Miracle-dz/UniFAR-FTUs huggingface dataset:
Interactive Algorithm Exploration using Meta Visualization

In volume rendering shadows provide an important visual cue, and enhance depth perception. However, shadowing has its own disadvantages. Shadows do not take into account the importance of features and could potentially result in too dark scenes. In this paper we propose an approach for inconsistent shadowing, which is designed to overcome these limitations. For the purpose of illustrative rendering, we propose two complementary techniques: 1. shadow caster inconsistency and 2. shadow receiver inconsistency. We demonstrate several advantages of the different approaches, using inconsistent shadowing. We present two approaches, based on shadow transfer function concept, an approach, introducing usage of gradient magnitude information in shadowing, and a method for adaptive shading and shadowing of the surface, depending on the gradient certainty.
DRAFT SUBMISSION – PLEASE DO NOT REDISTRIBUTE Motion Estimation from Image and Inertial Measurements ( revised 2 / 29 / 04 )

Cameras and inertial sensors are each good candidates for autonomous vehicle navigation, modeling from video, and other applications that require six degree of freedom motion estimation. But, these sensors are also good candidates to be deployed together, since each can be used to resolve the ambiguities in estimated motion that result from using the other modality alone. In this paper, we consider the specific problem of estimating sensor motion and other unknowns from image, gyro, and accelerometer measurements, in environments without known fiducials. This work targets applications where external positions references such as global positioning are not available, and focuses on the use of small and inexpensive inertial sensors, for applications where weight and cost requirements preclude the use of precision inertial navigation systems. We present two algorithms for estimating sensor motion from image and inertial measurements. The first algorithm is a batch method, which produces estimates of the sensor motion, scene structure, and other unknowns using measurements from the entire observation sequence simultaneously. The second algorithm recovers sensor motion, scene structure, and other parameters recursively, and is suitable for use with long or “infinite” sequences, in which no feature is always visible. We evaluate the accuracy of the algorithms and their sensitivity to their estimation parameters using a sequence of four experiments. These experiments focus on cases where estimates from image or inertial measurements alone are poor, on the relative advantage of using inertial measurements and omnidirectional images, and on long sequences in which the percentage of the image sequence in which individual features are visible is low.
Partition-based cloud data storage and processing model

How to maximally use and efficiently manage cloud storage resources has become one of major problem in cloud computing area. If cloud storage capacity is limited or restrictions on a single file size, user may hire more cloud computing storage services. Data partitioning and distributed storage technologies are focused on to solve the problem that size of large dataset is limited in cloud storage. A model of partition-based data storage in cloud is put forward and its availability is discussed. Fragment partition description is given and three algorithms are designed on the basis of model. The first algorithm is about partition and storage of data, the second algorithm is about data query and connection, and the last algorithm is about fragment updated and re-partitioned. The experimental results show that the model can be applied to the situation with multiple cloud storage services and large dataset or file.
The weight of the saddened soul: the bidirectionality between physical heaviness and sadness and its implications for sensory marketing

ABSTRACT Heaviness is a bodily metaphor used to express sadness. Building on embodied cognition theory and metaphor theory, we argue that sadness is grounded in bodily sensation of heaviness, which has important sensory marketing implications for engaging consumer senses to affect consumer decision-making and attitude formation processes. We found support for this metaphorical link between heaviness and sadness across six studies. We showed that carrying a heavy bag saddened individuals and increased the valuation of a teddy bear. Intention to donate to a charity supporting endangered tigers increased when burdened participants watched a sad video about these animals. Conversely, sadness induced physical heaviness and increased preference for an easy-to-maintain sofa. Further, sad individuals disliked an advertisement for a sports drink that figured energy-consuming actions. Our findings inform sensory marketing practice about embedding the bodily sensation of heaviness to induce sadness in marketing communication.
Supporting Object-Oriented Software Development with Intentional Software Views

Developing, maintaining and understanding large software systems is hard. One underlying cause is that existing modularization mechanisms are inadequate to handle crosscutting concerns. Intentional software views are an intuitive and lightweight means of modelling such concerns. They increase our ability to understand, modularize and browse the implementation of a software system by grouping together source-code entities that address a same concern. Alternative descriptions of the same intentional view can be provided and checked for consistency. Relations among intentional views can be declared, verified and enforced. Our model of intentional views is implemented using a logic meta-programming approach. This allows us to specify a kind of knowledge developers have about (object-oriented) software systems that is usually not captured by traditional program documentation mechanisms. It also facilitates software evolution by providing the ability to verify automatically the consistency of views and detect invalidation of important intentional relationships among views when the software is modified.
Combining generality and practicality in a conit-based continuous consistency model for wide-area replication

Replication is a key approach to scaling wide-area applications. However, the overhead associated with large-scale replication quickly becomes prohibitive across wide-area networks. One effective approach to addressing this limitation is to allow applications to dynamically trade reduced consistency for increased performance and availability. Although extensive study has been performed on relaxed consistency models in traditional replicated databases, none of the models can simultaneously achieve the following two typically conflicting requirements imposed by wide-area applications: generality (capturing application-specific consistency semantics) and practicality (enabling efficient application-independent consistency protocols to be designed and providing natural ways to express application semantics). We propose a conit-based continuous consistency model designed to simultaneously achieve generality and practicality. Our conit theory provides generality, where application-specific consistency requirements are exported as conits. Practicality is achieved by using a simple, spanning set of metrics for conit consistency and by using a per-write weight specification. We demonstrate the generality of our model through representative wide-area applications and by showing that a number of existing models can be expressed as instances of our model. Our efficient, application-independent consistency protocols and prototype implementation verify its practicality.
A temporal desynchronization resilient video watermarking scheme based on independent component analysis

Temporal synchronization is a problem that cannot be ignored in most video watermarking applications. In this paper, a video watermarking scheme is proposed to resist temporal desynchronization through a content dependent way. In this scheme, the to-be-watermarked video is first segmented into shots. And each shot is analyzed by using independent component analysis (ICA) to get its independent feature frames (IFFs). And then the watermark is embedded into these feature frames. Simulations show that this scheme is robust not only to temporal desynchronization, e.g., frame swapping, frame dropping, fps conversion, etc, but to most of the common video processing/attacks, e.g. noising, filtering, rescaling, MPEG2-4 transcoding, and intra-video collusion.
Model reuse through hardware design patterns

Increasing reuse opportunities is a well-known problem for software designers as well as for hardware designers. Nonetheless, current software and hardware engineering practices have embraced different approaches to this problem. Software designs are usually modelled after a set of proven solutions to recurrent problems called design patterns. This approach differs from the component-based reuse usually found in hardware designs: design patterns do not specify unnecessary implementation details. Several authors have already proposed translating structural design patterns concepts to hardware design. In this paper we extend the discussion to behavioural design patterns. Specifically, we describe how the hardware version of the Iterator can be used to enhance model reuse.
Manuscript Title: Recurrence Plot Based Measures of Complexity and Its Application to Heart Rate Variability Data

The knowledge of transitions between regular, laminar or chaotic behavior is essential to understand the underlying mechanisms behind complex systems. While several linear approaches are often insufficient to describe such processes, there are several nonlinear methods which however require rather long time observations. To overcome these difficulties, we propose measures of complexity based on vertical structures in recurrence plots and apply them to the logistic map as well as to heart rate variability data. For the logistic map these measures enable us not only to detect transitions between chaotic and periodic states, but also to identify laminar states, i. e. chaos-chaos transitions. The traditional recurrence quan-tification analysis fails to detect the latter transitions. Applying our new measures to the heart rate variability data, we are able to detect and quantify the laminar phases before a life-threatening cardiac arrhythmia occurs thereby facilitating a prediction of such an event. Our findings could be of importance for the therapy of malignant cardiac arrhythmias.
An Inverse Kinematic Analysis of a Robotic Sealer

A planar robotic sealing or brand stamping machine is presented for an automated factory line. The appropriate time to seal or to stamp an object is basically determined by a motor controller which relies critically on whether or not the object is in the best position. The extent of protraction and retraction of the piston head is largely dictated by an infrared sensor. Given the extent to protract or retract the piston head, the angular displacements of the link required are determined using the Inverse Kinematic (IK) techniques. The inertia and gravity effects of the links have been ignored to reduce the complexity of the equations and to demonstrate the technique.
Grapheme Gaussian model and prosodic syllable based Tamil speech recognition system

Automatic Speech Recognition is an active field of research to identify speech patterns for providing the equivalent text. The challenges in automatic speech recognition start right from choosing the appropriate unit for the language being dealt with. Some of the units that could be used are word, phoneme, triphone, syllable, demisyllable, senone and morpheme. A syllable based Speech model is used which reduces the vocabulary size and also easier to align. This also suits Tamil, which is a syllable based language. In the model described in this paper, the connected word inputs are segmented into individual words using short term energy and the isolated words are further broken down into characters using Varied-Length Maximum Likelihood (VLML) algorithm. Gaussian Mixture Model (GMM), which is a speaker-independent model suitable for large sets of data, is used for classifying the characters for later pattern matching against the trained syllables. This paper introduces a new algorithm named VLML algorithm that is used for identifying the boundary of each character and explains the proposed process of speech recognition system for Tamil language.
“ Institutions and the Viability of Macroeconomics : Some Perspectives on the Transformation Process in Post-Communist Economies

The building of a modern, market economy requires the establishment of undirected systems of coordination and order. Yet, for three hundred years, social theorists have grappled with the project of explaining the basis of socio-economic order. The more recent attempt of mainstream economics to base macroeconomics on ‘sound microeconomic foundations’ is a modern version of this project. All these efforts have been motivated by a specific form of reductionism, based on the use of the individual as the given and fundamental use of analysis. Both mathematically and philosophically, this project has now run into the sand. Mathematical attempts to derive aggregate macro relationships from microeconomic assumptions have reached insurmountable difficulties. More generally, philosophical objections have been developed against reductionism. Some of the latter employ the concept of emergence, which is explored here. In addition, suggestions are made here as to how institutional economics can develop a quite different articulation and understanding of micro-macro relationships. The implications for policy-makers in the economies in transition are briefly discussed.
Involvement and Acceptance of Custodial Fathers: The Role of Narcissism and Caregiving

Paternal involvement and acceptance were compared among 218 custodial divorced fathers, 222 married fathers, and 105 noncustodial divorced fathers. The predictors examined were narcissistic traits and caregiving behaviors, with coparental cooperation and child characteristics as moderators. Results indicated that compared with married and noncustodial fathers, custodial fathers were more involved with their children, cooperated less with their children’s mothers, and viewed their children as being difficult. The interactions underscore the uniqueness of custodial fathers: Unlike married and noncustodial divorced fathers, custodial fathers were more accepting of their children, regardless of their avoidant caregiving. Coparental cooperation and narcissistic traits were associated with the greater involvement of noncustodial fathers compared with custodial fathers. In addition, child difficulty moderated the association between acceptance and narcissistic traits.
An Internet local routing approach based on network structural connectivity

Internet is one of the largest synthetic complex system ever built. It consists in a collection of more than 30,000 networks each one known as an Autonomous System. In the last few years, Internet is experiencing an explosive growth that is compromising its navigation scalability due to its dependence on the Border Gateway Protocol (BGP). The BGP routing protocol requires to maintain an updated partial view of the network topology, involving a huge amount of data exchange and significant convergence times. The scale-free topology of Internet makes complex network theory the natural framework to analyze its problems and propose solutions. Here, we present a local alternative to BGP based on complex networks. Our approach uses the linear projection of the modular structure of the network to construct a navigable map of the Internet. This map guarantees a high reliability over time on the actual evolving network, in the sense that projection changes are negligible. The simulation results show that we are in high percentage close to optimal paths.
Cross-Language Question Answering at the University of Helsinki

Tikka is a cross-language question answering system developed at the University of Helsinki for the purposes of the QA@CLEF 2004 evaluation campaign, Tikka was conflgured to answer Finnish questions using a text corpus in English, but it is designed so that it can be conflgured to work with any other languages as well. Tikka is the flrst general domain question answering system ever reported to have used Finnish. The question type classifler, the translator, the answer extractor and the answer scorer are the components of Tikka that are especially developed for question answering.
Vector Mapping CLIR with Character Trigrams Los Alamos National Laboratory CLIR project Notebook Paper

Los Alamos National Laboratory has developed a character trigram-based vector mapping system for English->French document retrieval. We trained the system on parallel English/French Hansard data, aligned at the sentence level. The translation matrix was reduced based on the frequencies of the individual language trigrams and their cooccurrences. Queries were manually constructed in English and represented as trigram vectors. For comparison to French documents, they were multiplied by the translation matrix developed in training. For a first-time participant our performance was respectable. Our average precision was at median level or better on five out of 28 queries, and we were the best CLIR group at the 100-document cutoff level on two queries. 1 . Introduction Cross-language information retrieval is a new research topic at Los Alamos National Laboratory. We began working in this area in the fall of 1997, when we received funding from the Department of Energy under its Phase One program. This program aims to increase ties between the national laboratories and the intelligence community. Our technical monitors for the project are in the Department of Defense. Our research group, the Computer Research and Applications group (CIC-3) at Los Alamos, is actively interested in all manifestations of human language, including written text, document images, and speech; see www.c3. lanl.gov/~judithh and associated links. More generally, our group has expertise in pattern recognition, machine learning, and statistics. This has been very much a startup project, with a small staff and a lot to accomplish. We have tried to maximize our efficiency by using software previously written by our group (character trigrams) or available elsewhere (sentence marking and alignment), focusing on CLIR at the expense of the monolingual ad-hoc task, and only addressing one target language (French) in the CLIR task.
Response monitoring , repetitive behaviour and anterior cingulate abnormalities in ASD

Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02215, Department of Psychology, Suffolk University, Boston, MA 02114, Department of Anatomy and Neurobiology, Boston University Medical School, Boston, MA, Department of Radiology, Massachusetts General Hospital, Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA 02129, Harvard Medical School, Boston, MA 02215, Department of Neurology and Department of Ophthalmology and Visual Sciences, University of British Columbia, Vancouver, BC, Canada
Relationship between Natural Language Processing and AI: The Role of Constrained Formal-Computational Systems

Modeling various aspects of language-syntax, semantics, pragmatics, and discourse, among others -- by the use of constrained formal-computational systems, just adequate for such modeling, has proved to be an effective research strategy, leading to deep understanding of these aspects, with implications for both machine processing and human processing. This approach enables one to distinguish between the universal and stipulative constraints. This is in contrast to an approach where we start with the most powerful formal-computational system and then model the phenomena by making all constraints stipulative in a sense. The use of constrained systems for modeling leads to some novel ways of describing locality of structures and brings out the relationship between the complexity of description of primitives and local computations over them. These ideas serve to unify theoretical, computational, and statistical aspects of natural language processing in AI. It is expected that this approach will also be productive in other domains of AI.
SoC platform based design of MPEG-2/4 AAC audio decoder

This paper presents an SoC platform based design for the implementation of an AAC audio decoder. We present the approach not only for the characteristics of the algorithm, but also provide the numerical decision for evaluation of the various approaches. The overall system is first analyzed and profiled with the ARM profiler. Then the decoder system is partitioned into software part and hardware part respectively based on the property of analysis. The software part is developed for the implementation of intensive decision making operations needed for audio bitstreams. The hardware part is a dedicated hardware for the regular and computation intensive operations in AAC audio decoding. The decoder system is realized on the ARM integrator platform where the hardware and software is communicated efficiently with the AMBA architecture.
Modelspace - Cooperative Document Information Extraction in Flexible Hierarchies

Business document indexing for ordered filing of documents is a crucial task for every company. Since this is a tedious error prone work, automatic or at least semi-automatic approaches have a high value. One approach for semi-automated indexing of business documents uses self-learning information extraction methods based on user feedback. While these methods require no management of complex indexing rules, learning by user feedback requires each user to first provide a number of correct extractions before getting appropriate automatic results. To eliminate this cold start problem we propose a cooperative approach to document information extraction involving dynamic hierarchies of extraction services. We provide strategies for making the decision when to contact another information extraction service within the hierarchy, methods to combine results from different sources, as well as aging and split strategies to reduce the size of cooperatively used indexes. An evaluation with a large number of real-world business documents shows the benefits of our approach.
Seizure prediction and the preseizure period

Beginning in the 1970s engineers designed systems to predict epileptic seizures based upon quantitative changes in the electroencephalogram, which they hypothesized began well in advance of clinical seizure onset. These efforts flourished in the 1990s, as independent laboratories demonstrated evidence of a ‘preseizure period’ up to 20 min prior to clinical symptoms in patients implanted with intracranial electrodes during evaluation for epilepsy surgery. Years later, clinical and laboratory experiments leave little doubt that a preseizure period exists in temporal lobe and perhaps other forms of epilepsy. Its existence, however, raises fundamental questions about what constitutes a seizure, what brain regions are involved in seizure generation, and whether discrete interictal, preictal, ictal and post-ictal physiologies exist, or blend together in a continuous process. Pressing milestones, necessary for clinical utility, are: (1) demonstrating prospective seizure prediction from prolonged human data sets, (2) elucidating mechanisms underlying seizure precursors and (3) implementing these algorithms on implantable hardware platforms. The notion of a preseizure state is catalyzing new clinical and basic science research, which has the potential to dramatically increase our understanding of epilepsy, and to generate exciting new therapies for patients.