Miracle-dz/UniFAR-FTUs huggingface dataset:
The Effect of Interaction-Display Offset on User Performance for a 3 D-Widget Task in the Cave

Interaction in Immersive Virtual Environments (VEs) is fundamentally driven by the physical actions of the user’s body. The location of rendered virtual objects is, in contrast, the free choice of the VE application designer. The goal of Dmitri Lemmerman’s masters degree project is to explore the effect of the position of rendered graphical “widgets” on user performance in the use of those widgets. The particular task chosen was color-matching: using a 3D color picking widget, users were asked to match a target color. The independent variable was a scalar describing the offset between the interaction frame-of-reference (where the user moves his physical body) and the display frame-of-reference (where the graphical feedback appears). This relationship is not unique to the color picking widget, but generalizes to a larger set of 3D widgets in VEs. In the experiment, the relative position of the widget with respect to the user is tested in three conditions. While maintaining the same interaction frame-ofreference, the relative position of the display frame-of-reference is varied: to be the same as the interaction frame-of-reference (e.g. collocation), to be displayed at a 3 inch offset, and to be displayed at a 2 feet offset from the interaction frame-ofreference. Twenty-nine users were tested in a within-subjects design. Each subject was asked to match 15 colors in each of the 3 conditions. A distance scalar was computed based on a perceptual metric. A repeated measures ANOVA test on the data revealed a significant main effect of offset with a confidence of p < . 05. Paired sample t-tests between the conditions did show a significant difference between the collocated case and each of the offset cases, but did not show a significant difference between the two offset cases. These results suggest that the presence of the user’s body appears to degrade performance when it is collocated with the virtual objects on which the user must focus (as it was in one of the conditions). However, even a short offset of 3 inches seems to alleviate this problem. Studies in HMD-based VEs have demonstrated significant performance advantages to collocation and the “direct manipulation” of virtual objects. Unlike HMDbased systems, a Cave-based VE platform allows the user to see both his body as well as the virtual objects. The results of this study should inform future VE user interface design for real-world applications and spur further experimental research in human/VE interaction principles.
Models for Sample Selection Bias

When observations in social research are selected so that they are not independent of the outcome variables in a study, sample selection leads to biased inferences about social processes. Nonrandom selection is both a source of bias in empirical research and a fundamental aspect of many social processes. This chapter reviews models that attempt to take account of sample selection and their applications in research on labor markets, schooling, legal processes, social mobility, and social networks. Variants of these models apply to outcome variables that are censored or truncated—whether explicitly or incidentally—and include the tobit model, the standard selection model, models for treatment effects in quasi-experimental designs, and endogenous switching models. Heckman’s two-stage estimator is the most widely used approach to selection bias, but its results may be sensitive to violations of its assumptions about the way that selection occurs. Recent econometric research has developed a wide variety of pro.
Wizard-of-Oz prototyping for co-operative interaction design of graphical user interfaces

It is often difficult for users to specify requirements on interactivity in multimedia products. These properties are often designed by designers or software engineers and the users run the risk of playing a passive role having low influence on important decisions made. This paper presents an attempt to improve the interactive design process by using graphical Wizard-of-Oz prototyping. The study shows that graphical Wizard-of-Oz prototyping allow co-operative design and test of computer interaction early in the design process ahead of traditional programming. It also demonstrates that this type of prototyping can promote collaboration and constructive dialogue between users and designers, thus strengthening the user as a stakeholder in the development process.
A Primer on the Orthogonal GARCH Model

The generation of large, positive semi-definite covariance matrices has presented a great challenge to finance practitioners for many years. Since the 1996 Amendment to the 1988 Basle accord, where the principals of internal models for the calculation of market risk capital were outlined, it has been a major problem to generate the covariance matrices that are necessary to calculate firm-wide value-at-risk measures. Large covariance matrices also have a major role to play in investment analysis, because portfolio risk is normally determined by the covariance matrix of all the assets in the portfolio. In very large portfolios a risk factor model may be employed, but it is still necessary to have a covariance matrix of all the risk factors of the portfolio. The need for large covariance matrices is not just confined to the middle office of a large investment bank. The traders in the front office also require these matrices to price and hedge their option portfolios.
A new approach for epileptic seizure detection: sample entropy based feature extraction and extreme learning machine

The electroencephalogram (EEG) signal plays a key role in the diagnosis of epilepsy. Substantial data is generated by the EEG recordings of ambulatory recording systems, and detection of epileptic activity requires a time-consuming analysis of the complete length of the EEG time series data by a neurology expert. A variety of automatic epilepsy detection systems have been developed during the last ten years. In this paper, we investigate the potential of a recently-proposed statistical measure parameter regarded as Sample Entropy (SampEn), as a method of feature extraction to the task of classifying three different kinds of EEG signals (normal, interictal and ictal) and detecting epileptic seizures. It is known that the value of the SampEn falls suddenly during an epileptic seizure and this fact is utilized in the proposed diagnosis system. Two different kinds of classification models, back-propagation neural network (BPNN) and the recently-developed extreme learning machine (ELM) are tested in this study. Results show that the proposed automatic epilepsy detection system which uses sample entropy (SampEn) as the only input feature, together with extreme learning machine (ELM) classification model, not only achieves high classification accuracy (95.67%) but also very fast speed.
Is a CEO Turnover Good or Bad News

We investigate the information content of CEO turnovers by analyzing abnormal stock returns and the operating performance around the announcement date. The sample consists of 208 CEO turnovers between January 1998 and June 2009 for companies belonging to the Swiss Performance Index. In line with previous studies, outside successions and forced turnovers yield positive and significant abnormal returns. However, a forced turnover does not per se represent a positive signal to shareholders. On the contrary, investors seem to critically assess the quality of the board’s firing decision by considering the quality of the departing manager. When an outperforming CEO is dismissed or forced to leave - an event that occurs in as many as 33% of all dismissals in our sample - shareholders appear to disesteem the board’s decision. This finding is confirmed in multivariate cross-sectional regressions and is robust to time subperiods and alternative test statistics. Finally, the operating performance significantly increases (decreases) in the years following (preceding) CEO turnovers and reflects on average the short-term stock-price reaction around the announcement date.
Verification of a fast training algorithm for multi-channel sEMG classification systems to decode hand configuration

In this study, we evaluated a fast training algorithm to decode human hand configuration from sEMG signals on the forearms of five subjects. Eight skin surface electrodes were placed on the forearm of each subject to detect the sEMG signals corresponding to four different hand configurations and relax state. The preamplifier, which has 100 - 10000 times amplification gain and a 15 - 500 Hz bandpass filter, was designed to amplify the signals and eliminate noise. In order to enhance the performance of the classifier, feature extraction using class information was developed. The randomly assigned non-update learning method guarantees high speed classifier learning. The algorithm has been verified by experiments with five subjects.
Improved Image Retrieval Using Automatic Image Sorting and Semi-automatic Generation of Image Semantics

In this paper we propose a new image search system using keyword annotations and low-level visual meta-data to generate inter-image relationships. Unlike other approaches the new system does not try to learn the degree of confidence between images and associated keywords. We rather propose to model the degree of similarity between images by building up a network of linked images. The weights of the inter-image links are learned from the userspsila interaction with the system only. For each image search a set of candidate images is selected from a visually sorted arrangement of result images. This candidate set is used to refine the result by filtering out non-suiting images from a larger set of further result images. Semantic inter-image relation-ships of images can be modeled by collecting the candidate sets from many searches. Our system improves Internet image search significantly.
The $\overline\partial$-Neumann operator on Lipschitz pseudoconvex domains with plurisubharmonic defining functions

On a bounded pseudoconvex domain in C with a plurisubharmonic Lipschitz defining function, we prove that the ∂̄-Neumann operator is bounded on Sobolev (1/2)-spaces. 0. Introduction Let D be a bounded pseudoconvex domain in C with the standard Hermitian metric. The ∂̄-Neumann operator N for (p, q)-forms is the inverse of the complex Laplacian = ∂̄ ∂̄∗ + ∂̄∗∂̄ , where ∂̄ is the maximal extension of the Cauchy-Riemann operator on (p, q)-forms with L2-coefficients and ∂̄∗ is its Hilbert space adjoint. The existence of the ∂̄-Neumann operator for any bounded pseudoconvex domain follows from Hörmander’s L2-existence theorems for ∂̄ . The ∂̄-Neumann problem serves as a prototype for boundary value problems that are noncoercive and is of fundamental importance in the theory of several complex variables and partial differential equations. The ∂̄-Neumann problem has been studied extensively when the domain D has smooth boundary (see J. Kohn [21], [22] or H. Boas and E. Straube [4], [6] and the references within). In this paper we study the ∂̄-Neumann operator on a Lipschitz domain D when D has a plurisubharmonic defining function (see Theorem 1). Let H (p,q)(D) denote Hilbert spaces of (p, q)-forms with H (D)-coefficients. Their norms are denoted by ‖ ‖s(D) for s ≥ 0. The principal result of this paper is the following theorem. theorem 1 Let D C be a bounded pseudoconvex Lipschitz domain with a defining function that is plurisubharmonic in D. The ∂̄-Neumann operator N is bounded from DUKE MATHEMATICAL JOURNAL Vol. 108, No. 3, c © 2001 Received 30 September 1999. Revision received 22 August 2000. 2000 Mathematics Subject Classification. Primary 35N15; Secondary 32W05. Shaw’s work partially supported by National Science Foundation grant number DMS 98-01091.
Evaluating performance and acceptance of older adults using freehand gestures for TV menu control

In this paper, we explore alternative TV menu control methods, focusing specifically on older users. We investigated performance and acceptance of freehand gestures by implementing several techniques and conducting a user study with 24 older adults. We expected that older adults would like gesture techniques as they are generally fun to use and easy to conduct. As a possible alternative to physical remote control, gesture techniques may also introduce some physical activity for older adults (positive health effects). In the user study, we compared four different kinds of freehand gesture interaction to control a corresponding TV menu, investigating specifically on abilities of older adults. Each of the interaction types was analyzed regarding task completion time, error rate, usability and acceptance. Results showed that directly transferring tracked hand movements to control a cursor on a TV achieved the best performance and was preferred by the users. In general, the participating older adults showed a very positive attitude towards gesture-based interactions.
Structure and Subunit Arrangement of the A-type ATP Synthase Complex from the Archaeon Methanococcus jannaschii Visualized by Electron Microscopy*

In Archaea, bacteria, and eukarya, ATP provides metabolic energy for energy-dependent processes. It is synthesized by enzymes known as A-type or F-type ATP synthase, which are the smallest rotatory engines in nature (Yoshida, M., Muneyuki, E., and Hisabori, T. (2001) Nat. Rev. Mol. Cell. Biol. 2, 669–677; Imamura, H. , Nakano, M. , Noji, H. , Muneyuki, E. , Ohkuma, S. , Yoshida, M. , and Yokoyama, K. (2003) Proc. Natl. Acad. Sci. U. S. A. 100, 2312–2315). Here, we report the first projected structure of an intact A1A0 ATP synthase from Methanococcus jannaschii as determined by electron microscopy and single particle analysis at a resolution of 1.8 nm. The enzyme with an overall length of 25.9 nm is organized in an A1 headpiece (9.4 × 11.5 nm) and a membrane domain, A0 (6.4 × 10.6 nm), which are linked by a central stalk with a length of ∼8 nm. A part of the central stalk is surrounded by a horizontal-situated rodlike structure (“collar”), which interacts with a peripheral stalk extending from the A0 domain up to the top of the A1 portion, and a second structure connecting the collar structure with A1. Superposition of the three-dimensional reconstruction and the solution structure of the A1 complex from Methanosarcina mazei Gö1 have allowed the projections to be interpreted as the A1 headpiece, a central and the peripheral stalk, and the integral A0 domain. Finally, the structural organization of the A1A0 complex is discussed in terms of the structural relationship to the related motors, F1F0 ATP synthase and V1V0 ATPases.
A study on a robotic arm contacting with human skin using tactile sensing feedback strategies

Inspired by human's tactile sensing in daily lives, we present an approach using the tactile sensing plus force-torque information as the feedback to control the robotic arm interacting with our soft human skin in this paper. Three main types of contact between the end-effector of robotic arm and human skin are introduced and the contact model is built up. Hybrid impedance control method is applied to control both the position and force trajectories of the manipulator at the same time. With the feedback of tactile sensing data such as contact state, contact area and so on, several strategies of tactile sensing feedback are included in the control algorithm. Two groups of real experiments are made using a two-link robotic arm equipped with force/torque and tactile sensors to contact with human skin. The results have confirmed the effectiveness of the proposed strategies.
Simulation of user-interaction for performance evaluation of interactive image segmentation methods

Interactive image segmentation is often employed in the context of medical image analysis, as an alternative to automatic and manual image segmentation. In the last decade it has attracted a lot of attention due to the advent of efficient algorithms able to perform in interactive speed even for large three dimensional (3D) images. However, the human integration in the segmentation process restricts its repeatability and impedes its objective evaluation. Also, it inhibits the identification of the intrinsic properties of the algorithms. In this paper we report on a framework for performance evaluation of interactive image segmentation techniques, which is based on simulated user interaction. This allows for the construction of reproducible and tractable experiments, which can form the basis of a systematic and objective performance evaluation framework for interactive segmentation methods. We demonstrate quantitative results using three interactive segmentation algorithms from the literature.
User Behavior and Bias in Click-Based Recommender Evaluation

Measuring the quality of recommendations produced by a recommender system (RS) is challenging. Labels used for the evaluation are typically obtained from users of a RS; such explicit labels reflect true user preferences but may introduce significant biases in the evaluation process. In this paper, we investigate biases that may affect labels inferred from implicit feedback, such as clicks or other user interactions. Implicit feedback is easy to collect as it is a side product of users’ natural interactions, but can be particularly prone to biases, such as position bias. We examine this bias using click models that were developed in the information retrieval community, and show how bias following these models would affect the outcomes of RS evaluation. We find that evaluation based on implicit and explicit feedback can agree well, but only when the evaluation metrics are designed to take user behavior and preferences into account. Our results highlight the importance of understanding user behavior in deployed RS.
The Time and Location of Natural Reading Processes in the Brain

How is information organized in the brain during natural reading? Where and when do the required processes occur, such as the perception of individual words and the construction of sentence meanings. How are semantics, syntax and higher-level narrative structure represented? Answering these questions is core to understanding how the brain processes language and organizes complex information. However, due to the complexity of language processing, most brain imaging studies focus only on one of these questions using highly controlled stimuli which may not generalize beyond the experimental setting. This thesis proposes an alternative framework to study language processing. We acquire data using a naturalistic reading paradigm, annotate the presented text using natural language processing tools and predict brain activity with machine learning techniques. Finally, statistical testing is used to form rigorous conclusions. We also suggest the use of direct non-parametric hypothesis tests that do not rely on any model assumptions, and therefore do not suffer from model misspecification. Using our framework, we construct a brain reading map from functional magnetic resonance imaging data of subjects reading a chapter of a popular book. This map represents regions that our model reveals to be representing syntactic, semantic, visual and narrative information. Using this single experiment, our approach replicates many results from a wide range of classical studies that each focus on one aspect of language processing. We extend our brain reading map to include temporal dynamics as well as spatial information by using magnetoencephalography. We obtain a spatio-temporal picture of how successive words are processed by the brain. We show the progressive perception of each word in a posterior to anterior fashion. For each region along this pathway we show a differentiation of the word properties that best explain its activity.
OBDD-based Deterministic Planning using the UMOP

Model checking representation and search techniques were recently shown to be eeciently applicable to planning. Ordered Binary Decision Diagrams (obdds) encode a planning domain as a nite transition system and fast algorithms from model checking search for a solution plan. With proper encodings, obdds can effectively scale and can provide plans for complex planning domains. In this paper, we present results obtained in classical deterministic domains using umop, 1 a new universal obdd-based planning framework applicable to non-deterministic and multi-agent domains (Jensen & Veloso, 1999). A key diierence between umop and previous obdd-based planning systems is that the obdd encoding of planning problems is partitioned. This representation is known from model checking to scale up the problem size that can be handled (Ranjan et al., 1995). Experimental results from the strips track of the AIPS'98 planning competition show that this is also the case for obdd-based planning. The results further indicate that umop is an eecient deterministic planning system.
A Protocol for Text Retrieval in Structured P2P Networks

For the problems of complex queries, load balance and routing efficiency in structured P2P networks based on DHT, a protocol is presented for text retrieval on the basis of Kleinberg small world model. In this protocol, nodes are clustered to support complex query according to the similarity of nodes, and the grouped nodes could adjust their size to balance the load of networks. Routing path length is shortened by the long-link between node clusters. Experiment results show that search cost is increased with the curve of the square of logarithm and maintenance cost is linearly increased as the scale of networks goes up. The total cost will be minimized with proper cluster size.
CREATING A FIT BETWEEN OPEN INNOVATION AND MASS COLLABORATION – A Conceptual Model

This paper develops an alternative artefact for an open innovation and mass collaboration based on suggested Open Innovation Collaboration Model (OICM) enabled through social media. Web 2.0 technologies are key factors in long-term sustainability of Small Medium Enterprises (SME ́s). Business continuity, innovation and the long-term sustainability of SME depend partly on accumulated organizational knowledge. The suggested model helps in enabling and driving open innovation and mass collaboration. Central to this research is the creation of connection oriented dynamic relation between mass collaboration and open innovation. The created fit indicates that OICM ensures the collaboration among peers, which supports in creation of new knowledge and ultimately allows the innovation to happen and enter across the firm.
A middleware-based approach for heterogeneous wireless sensor networks

Wireless sensor networks (WSN) are networked embedded systems that use small size devices with some processing and short-range radio communication capabilities for monitoring and controlling systems and environments. However, languages and IDE (Integrated Development Environments) used to develop applications for WSN are often strictly related to the involved HW/SW platform leading to complex activities, especially when dealing with heterogeneous WSN composed of nodes with different hw features, operating systems, communication standards, etc. A middleware (MW) is a SW abstraction layer between operating systems and applications that simplify operations, enable heterogeneity and masks the basic HW/SW layers (of remote or local devices). Finally, a middleware concretely helps the designer to develop applications, and this is especially true in the heterogeneous WSN world. So, this work presents a middleware-based approach for WSN that copes with radio heterogeneity, i.e. it is able to transport data across heterogeneous networks (i.e. based on different communication standard) while offering to the designer an homogenous API (Application Programming Interface) for the applications development.