Miracle-dz/UniFAR-FTUs huggingface dataset:
An SDR platform using direction finding and statistical analysis for the detection of interferers

Radio frequency monitoring has gained a lot of research interest in spectrum management as it ensures an accurate and valid usage of the spectrum at both national and international levels while providing a protection of legal spectrum allocations against interference resulting from illegal use. Illegal repeaters are installed by end users, without the consent of authorities, because they are considered to be a cheap solution to the low signal strength problem. As these devices are not controlled by the operator, they transmit using a high power, thus jamming the useful signals and degrading the link's quality. In this paper, we propose and develop a Software Defined Radio (SDR) tool for the detection and localization of illegal transmission in both 3G and 4G networks. In our approach, we implement a direction finding tool on the Universal software Radio Peripherals (USRPs) and complement it with statistical analysis tool for the 3G network. Extensive lab and field test results show the high accuracy of the developed platform yet with a reduced cost.
The exterior problem for the Helmholtz equation with mixed boundary conditions in three dimensions

In this article, a new integral equation is derived to solve the exterior problem for the Helmholtz equation with mixed boundary conditions in three dimensions, and existence and uniqueness is proven for all wave numbers. We apply the boundary element collocation method to solve the system of Fredholm integral equations of the second kind, where we use constant interpolation. We observe superconvergence at the collocation nodes and illustrate it with numerical results for several smooth surfaces.
COX‐2‐dependent stabilization of survivin in non‐small cell lung cancer

Elevated tumor cyclooxygenase 2 (COX‐2) expression is associated with increased angiogenesis, tumor invasion and promotion of tumor cell resistance to apoptosis. The mechanism(s) by which COX‐2 exerts its cytoprotective effects are not completely understood but may be due to an imbalance of pro‐ and anti‐apoptotic gene expression. To analyze COX‐2‐dependent gene expression and apoptosis, we created cell lines constitutively expressing COX‐2 cDNA in sense and antisense orientations. Whereas COX‐2 sense cells have significantly heightened resistance to radiation and drug‐induced apoptosis, COX‐2 antisense cells are highly sensitive to apoptosis induction. We found that the expression of the anti‐apoptotic protein survivin correlated positively with COX‐2 expression. A COX‐2‐dependent modulation of survivin ubiquitination led to its stabilization in COX‐2 overexpressing cells, and this effect was replicated by exogenous PGE2 treatment of parental tumor cells. In contrast to previous studies in other cell types, in nonsmall cell lung cancer cells survivin was expressed in a cell cycle‐independent manner. When established in SCID mice in vivo, COX‐2 antisense‐derived tumors had significantly decreased survivin levels while COX‐2 sense‐derived tumors demonstrated elevated levels compared with controls. In accord with these findings, survivin and COX‐2 were frequently upregulated and co‐expressed in human lung cancers in situ.
Associations of apolipoprotein E exon 4 and lipoprotein lipase S447X polymorphisms with acute ischemic stroke and myocardial infarction

Abstract Background: Because apolipoprotein E (apoE) and lipopoprotein lipase (LPL) polymorphisms interact with each other and with other factors to affect lipid metabolism, we sought to determine their separate and combined effects in association with ischemic vascular disease. Methods: We performed a case-control study of 816 subjects: 246 acute ischemic stroke patients, 234 acute myocardial infarction patients, and 336 controls. APOE exon 4 and LPL S447X genotypes were determined. Results: APOE ɛ2 and ɛ4 homozygotes were increased in stroke (4.5% vs. 1.0%, p=0.008), while in myocardial infarction the ɛ4 allele was increased (12.6% vs. 9.5%, p=0.006) but ɛ2 was decreased (3.7% vs. 12.1%, p=0.000006). For subjects with either APOE ɛ2 or ɛ4 alleles, LPL X alleles were increased in vascular disease (OR=2.2, p=0.01). LPL X alleles displayed opposite tendencies toward association with disease when subjects were divided by sex, smoking, or APOE genotype. Meta-analysis and regression analysis of previous studies supported the sex and smoking dichotomies. Conclusion: This is the first report of an association of vascular disease with an interaction of APOE exon 4 and LPL S447X genotypes. Therefore, APOE genotypes and LPL S447X interactions with apoE, sex, and smoking may affect the risk of myocardial infarction and ischemic stroke.
Evaluating resources for query translation in cross-language information retrieval

Our goal is to evaluate the utility of a lexical resource containing Lexical Conceptual Structures LCS for use in cross language information retrieval Our evaluation makes use of a combination of techniques from interlingual machine translation Dorr with conventional information retrieval techniques Oard OardandDorr Given a query in one language we transform the query into the corresponding terms in a second language We evaluate this approach by comparing the resulting retrieval effectiveness with two translation based techniques as well as two techniques for determining the lower and upper bound The main innovation of this work is that it provides a principled framework for controlling translation ambiguity in cross language information retrieval applications Our focus is on the construction of disambiguated target language queries by using verb based entries in our lexicon to construct Lexical Conceptual Structures LCS We view our approach as a crucial step toward the evaluation of the utility of our LCS basedmultilingual lexicon Inaddition this work provides abasis formeasuring the extentto which disambiguation can enhance cross language information retrieval effectiveness
The D-TUNA Corpus: A Dutch Dataset for the Evaluation of Referring Expression Generation Algorithms

We present the D-TUNA corpus, which is the first semantically annotated corpus of referring expressions in Dutch. Its primary function is to evaluate and improve the performance of REG algorithms. Such algorithms are computational models that automatically generate referring expressions by computing how a specific target can be identified to an addressee by distinguishing it from a set of distractor objects. We performed a large-scale production experiment, in which participants were asked to describe furniture items and people, and provided all descriptions with semantic information regarding the target and the distractor objects. Besides being useful for evaluating REG algorithms, the corpus addresses several other research goals. Firstly, the corpus contains both written and spoken referring expressions uttered in the direction of an addressee, which enables systematic analyses of how modality (text or speech) influences the human production of referring expressions. Secondly, due to its comparability with the English TUNA corpus, our Dutch corpus can be used to explore the differences between Dutch and English speakers regarding the production of referring expressions.
Plagiarism Detection of C Program using Assembly Language

Source code plagiarism is becoming a common practice among higher education community. People duplicate and modify the source code of other people and show the program as their own program. In this paper, we want to draw researchers’ attention towards this problem and projected a novel approach which detects plagiarism in C language code by converting it into assembly language which is done with the help of GCC compiler. Assembly language converted by the compiler is not sensitive to all type of different code transformation, for example-swapping variable names, reformation of language, adding extra comment or blanks. Therefore, assembly language gives rise to reduced amount of variations, if there is a modification in the original code. Previous works in plagiarism compares the whole program but in this paper, we proposed a method which split the C program into assembly language code and divide each function of program into blocks and blocks are transformed into token strings. This method compares each function with other program function and provides a statistical output, according to the token string likeness of that function. If the output is above assigned specific plagiarism similarity threshold value then it counts under the case of plagiarism.
Bags of Trajectory Words for video indexing

A semantic indexing system capable of detecting both spatial appearance and motion-related semantic concepts requires the use of both spatial and motion descriptors. However, extracting motion descriptors on very large video collections requires great computational resources, which has caused most approaches to limit themselves to a spatial description. This paper explores the use of motion descriptors to complement such spatial descriptions and improve the overall performance of a generic semantic indexing system. We propose a framework for extracting and describing trajectories of tracked points that keeps computational cost manageable, then we construct Bag of Words representations with these trajectories. After supervised classification, a late fusion step combines information from spatial descriptors with that from our proposed Bag of Trajectory Words descriptors to improve overall results. We evaluate our approach in the very difficult context of the TRECVid Semantic Indexing (SIN) dataset.
How to select a good training-data subset for transcription: submodular active selection for sequences

Abstract : Given a large un-transcribed corpus of speech utterances, we address the problem of how to select a good subset for word-level transcription under a given fixed transcription budget. We employ submodular active selection on a Fisher-kernel based graph over un-transcribed utterances. The selection is theoretically guaranteed to be near-optimal. Moreover, our approach is able to bootstrap without requiring any initial transcribed data, whereas traditional approaches rely heavily on the quality of an initial model trained on some labeled data. Our experiments on phone recognition show that our approach outperforms both average-case random selection and uncertainty sampling significantly.
Study on Changes of Nitrobenzene Degrading Bacteria in ABR Reactor

By adding nitrobenzene to ABR (anaerobic baffled reactor) acclimation the flora in it, take 5 chambers sludge, extracted DNA and using PCR-DGGE technique amplification and separation product of bacterial 16S rDNA gene V3 region, then study the changes and diversity anaerobic sludge bacteria. The results showed that there was a succession in the communities of 5 reactor compartment, and the microbial diversity changes showing a characteristic of synergistic. ABR reactor has obvious characteristics of multi-phase process.
Measuring human emotions with modular neural networks and computer vision based applications

This paper describes a neural network architecture for emotion recognition for human-computer interfaces and applied systems. In the current research, we propose a combination of the most recent biometric techniques with the neural networks (NN) approach for real-time emotion and behavioral analysis. The system will be tested in real-time applications of customers’ behavior for distributed on-land systems, such as kiosks and ATMs.
Towards a method of identifying the causes of poor user experience on websites

User Experience, in particular the affective state of the user, is an important consideration in Human Computer Interaction, hence integrating affective measurements with software user experience testing would be valuable. Current approaches to this problem either lack the level of detail required to identify the causes of poor user experience, or can do so only with considerable human expertise and input. We aim to examine the possibility of automatically identifying the specific elements of a software system which cause user experience problems, without human input, by combining psychophysiological measurements and detailed user interaction data. This paper describes ongoing work to collect a dataset suitable for exploring the problem, and briefly discusses some future directions in which the data may allow us to proceed.
Accelerated People Tracking using Texture in a Camera Network

We present an approach to tracking multiple human subjects within a camera network. A particle filter framework is used in which we combine foreground-background subtraction with a novel approach to texture learning and likelihood computation based on an ellipsoid model. As there are inevitable problems with multiple subjects due to occlusion and crossing, we include a robust method to suppress distraction between subjects. To achieve real-time performance, we have also developed our code on a graphics processing unit to achieve a 10-fold reduction in processing time with an approximate frame rate of 10 frames per second.
Effect of Environment on Fracture Toughness and Debond Growth of Aluminum/FM ® 73/Boron-Epoxy Adhesively Bonded Joints

Tests were conducted to determine the fracture toughness of aluminum/FM®73/boron-epoxy adhesively bonded joints. Double cantilever beam (DCB) specimens and end-notched flexure (ENF) specimens were exposed to one of the following environments: hot/wet (71° C(160° F) and >90% RH) conditions for 5000 h, thermal cycles between 71° C (160° F) and −54° C (−65° F), or an outdoor “rooftop” environment for 10 000 h. The environmentally exposed specimens were tested along with as-received (or unexposed specimens). The different adherend materials had different coefficients of thermal expansion (CTE). The mismatch of CTE between adherends caused residual thermal stresses in the adhesive joints at every temperature other than the elevated cure temperature. The residual stresses could not be accounted for with closed form solutions. Finite element analysis (FEA) of the specimens was required. Using FEA solutions, it was determined that the fracture toughness of the environmentally exposed specimens was lower than the as-received specimens for every environment tested for both DCB and ENF specimens.
Counterfeiting attacks on block-wise dependent fragile watermarking schemes

In this paper, we present three counterfeiting attacks on the block-wise dependent fragile watermarking schemes. We consider vulnerabilities such as the exploitation of a weak correlation among block-wise dependent watermarks to modify valid watermarked images, where they could still be verified as authentic, though they are actually not. Experimental results successfully demonstrate the practicability and consequences of the proposed attacks for some relevant schemes. The development of the proposed attack models can be used as a means to systematically examine the security levels of similar watermarking schemes.
lncRNATargets: A platform for lncRNA target prediction based on nucleic acid thermodynamics

Many studies have supported that long noncoding RNAs (lncRNAs) perform various functions in various critical biological processes. Advanced experimental and computational technologies allow access to more information on lncRNAs. Determining the functions and action mechanisms of these RNAs on a large scale is urgently needed. We provided lncRNATargets, which is a web-based platform for lncRNA target prediction based on nucleic acid thermodynamics. The nearest-neighbor (NN) model was used to calculate binging-free energy. The main principle of NN model for nucleic acid assumes that identity and orientation of neighbor base pairs determine stability of a given base pair. lncRNATargets features the following options: setting of a specific temperature that allow use not only for human but also for other animals or plants; processing all lncRNAs in high throughput without RNA size limitation that is superior to any other existing tool; and web-based, user-friendly interface, and colored result displays that allow easy access for nonskilled computer operators and provide better understanding of results. This technique could provide accurate calculation on the binding-free energy of lncRNA-target dimers to predict if these structures are well targeted together. lncRNATargets provides high accuracy calculations, and this user-friendly program is available for free at http://www.herbbol. org:8001/lrt/ .
Acquisition of English-Chinese Transliterated Word Pairs from Parallel-Aligned Texts using a Statistical Machine Transliteration Model

This paper presents a framework for extracting English and Chinese transliterated word pairs from parallel texts. The approach is based on the statistical machine transliteration model to exploit the phonetic similarities between English words and corresponding Chinese transliterations. For a given proper noun in English, the proposed method extracts the corresponding transliterated word from the aligned text in Chinese. Under the proposed approach, the parameters of the model are automatically learned from a bilingual proper name list. Experimental results show that the average rates of word and character precision are 86.0% and 94.4%, respectively. The rates can be further improved with the addition of simple linguistic processing.
Schottky barrier height modulation by Arsenic Dopant segregation

High performance Schottky barrier MOSFETs require metallic source/drain contacts with very low Schottky barrier heights. This investigation focuses on barrier lowering via silicidation induced dopant segregation at the NiSi/Si interface with particular emphasis on the influence of dopant activation prior to Ni-silicidation. Diodes with activated dopants reveal significantly lower Schottky barrier heights than diodes made without dopant activation. The electrical measurements in combination with secondary-ion mass spectroscopy allowed the determination of the effective Schottky barrier heights resulting in minimum barrier heights of around 0.1 eV. Moreover, we present an n-type SB-MOSFET with dopant segregation on thin body SOI which shows an intrinsic performance comparable to a conventional MOSFET.
A novel biodegradable poly(ε-caprolactone urea)urethane incorporating polyhedral oligomeric silsesquioxane nanocomposite and applications for skin tissue engineering

Skin protects our bodies for a lifetime and extensive loss of this barrier renders the individual susceptible to infections and death. Clinically available treatment options, however, are limited in establishing both functional and cosmetic satisfaction. The work described in this thesis is therefore concerned with the development and characterization of a novel biodegradable nanocomposite system displaying suitable properties as skin tissue engineering scaffolds. A novel family of segmented polyurethanes (PU) with increasing hard segment content based on a poly(e-caprolactone urea)urethane backbone incorporating POSS nanoparticles was synthesized and analysed in terms of material characteristics and biocompatibility. Incorporation of POSS nanoparticles into the PU backbone yielded mostly amorphous materials as corroborated by distinct glass transitions visible on differential scanning calorimetry spectra. With incrementally increasing hard segment content, ultimate tensile strength increased from ~10 to 21 MPa accompanied by increased values for elastic moduli from 0.03 to 0.06 MPa. Number average molecular weights (Mn) decreased with increasing hard segment content due to a corresponding decrease in the proportion of PCL. Sterilization studies raised fundamental concerns regarding the suitability of conventionally available techniques since hydrolytically and temperature labile polymers are susceptible to degradation. The results obtained suggest 70 % ethanol to be a suitable laboratory-based disinfectant which was further demonstrated to have favourable effects on skin cell compatibility. Degradation studies revealed hard segment-dependent modulation of the degradation rate and the materials’ viscoelasticity. In vivo implantation studies of porous scaffolds demonstrated firm integration with the subcutaneous tissue and extensive vascularization. The results obtained in this work highlight (i) the ability to control scaffold degradation rates and mechanical properties and (ii) cellular as well as in vivo biocompatibility, all of which fundamental in the development of a versatile skin tissue engineering scaffold.
Cytokine-Induced Sickness Behavior: Where Do We Stand?

Sickness behavior refers to the coordinated set of behavioral changes that develop in sick individuals during the course of an infection. At the molecular level, these changes are due to the effects of proinflammatory cytokines, such as interleukin-1 (IL-1) and tumor necrosis factor-alpha (TNFalpha), in the brain. Peripherally released cytokines act on the brain via a fast transmission pathway involving primary afferent nerves innervating the body site of inflammation and a slow transmission pathway involving cytokines originating from the choroid plexus and circumventricular organs and diffusing into the brain parenchyma by volume transmission. At the behavioral level, sickness behavior appears to be the expression of a central motivational state that reorganizes the organism's priorities to cope with infectious pathogens. There is clinical and experimental evidence that activation of the brain cytokine system is associated with depression, although the exact relationship between sickness behavior and depression is still elusive.
LanguageNet: A novel framework for processing unstructured text information

In this paper we present LanguageNet—a novel framework for processing unstructured text information from human generated content. The state of the art information processing frameworks have some shortcomings: modeled in generalized form, trained on fixed (limited) data sets, and leaving the specialization necessary for information consolidation to the end users. The proposed framework is the first major attempt to address these shortcomings. LanguageNet provides extended support of graphical methods contributing added value to the capabilities of information processing. We discuss the benefits of the framework and compare it with the available state of the art. We also describe how the framework improves the information gathering process and contribute towards building systems with better performance in the domain of Open Source Intelligence.
Side Wall Coupling Via-Hole Array Cavity Band-Pass Filter

In this paper, we present a substrate integrated waveguide-based band-pass filter with wide stop-band rejection property. This band-pass filter is made up of two substrate integrated waveguide cavities, which couple to each other by an aperture on their common waveguide side wall. We employed the rigorous mode-matching method to analyze the electromagnetic boundary-value problem of the structure containing multiple discontinuities. In comparison with the conventional end-to-end coupled cavity filters, we found that our new side-wall-coupled cavity filter can suppress the second resonance frequency and, therefore, provide a considerably wide rejection band. It is interesting to note that the suppression of the second resonance frequency can be achieved by properly shifting the second cavity in lateral direction.