median filter is used to identify pixels which are likely to be contaminated by noise (noise candidates). In the second phase, the image is restored using a specialized regularization method that applies only to those selected noise candidates. In terms of edge preservation and noise suppression, our restored images show a significant improvement compared to those restored by using just nonlinear filters or regularization methods only. Our scheme can remove salt-and-pepper-noise with a noise level as high as 90%.

Programs for Machine Learning. Part I <=SEP=> 

Adaptive median filters: new algorithms and results <=SEP=> Based on two types of image models corrupted by impulse noise, we propose two new algorithms for adaptive median filters. They have variable window size for removal of impulses while preserving sharpness. The first one, called the ranked-order based adaptive median filter (RAMF), is based on a test for the presence of impulses in the center pixel itself followed by a test for the presence of residual impulses in the median filter output. The second one, called the impulse size based adaptive median filter (SAMF), is based on the detection of the size of the impulse noise. It is shown that the RAMF is superior to the nonlinear mean L(p) filter in removing positive and negative impulses while simultaneously preserving sharpness; the SAMF is superior to Lin's (1988) adaptive scheme because it is simpler with better performance in removing the high density impulsive noise as well as nonimpulsive noise and in preserving the fine details. Simulations on standard images confirm that these algorithms are superior to standard median filters.

AP3: cooperative, decentralized anonymous communication <=SEP=> This paper describes a cooperative overlay network that provides anonymous communication services for participating users. The Anonymizing Peer-to-Peer Proxy (AP3) system provides clients with three primitives: (i) anonymous message delivery, (ii) anonymous channels, and (iii) secure pseudonyms. AP3 is designed to be lightweight, low-cost and provides "probable innocence" anonymity to participating users, even under a large-scale coordinated attack by a limited fraction of malicious overlay nodes. Additionally, we use AP3's primitives to build novel anonymous group communication facilities (multicast and anycast), which shield the identity of both publishers and subscribers.

Probabilistic Encryption <=SEP=> 

THE ROLE OF MUSIC COMMUNICATION IN CINEMA <=SEP=> [Authors’ note: This paper is an abbreviated version of a chapter included in a forthcoming book entitled Music Communication (D. Miell, R. MacDonald, & D. Hargreaves, Eds.), to be published by Oxford University Press.] Past research leaves no doubt about the efficacy of music as a means of communication. In the following pages, after presenting a general model of music communication, the authors will introduce models – both empirical and theoretical – of film music perception and the role of music in film, referencing some of the most significant research investigating the relationship between sound and image in the cinematic context. We shall then enumerate the many ways in which the motion picture soundtrack can supplement, enhance, and expand upon the meaning of a film’s narrative. The relationship between the auditory and visual components in cinema is both active and dynamic, affording a multiplicity of possible relations than can evolve – sometimes dramatically – as the narrative unfolds. This paper will take a cognitive approach to the study of musical communication in cinema. As a result, much credence will be given to the results of empirical research investigating human cognitive processing in response to the motion picture experience. In conclusion, the present authors will argue for a more inclusive definition of the term “film music” than that utilized or implied in previous publications. In our view, film music is one component of a sonic fabric that includes the musical score, ambient sound, dialogue, sound effects, and silence. The functions of these constituent elements often overlap or interact with one another, creating a harmonious counterpoint to the visual image. 1. A MODEL OF MUSIC COMMUNICATION Many studies have investigated various aspects of musical communication as a form of expression (Bengtsson & Gabrielsson, 1983; Clarke, 1988; Clynes, 1983, Gabrielsson, 1988, Seashore, 1967/1938; Senju & Ohgushi, 1987; Sundberg, 1988; Sundberg et al., 1983). A tripartite communication model was proposed by Campbell and Heller (1980), consisting simply of a composer, performer, and listener. Using this previous model as a foundation, Kendall and Carterette (1990) elegantly expanded upon this model of music communication, detailing a process involving multiple states of coding, decoding, and recoding. Kendall and Carterette suggest that this process involves the “grouping and parsing of elementary thought units” (p. 132), these “thought units” (metasymbols) are mental representations involved in the process of creating, performing, and listening to musical sound. 2. MODELS OF FILM MUSIC COMMUNICATION 2.1 Empirical Evidence Several researchers have proposed models specific to the perception and cognition of music within the cinematic context. Initiating this systematic effort, Marshall and Cohen’s (1988) bipartite “congruence-associationist” model suggests that the meaning of a film is altered by the music as the result of two complex cognitive processes. Based upon subject responses, the researchers determined that musical sound directly effects subject ratings on the Potency (strong-weak) and Activity (active-passive) dimensions, while the Evaluative dimension (good-bad) relies on the degree of congruence between the audio and visual components on all three dimensions, as determined by a “comparator” component. The second part of the model describes how musical meaning is ascribed to the film. Marshall and Cohen claim that attention is directed to the overlapping congruent meaning of the music and the film. Referential meanings associated with the music are ascribed to the overlapped (congruent) audio-visual components upon which attention is focused. As a result, “the music alters meaning of a particular aspect of the film” (1988, p. 109). Marshall and Cohen also acknowledge the important role played by temporal characteristics of the sound and image, stating that “the assignment of accent to events will affect retention, processing, and interpretation” (1988, p. 108). Incorporation of this important component of the developing model was provided by Lipscomb and Kendall’s (1994) Film Music Paradigm, in which two implicit processes are considered as the basis for whether attentional focus is shifted to the musical component or whether it is likely to remain at the subconscious – cognitively “inaudible” – level. The authors suggested that these two implicit processes include an association judgment (similar to Marshall and Cohen’s assessment of “congruence”) and an evaluation of the accent structure relationship between the auditory and visual components. Based on the results of a series of three experiments utilizing stimuli ranging from extremely simple, single-object animations to actual movie excerpts, Lipscomb (1995) determined that the role of the two implicit judgments appears to be dynamic such that, with simple stimuli (such as that used in Lipscomb, 1995, Experiment 1 and Marshall & Cohen, 1988), accent structure alignment plays a dominant role. As the stimuli become more complex (e.g., multi-object animations and actual movie excerpts) the primary determinant of meaning in the auditory domain appears to shift to the associational judgment, with the accent structure alignment aspect receding to a supporting role, i.e., focusing audience attention on certain aspects of the visual image (Boltz, 2001). The most complex and fully developed model of film music perception proposed to date is Cohen’s (2001) “congruence-associationist framework for understanding film-music communication” (p. 259; see Figure 1). This multi-stage model attempts to account for meaning derived from the spoken narrative, visual images, and musical sound. Level A represents bottom-up processing based on physical features derived from input to each perceptual modality. Level B represents the determination of cross-modal congruence, based on both semantic (associational) and syntactic (temporal) grouping features. Level D represents top-down processing, determined by an individual’s past experience and the retention of that experience in long term memory. According to this model, the input from levels B (bottom-up) and D (top-down) meet in the observer’s conscious mind (level C), where information is prepared for transfer to short term memory. In its details, clearly documented in Cohen (2001), this model is based on an assumption of visual primacy, citing several studies that have suggested a subservient role for the auditory component (Bolivar et al., 1994; Driver, 1997; Thompson et al., 1994). Though a common assumption throughout the literature, the present authors would like to express reservation about this assumption and suggest that additional research is required before such a claim can be supported definitively. Figure 1. Cohen’s “congruence-associationist framework. 2.2 Theoretical Evidence Richard Wagner, creator of the idealized Gesamtkunstwerk in the form of the 19 century music drama, claimed that “as pure organ of the feeling, [music] speaks out the very thing which word speech in itself can not speak out ... that which, looked at from the standpoint of our human intellect, is the unspeakable” (Wagner 1849/1964, p. 217). According to Suzanne K. Langer, “music has all the earmarks of a true symbolism, except one: the existence of an assigned connotation” and, though music is clearly a symbolic form, it remains an “unconsummated symbol” (1942, p. 240). In order for a film to make the greatest possible impact, there must be an interaction between the verbal dialogue (consummated symbol), the cinematic images (also, typically, a consummated symbol), and the musical score (unconsummated symbol). To answer the question “How does music in film narration create a point of experience for the spectator?,” Gorbman (1987) suggests three methods by which music can “signify” in the context of a narrative film. Purely musical signification results from the highly coded syntactical relationships inherent in the association of one musical tone with another. Patterns of tension and release provide a sense of organization and meaning to the musical sound, apart from any extramusical association that might exist. Cultural musical codes are exemplified by music that has come to be associated with a certain mood or state of mind. These associations have been further canonized by the Hollywood film industry into certain conventional expectations – implicitly anticipated by enculturated audience members – determined by the narrative content of a given scene. Finally, cinematic codes influence musical meaning merely due to the placement of musical sound within the filmic context. Opening credit and end title music illustrate this type of signification, as well as recurring musical themes that come to represent characters or situations within the film. There is a commonly held belief that film music is not to be heard (Burt, 1994; Gorbman, 1987). Instead, it is believed to fulfill its role in communicating the underlying psychological drama of the narrative at a subconscious level (Lipscomb, 1989). There is, however, certain music that is intended to be heard by the audience as part of the cinematic diegesis, i.e., “the narratively implied spatiotemporal world of the actions and characters” (Gorbman 1987, p. 21). This “world” includes, naturally, a sonic component. Therefore, all sounds that are understood to be heard by characters in the narrative – including music – are referred to as diegetic, while those that are not part of the diegesis (e.g., the orchestral score) are referred to as nondiegetic. This would suggest that diegetic music is more likely to be processed at the conscious level while nondiegetic music might remain at the subconscious level, though research is needed to determine whether this is true, in fact. It is worth noting also, that the source of diegetic sound can be either seen or unseen. Michel Chion (199

Data Collection in Wireless Sensor Networks with Mobile Elements: A Survey <=SEP=> Wireless sensor networks (WSNs) have emerged as an effective solution for a wide range of applications. Most of the traditional WSN architectures consist of static nodes which are densely deployed over a sensing area. Recently, several WSN architectures based on mobile elements (MEs) have been proposed. Most of them exploit mobility to address the problem of data collection in WSNs. In this article we first define WSNs with MEs and provide a comprehensive taxonomy of their architectures, based on the role of the MEs. Then we present an overview of the data collection process in such a scenario, and identify the corresponding issues and challenges. On the basis of these issues, we provide an extensive survey of the related literature. Finally, we compare the underlying approaches and solutions, with hints to open problems and future research directions.

A Successive Approximation Recursive Digital Low-Dropout Voltage Regulator With PD Compensation and Sub-LSB Duty Control <=SEP=> This paper presents a recursive digital low-dropout (RLDO) regulator that improves response time, quiescent power, and load regulation dynamic range over prior digital LDO designs by 1–2 orders of magnitude. The proposed RLDO enables a practical digital replacement to analog LDOs by using an SAR-like binary search algorithm in a coarse loop and a sub-LSB pulse width modulation duty control scheme in a fine loop. A proportional-derivative compensation scheme is employed to ensure stable operation independent of load current, the size of the output decoupling capacitor, and clock frequency. Implemented in 0.0023 mm2 in 65 nm CMOS, the 7-bit RLDO achieves, at a 0.5-V input, a response time of 15.1 ns with a figure of merit of 199.4 ps, along with stable operation across a 20 000 $\times $  dynamic load range.

Imaging Cognition II: An Empirical Review of 275 PET and fMRI Studies <=SEP=> Positron emission tomography (PET) and functional magnetic resonance imaging (fMRI) have been extensively used to explore the functional neuroanatomy of cognitive functions. Here we review 275 PET and fMRI studies of attention (sustained, selective, Stroop, orientation, divided), perception (object, face, space/motion, smell), imagery (object, space/ motion), language (written/spoken word recognition, spoken/ no spoken response), working memory (verbal/numeric, object, spatial, problem solving), semantic memory retrieval (categorization, generation), episodic memory encoding (verbal, object, spatial), episodic memory retrieval (verbal, nonverbal, success, effort, mode, context), priming (perceptual, conceptual), and procedural memory (conditioning, motor, and nonmotor skill learning). To identify consistent activation patterns associated with these cognitive operations, data from 412 contrasts were summarized at the level of cortical Brodmann's areas, insula, thalamus, medial-temporal lobe (including hippocampus), basal ganglia, and cerebellum. For perception and imagery, activation patterns included primary and secondary regions in the dorsal and ventral pathways. For attention and working memory, activations were usually found in prefrontal and parietal regions. For language and semantic memory retrieval, typical regions included left prefrontal and temporal regions. For episodic memory encoding, consistently activated regions included left prefrontal and medial-temporal regions. For episodic memory retrieval, activation patterns included prefrontal, medial-temporal, and posterior midline regions. For priming, deactivations in prefrontal (conceptual) or extrastriate (perceptual) regions were consistently seen. For procedural memory, activations were found in motor as well as in non-motor brain areas. Analysis of regional activations across cognitive domains suggested that several brain regions, including the cerebellum, are engaged by a variety of cognitive challenges. These observations are discussed in relation to functional specialization as well as functional integration.

Exploring Synergies between Machine Learning and Knowledge Representation to Capture Scientific Knowledge <=SEP=> In this paper we explore synergies between the machine learning and knowledge representation fields by considering how scientific knowledge is represented in these areas. We illustrate some of the knowledge obtained through machine learning methods, providing two contrasting examples of such models: probabilistic graphical models (aka Bayesian networks) and artificial neural networks (including deep learning networks). From knowledge representation, we give an overview of ontological representations, qualitative reasoning, and planning. Then we discuss potential synergies that would benefit both areas.

Coupling Matrix Synthesis for a New Class of Microwave Filter Configuration <=SEP=> In this paper a new approach to the synthesis of coupling matrices for microwave filters is presente d. The new approach represents an advance on existing direct a nd optimization methods for coupling matrix synthesis in that it will exhaustively discover all possible coupling matrix solutions for a network if more than one exists. This enables a se lection to be made of the set of coupling values, resonator frequ ency offsets, parasitic coupling tolerance etc that will be best suited to the technology it is intended to realize the microwave filter with. To demonstrate the use of the method, the case of the r cently – introduced ‘extended box’ (EB) coupling matrix configuration is taken. The EB represents a new class of filter con figuration featuring a number of important advantages, one of which is the existence of multiple coupling matrix solutions for each prototype filtering function, eg 16 for 8 degree cases. This case is taken as an example to demonstrate the use of the synthesis method – yielding one solution suitable for dual-mode realiz ation and one where some couplings are small enough to neglect. Index Terms — Coupling matrix, filter synthesis, Groebner basis, inverted characteristic, multiple solutions.

An Artificial Bee Colony-Based COPE Framework for Wireless Sensor Network <=SEP=> In wireless communication, network coding is one of the intelligent approaches to process the packets before transmitting for efficient information exchange. The goal of this work is to enhance throughput by using the intelligent technique, which may give comparatively better optimization. This paper introduces a biologically-inspired coding approach called Artificial Bee Colony Network Coding (ABC-NC), a modification in the COPE framework. The existing COPE and its variant are probabilistic approaches, which may not give good results in all of the real-time scenarios. Therefore, it needs some intelligent technique to find better packet combinations at intermediate nodes before forwarding to optimize the energy and maximize the throughput in wireless networks. This paper proposes ABC-NC over the existing COPE framework for the wireless environment.

Fast Inference in Sparse Coding Algorithms with Applications to Object Recognition <=SEP=> Adaptive sparse coding methods learn a possibly overcomplete set of basis functions, such that natural image patches can be reconstructed by linearly combining a small subset of these bases. The applicability of these methods to visual object recognition tasks has been limited because of the prohibitive cost of the optimization algorithms required to compute the sparse representation. In this work we propose a simple and efficient algorithm to learn basis functions. After training, this model also provides a fast and smooth approximator to the optimal representation, achieving even better accuracy than exact sparse coding algorithms on visual object recognition tasks.

What are mobile developers asking about? A large scale study using stack overflow <=SEP=> The popularity of mobile devices has been steadily growing in recent years. These devices heavily depend on software from the underlying operating systems to the applications they run. Prior research showed that mobile software is different than traditional, large software systems. However, to date most of our research has been conducted on traditional software systems. Very little work has focused on the issues that mobile developers face. Therefore, in this paper, we use data from the popular online Q&A site, Stack Overflow, and analyze 13,232,821 posts to examine what mobile developers ask about. We employ Latent Dirichlet allocation-based topic models to help us summarize the mobile-related questions. Our findings show that developers are asking about app distribution, mobile APIs, data management, sensors and context, mobile tools, and user interface development. We also determine what popular mobile-related issues are the most difficult, explore platform specific issues, and investigate the types (e.g., what, how, or why) of questions mobile developers ask. Our findings help highlight the challenges facing mobile developers that require more attention from the software engineering research and development communities in the future and establish a novel approach for analyzing questions asked on Q&A forums.

Self-Supervised Adversarial Hashing Networks for Cross-Modal Retrieval <=SEP=> Thanks to the success of deep learning, cross-modal retrieval has made significant progress recently. However, there still remains a crucial bottleneck: how to bridge the modality gap to further enhance the retrieval accuracy. In this paper, we propose a self-supervised adversarial hashing (SSAH) approach, which lies among the early attempts to incorporate adversarial learning into cross-modal hashing in a self-supervised fashion. The primary contribution of this work is that two adversarial networks are leveraged to maximize the semantic correlation and consistency of the representations between different modalities. In addition, we harness a self-supervised semantic network to discover high-level semantic information in the form of multi-label annotations. Such information guides the feature learning process and preserves the modality relationships in both the common semantic space and the Hamming space. Extensive experiments carried out on three benchmark datasets validate that the proposed SSAH surpasses the state-of-the-art methods.

Arthrodesis with Intramedular Fixation in Posttraumatic Arthrosis of the Midfoot: A Case Report <=SEP=> We present two middle-aged men with posttraumatic arthrosis of the midfoot. Both patients suffered from severe pain and their foot was unable to bear weight. Both were operated using new fusion bolt 6.5 mm and additional screws. In their case, arthrodesis was mandatory and effective intervention. After surgical treatment both patients were pain free and able to walk without crutches and return to daily work.

Wavelet analysis of EEG for seizure detection: Coherence and phasesynchrony estimation. <=SEP=> This paper deals with the wavelet analysis method f or seizure detection in EEG time series and coherence estimation. The main part of the paper pr esents the basic principles of signal decomposition in connection with the EEG frequency ba nds. Wavelet analysis method has been used for detection of seizure onset. The wavelet fi ltered signal is used for the computation of spectral power ratio. The results show that our met hod can identify pre seizure, seizure, post seizure and non seizure phases. When dealing with s eizure detection and prediction problems it is important to identify seizure precursor dynamics and necessary to identify information about onset and spread of seizures. Therefore in th e second part the coherence and phase synchrony during pre seizure, seizure, post seizure an d non seizure are computed. We expect this method to provide more insight into dynamic aspects of the seizure generating process.

Evaluating Digital Forensic Options for the Apple iPad <=SEP=> The iPod Touch, iPhone and iPad from Apple are among the most popular mobile computing platforms in use today. These devices are of forensic interest because of their high adoption rate and potential for containing digital evidence. The uniformity in their design and underlying operating system (iOS) also allows forensic tools and methods to be shared across product types. This paper analyzes the tools and methods available for conducting forensic examinations of the Apple iPad. These include commercial software products, updated methodologies based on existing jailbreaking processes and the analysis of the device backup contents provided by iTunes. While many of the available commercial tools offer promise, the results of our analysis indicate that most comprehensive examination of the iPad requires jailbreaking to perform forensic duplication and manual analysis of its media content.

Enhancing scholarly use of digital libraries: A comparative survey and review of bibliographic metadata ontologies <=SEP=> The HathiTrust Research Center (HTRC) is engaged in the development of tools that will give scholars the ability to analyze the HathiTrust digital library's 14 million volume corpus. A cornerstone of the HTRC's digital infrastructure is the workset -- a kind of scholar-built research collection intended for use with the HTRC's analytics platform. Because more than 66% of the digital corpus is subject to copyright restrictions, scholarly users remain dependent upon the descriptive accounts provided by traditional metadata records in order to identify and gather together bibliographic resources for analysis. This paper compares the MADSRDF/MODSRDF, Bibframe, schema.org, BIBO, and FaBiO ontologies by assessing their suitability for employment by the HTRC to meet scholars' needs. These include distinguishing among multiple versions of the same work; representing the complex historical and physical relationships among those versions; and identifying and providing access to finer grained bibliographic entities, e.g., poems, chapters, sections, and even smaller segments of content.

Decreased gut microbiota diversity, delayed Bacteroidetes colonisation and reduced Th1 responses in infants delivered by caesarean section. <=SEP=> OBJECTIVE
The early intestinal microbiota exerts important stimuli for immune development, and a reduced microbial exposure as well as caesarean section (CS) has been associated with the development of allergic disease. Here we address how microbiota development in infants is affected by mode of delivery, and relate differences in colonisation patterns to the maturation of a balanced Th1/Th2 immune response.


DESIGN
The postnatal intestinal colonisation pattern was investigated in 24 infants, born vaginally (15) or by CS (nine). The intestinal microbiota were characterised using pyrosequencing of 16S rRNA genes at 1 week and 1, 3, 6, 12 and 24 months after birth. Venous blood levels of Th1- and Th2-associated chemokines were measured at 6, 12 and 24 months.


RESULTS
Infants born through CS had lower total microbiota diversity during the first 2 years of life. CS delivered infants also had a lower abundance and diversity of the Bacteroidetes phylum and were less often colonised with the Bacteroidetes phylum. Infants born through CS had significantly lower levels of the Th1-associated chemokines CXCL10 and CXCL11 in blood.


CONCLUSIONS
CS was associated with a lower total microbial diversity, delayed colonisation of the Bacteroidetes phylum and reduced Th1 responses during the first 2 years of life.

Whole-function vectorization <=SEP=> Data-parallel programming languages are an important component in today's parallel computing landscape. Among those are domain-specific languages like shading languages in graphics (HLSL, GLSL, RenderMan, etc.) and "general-purpose" languages like CUDA or OpenCL. Current implementations of those languages on CPUs solely rely on multi-threading to implement parallelism and ignore the additional intra-core parallelism provided by the SIMD instruction set of those processors (like Intel's SSE and the upcoming AVX or Larrabee instruction sets). In this paper, we discuss several aspects of implementing dataparallel languages on machines with SIMD instruction sets. Our main contribution is a language- and platform-independent code transformation that performs whole-function vectorization on low-level intermediate code given by a control flow graph in SSA form. We evaluate our technique in two scenarios: First, incorporated in a compiler for a domain-specific language used in realtime ray tracing. Second, in a stand-alone OpenCL driver. We observe average speedup factors of 3.9 for the ray tracer and factors between 0.6 and 5.2 for different OpenCL kernels.

Argumentation Theory: A Very Short Introduction <=SEP=> Since the time of the ancient Greek philosophers and rhetoricians, argumentation theorists have searched for the requirements that make an argument correct, by some appropriate standard of proof, by examining the errors of reasoning we make when we try to use arguments. These errors have long been called fallacies, and the logic textbooks have for over 2000 years tried to help students to identify these fallacies, and to deal with them when they are encountered. The problem was that deductive logic did not seem to be much use for this purpose, and there seemed to be no other obvious formal structure that could usefully be applied to them. The radical approach taken by Hamblin (1970) was to refashion the concept of an argument to think of it not just as an arbitrarily designated set of propositions, but as a move one party makes in a dialog to offer premises that may be acceptable to another party who doubts the conclusion of the argument. Just after Hamblin's time a school of thought called informal logic grew up that wanted to take a new practical approach to teaching students skills of critical thinking by going beyond deductive logic to seek other methods for analyzing and evaluating arguments. Around the same time, an interdisciplinary group of scholars associated with the term 'argumentation', coming from fields like speech communication, joined with the informal logic group to help build up such practical methods and apply them to real examples of argumentation (Johnson and Blair, 1987). The methods that have been developed so far are still in a process of rapid evolution. More recently, improvements in them have been due to some computer scientists joining the group, and to collaborative research efforts between argumentation theorists and computer scientists. Another recent development has been the adaption of argumentation models and techniques to fields in artificial intelligence, like multi-agent systems and artificial intelligence for legal reasoning. In a short paper, it is not possible to survey all these developments. The best that can be done is to offer an introduction to some of the basic concepts and methods of argumentation theory as they have evolved to the present point, and to briefly indicate some problems and limitations in them. 1. Arguments and Argumentation There are four tasks undertaken by argumentation, or informal logic, as it is also often called: identification, analysis, evaluation and invention. The task of identification …

Super Normal Vector for Activity Recognition Using Depth Sequences <=SEP=> This paper presents a new framework for human activity recognition from video sequences captured by a depth camera. We cluster hypersurface normals in a depth sequence to form the polynormal which is used to jointly characterize the local motion and shape information. In order to globally capture the spatial and temporal orders, an adaptive spatio-temporal pyramid is introduced to subdivide a depth video into a set of space-time grids. We then propose a novel scheme of aggregating the low-level polynormals into the super normal vector (SNV) which can be seen as a simplified version of the Fisher kernel representation. In the extensive experiments, we achieve classification results superior to all previous published results on the four public benchmark datasets, i.e., MSRAction3D, MSRDailyActivity3D, MSRGesture3D, and MSRActionPairs3D.

A Seed-Based Method for Generating Chinese Confusion Sets <=SEP=> In natural language, people often misuse a word (called a “confused word”) in place of other words (called “confusing words”). In misspelling corrections, many approaches to finding and correcting misspelling errors are based on a simple notion called a “confusion set.” The confusion set of a confused word consists of confusing words. In this article, we propose a new method of building Chinese character confusion sets.
 Our method is composed of two major phases. In the first phase, we build a list of seed confusion sets for each Chinese character, which is based on measuring similarity in character pinyin or similarity in character shape. In this phase, all confusion sets are constructed manually, and the confusion sets are organized into a graph, called a “seed confusion graph” (SCG), in which vertices denote characters and edges are pairs of characters in the form (confused character, confusing character).
 In the second phase, we extend the SCG by acquiring more pairs of (confused character, confusing character) from a large Chinese corpus. For this, we use several word patterns (or patterns) to generate new confusion pairs and then verify the pairs before adding them into a SCG. Comprehensive experiments show that our method of extending confusion sets is effective. Also, we shall use the confusion sets in Chinese misspelling corrections to show the utility of our method.

Learning Over Long Time Lags <=SEP=> The advantage of recurrent neural networks (RNNs) in learni ng dependencies between time-series data has distinguished RNNs from other deep learning models. Recent ly, many advances are proposed in this emerging field. However, there is a lack of comprehensive review on mem ory models in RNNs in the literature. This paper provides a fundamental review on RNNs and long short te rm memory (LSTM) model. Then, provides a surveys of recent advances in different memory enhancement s and learning techniques for capturing long term dependencies in RNNs.

Ethical Artificial Intelligence <=SEP=> First Edition Please send typo and error reports, and any other comments, to hibbard@wisc.edu.

Twitter Part-of-Speech Tagging for All: Overcoming Sparse and Noisy Data <=SEP=> Part-of-speech information is a pre-requisite in many NLP algorithms. However, Twitter text is difficult to part-of-speech tag: it is noisy, with linguistic errors and idiosyncratic style. We present a detailed error analysis of existing taggers, motivating a series of tagger augmentations which are demonstrated to improve performance. We identify and evaluate techniques for improving English part-of-speech tagging performance in this genre. Further, we present a novel approach to system combination for the case where available taggers use different tagsets, based on voteconstrained bootstrapping with unlabeled data. Coupled with assigning prior probabilities to some tokens and handling of unknown words and slang, we reach 88.7% tagging accuracy (90.5% on development data). This is a new high in PTB-compatible tweet part-of-speech tagging, reducing token error by 26.8% and sentence error by 12.2%. The model, training data and tools are made available.

Comparing Speech Recognition Systems (Microsoft API, Google API And CMU Sphinx) <=SEP=> The idea of this paper is to design a tool that will be used to test and compare commercial speech recognition systems, such as Microsoft Speech API and Google Speech API, with open-source speech recognition systems such as Sphinx-4. The best way to compare automatic speech recognition systems in different environments is by using some audio recordings that were selected from different sources and calculating the word error rate (WER). Although the WER of the three aforementioned systems were acceptable, it was observed that the Google API is superior.