Miracle-dz/UniFAR-FTUs huggingface dataset:
Active exploration for feature based global localization

Presents an algorithm for active exploration of the environment by a mobile robot when performing global localization. During the localization process interesting regions for future exploration are selected based on already detected features and on the hypotheses generated by the localization algorithm. The localization process is improved by presenting it a richer set of features. The proposed algorithm provides highly robust global localization in real world environments with very low computational effort spent in finding exploration goal points. Experimental results are given, demonstrating the effectiveness of the algorithm in a number of different situations.
JNK-Induced MCP-1 Production in Spinal Cord Astrocytes Contributes to Central Sensitization and Neuropathic Pain

Our previous study showed that activation of c-jun-N-terminal kinase (JNK) in spinal astrocytes plays an important role in neuropathic pain sensitization. We further investigated how JNK regulates neuropathic pain. In cultured astrocytes, tumor necrosis factor α (TNF-α) transiently activated JNK via TNF receptor-1. Cytokine array indicated that the chemokine CCL2/MCP-1 (monocyte chemoattractant protein-1) was strongly induced by the TNF-α/JNK pathway. MCP-1 upregulation by TNF-α was dose dependently inhibited by the JNK inhibitors SP600125 (anthra[1,9-cd]pyrazol-6(2H)-one) and D-JNKI-1. Spinal injection of TNF-α produced JNK-dependent pain hypersensitivity and MCP-1 upregulation in the spinal cord. Furthermore, spinal nerve ligation (SNL) induced persistent neuropathic pain and MCP-1 upregulation in the spinal cord, and both were suppressed by D-JNKI-1. Remarkably, MCP-1 was primarily induced in spinal cord astrocytes after SNL. Spinal administration of MCP-1 neutralizing antibody attenuated neuropathic pain. Conversely, spinal application of MCP-1 induced heat hyperalgesia and phosphorylation of extracellular signal-regulated kinase in superficial spinal cord dorsal horn neurons, indicative of central sensitization (hyperactivity of dorsal horn neurons). Patch-clamp recordings in lamina II neurons of isolated spinal cord slices showed that MCP-1 not only enhanced spontaneous EPSCs but also potentiated NMDA- and AMPA-induced currents. Finally, the MCP-1 receptor CCR2 was expressed in neurons and some non-neuronal cells in the spinal cord. Together, we have revealed a previously unknown mechanism of MCP-1 induction and action. MCP-1 induction in astrocytes after JNK activation contributes to central sensitization and neuropathic pain facilitation by enhancing excitatory synaptic transmission. Inhibition of the JNK/MCP-1 pathway may provide a new therapy for neuropathic pain management.
Prognostics in switching systems: Evidential markovian classification of real-time neuro-fuzzy predictions

Condition-based maintenance is nowadays considered as a key-process in maintenance strategies and prognostics appears to be a very promising activity as it should permit to not engage inopportune spending. Various approaches have been developed and data-driven methods are increasingly applied. The training step of these methods generally requires huge datasets since a lot of methods rely on probability theory and/or on artificial neural networks. This step is thus time-consuming and generally made in batch mode which can be restrictive in practical application when few data are available. A method for prognostics is proposed to face up this problem of lack of information and missing prior knowledge. The approach is based on the integration of three complementary modules and aims at predicting the failure mode early while the system can switch between several functioning modes. The three modules are: 1) observation selection based on information theory and Choquet Integral, 2) prediction relying on an evolving real-time neuro-fuzzy system and 3) classification into one of the possible functioning modes using an evidential Markovian classifier based on Dempster-Shafer theory. Experiments concern the prediction of an engine health based on more than twenty observations.
Use of the Hospital Anxiety and Depression Scale and the Taiwanese Depression Questionnaire for screening depression in head and neck cancer patients in Taiwan

Objective The purposes of this study are 1) to estimate the prevalence of common mental disorders including depressive disorder in patients with head and neck cancer (HNC) at baseline and at the 6-month follow-up and 2) to test the validity of two self-reported questionnaires, the Hospital Anxiety and Depression Scale (HADS) and the Taiwanese Depression Questionnaire (TDQ), for screening depression in patients with HNC. Methods Participants were recruited from the outpatient collaborative care clinic for HNC of a tertiary hospital in Taiwan between January 2010 and January 2011. Ninety-three patients with HNC were enrolled and assessed using the HADS, TDQ, and Structured Clinical Interview for Diagnostic and Statistical Manual of Mental Disorders, fourth edition, Patient edition, at baseline and at the 6-month follow-up. Conventional validity indices of the HADS and TDQ were examined. Results Our results showed that the validity of the TDQ was satisfactory and comparable to that of both the HADS depression subscale and the HADS total scale. The cutoff scores of the HADS and TDQ for screening possible depressive disorders were 8 and 15, respectively. The areas under the receiver operating characteristic curve of the HADS and TDQ were mean 0.975±0.015 and 0.966±0.019, respectively. Thirteen participants (14%) were diagnosed with depressive disorders at the 6-month follow-up, compared with 8.5% at baseline. Conclusion Our results indicate that both the HADS and TDQ are valid instruments for screening depression in patients with HNC.
Low Bit Rate Video Coding Using DCT-Based Fast Decimation/Interpolation and Embedded Zerotree Coding

In this paper, we propose a low bit rate video coding procedure in the discrete cosine transform (DCT) domain that is based in an embedded zerotree algorithm and uses decimation and interpolation. Theory for decimation/interpolation in the DCT domain is presented, and its implementation with fast algorithms is shown. Motivated by the compositing of several video sources in multipoint video conferencing, we propose a new method for single streams that uses the proposed DCT-decimation in the encoder and the corresponding DCT-interpolation in the decoder. Decimated video frames are encoded using an embedded zerotree and an adaptive arithmetic coder to improve the quality of the decoded videos. Zerotree coding is a progressive coding method that quantizes amplitudes of DCT coefficients of video frames into bit streams with increasing precision. Embedded coding scheme depends on coding a symbol by an adaptive arithmetic encoder as soon as the symbol is obtained by the zerotree coding. Zerotree coder gives flexibility of controlling the bit rate precisely at given target bit rate. Compared to conventional coding our proposed algorithm achieves peak signal-to-noise ratio improvements at low bit rate video coding.
Making the Long Code Shorter

The long code is a central tool in hardness of approximation, especially in questions related to the unique games conjecture. We construct a new code that is exponentially more efficient, but can still be used in many of these applications. Using the new code we obtain exponential improvements over several known results, including the following: 1) For any ε >; 0, we show the existence of an n vertex graph G where every set of o(n) vertices has expansion 1 - ε, but G's adjacency matrix has more than exp(logδ n) eigenvalues larger than 1 - ε, where δ depends only on ε. This answers an open question of Arora, Barak and Steurer (FOCS 2010) who asked whether one can improve over the noise graph on the Boolean hypercube that has poly(log n) such eigenvalues. 2) A gadget that reduces unique games instances with linear constraints modulo K into instances with alphabet k with a blowup of Kpolylog(K), improving over the previously known gadget with blowup of 2Ω(K). 3) An n variable integrality gap for Unique Games that survives exp(poly(log log n)) rounds of the SDP + Sherali Adams hierarchy, improving on the previously known bound of poly(log log n). We show a connection between the local testability of linear codes and small set expansion in certain related Cayley graphs, and use this connection to derandomize the noise graph on the Boolean hypercube.
A SURVEY ON TRUST MANAGEMENT FOR MOBILE AD HOC NETWORKS

Mobile Ad Hoc Network (MANETs) is a Collection of mobile nodes connected with wireless links. MANET has no fixed topology as the nodes are moving constantly form one place to another place. All the nodes must co-operate with each other in order to route the packets. Cooperating nodes must trust each other. In defining and managing trust in a military MANET, we must consider the interactions between the composite cognitive, social, information and communication networks, and take into account the severe resource constraints (e.g., computing power, energy, bandwidth, time), and dynamics (e.g., topology changes, mobility, node failure, propagation channel conditions). Therefore trust is important word which affects the performance of MANET. There are several protocols proposed based on the trust. This paper is a survey of trust based protocols and it proposes some new techniques on trust management in MANETs.
Reaching a consensus on access detection by a decision system

Classification techniques based on Artificial Intelligence are computational tools that have been applied to detection of intrusions (IDS) with encouraging results. They are able to solve problems related to information security in an efficient way. The intrusion detection implies the use of huge amount of information. For this reason heuristic methodologies have been proposed. In this paper, decision trees, Naive Bayes, and supervised classifying systems UCS, are combined to improve the performance of a classifier. In order to validate the system, a scenario based on real data of the NSL-KDD99 dataset is used.
The dynamic sharing system of BitTorrent seed service: Based on EUCALYPTUS private cloud

This paper will present an application of EUCALYPTUS[1] in BitTorrent[2,7] seed services as a private cloud[13]. BitTorrent download is becoming increasingly popular, which brings seed servers[3] growing bandwidth pressure. If the traditional approach by adding multiple physical machines are taken to share the flow, not only to increase costs, but also not with dynamic scalability. In addition, the increase of one physical machine is only equivalent to the addition of one seed peer. Therefore, we provide a new, efficient, dynamic and easily managed solution: making use of EUCALYPTUS private cloud system to solve the problem of how to dynamically sharing the flow of BitTorrent seed server. In this paper, we use the characteristics of EUCALYPTUS, that is can be freely and quickly to start and stop multiple VMs(virtual machine) of same content[4,5], to elastic organize quantity of seed server according to heat of a certain seed. Then, GlusterFS [10] distributed file system is used to organize the background of storage resources. Moreover, this paper also discusses the improvements of EUCALYPTUS's resource management, as well as the performance analysis of this sharing system and related improvement mechanism.
Can Scheduling with Error Rate Consideration Support TCP Performance Comparable to Packet Combining HARQ in Evolved UTRA and UTRAN Networks?

As a key technology of evolved UTRA and UTRAN, hybrid ARQ with packet combining (HARQ with PC) can effectively improve the throughput performance for poor channel condition users without doing unacceptable level of harm to the system transmission efficiency or the throughput performance of good condition users. In the present study, we attempt to apply scheduling with error rate consideration as an alternative method by which to realize a comparable TCP performance to HARQ with PC. Scheduling with error rate consideration introduces the transmission failure possibility (error rate) in order to modify the existing channel-aware scheduling schemes to avoid high-risk transmissions, and thus improves TCP performance. Simulations show that scheduling with error rate consideration can realize a TCP performance comparable to HARQ with PC when no user continuously experiences a nearly zero successful transmission possibility environment. Moreover, it is shown herein that a synergistic improvement can be achieved by applying scheduling with error rate consideration to HARQ with PC
A Comparative Study of Coordinate Interleaved Orthogonal Design

ABSTRACT: Space time block code is a transmit diversity strategy used in MIMO technology. STBC-OD design is an attractive code which is having the property of full code rate and full diversity and single symbol decoding for two transmit antennas. Whereas this codes fails for the rate-1 transmission of more than two transmit antennas with the complex signal constellations. To achieve a full code rate and full diversity Space-time block code from coordinate interleaved orthogonal design (STBC-CIOD) is used in this paper.
A SMOOTHING NEWTON METHOD FOR THE BOUNDARY-VALUED ODEs

In this thesis, we focus on the Nonsmooth Boundary-valued ODEs, whose right- hand functions are parameterized by algebraic variables that solve the initial-valued problems and the nonsmooth equations. Based on the idea of the initial value tech- niques used in traditional ODEs, a smoothing Newton method originated from the QSZ method is applied to the nonmsmooth dynamic systems. Most significantly, we address a reformulation of the nonsmooth ODEs to make them applicable to the smoothing algorithm and facilitate the convergence analysis. Especially, the differential variational inequalities are served as the special case for discussion.
Anxiety Reduction With Music and Tempo Synchronization on Magnetic Resonance Imaging Patients

Anxiety and claustrophobic reactions in MRI examinations cause unintentional movements, and such motion artifacts lead to interpretation problems. Furthermore, requested anesthesia makes the process costly. A total of 60 outpatients were examined in the Diagnostic Centre of Pécs, Hungary, to test whether synchronizing recorded music to the gradient pulsation of the MRI device can improve the sedative effect of the music. The patients were assigned to three groups: a nonmusic (control), an original tempo (random) and a synchronized music (synchronous) group. Results showed a significantly decreased state anxiety level after the MRI examination in the random and synchronous groups as compared with the control group. However, there was no difference in the effectiveness of either music conditions regarding state anxiety level after the examination. Participants in the music groups found the examination significantly more pleasant compared with the control group. In conclusion, the present study provides support for the notion that listening to music during an MRI examination significantly reduces patient anxiety, whereas noise attenuating devices do not provide the same effect.
The influence of material constants on band gaps of piezoelectric phononic crystal

Band gaps of 2D piezoelectric phononic crystal and the influence of material constants are studied. Dispersive equations of 2D phononic crystal with piezoelectric ceramic cylinders embedded periodically in polymer host are derived based on plane wave expansion method firstly. Then, dispersive equations are numerically solved and the wave band gap distribution is obtained in the first Brillouin zone. The influence on wave band gap of elastic constants, piezoelectric constants and dielectric constants are compared and some interesting conclusions are finally given.
Improving Application Performance on HP/Convex Exemplar

The Earth and space sciences community faces rich computational challenges ranging from static, regular, and embarrassingly parallel to dynamic, unstructured, and tightly coupled. This problem domain requires highly scalable systems exhibiting broad generality, efficiency, and programmability. These capabilities are appearing in the emerging scalable shared memory cache-coherent architectures like that of the HP/Convex Exemplar SPP-1000. The goal of this class of architecture is to make scientific programming as easy and efficient as it is on vector supercomputers. The authors describe the Exemplar's architecture, whose global system organization comprises up to 16 multiprocessors interconnected by four SCI (Scalable Coherent Interface) ring networks. They then present the findings from four applications: the piecewise parabolic method, a finite-element method for unstructured meshes, a tree code for the n-body problem, and a particle-in-cell code. The authors present application performance data derived after the Exemplar at Goddard Space Flight Center went into production use. These studies expose the operational properties of the Exemplar and determine its suitability for Earth and space sciences applications. The testing reveals that global cache coherence can be used effectively to simplify programming and data migration. However, the basic problem of locality sensitivity still demands direct programmer involvement to achieve effective system behavior. The question of whether message-passing or shared memory programming models are better remains open.
Mothers with attention-deficit/hyperactivity disorder (ADHD) in the first twelve months postpartum : challenges, coping supports, strengths, and resilience : a two-part project based upon an investigation at MotherWoman, Hadley Massachusetts

This mixed-method study was undertaken to expand the knowledge base about mothers with a diagnosis of Attention-Deficit/Hyperactivity Disorder (ADHD) in the first twelve months after the birth of a baby. Nine mothers with an ADHD diagnosis and a child under the age of 60 months were interviewed. These mothers were asked to identify experiences with challenges, coping, depression, anxiety, and support in the first year postpartum. Quantitative data contrasting pre-child and postpartum executive functioning was retrieved during the interviews using the ASRS-v1.1© (Kessler et al., 2005). This quantitative data was also retrieved from 57 mothers as one part of a larger, on-line survey of mothers who had attended MotherWoman support groups. Findings from this study concurred with research regarding vulnerability of mothers with ADHD to perinatal depression and anxiety. This study indicated that social anxiety may be a recursive risk factor exerting a negative influence on maternal identity, self-esteem, and parenting self-efficacy in mothers with ADHD. Executive functioning skills appear to be impaired for many women in the postpartum period; however, questions were raised regarding the validity of the ASRS-v1.1© for ADHD screening in the postpartum period. This study allowed the voices of mothers with ADHD to be heard, thereby enriching and expanding upon the previous knowledge base. It shed light on challenges and coping; risks of perinatal mood and anxiety disorders; strengths; and supports of mothers with ADHD that may have potential bearing on the health and well-being of the mother, infant, and infant-mother dyad relationship. MOTHERS WITH ATTENTION-DEFICIT/HYPERACTIVITY DISORDER (ADHD) IN THE FIRST TWELVE MONTHS POSTPARTUM: CHALLENGES, COPING, SUPPORTS, STRENGTHS, AND RESILIENCE A two-part project based upon an independent investigation and an investigation at MotherWoman, Hadley, Massachusetts, submitted in partial fulfillment of the requirements for the degree of Master of Social Work. Maria T. Curtin-McKenna Smith College School for Social Work Northampton, Massachusetts 01063
From StirMark to StirTrace: Benchmarking pattern recognition based printed fingerprint detection

Artificial sweat printed fingerprints need to be detected during crime scene investigations of latent fingerprints. Several detection approaches have been suggested on a rather small test set. In this paper we use the findings from StirMark applied to exemplar fingerprints to build a new StirTrace tool for simulating different printer effects and enhancing test sets for benchmarking detection approaches. We show how different influence factors during the printing process and acquisition of the scan sample can be simulated. Furthermore, two new feature classes are suggested to improve detection performance of banding and rotation effects during printing. The results are compared with original existing detection feature space. Our evaluation based on 6000 samples indicates that StirTrace is suitable to simulate influence factors resulting into overall 195000 simulated samples. Furthermore, the original and our extended feature set show resistance towards image manipulations with the exception of scaling (to 50 and 200%) and cropping to 25%. The new feature space enhancement is capable for handling banding, rotation as well as removal of lines and columns and shearing artifacts, while the original feature space performs better for additive noise, median cut and stretching in X-direction.
Delay-range-Dependent Exponential Synchronization of Lur-e Systems with Markovian Switching

The problem of delay-range-dependent exponential synchronization is investigated for Lur’e master-slave systems with delay feedback control and Markovian switching. Using LyapunovKrasovskii functional and nonsingular M-matrix method, novel delayrange-dependent exponential synchronization in mean square criterions are established. The systems discussed in this paper is advanced system, and takes all the features of interval systems, Itô equations, Markovian switching, time-varying delay, as well as the environmental noise, into account. Finally, an example is given to show the validity of the main result. Keywords—Synchronization, Delay-range-dependent, Markov chain, Generalized Itô’s formula, Brownian motion, M-matrix.
A refined ICP algorithm for robust 3-D correspondence estimation

Robust registration of two 3-D point sets is a common problem in computer vision. The iterative closest point (ICP) algorithm is undoubtedly the most popular algorithm for solving this kind of problem. In this paper, we present the Picky ICP algorithm, which has been created by merging several extensions of the standard ICP algorithm, thus improving its robustness and computation time. Using pure 3-D point sets as input data, we do not consider additional information like point color or neighborhood relations. In addition to the standard ICP algorithm and the Picky ICP algorithm proposed in this paper, a robust algorithm due to Masuda and Yokoya and the RICP algorithm by Trucco et al. are evaluated. We have experimentally determined the basin of convergence, robustness to noise and outliers, and computation time of these four ICP based algorithms.
Reliability challenges and recent advances for Cu interconnects

Summary form only given. This paper discusses the reliability issues for Cu/low k interconnects, focusing on the impact due to the thermomechanical properties of low k dielectrics. Several basic questions arise concerning the dielectric effects on interconnect reliability, including the rate of mass transport, thermal stress and deformation behavior and failure mechanisms. In this paper, we address these issues and highlight some recent advances in understanding and improvement of electromigration (EM) and packaging reliability. We first discuss how materials and processes of the damascene structure lead to distinct characteristics and mechanisms for EM and packaging reliability of Cu interconnects. Then the impact of the low k dielectrics on reliability are discussed by comparing results from Cu/oxide and Cu/low k interconnects. Finally, we discuss recent advances and approaches developed to address these reliability challenges.