Miracle-dz/UniFAR-FTUs huggingface dataset:
Cellular Networks : Radio Link Performance

In this paper, we explore the feasibility of designing an outdoor cellular network based on the IEEE 802.11 standard, which was developed originally for wireless local-area networks. For channels typical in cellular networks, we study the radio link power budget and, via simulation, the bit-error performance of three kinds of receiver: (1) the constrained RAKE, which is limited to a 1 s μ multipath span; (2) the full RAKE, which uses the full multipath channel information; and (3) the ideal equalizer, the performance of which is represented by the matched filter bound. Our link budget reveals that the maximum cell radius in an outdoor 802.11 network ranges from 0.7 to 3 km, about half that supported by W-CDMA and EDGE networks. For an rms delay spread of 1 s μ , typical for urban-area cells of this size, our simulation results show that the conventional constrained RAKE receiver may yield a satisfactory performance. The improved receivers, however, yield 1–5 dB gain over the constrained implementation. Combining these results with those in a companion paper on the MAC protocol, we conclude that an 802.11-based cellular network with a cell radius of a few km is feasible. Index Terms — Cellular networks, dispersive channel, equalization, IEEE 802.11, radio link budget, radio link performance, RAKE receiver, wireless local-area networks.
Reverse engineering of test cases for selective regression testing

A problem arises in the maintenance of large systems when the links between the specification based test cases and the code components they test are lost. It is no longer possible to perform selective regression testing because it is not known which test cases to run when a particular component is corrected or altered. To regain that knowledge, it is necessary to restore the links between test cases and code. We describe two complementary approaches to achieving that goal of reverse engineering - one by static analysis and the other by dynamic analysis. The objective in both cases is to determine which test cases exercise which methods in which components in order to enable selective regression testing.
On the Multi-User Diversity with Secrecy in Uplink Wiretap Networks

In this letter, we consider the uplink wiretap network which consists of a base station, N legitimate users, and several eavesdroppers. We propose a novel user scheduling algorithm based on a threshold, which achieves the optimal multi-user diversity gain, i.e., log log N. To the best of our knowledge, there has been no such result in uplink wiretap networks. In order to obtain good throughput performance in the network, the threshold value needs to be carefully chosen. Through extensive simulations, we observe that the proposed user scheduling outperforms the conventional scheduling algorithms and it approaches the throughput performance of the optimal user scheduling algorithm in various scenarios.
Exploiting Data-Dependent Structure for Improving Sensor Acquisition and Integration

Title of dissertation: EXPLOITING DATA-DEPENDENT STRUCTURE FOR IMPROVING SENSOR ACQUISITION AND INTEGRATION Alexander Cloninger, Doctor of Philosophy, 2014 Dissertation directed by: Professor Wojciech Czaja Professor John J. Benedetto Department of Mathematics This thesis deals with two approaches to building efficient representations of data. The first is a study of compressive sensing and improved data acquisition. We outline the development of the theory, and proceed into its uses in matrix completion problems via convex optimization. The aim of this research is to prove that a general class of measurement operators, bounded norm Parseval frames, satisfy the necessary conditions for random subsampling and reconstruction. We then demonstrate an example of this theory in solving 2-dimensional Fredholm integrals with partial measurements. This has large ramifications in improved acquisition of nuclear magnetic resonance spectra, for which we give several examples. The second part of this thesis studies the Laplacian Eigenmaps (LE) algorithm and its uses in data fusion. In particular, we build a natural approximate inversion algorithm for LE embeddings using L regularization and MDS embedding techniques. We show how this inversion, combined with feature space rotation, leads to a novel form of data reconstruction and inpainting using a priori information. We demonstrate this method on hyperspectral imagery and LIDAR. We also aim to understand and characterize the embeddings the LE algorithm gives. To this end, we characterize the order in which eigenvectors of a disjoint graph emerge and the support of those eigenvectors. We then extend this characterization to weakly connected graphs with clusters of differing sizes, utilizing the theory of invariant subspace perturbations and proving some novel results. EXPLOITING DATA-DEPENDENT STRUCTURE FOR IMPROVING SENSOR ACQUISITION AND INTEGRATION
Fibrillar Collagen Specifically Regulates Human Vascular Smooth Muscle Cell Genes Involved in Cellular Responses and the Pericellular Matrix Environment

Abstract— Proliferation and &agr;v&bgr;3 integrin-dependent migration of vascular smooth muscle cells are suppressed on polymerized type I collagen. To identify genes specifically regulated in human smooth muscle cells by polymerized collagen, we used the suppressive subtraction hybridization technique. Compared with smooth muscle cells cultured on monomer collagen, polymerized collagen suppresses the following: (1) a number of other extracellular matrix proteins, including fibronectin, thrombospondin-1, tenascin-C, and cysteine-rich protein 61; (2) actin binding proteins including &agr;-actinin; (3) signaling molecules; (4) protein synthesis-associated proteins; and (5) genes with unknown functions. Some of the identified genes, including cysteine-rich protein 61, show unique kinetics of mRNA regulation by monomer or polymerized collagen distinct from growth factors, suggesting extracellular matrix-specific gene modulation. Moreover, in vivo balloon catheter-mediated injury to the rat carotid artery induces many of the genes that are suppressed by polymerized collagen. Protein levels of thrombospondin-1 and fibronectin are also suppressed by polymerized collagen. Thrombospondin-1-mediated smooth muscle cell migration on vitronectin is significantly inhibited after culture on polymerized collagen for 24 hours, which is associated with decreased &agr;-actinin accumulation at focal adhesions. Thus, polymerized type I collagen dynamically regulates gene expression, pericellular accumulation of extracellular matrix molecules, and the response to a given matrix molecule.
A reusable library of 3D interaction techniques

We present a library of reusable, abstract, low granularity components for the development of novel interaction techniques. Based on the InTml language and through an iterative process, we have designed 7 selection and 5 travel techniques from [5] as dataflows of reusable components. The result is a compact set of 30 components that represent interactive content and useful behavior for interaction. We added a library of 20 components for device handling, in order to create complete, portable applications. By design, we achieved a 68% of component reusability, measured as the number of components used in more than one technique, over the total number of used components. As a reusability test, we used this library to describe some interaction techniques in [1], a task that required only 2% of new components.
Evolutionary Approach to Investigations of Cognitive Systems

Evolutionary approach to investigations of cognitive systems is analyzed. Modeling of cognitive evolution (a study of evolution of animal cognitive features) is considered as interesting direction of these investigations. Backgrounds of models of cognitive evolution that are developed in the area of researches “Adaptive behavior” are outlined. Our initial models of cognitive evolution investigations are described. The sketch program for future modeling of cognitive evolution is proposed.
Public Health Assessment of Potential Biological Terrorism Agents

As part of a Congressional initiative begun in 1999 to upgrade national public health capabilities for response to acts of biological terrorism, the Centers for Disease Control and Prevention (CDC) was designated the lead agency for overall public health planning. A Bioterrorism Preparedness and Response Office has been formed to help target several areas for initial preparedness activities, including planning, improved surveillance and epidemiologic capabilities, rapid laboratory diagnostics, enhanced communications, and medical therapeutics stockpiling (1). To focus these preparedness efforts, however, the biological agents towards which the efforts should be targeted had to first be formally identified and placed in priority order. Many biological agents can cause illness in humans, but not all are capable of affecting public health and medical infrastructures on a large scale. The military has formally assessed multiple agents for their strategic usefulness on the battlefield (2). In addition, the Working Group on Civilian Biodefense, using an expert panel consensus-based process, has identified several biological agents as potential high-impact agents against civilian populations (3–7). To guide national public health bioterrorism preparedness and response efforts, a method was sought for assessing potential biological threat agents that would provide a reviewable, reproducible means for standardized evaluations of these threats. In June 1999, a meeting of national experts was convened to 1) review potential general criteria for selecting the biological agents that pose the greatest threats to civilians and 2) review lists of previously identified biological threat agents and apply these criteria to identify which should be evaluated further and prioritized for public health preparedness efforts. This report outlines the overall selection and prioritization process used to determine the biological agents for public health preparedness activities. Identifying these priority agents will help facilitate coordinated planning efforts among federal agencies, state and local emergency response and public health agencies, and the medical community.
A Review Paper on Study and optimization of Process Parameter in Plasma arc Cutting

: The plasma arc cutting process was developed for difficult to machine materials in order to overcome the inefficiency and ineffectiveness of conventional machining method when it come to complex shape and work piece. Plasma cutting is a process that cut through electrically conductive material by means of jet of hot plasma. In this research work the study has been carried out on the PAC of Carbon steel by considering gas pressure (bar), current flow rate (A), cutting speed (mm/min) and arc gap (mm) as the process parameters and analysing the effect on the surface roughness (Ra), material removal rate. A comprehensive review was carried out on development in analysis and optimization of PAC for Carbon steel (A36). The Experimental study has been carried out by using Taguchi design methods and ANOVA analysis for Material removal rate (MRR), Surface roughness by performing cuts of different run sets of L9 orthogonal Array.
Guided Gabor Filter for Finger Vein Pattern Extraction

In this paper, a novel explicit image filter, called Guided Gabor filter, is proposed to extract the finger vein pattern without any segmentation processing, and lower performance reduction for poor quality images which result from low contrast, illumination, or noise effects, etc. The proposed filter is contributed for finger vein enhancement, noise reduction, and haze removal without being affected by the brightness of the vein. It performs well not only on ridge detection like the Gabor filter, but on image enhancement as an edge-preserving smoothing operator without the gradient reversal artifacts. The experimental results show that the proposed method is able to get vein pattern more clearly and faster than the existing methods, and improve the matching performance with higher recognition rate.
Delay-dependent robust stability and stabilization for uncertain singular system with time-varying delay

The problems of delay-dependent robust stability and stabilization for uncertain singular systems with time-varying delay are addressed in this paper. The uncertainty is assumed to be norm bounded. By establishing an integral inequality based on quadratic terms, a new delay-dependent robust stability criterion is derived and expressed in terms of linear matrix inequality (LMI). Based on the criterion, the problem of robust stabilization is solved via state feedback controller, which guarantees that the resultant closed-loop system is regular, impulse-free and stable for all admissible uncertainties. An explicit expression for the desired controller is also given. Numerical examples are given to demonstrate the applicability and the less conservatism of the proposed method.
Can the ICF be used as a rehabilitation outcome measure? A study looking at the inter- and intra-rater reliability of ICF categories derived from an ADL assessment tool.

PURPOSE The categories of the International Classification of Functioning , Disability and Health (ICF) could potentially be used as components of outcome measures. Literature demonstrating the psychometric properties of ICF categories is limited. OBJECTIVE Determine the agreement and reliability of ICF activities of daily living category scores and compare these to agreement and reliability of the Functional Independence Measure (FIM) item scores. METHOD Two investigators independently reviewed the clinical notes to score the ICF activities of daily living cate-gories, of 100 patients using ICF qualifiers with additional scoring guidelines. The percentage agreement, interrater and intrarater reliability were compared with the matched FIM items scored by a separate set of two investigators using the same methodology. Kappa Statistic was calculated using Med Calc. RESULTS ICF interrater reliability as indicated by Kappa values ranging from 0.42 to 0.81 was moderate or better for the eleven self care and mobility categories. The language ICF categories and problem solving generally have fair agreement, with Kappa values ranging from 0.21 for receiving verbal messages to 0.44 for basic social interactions. Absolute agreement was above 72% for all categories. Reliability and agreement of the FIM items was generally lower than the corresponding ICF categories. CONCLUSION The inter-rater and intra-rater reliability and agreement of the ICF activities of daily living categories were comparable or better than the corresponding FIM items. The results of this study provide an indication that the ICF categories could be used as components of rehabilitation outcome measures.
Selection strategies for binaural and monaural cochlear implantation.

PURPOSE We propose theoretical guidelines for cochlear implant selection criteria in adults and children that emphasize the contribution of each ear to the binaural advantage. The guidelines outline options for implanting one ear only, implanting one ear plus use of a contralateral hearing aid, and implanting both ears. METHOD Our method for selecting the best cochlear implant or hearing aid outcome is derived from the amount of usable hearing of the patient. This approach requires the measurement of aided speech perception with each ear separately and then bilaterally. Guidelines are based on the following: (a) overall level of performance with hearing aids relative to what is expected from a cochlear implant, (b) the contributions from each ear, and (c) whether there is a binaural advantage. CONCLUSIONS Our general recommendation is to provide the patient with the best opportunity for binaural hearing. Since the guidelines put forth in this article are theoretically based, future efforts should be aimed at examining the validity of these guidelines.
Postoperative desogestrel for pelvic endometriosis-related pain: a randomized controlled trial

Abstract Objective: To determine the effectiveness of desogestrel for relieving endometriosis-related pain. Methods: A double-blinded randomized placebo-controlled trial was conducted in 40 patients who had endometriosis with moderate-to-severe dysmenorrhea or chronic pelvic pain undergoing laparoscopic conservative surgery. After surgery, patients were randomized to desogestrel or placebo group. Outcomes included changes in visual analog scale (VAS) of dysmenorrhea, pelvic pain and dyspareunia, patient satisfaction, and adverse effects. Results: Forty patients were randomized to desogestrel group (n = 20) and placebo group (n = 20). At month 6, the desogestrel group had significantly lower median VAS of overall pelvic pain, dysmenorrhea and noncyclic pelvic pain. Comparing with the placebo group, the desogestrel group had greater reduction in VAS of overall pain, dysmenorrhea and pelvic pain, but comparable reduction in VAS of dyspareunia. No patient in the desogestrel group but 4 patients in the placebo group still had moderate-to-severe pelvic pain at 6 months postoperatively. The proportion of patients who rated the treatment as very satisfied was higher in the desogestrel group than in the placebo group. There was no serious adverse event during the study period. Conclusions: Desogestrel is effective and acceptable for postoperative therapy for patients with moderate-to-severe pain related to endometriosis.
Assessment of the azimuth wavelength cut-off dependence on the ocean state and on the surface wind speed for Sentinel-1 SAR images

The empirical dependence of the azimuth wavelength cut-off on the significant wave height and on the wind speed have been studied. The azimuth cut-off is estimated on the fitting of a Gaussian function to the azimuth autocorrelation function of the radar cross section. The feasibility of estimating the significant wave height and/or the wind speed has been investigated as well. We use SAR images acquired by the European Sentinel 1 from the beginning of November 2014 to the end of April 2015 co-located with the scatterometer winds acquired by the Chinese sensor HSCAT and the significant wave height from ECMWF forecasts. The correlation between the azimuth cut-off and the significant wave height is rather strong. A linear geophysical model function is fitted in order to estimate it. The dependence on the wind speed is secondary and becomes remarkable only when the sea state is fully developed. A significant wave height retrieval exercise is proposed and the results are compared with the buoy measurements of the National Data Buoy Center (NDBC) network.
Multi-label classification with clustering for image and text categorization

This paper explores effective multi-label classification methods for multi-semantic image and text categorization. We perform an experimental study of clustering based multi-label classification (CBMLC) for the target problem. Experimental evaluation is conducted for identifying the impact of different clustering algorithms and base classifiers on the predictive performance and efficiency of CBMLC. In the experimental setting, three widely used clustering algorithms and six popular multi-label classification algorithms are used and evaluated on multi-label image and text datasets. A multi-label classification evaluation metrics, micro F1-measure, is used for presenting predictive performances of the classifications. Experimental evaluation results reveal that clustering based multi-label learning algorithms are more effective compared to their non-clustering counterparts.
Comparison of Dry and Gel Based Electrodes for P300 Brain–Computer Interfaces

Most brain–computer interfaces (BCIs) rely on one of three types of signals in the electroencephalogram (EEG): P300s, steady-state visually evoked potentials, and event-related desynchronization. EEG is typically recorded non-invasively with electrodes mounted on the human scalp using conductive electrode gel for optimal impedance and data quality. The use of electrode gel entails serious problems that are especially pronounced in real-world settings when experts are not available. Some recent work has introduced dry electrode systems that do not require gel, but often introduce new problems such as comfort and signal quality. The principal goal of this study was to assess a new dry electrode BCI system in a very common task: spelling with a P300 BCI. A total of 23 subjects used a P300 BCI to spell the word “LUCAS” while receiving real-time, closed-loop feedback. The dry system yielded classification accuracies that were similar to those obtained with gel systems. All subjects completed a questionnaire after data recording, and all subjects stated that the dry system was not uncomfortable. This is the first field validation of a dry electrode P300 BCI system, and paves the way for new research and development with EEG recording systems that are much more practical and convenient in field settings than conventional systems.
Device and circuit optimization of RRAM for neuromorphic computing

RRAM is a promising electrical synaptic device for efficient neuromorphic computing. A human face recognition task was demonstrated on a 1k-bit 1T1R array using an online training perceptron network. The RRAM device structure and materials stack were optimized to achieve reliable bidirectional analog switching behavior. A binarized-hidden-layer (BHL) circuit architecture is proposed to minimize the needs of A/D and D/A converters between RRAM crossbars. Several RRAM non-ideal characteristics were carefully evaluated for handwritten digits' recognition task with proposed BHL architecture and modified neural network algorithm.
A New Oligonucleotide Microarray for Detection of Pathogenic and Non-Pathogenic Legionella spp.

Legionella pneumophila has been recognized as the major cause of legionellosis since the discovery of the deadly disease. Legionella spp. other than L. pneumophila were later found to be responsible to many non-pneumophila infections. The non-L. pneumophila infections are likely under-detected because of a lack of effective diagnosis. In this report, we have sequenced the 16S-23S rRNA gene internal transcribed spacer (ITS) of 10 Legionella species and subspecies, including L. anisa, L. bozemanii, L. dumoffii, L. fairfieldensis, L. gormanii, L. jordanis, L. maceachernii, L. micdadei, L. pneumophila subspp. fraseri and L. pneumophila subspp. pasculleii, and developed a rapid oligonucleotide microarray detection technique accordingly to identify 12 most common Legionella spp. , which consist of 11 pathogenic species of L. anisa, L. bozemanii, L. dumoffii, L. gormanii, L. jordanis, L. longbeachae, L. maceachernii, L. micdadei, and L. pneumophila (including subspp. pneumophila, subspp. fraseri, and subspp. pasculleii) and one non-pathogenic species, L. fairfieldensis. Twenty-nine probes that reproducibly detected multiple Legionella species with high specificity were included in the array. A total of 52 strains, including 30 target pathogens and 22 non-target bacteria, were used to verify the oligonucleotide microarray assay. The sensitivity of the detection was at 1.0 ng with genomic DNA or 13 CFU/100 mL with Legionella cultures. The microarray detected seven samples of air conditioner-condensed water with 100% accuracy, validating the technique as a promising method for applications in basic microbiology, clinical diagnosis, food safety, and epidemiological surveillance. The phylogenetic study based on the ITS has also revealed that the non-pathogenic L. fairfieldensis is the closest to L. pneumophila than the nine other pathogenic Legionella spp.