Miracle-dz/UniFAR-FTUs huggingface dataset:
cation of Incomplete Data Using the FuzzyARTMAP Neural

The fuzzy ARTMAP neural network is used to classify data that is incomplete in one or more ways. These include a limited number of training cases, missing components, missing class labels, and missing classes. Modiications for dealing with such incomplete data are introduced, and performance is assessed on an emitter identiication task using a database of radar pulses. 1 A taxonomy of data incompleteness Data presented to a classiier, during either the training or testing phases, may be incomplete in one or more ways: 1. Limited number of training cases: It is of interest to know how the performance of the classiier declines as the amount of training data is decreased, so that, e.g., more training data may be gathered, if necessary, before the classiier is put to use. 2. Missing components of the input patterns: For example, the information in the diierent components of the input patterns may come from diierent sensors, one or more of which may be temporarily unavailable. 3. Missing class labels during training: Some of the training data may have missing class labels. This is referred to as \semi-supervised learning" (Demiriz et al., 1999) or \partially supervised clustering" (Bensaid et al., 1996). (\Missing class labels during testing" is, of course, just the usual situation.) 4. Missing classes: Some classes that were not present in the training set may be encountered during testing. When the classiier encounters a pattern belonging to such an unfamiliar class, it should \\ag" the pattern as belonging to an unfamiliar class, rather than make a meaningless guess as to its identity. This may be implemented by using \familiarity discrimination" (Carpenter et al., 1997). (a) Pure familiarity discrimination. As is common practice when evaluating the performance of a classiier, the classiier does not learn during the testing phase. Test patterns which are agged as unfamiliar are not processed further. In addition to high accuracy of classiication of familiar patterns, the quality of the classiier is measured by a high \hit rate"|fraction of familiar-class test patterns correctly declared to belong to classes familiar during testing and classiied (correctly or not)|and low \false alarm rate"|fraction of unfamiliar-class test patterns incorrectly declared familiar by the classiier. (b) Learning of unfamiliar classes (LUC). The classiier continues to learn during testing. When an unfamiliar class is agged, the classiier deenes a new class, and the criteria for familiarity discrimination are adjusted as necessary. Subsequent test patterns may …
Seasonal movements of adult female polar bears in the Bering and Chukchi seas

Ten adult female polar bears (Ursus maritimus) were fitted with satellite telemetry collars during March 1986 in the Kotzebue Sound area ofthe Chukchi Sea. During March-April 1987,2 of these bears were refitted with satellite telemetry collars and an additional 10 adult females were collared in the northern Bering and eastern Chukchi seas. Data for 1,560 point locations recorded through May 1988 indicated that female polar bears in the Bering and Chukchi seas were resident in western Alaskan waters from November through March, then moved northward with the receding pack ice during April and May. They remained in the northern and northwestern Chukchi Sea during June through September, often adjacent to the Soviet coastline. Satellite telemetry data indicated that 4 females marked in Alaskan waters ofthe Chukchi Sea apparently denned in the vicinity of Wrangel Island during winter 1987/1988. Denning in American territory of bears marked in the Chukchi and Bering seas has not been documented using satellite telemetry data. Some polar bears moved from the Chukchi Sea into the western Beaufort Sea during summer and fall, then returned to the Chukchi and Bering seas the following winter. Movements of bears from the Chukchi Sea into the central or eastern Beaufort Sea were not documented through spring 1988. These data document that polar bears occurring in the Bering and Chukchi seas are shared internationally between the United States and the Soviet Union. Int. Conf. Bear Res. and Manage. 8:219-226 Polar bears are circumpolar in their distribution and were once believed to be circumpolar wanderers (Pederson 1945, as cited in Lentfer 1983). Currently, it is thought that there are 6 distinct populations of polar bears in the polar basin (DeMaster and Stirling 1981) and tagging data indicate limited exchange of individuals between these hypothesized populations (Taylor 1982). Movement information during the 1970's was primarily limited to mark/recapture data (Sch weinsburg et al. 1982(2, Lentfer 1983). Use of conventional radio-telemetry was first used during the late 1970's and became more com? mon during the 1980's (Amstrup 1986a, Calvert et al. 1986). However in northern Alaska, the cost and size of the area surveyed limited the number of locations per marked bear to 3-6 locations per year (S.C. Amstrup,
Layer 1 : Layer 2 : Layer 3 :

Natural language processing and machine learning algorithms have been shown to be effective in a variety of applications. In this work, we contribute to the area of AI adoption in the public sector. We present an automated system that was used to process textual information, generate important keywords, and automatically summarize key elements of the Meadville community statements. We also describe the process of collaboration with My Meadville administrators during the development of our system. My Meadville, a community initiative, supported by the city of Meadville conducted a large number of interviews with the residents of Meadville during the community events and transcribed these interviews into textual data files. Their goal was to uncover the issues of importance to the Meadville residents in an attempt to enhance public services. Our AI system cleans and pre-processes the interview data, then using machine learning algorithms it finds important keywords and key excerpts from each interview. It also provides searching functionality to find excerpts from relevant interviews based on specific keywords. Our automated system allowed the city to save over 300 hours of human labor that would have taken to read all interviews and highlight important points. Our findings are being used by My Meadville initiative to locate important information from the collected data set for ongoing community enhancement projects, to highlight relevant community assets, and to assist in identifying the steps to be taken based on the concerns and areas of improvement identified by the community
Optimization of neural networks for time-domain simulation of mooring lines

When using artificial neural networks in methods for dynamic analysis of slender structures, the computational effort associated with time-domain response simulation may be reduced drastically compared to classic solution strategies. This article demonstrates that the network structure of an artificial neural network, which has been trained to simulate forces in a mooring line of a floating offshore platform, can be optimized and reduced by different optimization procedures. The procedures both detect and prune the least salient network weights successively, and besides trimming the network, they also can be used to rank the importance of the various network inputs. The dynamic response of slender marine structures often depends on several external load components, and by applying the optimization procedures to a trained artificial neural network, it is possible to classify the external force components with respect to importance and subsequently determine which of them may be ignored in the analysis. The performance of the optimization procedures is illustrated by a numerical example, which shows that, in particular, the most simple procedures are able to remove more than half of the network weights in an artificial neural network without significant loss of simulation accuracy.
Mitigating Demographic Bias in Facial Datasets with Style-Based Multi-Attribute Transfer

Non-face datasets We show here two experiments to showcase the applicability of our method in different domains. Firstly, we introduce two additional modes of variation into the Morpho-MNIST dataset [1]: ‘color’, and ‘thickness’. We then train our model to transfer these two attributes simultaneously, showcasing the results of the transfers in Fig. 2, where thickness and color are transferred in a realistic manner. In Fig. 1 we also show an experiment on the CompCars dataset [3]. We threshold each images’ average pixel intensity to introduce a ‘daytime’ attribute, and then train a model to transfer both color (red, white and black) and the time of day (day and night) simultaneously. Our model learns a continuous representation of car color, leading to the ability to translate various intensities of each attribute, despite only being shown discrete labels at train-time. Indicatively, our models generates different shades of the annotated colors (e.g., magenta) as well as continuous illumination.
Toward Secure Embedded Web Interfaces

Stross covered many possible future scenarios. He decried the notion of the AI Singularity, the point of human-equivalent artificial intelligences, saying this was a fantasy akin to a steam-powered tin man. Reading his speech from his iPad (no graphics), Stross spoke eloquently, sometimes dancing closer to his supposed target, network security. I highly suggest listening to the MP3 of his speech on the USENIX Web site.
REGIONÁLNÍ ROZVOJ A RIO PO 20 LETECH

The article is devoted to the role of marketing communication in digital environment. The key features of marketing communication strategy are revealed. Authors analyze the efficiency of marketing communication, which make enable companies to increase their business results. The ways how companies interact with customers and carry out their operations are considered. The article refers to vital marketing trends in the digital environment.
Efficiency or Innovation: How do Industry Environments Moderate the

4 Firms invest in a variety of information technologies and seek to align their IT asset portfolios 5 with two key performance outcomes: efficiency and innovation. Existing research makes the 6 universalistic assumption that both outcomes will always be realized through firms’ IT asset 7 portfolios. There has been limited research on the conditions under which firms’ IT asset 8 portfolios should be more oriented toward efficiency or innovation. Here, we argue that the 9 nature of the industry where a firm competes will have a significant moderating effect on the 10 links between firms’ IT asset portfolios and efficiency or innovation outcomes. Using panel data 11 that covers a wide range of industry environments, we find that at lower levels of dynamism, 12 munificence and complexity, IT asset portfolios are associated with a greater increase in 13 efficiency. In contrast, in environments with higher levels of complexity, IT asset portfolios are 14 associated with a greater increase in innovation (i.e., development of new products and processes, 15 and exploration of growth opportunities). These results provide insights about how firms could 16 realize strategic alignment by tailoring their IT asset portfolios toward an efficiency or 17 innovation focus. 18 19 20
Programming Massively Parallel Processors, Third Edition: A Hands-on Approach

Programming Massively Parallel Processors: A Hands-on Approach, Third Edition shows both student and professional alike the basic concepts of parallel programming and GPU architecture, exploring, in detail, various techniques for constructing parallel programs. Case studies demonstrate the development process, detailing computational thinking and ending with effective and efficient parallel programs. Topics of performance, floating-point format, parallel patterns, and dynamic parallelism are covered in-depth. For this new edition, the authors have updated their coverage of CUDA, including coverage of newer libraries, such as CuDNN, moved content that has become less important to appendices, added two new chapters on parallel patterns, and updated case studies to reflect current industry practices. Teaches computational thinking and problem-solving techniques that facilitate high-performance parallel computing Utilizes CUDA version 7.5, NVIDIA's software development tool created specifically for massively parallel environments Contains new and updated case studies Includes coverage of newer libraries, such as CuDNN for Deep Learning
Analysing metaphors in commercial advertising

espanolDesde el punto de vista de la linguistica cognitiva, una metafora (Lakoff & Johnson, 1980) se define como una herramienta que nos ayuda a entender un concepto en terminos de otro. En un principio se entendia que la metafora solamente podia ocurrir de manera oral, aunque mas tarde se desarrollaron nuevos pensamientos sobre otras modalidades en las que esta podia aparecer. Por ejemplo, se han llevado a cabo muchas investigaciones con relacion a la metafora visual monomodal y multimodal. Este articulo parte de varios estudios realizados por Charles Forceville en los que presenta la diferencia entre metafora monomodal y multimodal. Por lo tanto, el objetivo es presentar un analisis cognitivo de metaforas visuales con el que se espera demostrar un posible continuo entre estos dos tipos de metafora. En alguna ocasion, ha sido necesario recurrir al analisis de la metonimia, ya que son dos terminos que van generalmente ligados. EnglishAccording to the Cognitive Linguistic view, a metaphor (Lakoff & Johnson, 1980) is defined as a tool which allows us to understand one conceptual domain in terms of another. At first, it was thought that metaphors could only occur verbally, but later new thoughts about the concept of metaphor appeared and more research about other kinds of metaphors was developed; for instance, a lot of research dealing with monomodal and multimodal metaphors was carried out. Based on Charles Forceville’s research, the aim of this article is to present a cognitive analysis of metaphors in commercial advertising, in order to show a possible continuum between monomodal and multimodal images. The analysis is expected to present some borderline cases between monomodal and multimodal metaphors. In order to do this, the use of the metonymy is needed in some cases, since metaphor and metonymy are sometimes strongly linked.
Foundations of robotics : analysis and control

Foundations of Robotics presents the fundamental concepts and methodologies for the analysis, design, and control of robot manipulators. It explains the physical meaning of the concepts and equations used, and it provides, in an intuitively clear way, the necessary background in kinetics, linear algebra, and control theory. Illustrative examples appear throughout.The author begins by discussing typical robot manipulator mechanisms and their controllers. He then devotes three chapters to the analysis of robot manipulator mechanisms. He covers the kinematics of robot manipulators, describing the motion of manipulator links and objects related to manipulation. A chapter on dynamics includes the derivation of the dynamic equations of motion, their use for control and simulation and the identification of inertial parameters. The final chapter develops the concept of manipulability.The second half focuses on the control of robot manipulators. Various position-control algorithms that guide the manipulator's end effector along a desired trajectory are described Two typical methods used to control the contact force between the end effector and its environments are detailed For manipulators with redundant degrees of freedom, a technique to develop control algorithms for active utilization of the redundancy is described. Appendixes give compact reviews of the function atan2, pseudo inverses, singular-value decomposition, and Lyapunov stability theory.Tsuneo Yoshikawa teaches in the Division of Applied Systems Science in Kyoto University's Faculty of Engineering.
IMPROVING SEQUENTIAL LATENT VARIABLE MODELS

We propose an approach for sequence modeling based on autoregressive normalizing flows. Each autoregressive transform, acting across time, serves as a moving reference frame for modeling higher-level dynamics. This technique provides a simple, general-purpose method for improving sequence modeling, with connections to existing and classical techniques. We demonstrate the proposed approach both with standalone models, as well as a part of larger sequential latent variable models. Results are presented on three benchmark video datasets, where flowbased dynamics improve log-likelihood performance over baseline models.
AIS Electronic Library (AISeL)

Although the Net is an indispensable business/personal tool for many, indications are that a growing population chunk – the Alzheimer’s afflicted – will be unable to harness it due to inappropriate interface design. By 2050, over 80 million will exceed age 65, the Worker/Retiree ratio will shrink to 2, and the number of Alzheimer’s Disease (AD) patients will triple to 14 million. Annual estimated societal costs attributable to AD are about $100 billion with no cure in sight. Simultaneously, more Americans must remain productive post retirement age and non-retirees are increasingly being diagnosed with AD. The socio-economic ramifications are tremendous. The World Wide Web Consortium (W3C) and Congress have advanced guidelines/laws to make IT more disabled friendly. However, a fundamental issue remains: to our knowledge, the guidelines are entirely prescriptive and we are unaware of rigorous research evidence demonstrating benefits to compliance. Our work focuses on specific aspects of this research opportunity.
Formal Policy based Authorization Model for Ubiquitous Enterprise Computing Environment

Ubiquitous computing environment demands a dynamic access control mechanism that can adapt to the changing security requirement of the computing environment. In this paper an authorization model for ubiquitous computing environment is proposed and a formal approach is adopted to design a flexible and scalable model to support intelligent authorization process in ubiquitous computing environment. Keywords Access Control, Authorization, Formal Methods, Security Model, Ubiquitous Computing.
IEICE Proceeding Series Strongly assortative networks: creation, structure and dynamics

—Finite realizations of archetypal complex networks (including, most notably, the preferential attachment model) are typically mildly disassortative — in part due to the attachment of the most recent nodes, with fewest links, directly to the hubs. In contrast, the extant collection of real world networks exhibits a very wide range of as-sortativity. In this paper we explore both this bias and the opposite end of the spectrum: what can be done to make strongly assortative networks, what do they look like and, what e ﬀ ect does this have on the dynamical behaviour of such systems.
Tracking of hidden parts in video sequences and other problems raised by the 3D reconstruction of the urban environment

This thesis deals with the urban environment reconstruction through the use of cameras and telemetric sensors. First, we focus on the spatiotemporal segmentation of video sequences in order to treat photographic data. We present a new technique of layer segmentation which extracts regions of similar parametric motion in a video sequence. It is based on temporal constraints defined and optimized over all images simultaneously and not successively, without any a priori on the observed scene. Taking advantage of temporal continuity, our framework considers both the visible and the hidden parts of each layer in order to increase robustness. The hidden parts of the layers are recovered, which could be of a great help in many high level vision tasks. Modeling the problem as a labeling task, we state it in a MRF-optimization framework and solve it with a graph-cut algorithm. Both synthetic and real video sequences show a visible layers extraction comparable to the one usually performed by state of the art methods, as well as a novel and successful segmentation of hidden layers. Secondly, we consider the use of heterogeneous telemetric and photographic data, in the same framework to obtain a 3D and textural reconstruction of the urban scenes. It has proved to be a powerful technique. A necessary condition to obtain good results is to calibrate accurately the single-row based telemetric sensor and the cameras together. We present a study of this calibration process and propose an improved extrinsic calibration technique. It is based on an existing technique which consists in scanning a planar pattern in several poses, giving a set of relative position and orientation constraints. The innovation is the use of a more appropriate laser beam distance between telemetric points and the planar target. Moreover, we use robust methods to manage outliers at several steps of the algorithm. Improved results on both theoretical and experimental data are given.
Automated freezing of gait assessment with marker-based motion capture and deep learning approaches expert-level detection

Freezing of gait (FOG) is a common and debilitating gait impairment in Parkinson’s disease. Further insight in this phenomenon is hampered by the difficulty to objectively assess FOG. To meet this clinical need, this paper proposes a motion capture-based FOG assessment method driven by a novel deep neural network. The proposed network, termed multi-stage graph convolutional network (MS-GCN), combines the spatial temporal graph convolutional network (ST-GCN) and the multi-stage temporal convolutional network (MS-TCN). The ST-GCN captures the hierarchical motion among the optical markers inherent to motion capture, while the multi-stage component reduces oversegmentation errors by refining the predictions over multiple stages. The proposed model was validated on a dataset of fourteen freezers, fourteen non-freezers, and fourteen healthy control subjects. The experiments indicate that the proposed model outperforms state-of-the-art baselines. An in-depth quantitative and qualitative analysis demonstrates that the proposed model is able to achieve clinician-like FOG assessment. The proposed MS-GCN can provide an automated and objective alternative to labor-intensive clinician-based FOG assessment.
TREC12 Web and Interactive Tracks at CSIRO

This year, CSIRO teams participated in all three tasks of the web track; these being: the automatic topic distillation task, the home/named page finding task and the interactive topic distillation task. This paper describes our approaches, experiments and results. The following section describes our experiments in the two automatic tasks, and Section 3 describes our experiment in the interactive task.