Miracle-dz/UniFAR-FTUs huggingface dataset:
Cognitive Processing of Causal Knowledge

There is a brief description of the probabilistic causal graph model for representing, reasoning with, and learning causal structure using Bayesian networks. It is then argued that this model is closely related to how humans reason with and learn causal structure. It is shown that studies in psychology on discounting (reasoning concerning how the presence of one cause of an effect makes another cause less probable) support the hypothesis that humans reach the same judgments as algorithms for doing inference in Bayesian networks. Next, it is shown how studies by Piaget indicate that humans learn causal structure by observing the same independencies and dependencies as those used by certain algorithms for learning the structure of a Bayesian network. Based on this indication, a subjective definition of causality is forwarded. Finally, methods for further testing the accuracy of these claims are discussed.
Rhythmic entrainment, syncopation and pleasantness

Although several authors have speculated that rhythmic entrainment induces positive affect (e.g. Juslin & VastfjaIˆll, 2008; Clayton et al. 2004), so far there is no direct experimental evidence to support this claim. Therefore, the experiment hereby reported aimed to test the hypothesis that moving in time with music induces pleasantness and that this effect interacts with the level of syncopation of the music. Six short rhythmic musical stimuli with three levels of syncopation (low, medium, high), were presented to 77 participants, who were divided into two groups: one was asked to move along with the pulse of the music (by tapping with one foot), and the other was asked to listen without moving. The changes in the participants’ affective state were measured by using two techniques: self-report scales of pleasantness and arousal, and an indirect technique consisting of asking participants to evaluate the level of pleasantness expressed by emotionally ambiguous facial expressions –The perceived pleasantness works as an indicator of the observer’s own affective state (Niedenthal et al., 2000)-. It was predicted that: 1) intermediate levels of syncopation would be associated with the most pleasantness, and that 2) these effects would be larger in the ”˜tapping’ condition. The results revealed that even though the data from the indirect technique showed a trend in the predicted direction, there was a great amount of within-subjects variability which made these results unreliable. The data from self-reports supported the first prediction –participants experienced slightly higher levels of positive affect when tapping along to stimuli with a medium level of syncopation-; but not the second prediction –participants in the ”˜tapping’ condition did not experience more pleasantness nor unpleasantness than the participants in the ”˜stationary’ condition. No significant differences were found in any of the measures of arousal. These findings suggest that the effect of musical entrainment on the induction of pleasantness is primarily the result of the expectations aroused by syncopated rhythms, not by the movements made by the listener. References Clayton, M. , Sager, R. , & Will, U. (2004). In time with the music: The concept of entrainment and its significance for ethnomusicology. ESEM CounterPoint, 1, 1–45. Juslin, P. N. , & VaIˆstfjaIˆll, D. (2008). Emotional responses to music: the need to consider underlying mechanisms. The Behavioral and Brain Sciences, 31(5), 559–75; discussion 575–621. doi:10.1017/S0140525X08005293 Niedenthal, P. M. , Halberstadt, J. B. , & Margolin, J. (2000). Emotional state and the detection of change in facial expression of emotion. European Journal of Social Psychology, 30(May 1999), 211–223.
Some Properties of Generalized Scattering Matrix Representations for Metallic Waveguides With Periodic Dielectric Loading

Some new results are presented on the properties of generalized scattering matrix representations for metallic waveguides with axially periodic dielectric loadings. A unified framework is given for describing the frequency dependence and for identifying the emergence of propagating, nonpropagating, and complex Floquet modes in single mode, as well as multimode, regions. Two new conservation relations are formulated for the generalized scattering matrix of the unit cell in lossless periodic structures. One of these relations provides a convenient means for checking the correctness of the values of calculated matrix elements, while the other relation yields accurate estimates for the stopband-passband transition frequencies located within single Floquet-mode regions.
Testing Hardware Security Properties and Identifying Timing Channels /

Computers are being placed in charge of the systems and devices we trust with our safety and security. These embedded systems control our automobiles, commercial airlines, medical devices, mobile phones, and many other aspects that we hope will behave in a secure and reliable manner. In addition, the hardware in these systems are becoming increasingly complex; making security testing and evaluation a very difficult problem. Unfortunately, we have already seen many attacks performed on many of these systems including automobiles and medical devices. Many of these issues could have been prevented had there been better methods for security assessment. Specifically, hardware and embedded system designers are lacking the tools and methods for testing various security properties of their designs. Recently, a method known as gate-level information flow tracking (GLIFT) was introduced to dynamically monitor information flows in hardware for security. This dissertaion shows that this same technique can be very effectively applied statically to hardware designs to systematically test various different hardware security properties (e.g. to ensure that secret encryption keys are not leaking). Even further, this thesis demonstrates that GLIFT can effectively capture timing- channels (where information leaks in the amount of time a computation takes). These timing channels have been exploited in many past works to extract secret keys from different stateful hardware resources such as caches and branch predictors. This thesis presents some very fundamental background of GLIFT, shows how it can be used statically using several application examples, and formalizes how it can be used to detect timing channels. These contributions ultimately provide a method to do hardware security testing and verification for our future computing systems
Robustness and Recovery in Train Scheduling - a simulation study from DSB S-tog a/s

This paper presents a simulation model to study the robust- ness of timetables of DSB S-tog a/s, the city rail of Copenhagen. Deal- ing with rush hour scenarios only, the simulation model investigates the eects of disturbances on the S-tog network. Several timetables are an- alyzed with respect to robustness. Some of these are used in operation and some are generated for the purpose of investigating timetables with specic alternative characteristics.
Head-tracking virtual 3-D display for mobile devices

Computer vision enables camera data to be utilized in user interfaces to analyze the 3-D context and automatically detect the user intentions. Using cameras as an input modality provides single-handed operations in which the users' actions are recognized without interactions with the screen or keypad. In this context, we have constructed a real-time mobile application prototype where the user's position and gaze is determined in real time, a technique that enables the display of true three-dimensional objects even on a typical 2-D LCD screen. We have defined a series of interaction methods where the user's motion and camera input realistically control the viewpoint on a 3-D scene. The head movement and gaze can be used to interact with hidden objects in a natural manner just by looking at them. We provide a description of the embedded implementation at a system-level where we highlight the application development challenges and trade-offs that need to be dealt with battery powered mobile devices. The implementation includes a parallel pipeline that reduces the latencies of the application.
On-line Method for Evaluating Driver Distraction of Memory-decision Workload Based on Dynamics of Vestibulo-ocular Reflex

Recently, development of in-vehicle information systems provides much information to driver. Despite the usefulness of such systems, it is concerned that information processing demand to the drivers leads to distractions that exert a negative effect on the appropriate driving behavior with handle, quick detection of obstacles and reaction on brake pedal. However, the on-line method to evaluate the influence of distractions while driving has not yet been proposed. Therefore, the purpose of this study is to propose the method to quantitatively evaluate the influence of driver distractions caused by information processing demand in real time. For this purpose, we focus on VOR (vestibulo-ocular reflex) which is involuntary eye movement to compensate against disturbance on the head position for gaze stabilization. First, our method is to identify the eye movement model for a particular subject from measured data without another information processing demand. This model represents the subject's dynamics of VOR. After that, the eye movement is measured when the subject get distracted by paying attention to information processing demand, and it is compared with the identified model output in real time. This model-based method makes it possible to quantitatively evaluate the influence of distraction on VOR. This study experimentally has confirmed that the proposed on-line method is effective to evaluate the influence of driver distractions.
The VOT2013 challenge: overview and additional results

Visual tracking has attracted a significant attention in the last few decades. The recent surge in the number of publications on tracking-related problems have made it almost impossible to follow the developments in the field. One of the reasons is that there is a lack of commonly accepted annotated data-sets and standardized evaluation protocols that would allow objective comparison of different tracking methods. To address this issue, the Visual Object Tracking (VOT) challenge and workshop was organized in conjunction with ICCV2013. Researchers from academia as well as industry were invited to participate in the first VOT2013 challenge which aimed at single-object visual trackers that do not apply pre-learned models of object appearance (model-free). In this paper we provide an overview of the VOT2013 challenge, point out its main results and document the additional previously unpublished experiments and results.
Expanding Queries Using Multiple Resources

We describe our participation in the TREC 2006 Genomics track, in which our main focus was on query expansion. We hypothe- sized that applying query expansion techniques would help us both to identify and retrieve syn- onymous terms, and to cope with ambiguity. To this end, we developed several collection-specific as well as web-based strategies. We also per- formed post-submission experiments, in which we compare various retrieval engines, such as Lucene, Indri, and Lemur, using a simple baseline topic- set. When indexing entire paragraphs as pseudo- documents, we find that Lemur is able to achieve the highest document-, passage-, and aspect-level scores, using the KL-divergence method and its default settings. Additionally, we index the col- lection at a lower level of granularity, by creating pseudo-documents comprising of individual sen- tences. When we search these instead of para- graphs in Lucene, the passage-level scores im- prove considerably. Finally we note that stemming improves overall scores by at least 10%.
Automatic image tagging via category label and web data

Image tagging is an important technique for the image content understanding and text based image processing. Given a selection of images, how to tag these images efficiently and effectively is an interesting problem. In this paper, a novel semi-auto image tagging technique is proposed: By assigning each image a category label first, our method can automatically recommend those promising tags to each image by utilizing existing vast web data. The main contributions of our paper can be highlighted as follows: (i) By assigning each image a category label, our method can automatically recommend other tags to the image, thus reducing the human annotation efforts. Meanwhile, our method guarantee tags' diversity due to abundant web data. (ii) We use sparse coding to automatically select those semantically related images for tag propagation. (iii) Local & global ranking agglomeration will make our method robust to noisy tags. We use Event dataset as the images to be tagged, and crawled Flickr images with their associated tags according to the category label in Event dataset as the auxiliary web data. Experimental results show that our method achieves promising performance for image tagging, which proves the effectiveness of our method.
Insights on Human Adapted Control of Networked Telepresence and Teleaction Systems

Multimodal telepresence and teleaction systems enable a human operator to perform in remote environments through a telerobot and a communication network. The focus of this article is on the networked haptic (force feedback) control system with the key challenges of stability and transparency. Transparency is achieved if the human cannot distinguish between direct and teleinteraction. Human perception plays an important role for transparency evaluation. The first part of this article discusses insights how human haptic perception of the remote environment is affected by communication time delay when using the standard passivation control approach with the wave variable (scattering) transformation to achieve stability. The second line of discussion concentrates on network traffic reduction by a novel psychophysically motivated deadband control approach. Human perception is considered in both approaches and experimental validation results are presented.
The Cerebellum in Emotional Processing: Evidence from Human and Non-Human Animals

The notion that the cerebellum is a central regulator of motor function is undisputed. There exists, however, considerable literature to document a similarly vital role for the cerebellum in the regulation of various non-motor domains, including emotion. Research from numerous avenues of investigation (i.e., neurophysiological, behavioural, electrophysiological, imagining, lesion, and clinical studies) have documented the importance of the cerebellum, in particular, the vermis, in affective processing that appears preserved across species. The cerebellum possesses a distinct laminar arrangement and highly organized neuronal circuitry. Moreover, the cerebellum forms reciprocal connections with several brain regions implicated in diverse functional domains, including motor, sensory, and emotional processing. It has been argued that these unique neuroanatomical features afford the cerebellum with the capacity to integrate information about an organism, its environment, and its place within the environment such that it can respond in an appropriate, coordinated fashion, with such theories extending to the regulation of emotion. This review puts our current understanding of the cerebellum and its role in behaviour in historical perspective, presents an overview of the neuroanatomical and functional organization of the cerebellum, and reviews the literature describing the involvement of the cerebellum in emotional regulation in both humans and non-human animals. In summary, this review discusses the importance of the functional connectivity of the cerebellum with various brain regions in the ability of the cerebellum to effectively regulate emotional behaviour.
BioC-compatible full-text passage detection for protein–protein interactions using extended dependency graph

There has been a large growth in the number of biomedical publications that report experimental results. Many of these results concern detection of protein–protein interactions (PPI). In BioCreative V, we participated in the BioC task and developed a PPI system to detect text passages with PPIs in the full-text articles. By adopting the BioC format, the output of the system can be seamlessly added to the biocuration pipeline with little effort required for the system integration. A distinctive feature of our PPI system is that it utilizes extended dependency graph, an intermediate level of representation that attempts to abstract away syntactic variations in text. As a result, we are able to use only a limited set of rules to extract PPI pairs in the sentences, and additional rules to detect additional passages for PPI pairs. For evaluation, we used the 95 articles that were provided for the BioC annotation task. We retrieved the unique PPIs from the BioGRID database for these articles and show that our system achieves a recall of 83.5%. In order to evaluate the detection of passages with PPIs, we further annotated Abstract and Results sections of 20 documents from the dataset and show that an f-value of 80.5% was obtained. To evaluate the generalizability of the system, we also conducted experiments on AIMed, a well-known PPI corpus. We achieved an f-value of 76.1% for sentence detection and an f-value of 64.7% for unique PPI detection. Database URL: http://proteininformationresource.org/iprolink/corpora
An Energy Efficiency Trusted Dynamic Routing Protocol for Wireless Sensor Networks

Wireless Sensor Networks (WSNs) consists of a large number of low-power, limited-processing and limited-storage sensors, which is applied for all kinds of areas. In the paper, we introduce an energy efficiency trusted dynamic routing protocol for wireless sensor network (EETDRP), which is designed based on Destination Sequenced Distance Vector Protocol and trusted management. And the wireless sensor network topology, architecture framework, design and simulation of the EETDRP are discussed in detail. The simulation test shows that the EETDRP is reliable and effective in case of some failure sensor nodes in wireless sensor network.
Does Ethnic Discrimination Vary Across Minority Groups? Evidence from a Field Experiment

We conduct a large-scale field experiment to measure labour market discrimination in Australia, one quarter of whose population was born overseas. To denote ethnicity, we use distinctively Anglo-Saxon, Indigenous, Italian, Chinese and Middle Eastern names. We compare multiple ethnic groups, rather than a single minority as in most other studies. In all cases we applied for entry-level jobs and submitted a CV indicating that the candidate attended high school in Australia. We find significant differences in callback rates: ethnic minority candidates would need to apply for more jobs in order to receive the same number of interviews. These differences vary systematically across ethnic groups.
Integrating usability engineering and software engineering in mixed reality system development

The integration of user centred design activities into software engineering processes is a challenge. This is especially true for next-generation user interfaces that employ interface paradigms like mixed reality. Guidance for designers and developers has to address the integration of software engineering and user centred design on all levels from abstract standards to operational development. We analyze standards in software engineering and usability engineering and derive recommendations for integrated development processes. To support developers we propose the MVCE architecture as an extension of the common model-view-controller pattern to address the specific requirements of mixed reality interfaces through an additional environment component.
Tagr : Automatic Image Tagging for Random Imagery

Tagr, an automatic image tagging system is introduced, that assigns content description tags to arbitrary photographic and non-photographic images, using massive online image libraries, such as Flickr for training. Combining techniques from machine learning and content-based image retrieval, a flexible system is introduced to automatically tag a wide variety of images from various sources. A number of image classification and comparison techniques, as well as various interesting properties of random web images are analyzed and evaluated.
Techniques for Text Planning with XSLT

We describe an approach to text planning that uses the XSLT template-processing engine to create logical forms for an external surface realizer. Using a realizer that can process logical forms with embedded alternatives provides a substitute for backtracking in the text-planning process. This allows the text planner to combine the strengths of the AI-planning and template-based traditions in natural language generation.
Effect of Exercise on Adult Neurogenesis in Crayfish

Adult neurogenesis, formation of new neurons, has been determined to be a part of the normal physiology in all species of animals studied to date. There have been several factors observed to increase the number of newly formed cells; the most potent of these factors being exercise. Though exercise has a strong effect on neurogenesis by increasing proliferation and new cell survival it has not been extensively studied in many model organisms. This study is the first to look at the effect of exercise on neurogenesis in an invertebrate through the use of crayfish, Orconectes propinquus. Experimental designs, drying protocols and equipment troubleshooting developed here will guide future studies of invertebrate neurogenesis and its relationship to exercise. EXERCISE AND NEUROGENESIS IN CRAYFISH v
Role Mining for Engineering and Optimizing Role Based Access Control Systems

Role engineering is the process of designing an RBAC system. A promising approach to role engineering is role mining, which uses data mining techniques to find an RBAC system from existing permission assignment data. Role mining techniques are also useful for optimizing and refactoring an existing RBAC system, which can become increasingly chaotic over time. In this paper we study the problem of mining an RBAC system that optimizes some objective measure of “goodness” for RBAC systems. We introduce the weighted structural complexity measure, which sums up the sizes of different RBAC system components (e.g., the number of roles, the number of user-role assignments, etc.), possibly with different weights for each component. Different optimization objectives can be achieved by choosing different weight combinations. We show that the optimization problem is NP-complete. We then develop heuristic techniques for mining RBAC systems with low weighted structural complexity. We show that the problem of mining a hierarchical RBAC system is closely related to formal concept analysis, and develop an algorithm using the notion of a concept lattice. We also introduce new approaches to generating synthetic data for evaluating role mining techniques. Our experiments show that our algorithms outperform existing approaches.
A New Centroid-Based Classifier for Text Categorization

In recent years, centroid-based document classifiers receive wide interests from text mining community because of their simplicity and linear-time complexity. However, the traditional centroid-based classifiers usually perform less effectively for Chinese text categorization. In this paper, we tackle the problem by developing a new way to calculate the class-specific weights for each term in the training phase; in the testing phase, the new documents are assigned to the centroid to which the document is most similar based on the weighted distance measurement. The experimental results demonstrate that the accuracy of our algorithm outperforms the traditional centroid-based classifiers, as well as outstanding efficiency compared with the Support Vector Machine (SVM) based classifiers for Chinese text categorization.