Miracle-dz/UniFAR-FTUs huggingface dataset:
Designing user-, hand-, and handpart-aware tabletop interactions with the TouchID toolkit

Recent work in multi-touch tabletop interaction introduced many novel techniques that let people manipulate digital content through touch. Yet most only detect touch blobs. This ignores richer interactions that would be possible if we could identify (1) which part of the hand, (2) which side of the hand, and (3) which person is actually touching the surface. Fiduciary-tagged gloves were previously introduced as a simple but reliable technique for providing this information. The problem is that its low-level programming model hinders the way developers could rapidly explore new kinds of user- and handpart-aware interactions. We contribute the TouchID toolkit to solve this problem. It allows rapid prototyping of expressive multi-touch interactions that exploit the aforementioned characteristics of touch input. TouchID provides an easy-to-use event-driven API as well as higher-level tools that facilitate development: a glove configurator to rapidly associate particular glove parts to handparts; and a posture configurator and gesture configurator for registering new hand postures and gestures for the toolkit to recognize. We illustrate TouchID's expressiveness by showing how we developed a suite of techniques that exploits knowledge of which handpart is touching the surface.
Sampling based hybrid algorithms for imbalanced data classification

The microarray technology can exhibit the expression levels of tens of thousands of genes simultaneously, which helps to diagnose diseases particularly cancer at molecular level. But one of the most challenging issues associated with this technology is the skewed nature of the datasets, which makes the traditional classifiers inefficient in producing accurate classification results. However, a lot of work addressing this issue on binary class problems has been done by many researchers. This paper has com- bined three different sampling techniques namely, over sampling; under sampling and SMOTE with a meta-learning algorithm 'DECORATE' to deal with a highly imbalanced multi-class microarray cancer dataset. The rate of accuracy of classification of the predictive models in case of imbalanced problem cannot be considered as an appropriate measure of effectiveness. Hence, different metrics are applied here to measure the performance of the proposed hybrid methods of classification. The experimen- tal results show that unlike other traditional classification algorithms, our proposed hybrid methods are not sensitive to highly skewed multi-class microarray dataset.
Geometric Imperfections and Residual Stresses for Use in the Analytical Modeling of Cold-formed Steel Members

Geometric imperfections and residual stresses influence the behavior and ultimate strength of cold-formed steel members. Advanced analytical models (Le. nonlinear finite element models) must reflect this by including appropriate geometric imperfections and residual stresses. To date, little has been done to summarize the existing literature on these topics. As a result, no consensus exists for what magnitudes or distributions should be used when including geometric imperfections and residual stresses in the analysis, In this paper existing literature is reviewed and a new series of measurements carried out with the goal of providing basic guidelines for the use of geometric imperfections and residual stresses in analytical models. The study results in promising methods for the measurement of imperfections, and shows that the existing literature can be used to at least partially realize the goal of using "practical inputs" in advanced analytical models.
Covariant Action for the Super-Five-Brane of M Theory

We propose a complete, d=6 covariant and kappa-symmetric, action for the M theory five-brane propagating in D=11 supergravity background. This opens a direct way of relating a wide class of super-p -brane solutions of string theory with the five-brane of M theory, which should be useful for studying corresponding dualities and nonperturbative aspects of these theories. {copyright} {ital 1997} {ital The American Physical Society}
Organizational Adoption of Web 2.0 Technologies: An Empirical Analysis

While Web 2.0 technologies such as blogs, wikis, and social networks have been popular in the consumer space, there is significant variation in adoption of Web 2.0 technologies in business. Yet, little is known about why firms adopt Web 2.0 technologies. There is a paucity of empirical research examining the antecedents of the use of Web 2.0 technologies in organizations. Drawing on the Technological-Organizational-Environmental theoretical framework, our study presents and empirically tests a model of factors associated with organizational adoption of Web 2.0 technologies. We find that importance to open standards is positively associated with the propensity for adoption of Web 2.0 technologies. Further, larger organizations are found to have a higher propensity for adoption. Finally, industry knowledge intensity is found to be positively associated with a higher propensity for adoption. Our results suggest that open architectures, firm size, and industry knowledge intensity play pivotal roles in Web 2.0 technology adoption. The study sheds light on antecedents of organizational adoption of Web 2.0 technologies and can help researchers and practitioners build an understanding of what factors are likely to motivate firms to adopt Web 2.0 technologies.
Cluster states, algorithms and graphs

The present paper is concerned with the concept of the one-way quantum computer,beyond binary-systems, and its relation to the concept of stabilizer quantum codes.This relation is exploited to analyze a particular class of quantum algorithms calledgraph algorithms, which correspond in the binary case to the Clifford group part of anetwork and which can efficiently be implemented on a one-way quantum computer.These algorithms can "completely be solved" in the sense that the manipulation ofquantum states in each step can be computed explicitly. Graph algorithms ace preciselythose which implement encoding schemes for graph codes. Starting from a given initialgraph, which represents the underlying resource of multipartite entanglement, each stepof the algorithm is related to a explicit transformation on the graph.
On Visualizing and Modelling BPEL with BPMN

The advantages of the process-based approach toimplementing applications lead to the development ofnotations for modelling business processes andlanguages for enacting them in a process engine forthe purpose of process automation. Currently theBusiness Process Modeling Notation (BPMN) istypically used for modelling business processes andthe Business Process Execution Language (BPEL) isused as the process execution format. Both languagesdiffer in purpose, expressivity and operationalsemantics. Recently it has been shown that there is nocomplete bi-directional mapping between BPMN andBPEL and transformations have been defined betweenthe two formalisms. However, these transformationslead to more complex models in both, BPEL andBPMN, and enable a roundtrip for only a limitednumber of scenarios. In this paper we show how BPELprocesses can be modelled using the graphical aspectof BPMN in order to facilitate modelling of executableprocesses using BPMN while avoiding modeltransformations.
Dynamic Authentication for Cross-Realm SOA-Based Business Processes

Modern distributed applications are embedding an increasing degree of dynamism, from dynamic supply-chain management, enterprise federations, and virtual collaborations to dynamic resource acquisitions and service interactions across organizations. Such dynamism leads to new challenges in security and dependability. Collaborating services in a system with a Service-Oriented Architecture (SOA) may belong to different security realms but often need to be engaged dynamically at runtime. If their security realms do not have a direct cross-realm authentication relationship, it is technically difficult to enable any secure collaboration between the services. A potential solution to this would be to locate intermediate realms at runtime, which serve as an authentication path between the two separate realms. However, the process of generating an authentication path for two distributed services can be highly complicated. It could involve a large number of extra operations for credential conversion and require a long chain of invocations to intermediate services. In this paper, we address this problem by designing and implementing a new cross-realm authentication protocol for dynamic service interactions, based on the notion of service-oriented multiparty business sessions. Our protocol requires neither credential conversion nor establishment of any authentication path between the participating services in a business session. The correctness of the protocol is formally analyzed and proven, and an empirical study is performed using two production-quality Grid systems, Globus 4 and CROWN. The experimental results indicate that the proposed protocol and its implementation have a sound level of scalability and impose only a limited degree of performance overhead, which is for example comparable with those security-related overheads in Globus 4.
Development, Synthesis, and Analysis of Surrogate Post-Detonation Nuclear Melt Glass

With the threats facing the world today, there is an ever-increasing need for training the the fields of radiochemistry and nuclear forensics. Training and research in these fields requires reference materials that accurately represent materials that could potentially be encountered. Unfortunately, many of the historical samples of debris from nuclear weapons tests remains classified. Because of this, there is a need for realistic surrogates. This research focuses on the development of surrogates for the bulk and particulate nuclear melt glass that is expected to be found in an urban setting after a nuclear event. A mathematical model for the creation of surrogate melt glass precursor matrices was developed. The model was used to determine the elemental composition of melt glass precursor for the Trinity site, New York City, and Houston, Texas. The precursor matrices were used to generated surrogate bulk nuclear melt glass. While this has been previously done for the Trinity site, this study marks the first time that surrogate bulk nuclear melt glass has been produced for urban scenarios. A thermal spray coater was used to demonstrate that the precursor matrices can be used to generate surrogate particulate melt glass. Both the bulk and particulate surrogate melt glasses were analyzed using scanning electron microscopy (SEM). Chemical differences on the surface of the samples was determined using backscatter electron analysis (BSE). Energy dispersive spectroscopy (EDS) was used to determine the elemental composition of features observed via SEM. A more complete elemental analysis of the surrogates was
On the impact of wireless multimedia network for multi-modal activity recognition

Due to the rapid development of sensor devices, many types of multimedia sensor data can be collected and analyzed to develop useful multimedia applications such as human activity recognition. Our objective of this research work is to study and analyze the impact of the wireless multimedia network quality on human activity recognition accuracy in an end-to-end networked multimedia system environment - Ocha House. We utilized the new improved Generalized Time Warping (GTW) algorithm and its variants for temporally aligning multi-modal sequences from multiple subjects performing similar human activities. In Ocha House, we captured the human activity data with camera sensors which are transmitted via wireless network for server processing and analysis. We evaluated the human activity recognition accuracy using GTW and its variants by taking into consideration of the wireless network data packet loss phenomenon due to common wireless network protocol behaviors as a result of network flow control and congestion management. We discovered that GTW and its variants are sensitive to wireless network packet loss and observed interesting characteristics resulting in deteriorated human activity recognition accuracy - when wireless network packet loss rate is nominal, the human activity recognition accuracy decreases dramatically.
Lignan Content in Cereals, Buckwheat and Derived Foods

Cereal foods are a fundamental part of a balanced diet and several studies have assigned to wholemeal cereal products a protective role in human health, due to their content of bioactive compounds. Within the phytochemicals, lignans are of increasing interest for their potential anticarcinogenic, antioxidant, estrogenic and antiestrogenic activities. The aim of this work is to contribute to the updating of food lignan databases by providing the profile and the amount of lignans in cereals, buckwheat and several cereal based foods commonly consumed in human diets. Values were taken from published papers. Items were divided in different groups, namely grains, brans and flours, bread, cereal staple foods, breakfast cereals and other cereal products, and values for secoisolariciresinol, matairesinol, pinoresinol, lariciresinol are given. For example, the total average values for the mentioned lignans in grains ranged between 23 μg/100 g and 401 μg/100 g dry weight. The contribution of each single lignan molecule to the total value of lignans appears to be different for every cereal species. Lignan content and typology in processed foods depends on the raw materials used, their degree of refinement and on processing conditions.
Incorporating Knowledge in Natural Language Learning: A Case Study

Incorporating external information during a learning process is expected to improve its eeciency. We study a method for incorporating noun-class information , in the context of learning to resolve Prepo-sitional Phrase Attachment (PPA) disambiguation. This is done within a recently introduced architecture , SNOW, a sparse network of threshold gates utilizing the Winnow learning algorithm. That architecture has already been demonstrated to perform remarkably well on a number of natural language learning tasks. The knowledge sources used were compiled from the WordNet database for general linguistic purposes , irrespective of the PPA problem, and are being incorporated into the learning algorithm by enriching its feature space. We study two strategies of using enriched features and the eeects of using class information at diierent granularities, as well as randomly-generated knowledge which serves as a control set. Incorporating external knowledge sources within SNOW yields a statistically signiicant performance improvement. In addition, we nd an interesting relation between the granularity of the knowledge sources used and the magnitude of the improvement. The encouraging results with noun-class data provide a motivation for carrying out more work on generating better linguistic knowledge sources.
Subjective quality assessment of zooming levels and image reconstructions based on region of interest for light field displays

As Light Field Displays are becoming widely investigated among the research community and are recently entering consumer market, the Quality of Experience reached on such displays plays a more and more essential role in the determination of their value. Apart from the common characteristics of autostereoscopic displays, the level of zoom on a given spatial resolution also affects the subjective quality assessment of the visualized content. In this paper, we present a subjective study on the level of zoom for Light Field Displays. The perceptual effects of reconstruction based on Region of Interest are also taken into consideration due to their direct connection to zooming. Two independent experiments were carried out and they were completed by 20 test participants each, and the results of the subjective evaluation are detailed in this paper. Our work also addresses subjective quality assessment methodologies, as they influence the results obtained by such experiments.
Pseudo-linear Programming

This short note revisits an algorithm previously sketched by Mathis and Mathis, Siam Review 1995, and used to solve a nonlinear hospital fee optimization problem. An analysis of the problem structure reveals how the Simplex algorithm, viewed under the correct light, can be the driving force behind a successful algorithm for a nonlinear problem. 1 A seemingly nonlinear program In a past Classroom Notes column, 6] Mathis and Mathis introduces an interesting optimization problem. Practical, in this era of budget constraints, their model describes a facet of hospital revenue and is used by managers in Texas to help in decision making. Even more interesting, for the theoretically minded, is the fact that a trivial algorithm seems to solve, albeit without a convergence proof, a nonlinear, arguably diicult problem. We revisit this problem to give a strong mathematical foundation to a slightly modiied algorithm and explain, along the way, why the problem is much simpler than expected at rst glance. The historically inclined will notice that the results used for this analysis are all thirty years old. Mathis and Mathis give a complete description of the problem to which we refer the reader. We just repeat the more important points of the model formulation.
Bipanconnectivity and Bipancyclicity in k-ary n-cubes

In this paper we give precise solutions to problems posed by Wang, An, Pan, Wang and Qu and by Hsieh, Lin and Huang. In particular, we show that Qn k is bipanconnected and edge-bipancyclic, when k ges 3 and n ges 2, and we also show that when k is odd, Qn k is m-panconnected, for m=(n(k-1)+2k-6)/2, and (k-1)-pancyclic (these bounds are optimal). We introduce a path-shortening technique, called progressive shortening, and strengthen existing results, showing that when paths are formed using progressive shortening then these paths can be efficiently constructed and used to solve a problem relating to the distributed simulation of linear arrays and cycles in a parallel machine whose interconnection network is Qn k, even in the presence of a faulty processor.
Statistical Determination of the Gating Windows for Respiratory-Gated Radiotherapy Using a Visible Guiding System

Respiratory-gated radiation therapy (RGRT) is used to minimize the radiation dose to normal tissue in lung-cancer patients. Although determining the gating window in the respiratory phase of patients is important in RGRT, it is not easy. Our aim was to determine the optimal gating window when using a visible guiding system for RGRT. Between April and October 2014, the breathing signals of 23 lung-cancer patients were recorded with a real-time position management (RPM) respiratory gating system (Varian, USA). We performed statistical analysis with breathing signals to find the optimal gating window for guided breathing in RGRT. When we compared breathing signals before and after the breathing training, 19 of the 23 patients showed statistically significant differences (p < 0.05). The standard deviation of the respiration signals after breathing training was lowest for phases of 30%–70%. The results showed that the optimal gating window in RGRT is 40% (30%–70%) with respect to repeatability for breathing after respiration training with the visible guiding system. RGRT was performed with the RPM system to confirm the usefulness of the visible guiding system. The RPM system and our visible guiding system improve the respiratory regularity, which in turn should improve the accuracy and efficiency of RGRT.
88. Study of the Elemental Partitioning for Different Transformation Conditions in the Ti-5553 Alloy

The microstructure and the solute distribution inside the phases after isothermal holding in the temperature range between 420°C and 700°C in the Ti-5553 alloy were analyzed using TEM equipped with an EDX analyzer and atom probe tomography. When phase transformation occurred at high temperatures (≥ 600°C), a significant partitioning of all solute elements was characterized. After a long holding time, the distribution was nearly homogeneous in each phase. For a transformation at lower temperature (410°C), a low partitioning was observed at the beginning of the transformation, after 40 min, and the precipitates composition notably evolved with increasing time toward an expected composition of equilibrium alpha phase.
Text mining: a new frontier for lossless compression

Data mining, a burgeoning new technology, is about looking for patterns in data. Likewise, text mining is about looking for patterns in text. Text mining is possible because you do not have to understand text in order to extract useful information from it. Here are four examples. First, if only names could be identified, links could be inserted automatically to other places that mention the same name, links that are "dynamically evaluated" by calling upon a search engine to bind them at click time. Second, actions can be associated with different types of data, using either explicit programming or programming-by-demonstration techniques. A day/time specification appearing anywhere within one's E-mail could be associated with diary actions such as updating a personal organizer or creating an automatic reminder, and each mention of a day/time in the text could raise a popup menu of calendar-based actions. Third, text could be mined for data in tabular format, allowing databases to be created from formatted tables such as stock-market information on Web pages. Fourth, an agent could monitor incoming newswire stories for company names and collect documents that mention them, an automated press clipping service. This paper aims to promote text compression as a key technology for text mining.
On the Limiting Distribution for the Length of the Longest Alternating Sequence in a Random Permutation

Recently Richard Stanley initiated a study of the distribution of the length as$_n(w)$ of the longest alternating subsequence in a random permutation $w$ from the symmetric group ${\cal S}_n$. Among other things he found an explicit formula for the generating function (on $n$ and $k$) for Pr$\,$(as$_n(w)\le k)$ and conjectured that the distribution, suitably centered and normalized, tended to a Gaussian with variance 8/45. In this note we present a proof of the conjecture based on the generating function.
Software Techniques for Multimodal Input Processing in Realtime Interactive Systems

Multimodal interaction frameworks are an efficient means of utilizing many existing processing and fusion techniques in a wide variety of application areas, even by non-experts. However, the application of these frameworks to highly interactive application areas like VR, AR, MR, and computer games in a reusable, modifiable, and modular manner is not straightforward. It currently lacks some software technical solutions that (1) preserve the general decoupling principle of platforms and at the same time (2) provide the required close temporal as well as semantic coupling of involved software modules and multimodal processing steps. This thesis approches current challenges and aims at providing the research community with a framework that fosters repeatability of scientific achievements and the ability to built on previous results.