Miracle-dz/UniFAR-FTUs huggingface dataset:
ShopBot: Progress in developing an interactive mobile shopping assistant for everyday use

The paper describes progress achieved in our long-term research project ShopBot, which aims at the development of an intelligent and interactive mobile shopping assistant for everyday use in shopping centers or home improvement stores. It is focusing on recent progress concerning two important methodological aspects: (i) the on-line building of maps of the operation area by means of advanced Rao-Blackwellized SLAM approaches using both sonar-based gridmaps as well as vision-based graph maps as representations, and (ii) a probabilistic approach to multi-modal user detection and tracking during the guidance tour. Experimental results of both the map building characteristics and the person tracking behavior achieved in an ordinary home improvement store demonstrate the reliability of both approaches. Moreover, we present first very encouraging results of long-term field trials which have been executed with three robotic shopping assistants in another home improvement store in Bavaria since March 2008. In this field test, the robots could demonstrate their suitability for this challenging real-world application, as well as the necessary user acceptance.
On the feasibility of collision detection in full-duplex 802.11 radio

Full-duplex radios are becoming a feasible reality thanks to recent advances in self-interference cancellation. Switching from half- to full-duplex requires a major re-design of many network features and characteristics, including the MAC layer. The literature provides several new proposals or improvements that are applicable in different topologies: centralized, distributed, and multi-hop Wireless LANs (WLANs). These proposals, however, mostly focus on directional, unicast communication. While the main goal of unicast-focused approaches is to get as close as possible to doubling the throughput, it is still unclear how to exploit full-duplex radios in broadcast-like environments such as the vehicular one or in general in WiFi-like scenarios where interference is the dominating impairment. In this work we analyze the possible benefits and drawbacks of exploiting self-interference cancellation in full-duplex radios to implement collision detection. We show that, if proved feasible, the required changes to the MAC layer of an 802.11-based transceiver would be minimal, and could largely improve the performance with respect to a standard collision avoidance mechanism. In addition, the paper discusses the tricky aspects and the parameters required to identify a collision in a wireless network and discusses the many differences between managing collisions in a wired and in a wireless environment.
Landmark-based sparse color representations for color transfer

We present a novel image representation that characterizes a color image by an intensity image and a small number of color pixels. Our idea is based on solving an inverse problem of colorization: Given a color image, we seek to obtain an intensity image and a small subset of color pixels, which are called landmark pixels, so that the input color image can be recovered faithfully using the intensity image and the color cues provided by the selected landmark pixels. We develop an algorithm to derive the landmark-based sparse color representations from color images, and use the representations in the applications of color transfer and color correction. The computational cost for these applications is low owing to the sparsity of the proposed representation. The landmark-based representation is also preferable to statistics-based representations, e.g. color histograms and Gaussian mixture models, when we need to reconstruct the color image from a given representation.
A security framework for the analysis and design of software attestation

Software attestation has become a popular and challenging research topic at many established security conferences with an expected strong impact in practice. It aims at verifying the software integrity of (typically) resource-constrained embedded devices. However, for practical reasons, software attestation cannot rely on stored cryptographic secrets or dedicated trusted hardware. Instead, it exploits side-channel information, such as the time that the underlying device needs for a specific computation. As traditional cryptographic solutions and arguments are not applicable, novel approaches for the design and analysis are necessary. This is certainly one of the main reasons why the security goals, properties and underlying assumptions of existing software attestation schemes have been only vaguely discussed so far, limiting the confidence in their security claims. Thus, putting software attestation on a solid ground and having a founded approach for designing secure software attestation schemes is still an important open problem. We provide the first steps towards closing this gap. Our first contribution is a security framework that formally captures security goals, attacker models and various system and design parameters. Moreover, we present a generic software attestation scheme that covers most existing schemes in the literature. Finally, we analyze its security within our framework, yielding sufficient conditions for provably secure software attestation schemes. We expect that such a consolidating work allows for a meaningful security analysis of existing schemes, supports the design of secure software attestation schemes and will inspire new research in this area.
Low-Overhead LogGP Parameter Assessment for Modern Interconnection Networks

Network performance measurement and prediction is very important to predict the running time of high performance computing applications. The LogP model family has been proven to be a viable tool to assess the communication performance of parallel architectures. However, non-intrusive LogP parameter assessment is still a very difficult task. We compare well known measurement methods for Log(G)P parameters and discuss their accuracy and network contention. Based on this, a new theoretically exact measurement method that does not saturate the network is derived and explained in detail. Our method only uses benchmarked values instead of computed parameters to compute other parameters to avoid propagation of first-order errors. A methodology to detect protocol changes in the underlying communication subsystem is also proposed. The applicability of our method and the protocol change detection is shown for the low-level API as well as MPI implementations of different modern high performance interconnection networks. The whole method is implemented in the tool Netgauge and it is available as open source to the public.
On liquid crystal flows with free-slip boundary conditions

In this paper, we study a coupled dynamic system describing nematic liquid crystal flows. The system was motivated by the Ericksen-Leslie equations modeling the flow of nematic liquid crystals. The purpose of studying the simplified system is to understand the flow properties of more complicated materials, the material configurations , as well as the interactions between them. Unlike in the previous studies where the Dirichlet boundary conditions are prescribed, we consider here the free-slip boundary conditions which possess a number of distinct advantages. The results in this paper form the analytical background for the forthcoming numerical simulations of the system.
Nonlinear analysis for chemical processes based on incremental dissipativity

Many chemical processes exhibit strong nonlinear dynamic behaviours which may present significant challenges to process operation and control, including input and output multiplicities. Input multiplicity refers to the phenomenon where different inputs (control action) result in the same steady state process output, which is commonly encountered in biochemical reactors. A process with input multiplicity is not invertible and thus is difficult to control as a feedback controller essentially attempts to invert the process model. A process with output multiplicity may produce different steady-state output depending on its initial state, which is often observed in exothermic reactors and obviously leads to a difficulty in achieving the desired output. The work provides a link between these properties of nonlinear chemical processes and the concept of incrementally dissipative systems in nonlinear system theory. The quantitative analysis of the above two phenomena is proposed. Furthermore, a test of the feasibility of controlling nonlinear chemical processes using linear controllers is developed. Such a test is of practical significance because it is often attempted to control nonlinear chemical processes using linear controllers in control practice due to the simplicity in control system design. As the concept of dissipativity can be linked to thermodynamics, the dissipativity based analysis can be potentially related to process design and provides more insights into integrated process design and control.
Growth Hormone (GH) Hypersecretion and GH Receptor Resistance in Streptozotocin Diabetic Mice in Response to a GH Secretagogue

The growth hormone (GH) and insulin-like growth factor I (IGF-I) axis were studied in streptozotocin (STZ) diabetic and nondiabetic female mice following intravenous (IV) injection of the GH secretagogue (GHS) ipamorelin or saline. On day 14, blood samples were obtained before and 10 minutes after the injection. Livers were removed and frozen for determination of the mRNA expressions of the GH receptor, GH-binding protein, and IGF-I, and hepatic IGF-I peptide. Serum samples were analyzed for GH and IGF-I. Following ipamorelin injection, the GH levels were found to be 150 ± 35 μg/L and 62 ± 11 μg/L in the diabetic compared to the nondiabetic mice (P < .05). Serum IGF-I levels were lower in diabetic than in nondiabetic animals, and rose after stimulation only in the nondiabetic animals. Furthermore, hepatic GH resistance and IGF-I mRNA levels and IGF-I peptide were increased in nondiabetic animals in response to GH stimulation, whereas the low levels per se of all these parameters in diabetic mice were unaffected. The study shows that STZ diabetic mice demonstrate a substantial part of the clinical features of type 1 diabetes in humans, including GH hypersecretion and GH resistance. Accordingly, it is proposed that STZ diabetic mice may be a better model of the perturbations of the GH/IGF-I axis in diabetes than STZ diabetic rats.
Assigning numbers to the arrows: Parameterizing a gene regulation network by using accurate expression kinetics

A basic challenge in systems biology is to understand the dynamical behavior of gene regulation networks. Current approaches aim at determining the network structure based on genomic-scale data. However, the network connectivity alone is not sufficient to define its dynamics; one needs to also specify the kinetic parameters for the regulation reactions. Here, we ask whether effective kinetic parameters can be assigned to a transcriptional network based on expression data. We present a combined experimental and theoretical approach based on accurate high temporal-resolution measurement of promoter activities from living cells by using green fluorescent protein (GFP) reporter plasmids. We present algorithms that use these data to assign effective kinetic parameters within a mathematical model of the network. To demonstrate this, we employ a well defined network, the SOS DNA repair system of Escherichia coli. We find a strikingly detailed temporal program of expression that correlates with the functional role of the SOS genes and is driven by a hierarchy of effective kinetic parameter strengths for the various promoters. The calculated parameters can be used to determine the kinetics of all SOS genes given the expression profile of just one representative, allowing a significant reduction in complexity. The concentration profile of the master SOS transcriptional repressor can be calculated, demonstrating that relative protein levels may be determined from purely transcriptional data. This finding opens the possibility of assigning kinetic parameters to transcriptional networks on a genomic scale.
SignalSense: towards quality service

The craving to remain "connected" has exploded since mobile phones became popular a few decades ago and are now fully entrenched in our lives as we become more and more dependent on connected services for professional, daily and social needs. Despite the significant demand from consumers and the push towards improved mobile technologies, many services delivered to the average consumer exhibit poor performance and quality. In this paper, we propose SignalSense, a highly interactive and novel mobile application that senses and records real-time mobile and wifi signal strength and quality for indoor/outdoor mapping. The application also uses mobile sensing to crowd-source signal information and intelligently combines them with geo-location data to make recommendations to users, leading to improved user experience. Initial evaluation demonstrates the need for such an application.
Game-Based Analysis and Improvement of a Fair Contract Signing Protocol

Traditional temporal logic regards protocols as close system to analyze. In order to overcome the shortcoming of traditional temporal logic, an game-based analysis method is inducted. This method is applied to formal analyze a fair contract signing protocol, and then some defects of the protocol are found. An improvement protocol is proposed which fixes the flaw by adding some extra time limit information and an abort sub-protocol. The fairness and the timeliness of the improvement protocol are validated by ATL formula and Invariant Checking. It is found that the improvement protocol satisfies the timeliness and the fairness.
E-Cadherin Methylation Status in Normal Thyroid Tissue , Goiter and Papillary Thyroid Cancer

Institution: Hospital São Lucas PUCRS. Porto Alegre / RS – Brazil. Address for correspondence: Bernardo Garicochea – Hospital São Lucas PUCRS – Oncology Department 2o fl, room 228 – Av. Ipiranga 6690 – Porto Alegre / RS – Brazil – Zip code: 90610-000 – Telephone: (+55 51) 3320-3319 – Fax: (+55 51) 3339-6039 – Email: bgarico@terra.com. br Article received on March 25, 2008. Article approved on July 1, 2008.
Maltese-cross slot-array type frequency selective surface for a submillimeter-wave band

A dual-polarization Maltese-cross slot array (MCSA) type frequency selective surface (FSS) is designed for separating the submillimeter-wave band around 600 GHz in view of future application to spaceborne submillimeter-wave spectrometric radiometer. Based on this design, the FSS is fabricated by applying a photolithographic process on a thin dielectric (SiN) substrate. The transmission and reflection characteristics measured for the fabricated MCSA agree well with those simulated by the method-of-moment calculation. The possibility of the broadening of the transmission bandwidth by stacking the MCSA in two layers is also discussed.
Trade Liberalisation and Import Margins

Trade policy has well documented effects on trade volumes. Reaching beyond volumes, I explore the impact of European emerging economies’ recent institutional trade liberalisation on extensive (i.e., the set of imported goods) versus intensive import margins (volumes per imported good) with highly disaggregated data. Differentiating goods categories by use, I find robust evidence of stronger extensive import margin effects of liberalisation for intermediate and capital goods compared to consumer goods. This identifies an important channel for the link between reforms and growth in transition. The results also support new models of heterogeneous firms and trade, which predict that extensive import margin effects of a country’s institutional trade liberalisation should – via lowering fixed costs for rest of the world exporters – increase with decreasing substitutability among products.
Methods to Optimize Recruitment and Retention to an Exercise Study in Chinese Immigrants

Background: To counter pervasive disparities in healthcare and guide public health prevention programs, culturally sensitive recruitment and retention strategies for Chinese immigrants participating in health-related research studies are needed. Objectives: The aim of this study was to develop and implement recruitment and retention strategies with Chinese immigrants in a Tai Chi exercise study. Methods: After substantial project planning and incorporating community-based research principles, a multidimensional approach was used to ensure minimal loss to follow-up. Recruitment strategies included partnering with a community-based agency, distributing study information using a multimedia approach, communicating in the native language, and demonstrating cultural sensitivity. Retention strategies included establishing a tracking method during recruitment, providing personalized feedback, maintaining the same location for all aspects of the study, eliminating potential linguistic barriers, providing personal attention and encouragement, monitoring attendance, utilizing a charismatic Tai Chi instructor, respecting Chinese culture, providing appropriate incentives, and maintaining good communication. Results: Sixty persons showed interest in the study, 52 persons were screened, and 39 persons were enrolled. Recruitment was completed within 3 weeks. An advertisement in the Chinese newspaper was the most fruitful recruitment source, yielding approximately 60% of the study participants. Retention in the study was also very high (97%, n = 38). Discussion: The successful recruitment and retention of Chinese immigrants in this Tai Chi exercise study are due to a variety of factors on many levels, including the participants, study investigator, and community-based agency.
CD-HIT Workflow Execution on Grids Using Replication Heuristics

Grid computing has proven to be a solution for big workflow execution, especially in Bioinformatics. However, grid nature itself introduces overheads that make its use in many cases an unfeasible solution if considering wall-time. Different heuristics such as list scheduling, agglomeration and replication are available for optimizing workflow execution. In particular, the replication heuristics have been previously used in heterogeneous environments with good results. In this work, we analyze their use for workflow scheduling on Grid infrastructures. In particular, we study its applications to an intree workflow, generated by the distribution of the CD-HIT application. The experiments were conducted on a testbed made of resources from two different grids and results show a significant reduction of the workflow execution time.
Morphological filtering in shape spaces: Applications using tree-based image representations

Connected operators are filtering tools that act by merging elementary regions of an image. A popular strategy is based on tree-based image representations: for example, one can compute an attribute on each node of the tree and keep only the nodes for which the attribute is sufficiently strong. This operation can be seen as a thresholding of the tree, seen as a graph whose nodes are weighted by the attribute. Rather than being satisfied with a mere thresholding, we propose to expand on this idea, and to apply connected filters on this latest graph. Consequently, the filtering is done not in the space of the image, but on the space of shapes build from the image. Such a processing is a generalization of the existing tree-based connected operators. Indeed, the framework includes classical existing connected operators by attributes. It also allows us to propose a class of novel connected operators from the leveling family, based on shape attributes. Finally, we also propose a novel class of self-dual connected operators that we call morphological shapings.
An investigation of performance enhancement for tunable microstrip filter

This paper reports an investigation of performance enhancement for electronically tunable microstrip filter. Based on the effects of lossy components on passband response of a bandpass filter, a new concept to improve the performance (passband flatness and selectivity) is proposed. Unlike other techniques published, this new concept results in nonuniform Q distribution by loading lumped elements to reduce the unloaded Q of the resonator. As examples, fixed and tunable microstrip combline filters with narrow band are simulated and fabricated to validate the proposed concept.
Online Similarity Prediction of Networked Data from Known and Unknown Graphs

We consider online similarity prediction problems over networked data. We begin by relating this task to the more standard class prediction problem, showing that, given an arbitrary algorithm for class prediction, we can construct an algorithm for similarity prediction with "nearly" the same mistake bound, and vice versa. After noticing that this general construction is computationally infeasible, we target our study to {\em feasible} similarity prediction algorithms on networked data. We initially assume that the network structure is {\em known} to the learner. Here we observe that Matrix Winnow \cite{w07} has a near-optimal mistake guarantee, at the price of cubic prediction time per round. This motivates our effort for an efficient implementation of a Perceptron algorithm with a weaker mistake guarantee but with only poly-logarithmic prediction time. Our focus then turns to the challenging case of networks whose structure is initially {\em unknown} to the learner. In this novel setting, where the network structure is only incrementally revealed, we obtain a mistake-bounded algorithm with a quadratic prediction time per round.
A method to accelerate writer adaptation for on-line handwriting recognition of a large character set

An approach to accelerate writer adaptation for on-line handwriting recognition is proposed. It is known that adapting to a writer by learning the writer's own style significantly improves recognition accuracy. However, adapting to a writer can take considerable time until the performance comes up to a satisfactory level, particularly for recognition of a large character set. This paper proposes an adaptation method which uses not only misclassified patterns but also correctly-classified patterns as learning samples. The strategy employed in the method selects acquired prototypes based on their contribution to classification, while treating the misclassified prototypes (i.e. the acquired prototypes that were misclassified before being added) with higher priority when updating the prototype set. The results demonstrate that the proposed method improves the performance and accelerates adaptation especially during the early phase of adaptation. It is also shown that the method yields stable improvement in accuracy over a long period of adaptation with the computational cost acceptable for most real applications.
Random Subspace Method in Text Categorization

In text categorization (TC), which is a supervised technique, a feature vector of terms or phrases is usually used to represent the documents. Due to the huge number of terms in even a moderate-size text corpus, high dimensional feature space is an intrinsic problem in TC. Random subspace method (RSM), a technique that divides the feature space to smaller ones each submitted to a (base) classifier (BC) in an ensemble, can be an effective approach to reduce the dimensionality of the feature space. Inspired by a similar research on functional magnetic resonance imaging (fMRI) of brain, here we address the estimation of ensemble parameters, i.e., the ensemble size (L) and the dimensionality of feature subsets (M) by defining three criteria: usability, coverage, and diversity of the ensemble. We will show that relatively medium M and small L yield an ensemble that improves the performance of a single support vector machine, which is considered as the state-of-the-art in TC.