Miracle-dz/UniFAR-FTUs huggingface dataset:
The mutual coupling and diffraction effects on the performance of a CMA adaptive array

The performance of the constant modulus algorithm (CMA) with the steepest descent method used in an adaptive array of monopole antennas mounted on a rectangular conducting plate was investigated. The mutual coupling (MC) effect among the array elements and the diffraction effect caused by the conducting plate were taken into account in the calculation by a hybrid method of moment method (MM) and geometrical theory of diffraction (GTD). Simulations showed that the CMA adaptive array performs differently when the MC and the diffraction effects are taken into account. In some cases, the speed of convergence is slower with MC, and in other cases it is faster. Also, in multipath scenarios the array sometimes converges on a weaker delayed ray rather than the direct ray when MC is included. The capture property is explained by the fact that the CMA algorithm is sensitive to initial conditions and the initial array pattern is directional due to MC-not omnidirectional as in the ideal case. The performance of the array on a finite ground plane is different from that on an infinite ground plane due to diffraction effects.
Learning at the Boundaries: An Action Agenda for Business Analysts

The business analyst role was established in response to concerns about a 'gap' between technical IT staff and users. Such a 'gap' has been implicated in the failure of information systems to consistently deliver business value. However research suggests that while business analysts may facilitate the relationship between technical staff and business users, boundaries may still occur between business analysts and user groups on one hand, and business analysts and IT staff on the other. Nonetheless, these boundaries present opportunities for all the participant groups to learn by developing new understandings, knowledge and practices, thus enabling them to more effectively interact with their constituents. Through the adopted practice perspective, our research demonstrates that learning via socio-spatial and instrumental-developmental expansions at the boundaries can improve the practice of business analysts. Our findings make a contribution to the practice perspective literature by highlighting the importance of boundaries as opportunities for learning.
The useful dimensions of sensitivity.

WHAT I am going to talk about is the relation of sensing to perceiving. We have all believed that we understood the process of sensation fairly well and that only the process of perception gave us difficulties. But I am going to suggest on the contrary that a straightforward theory of perception is possible and that it is our understanding of sensation which is confused. First let us make sure that there is really a problem in how to treat sensing and perceiving. Some psychologists now maintain that there is no difference between them in fact. The distinction has broken down; they say it has no validity and we should forget it. I think that what they mean is this. An individual can make discriminations in many ways. We can say either that he is sensitive to many variables of stimulation or that he can experience many kinds of differences between things but what has importance, the argument goes, are only the facts of discrimination, not whether they are called sensory or perceptual. There is something valid in this argument. I would call it the experimentalist's position—stick to the facts and cut the cackle! It is enough to determine just what differences an animal, a child, or a man can respond to and what others he cannot. This limited aim of psychology might be called simple psychophysics (not metric psychophysics) and it is good experimental science. But it provides no explanation of how the individual keeps in touch with the environment around him. The problem of perception, then, the problem of contact with the environment, still remains. The variables of sensory discrimination are radically different from the variables of perceptual discrimination. The former are said to be dimensions like quality, intensity, extensity, and duration, dimensions of hue, brightness, and saturation, of pitch, loudness, and timbre, of pressure,
A Recombinant Sal k 1 Isoform as an Alternative to the Polymorphic Allergen from Salsola kali Pollen for Allergy Diagnosis

Background: The incidence of Amaranthaceae pollen allergy has increased due to the desertification occurring in many countries. In some regions of Spain, Salsola kali is the main cause of pollinosis, at almost the same level as olive and grass pollen. Sal k 1 - the sensitization marker of S. kali pollinosis - is used in clinical diagnosis, but is purified at a low yield from pollen. We aimed to produce a recombinant (r)Sal k 1 able to span the structural and immunological properties of the natural isoforms from pollen, and validate its potential use for diagnosis. Methods: Specific cDNA was amplified by PCR, cloned into the pET41b vector and used to transform BL21 (DE3) Escherichia coli cells. Immunoblotting, ELISA, basophil activation and skin-prick tests were used to validate the recombinant protein against Sal k 1 isolated from pollen. Sera and blood cells from S. kali pollen-sensitized patients and specific monoclonal and polyclonal antisera were used. Results: rSal k 1 was produced in bacteria with a yield of 7.5 mg/l of cell culture. The protein was purified to homogeneity and structural and immunologically validated against the natural form. rSal k 1 exhibited a higher IgE cross-reactivity with plant-derived food extracts such as peanut, almond or tomato than with pollen sources such as Platanus acerifolia and Oleaceae members. Conclusions: rSal k 1 expressed in bacteria retains intact structural and immunological properties in comparison to the pollen-derived allergen. It spans the immunological properties of most of the isoforms found in pollen, and it might substitute natural Sal k 1 in clinical diagnosis.
Planar epipolar constraint for UAV navigation

Unmanned aerial vehicles (UAVs) are widely used for commercial and military purposes. UAVs are mostly dependent on an Inertial Measurement Unit(IMU) for navigation. We have presented an alternate approach to estimate the states of an UAV using only onboard camera which can be either used alone or assimilated with the IMU output to enable reliable, accurate and robust navigation. As UAVs are generally fitted with cameras, they present information rich sensor alternative for obtaining useful information from the craft, with the added benefits of being light weight, small and no extra payload. Assuming a pinhole camera model and perspective projection, the first approach is based on optical flow and horizon detection. In the second method, the craft state is estimated using differential and discrete epipolar constraint with planar constraint assuming the scene is slowly moving. Algorithms results are compared with real time data collected from the IMU.
Effect of interleukin 1 receptor antagonist gene transduction on human melanoma xenografts in nude mice.

Interleukin (IL)-1 is a pleiotropic inflammatory cytokine that promotes angiogenesis and enhances tumor growth and metastases. We evaluated the effects of IL-1 receptor antagonist (IL-1ra) on tumor growth and metastases in human melanoma xenografts. We selected two human melanoma lines (SMEL and PMEL) with differential (high versus low, respectively) constitutive production of IL-1 by ELISA. The IL-1ra gene was isolated from monocyte RNA by PCR and retrovirally transduced into SMEL and PMEL. In vitro cell proliferation was evaluated using a WST-1 assay. Athymic nude mice received s.c. or i.v. injection with parental, vector-transduced, or IL-1ra-transduced melanoma cells, and tumor growth, lung metastases, and histology were characterized. IL-1 was produced by SMEL in vitro and ex vivo (117 and 67 pg/ml/10(6) cells/24 h, respectively), but not by PMEL (15 and 0 pg/ml/10(6) cells/24 h, respectively). Neither made IL-1ra natively. Gene-transduced cell lines secreted >1000 pg/ml/10(6) cells/24 h of IL-1ra by ELISA. In vitro proliferation of each parental cell line was comparable to the proliferation rate of each transduced cell line. IL-1ra-transduced SMEL (SMEL/IL-1ra) showed significantly slower tumor growth compared with null-transduced and parental cell lines (P < 0.001, ANOVA-Bonferroni/Dunn). There was no difference in growth rates between PMEL and IL-1ra-transduced PMEL (PMEL/IL-1ra). A mixing study of SMEL and SMEL/IL-1ra showed significant inhibition of tumor growth at various ratios (P < 0.001, ANOVA-Bonferroni/Dunn). There were significantly fewer lung metastases with SMEL/IL-1ra versus SMEL (P < 0.002). IL-1ra decreases in vivo growth and metastatic potential of a human melanoma xenograft that constitutively secretes IL-1. This effect may be exploitable using clinically available IL-1ra for the treatment of human cancers.
Outcomes among African-American/non-African-American patients with advanced non-small-cell lung carcinoma: report from the Cancer and Leukemia Group B.

BACKGROUND Among patients diagnosed with advanced non-small-cell lung carcinoma (NSCLC), African-Americans have lower survival rates than non-African-Americans. Whether this difference is due to innate characteristics of the disease in the two ethnicities or to disparities in health care is not known. We investigated whether the disparity in survival would persist when patients were treated with similar systemic therapies (i.e., in phase II and phase III Cancer and Leukemia Group B [CALGB] trials). METHODS We assessed 504 consecutive patients (458 non-African-American and 46 African-American) receiving systemic chemotherapy in CALGB studies for advanced NSCLC during the period from 1989 through 1998. Clinical and demographic characteristics, treatment received, and survival data were obtained from the CALGB database. Cox's proportional hazards model was used to assess the effect of race/ethnicity on survival after adjustment for other known prognostic factors. All statistical tests were two-sided. RESULTS The unadjusted 1-year survival rate was 22% (95% confidence interval [CI] = 13% to 38%) for African-American patients and 30% (95% CI = 26% to 35%) for non-African-American patients, a statistically significant difference (8%; 95% CI on the difference = 5% to 12%; P =.03). Multivariable adjustment for the effect of treatment arm, histology, and metastatic site at presentation did not alter the worse outcome for African-American patients. However, the effect of race/ethnicity disappeared after adjustment for performance status and weight loss. African-American patients were more likely than non-African-Americans to present with a poor performance status (83% versus 60%) and substantial weight loss (41% versus 27%) and to be unmarried (59% versus 28%), disabled (31% versus 15%), unemployed (17% versus 7%), and Medicaid recipients (30% versus 8%). CONCLUSIONS The relationship that we observed between poor performance, weight loss, and socioeconomic status suggests that social circumstances lead to African-Americans presenting with poorer prognostic features.
STATISTICAL MACHINE TRANSLATION WITHOUT PARALLEL DATA

We examine approaches of statistical machine translation without parallel data (SMT). SMT has achieved impressive performance by leveraging large amounts of parallel data in the source and target languages. But such data is available only for a few language pairs and domains. Using human annotation to create new parallel corpora sufficient for building a good translation system is too expensive. On the other hand, there are many resources of text for many languages. This has raised a new research challenge in SMT: How can we train a statistical language translation system without parallel data? There has been a long line of research on learning translation from monolingual data, beginning with Rapp (1995). Many of these works have focused on extracting a translation lexicon by mining monolingual resources of data. More recent works have extended research from building translation lexicons to translation systems. We categorize methods of SMT without parallel data based on end product (translation lexicon or translation system) and type of available resources which can be used (limited parallel information or just monolingual data). We characterize the methods in terms of quality of translation and scalability.
An adaptive security management model for emergency networks

In disasters and emergency scenarios, due to a lack of network infrastructure, first-responders can build mobile ad hoc networks to send information and help disaster response coordination. However, the communication in these situations can suffer from long interruptions. This paper proposes a security management framework to dynamically configure or reconfigure emergency networks, in order to adapt the use of security components according to management information received by the decision-maker entities. The security management model includes the definition of security levels, the management information base, protocol messages and events. The emergency network activates the security mechanisms only when necessary, which avoid attacks effects and save resources.
Use of latent words language models in ASR: A sampling-based implementation

This paper applies the latent words language model (LWLM) to automatic speech recognition (ASR). LWLMs are trained taking into account related words, i.e., grouping of similar words in terms of meaning and syntactic role. This means, for example, if a technical word and a general word play a similar syntactic role, they are given a similar probability. This is expected that the LWLM performs robustly over multiple domains. Furthermore, we can expect that the interpolation of the LWLM and a standard n-gram LM will be effective since each of the LMs have different learning criterion. In addition, this paper also describes an approximation method of the LWLM for ASR, in which words are randomly sampled on the LWLM and then a standard word n-gram language model is trained. This enables us one-pass decoding. Our experimental results show that the LWLM performs comparable to the hierarchical Pitman-Yor language model (HPYLM) in a target domain task, and more robustly performs in out-domain tasks. Moreover, an interpolation model with the HPYLM provides a lower word error rate in all the tasks.
VISCORS: a visual-content recommender for the mobile Web

Current search methods for mobile-Web content can be frustrating to use. To shorten searches for cell phone wallpaper images, VISCORS combines collaborative filtering with content-based image retrieval. An increasing selection of content is becoming available in the mobile-Web environment, where users navigate the Web using wireless devices such as cell phones and PDAs. The fast growth and excellent prospects of the mobile-Web content market have attracted many content providers.
A Utility Centered Approach for Evaluating and Optimizing Geo-tagging

Geo-tagging is the process of annotating a document with its geographic focus by extracting a unique locality that describes the geographic context of the document as a whole. Accurate geographic annotations are crucial for geospatial applications such as Google Maps or the IDIOM Media Watch on Climate Change, but many obstacles complicate the evaluation of such tags. This paper introduces an approach for optimizing geo-tagging by applying the concept of utility from economic theory to tagging results. Computing utility scores for geo-tags allows a fine grained evaluation of the tagger's performance in regard to multiple dimensions specified in use case specific domain ontologies and provides means for addressing problems such as different scope and coverage of evaluation corpora. The integration of external data sources and evaluation ontologies with user profiles ensures that the framework considers use case specific requirements. The presented model is instrumental in comparing different geo-tagging settings, evaluating the effect of design decisions, and customizing geo-tagging to a particular use cases.
High‐throughput flow cytometry data normalization for clinical trials

Flow cytometry datasets from clinical trials generate very large datasets and are usually highly standardized, focusing on endpoints that are well defined apriori. Staining variability of individual makers is not uncommon and complicates manual gating, requiring the analyst to adapt gates for each sample, which is unwieldy for large datasets. It can lead to unreliable measurements, especially if a template‐gating approach is used without further correction to the gates. In this article, a computational framework is presented for normalizing the fluorescence intensity of multiple markers in specific cell populations across samples that is suitable for high‐throughput processing of large clinical trial datasets. Previous approaches to normalization have been global and applied to all cells or data with debris removed. They provided no mechanism to handle specific cell subsets. This approach integrates tightly with the gating process so that normalization is performed during gating and is local to the specific cell subsets exhibiting variability. This improves peak alignment and the performance of the algorithm. The performance of this algorithm is demonstrated on two clinical trial datasets from the HIV Vaccine Trials Network (HVTN) and the Immune Tolerance Network (ITN). In the ITN data set we show that local normalization combined with template gating can account for sample‐to‐sample variability as effectively as manual gating. In the HVTN dataset, it is shown that local normalization mitigates false‐positive vaccine response calls in an intracellular cytokine staining assay. In both datasets, local normalization performs better than global normalization. The normalization framework allows the use of template gates even in the presence of sample‐to‐sample staining variability, mitigates the subjectivity and bias of manual gating, and decreases the time necessary to analyze large datasets. © 2013 International Society for Advancement of Cytometry
On throughput-reliability tradeoff analysis of general fading channels

The throughput-reliability tradeoff (TRT) for MIMO and co-operative systems are first proposed and studied under Rayleigh fading assumptions. While the interplay among signal-to-noise ratio, transmission rate and outage/error probability for MIMO and co-operative channels have been explored, those corresponding to many practical scenarios are still wide open. In this work, we deal with the TRT analysis of MIMO systems with generic distribution for channel coefficients that includes many known models as special cases.
Multi-modal Person Localization And Emergency Detection Using The Kinect

Person localization is of paramount importance in an ambient intelligence environment since it is the first step towards context-awareness. In this work, we present the development of a novel system for multi-modal person localization and emergency detection in an assistive ambient intelligence environment for the elderly. Our system is based on the depth sensor and microphone array of 2 Kinect devices. We use skeletal tracking conducted on the depth images and sound source localization conducted on the captured audio signal to estimate the location of a person. In conjunction with the location information, automatic speech recognition is used as a natural and intuitive means of communication in order to detect emergencies and accidents, such as falls. Our system attained high accuracy for both the localization and speech recognition tasks, verifying its effectiveness. Keywords-localization; multi-modal; Kinect; speech recognition; context-awareness; 3-D interaction
The Field Matching Problem: Algorithms and Applications

To combine information from heterogeneous sources, equivalent data in the multiple sources must be identified. This task is the field matching problem. Specifically, the task is to determine whether or not two syntactic values are alternative designations of the same semantic entity. For example the addresses Dept. of Comput. Sci. and Eng., University of California, San Diego, 9500 Gilman Dr. Dept. 0114, La Jolla. CA 92093 and UCSD, Computer Science and Engineering Department, CA 92093-0114 do designate the same department. This paper describes three field matching algorithms, and evaluates their performance on real-world datasets. One proposed method is the well-known Smith-Waterman algorithm for comparing DNA and protein sequences. Several applications of field matching in knowledge discovery are described briefly, including WEBFIND, which is a new software tool that discovers scientific papers published on the worldwide web. WEBFIND uses external information sources to guide its search for authors and papers. Like many other worldwide web tools, WEBFIND needs to solve the field matching problem in order to navigate between information sources.
An integrated algorithm for 3D-IC TSV assignment

Through-Silicon Via (TSV) is a technology that enables vertical integration of silicon dies forming a single 3D-IC stack. In this paper, a practical model is proposed for the TSV assignment problem of the stacked-die 3D nets. We present the first work in the literature to prove that the general 3D-IC TSV assignment problem with more than two dies is NP-complete. An efficient heuristic algorithm that combines Shortest Path, Bipartite Matching, Min-cost Max-flow and Integer Linear Programming is developed. Experimental results demonstrate that our flow achieves good quality of results (within 98% of the optimal solution) with reasonable run-time compared to related works.
Near-Real-Time Monitoring of Global Rivers and Lake Heights using EnviSat and Jason-1 Altimeter data

The ESA River and Lake Pilot project has now been running for some time, generating river and lake heights for targets globally. This paper presents a synopsis of the current system for generating river and lake heights from EnviSat Near Real Time (NRT) data and outlines a series of proposed enhancements, including extension of the NRT capability to ingest Jason-1 data. Results from a global analysis of system outputs is given, together with validation results against gauge data. The results demonstrate that very good time series are being recovered from the EnviSat NRT system, and that the current severe filtering of waveform shapes might be relaxed to some extent without significant loss of quality in the output, permitting many more river and lake measurements to be generated.
Using static analysis for knowledge extraction from industrial User Interfaces

Graphical User Interfaces (GUI) play an essential role in operating industrial facilities and machines. Depending on the range and variability of a manufacturer's product portfolio a huge library of GUI software may exist. This poses quite a challenge when it comes to testing or re-engineering. Static analysis helps to unveil valuable, inherent knowledge and prepare it for further analysis and processing. In our case at ENGEL Austria GmbH, we extract the internal structure of the GUI screens, their variants and the control system context they are used in, i.e. which PLC variables they access. In another step, we analyze the usage pattern of method calls to certain UI widgets. In this paper we show our approach to gain these information based on static analysis of existing GUI source code for injection molding machines.