Miracle-dz/UniFAR-FTUs huggingface dataset:
Metric Spaces

As calculus developed, eventually turning into analysis, concepts first explored on the real line (e.g., a limit of a sequence of real numbers) eventually extended to other spaces (e.g., a limit of a sequence of vectors or of functions), and in the early 20th century a general setting for analysis was formulated, called a metric space. It is a set on which a notion of distance between each pair of elements is defined, and in which notions from calculus in R (open and closed intervals, convergent sequences, continuous functions) can be studied. Many of the fundamental types of spaces used in analysis are metric spaces (e.g., Hilbert spaces and Banach spaces), so metric spaces are one of the first abstractions that has to be mastered in order to learn analysis.
A novel flow control scheme for improving TCP fairness and throughput over heterogeneous networks with wired and wireless links

Most of the recent research on TCP over heterogeneous networks has concentrated on differentiating between packet drops caused by link congestion versus drops caused by link errors. Handling the two types of packet drop differently avoids significant throughput degradations caused by frequent TCP window shut downs due to non-congestive drops. However, TCP also exhibits inherent unfairness for connections with long round-trip times and connections that traverse multiple congested routers. In heterogeneous networks, the difference in bit error rates between wireless and wired links aggravates the situation even more. In this paper, we propose a new TCP bandwidth allocation (NTBA) algorithm to solve these problems. The primary contribution is a wireless access node algorithm with a simple new shadow price scheme provided by the network node. The advantage of our algorithm is that it simplifies the TCP sender-side implementation and keeps the receiver-side protocol stack unchanged. We propose to apply wireless explicit congestion notification (WECN) to decouple congestion control from loss recovery in wireless networks. Simulation results show that not only can the combined NTBA/WECN mechanism improve TCP fairness, but it can also maintain very good throughput performance in the presence of wireless channel losses.
Osr1 Interacts Synergistically with Wt1 to Regulate Kidney Organogenesis

Renal hypoplasia is a common cause of pediatric renal failure and several adult-onset diseases. Recent studies have associated a variant of the OSR1 gene with reduction of newborn kidney size and function in heterozygotes and neonatal lethality with kidney defects in homozygotes. How OSR1 regulates kidney development and nephron endowment is not well understood, however. In this study, by using the recently developed CRISPR genome editing technology, we genetically labeled the endogenous Osr1 protein and show that Osr1 interacts with Wt1 in the developing kidney. Whereas mice heterozygous for either an Osr1 or Wt1 null allele have normal kidneys at birth, most mice heterozygous for both Osr1 and Wt1 exhibit defects in metanephric kidney development, including unilateral or bilateral kidney agenesis or hypoplasia. The developmental defects in the Osr1+/-Wt1+/- mouse embryos were detected as early as E10.5, during specification of the metanephric mesenchyme, with the Osr1+/-Wt1+/- mouse embryos exhibiting significantly reduced Pax2-positive and Six2-positive nephron progenitor cells. Moreover, expression of Gdnf, the major nephrogenic signal for inducing ureteric bud outgrowth, was significantly reduced in the metanephric mesenchyme in Osr1+/-Wt1+/- embryos in comparison with the Osr1+/- or Wt1+/- littermates. By E11.5, as the ureteric buds invade the metanephric mesenchyme and initiate branching morphogenesis, kidney morphogenesis was significantly impaired in the Osr1+/-Wt1+/- embryos in comparison with the Osr1+/- or Wt1+/- embryos. These results indicate that Osr1 and Wt1 act synergistically to regulate nephron endowment by controlling metanephric mesenchyme specification during early nephrogenesis.
NO synthase? Generation of nitric oxide in plants

It has now become well accepted that nitric oxide (NO) has a key role to play in the signalling that takes place in plant cells. However, the sources of NO in plants has been hard to determine and there is considerable debate as to exactly how NO is made by plant cells. In animals nitric oxide synthase (NOS) enzymes have been characterised and such data has been used to informthestudieswhichhavebeentakingplaceinplants.However,despite several genomes from higher plants being sequenced, there is no evidence that such species contain NOS sequences. Despite this, a recent search using algal sequences did reveal a NOS-like sequence and such a finding may spark new enthusiasm for the search for a higher plant NOS. However, considerablecareneedstobetakeninsuchstudies,astherobustnessofmany of the inhibitors and probes which could be used in such work has been questioned. Here, some of the previous evidence that has been presented for theexistenceofaplantNOS,alongwithadiscussionofhowelseplantsmay produce NO is given.
Simulation of a Secure CPU with SecureTag Technique to Defend Embedded Systems Against Buffer Overflow Attacks

The research on security issues is getting more important, as the number of embedded and networked computing systems is constantly increasing. Due to strict restrictions and strong requirements, only special software applications can be used in security-critical embedded systems. So, it is necessary to secure those software applications with a special hardware implementation of a secure processor architecture. In this paper, we propose the architecture of the Secure CPU, including a memory structure using the SecureTag technique for marking memory lines. Our basic idea was to extend CPU registers by two replicas, which represent the lowest and highest value of a particular register. The advantages of this concept are minor changes in the architecture, the permanent and implicit checking of bounds, the secure storage of bounds in the memory and the high compatibility to several software applications. We verified our concept with an adapted processor simulator and describe its adaptations.
Frequency Scalable Model for MEMS Capacitive Shunt Switches at Millimeter-Wave Frequencies

This paper presents an approach to RF microelectromechanical systems (MEMS) capacitive shunt switch design from K-band up to W-band based on the scalability of the RF MEMS switch with frequency. The parameters of the switch's equivalent-circuit model also follow scaling rules. The measurement results of the fabricated switches show an excellent agreement with simulations that allow to validate the MEMS model in the entire band from 20 up to 94 GHz. This model is going to be used in the phase shifter circuit design for antenna array applications. The first 60-GHz phase shifter results are also reported here.
A Spectral Series Approach to High-Dimensional Nonparametric Regression

A key question in modern statistics is how to make fast and reliable inferences for complex, high-dimensional data. While there has been much interest in sparse techniques, current methods do not generalize well to data with nonlinear structure. In this work, we present an orthogonal series estimator for predictors that are complex aggregate objects, such as natural images, galaxy spectra, trajectories, and movies. Our series approach ties together ideas from kernel machine learning, and Fourier methods. We expand the unknown regression on the data in terms of the eigenfunctions of a kernel-based operator, and we take advantage of orthogonality of the basis with respect to the underlying data distribution, P, to speed up computations and tuning of parameters. If the kernel is appropriately chosen, then the eigenfunctions adapt to the intrinsic geometry and dimension of the data. We provide theoretical guarantees for a radial kernel with varying bandwidth, and we relate smoothness of the regression function with respect to P to sparsity in the eigenbasis. Finally, using simulated and real-world data, we systematically compare the performance of the spectral series approach with classical kernel smoothing, k-nearest neighbors regression, kernel ridge regression, and state-of-the-art manifold and local regression methods.
Understanding Open Proxies in the Wild

This paper conducts an extensive measurement study of open proxies to characterize how much these systems are used, what they are used for, and who uses them. We scanned the Internet to track proxy prevalence and monitored public statistics interfaces to gain insight into the machines hosting open proxies. We estimate that 220 TB of trafﬁc ﬂows through open proxies each day, making them one of the largest overlay networks in existence. We ﬁnd that automatic trafﬁc taking advantage of multiple vantage points to the Internet overwhelms the trafﬁc of individual ‘end users’ on open proxies. We present a characterization of the workload experienced by these systems that can inform the design of future open access systems.
Design of loss of signal detector for Synchro-to-Digital Converter

This paper presents a design for loss of signal detection between synchro and Synchro-to-Digital-Converter. The loss of signal over the rotor and stator terminals of synchro is indicated by Light Emitting Diodes (LED). The proposed technique performs the generation of zero crossing outputs for the corresponding rotor and stator signals of the synchro. The monoshots takes these zero crossing signals as data inputs and outputs low or high based on the availability of the signal. The design implementation and simulation results are described.
A classification scheme for user intentions in image search

Searching for images on the web is still an open problem. While multiple approaches have been presented, there has been surprisingly little work on the actual goals and intentions of users. In this poster we present our classification scheme for user goals in image search and describe our ongoing work focusing on identification and classification of user intentions during image search tasks.
Supporting the Investigation and Planning of Pragmatic Reuse Tasks

Software reuse has long been promoted as a means to increase developer productivity; however, reusing source code is difficult in practice and tends to be performed in an ad hoc manner. This is problematic because poor decisions can be made either to attempt an unwise, overly complex reuse task, or to avoid a reuse task that would have saved time and effort. This paper describes a lightweight tool that supports the investigation and planning of pragmatic reuse tasks. The tool helps developers to identify the dependencies from the source code they wish to reuse, and to decide how to deal with those dependencies. Questions about pragmatic reuse are evaluated through a survey of industrial developers. The tool is evaluated through the planning and execution of reuse tasks by industrial developers.
Foreground segmentation in a video by using a novel dynamic codebook

Foreground segmentation in a video is a key process in many applications such as object detection, an object tracking, and a behavior analysis. Since the extracted foreground objects are often used in the analytical process, the quality of the foreground is a significant factor to the success of these applications. However, there are many key challenges in the foreground segmentation, including dynamic backgrounds, gradual illumination changes, sudden illumination changes, shadows, and long-term scene changes. This paper proposes a novel dynamic codebook method to address such challenges. The dynamic codebook aims to significantly improve the conventional well-known codebook technique by introducing a technique to make a dynamic boundary of each codeword. In this technique, the lab color space is used in order to make the model more resilient to the illumination change. The experimental results and comprehensive comparisons demonstrate that the proposed method can achieve very promising performance.
Co-channel interference modelling between RATs in heterogeneous wireless networks

Co-channel interference models are increasingly becoming important in wireless networking. This is especially true in heterogeneous networks where a single device may cause unintended interactions between multiple radios using difference radio access technologies, even though they are located on the same device. Currently simulation tools provide varying levels of modelling of this phenomenon. This paper tries to quantify how well popular wireless simulation tools capture these effects using qualitative techniques while providing quantitative evaulation of the effects of interference between two radio access technologies - Bluetooth and Wi-Fi. Each tool is compared according to level of interference modelling offered, the technique for interference modelling and the types of RATs which are supported. The effect of co-channel interference between Bluetooth and Wi-Fi is evaluated with respect to throughput using devices equipped with both Blutooth and Wi-Fi radios.
Cross-View Action Recognition via a Continuous Virtual Path

In this paper, we propose a novel method for cross-view action recognition via a continuous virtual path which connects the source view and the target view. Each point on this virtual path is a virtual view which is obtained by a linear transformation of the action descriptor. All the virtual views are concatenated into an infinite-dimensional feature to characterize continuous changes from the source to the target view. However, these infinite-dimensional features cannot be used directly. Thus, we propose a virtual view kernel to compute the value of similarity between two infinite-dimensional features, which can be readily used to construct any kernelized classifiers. In addition, there are a lot of unlabeled samples from the target view, which can be utilized to improve the performance of classifiers. Thus, we present a constraint strategy to explore the information contained in the unlabeled samples. The rationality behind the constraint is that any action video belongs to only one class. Our method is verified on the IXMAS dataset, and the experimental results demonstrate that our method achieves better performance than the state-of-the-art methods.
Problems associated with current area-based visual speech feature extraction techniques

Techniques such as principle component analysis (PCA), linear discriminant analysis (LDA) and the discrete cosine transform (DCT) have all been used to good effect in face recognition. As these techniques are able to compactly represent a set of features, researchers have sought to use these methods to extract the visual speech content for audio-visual speech recognition (AVSR). In this paper, we expose the problems of employing such techniques in AVSR by running some visual-only speech recognition experiments. The results of these experiments illustrate that current area-based feature extraction techniques are heavily dependent on the visual front-end, as well as being ineffective in decoupling adequate speech content from a speaker’s mouth. As a potential solution, we introduce the concept of a free-parts representation, which may be able to circumvent many of these problems experienced by current area-based techniques.
On spin scale-discretised wavelets on the sphere for the analysis of CMB polarisation

Abstract A new spin wavelet transform on the sphere is proposed to analyse the polarisation of the cosmic microwave background (CMB), a spin ± 2 signal observed on the celestial sphere. The scalar directional scale-discretised wavelet transform on the sphere is extended to analyse signals of arbitrary spin. The resulting spin scale-discretised wavelet transform probes the directional intensity of spin signals. A procedure is presented using this new spin wavelet transform to recover E- and B-mode signals from partial-sky observations of CMB polarisation.
Role of the ACE ID and PPARG P12A Polymorphisms in Genetic Susceptibility of Diabetic Nephropathy in a South Indian Population

Background Diabetic nephropathy (DN) is one of the life-threatening disorders characterized by persistent albuminuria, raised arterial blood pressure, a lowered glomerular filtration rate, and high risk of cardiovascular morbidity and mortality. The vascular genes ACE (Angiotensin-converting enzyme), and PPARG (peroxisome proliferator activated receptor gamma) are involved in alterations in vascular endothelium, and are suggested to play a role in the susceptibility of diabetic nephropathy. Objectives The aim of our study was to find out the role of ACE ID and PPARG P12A polymorphisms in genetic susceptibility of diabetic nephropathy in south Indian population. Patients and Methods A total of 54 cases with diabetic nephropathy and 67 control subjects with diabetes were enrolled for our study. DNA was isolated from peripheral blood leucocytes, and genotyped using PCR-electrophoresis (ACE ID) or PCR-RFLP (PPARG P12A) methods. Results ACE ID genotypes followed Hardy-Weinberg equilibrium in both cases and controls. But P12A genotypes deviated from Hardy-Weinberg equilibrium in diabetic controls. Chi2 test was applied for the analysis of genotypic distributions in genotypic and dominant models. Odds ratios were also calculated. No significant differences in genotype frequencies of ACE ID and PPARG P12A polymorphisms were found on comparing patients with diabetic nephropathy with diabetic controls. The synergistic role of ACE ID* PPARG P12A interaction, did not show any association in patients with diabetic nephropathy when compared to diabetic controls. Conclusions In conclusion, the ACE and PPARG genes do not have a key role in conferring risk for diabetic nephropathy.
Adaptive ML-weighting in multi-band recombination of Gaussian mixture ASR

Multi-band speech recognition is powerful in band-limited noise, when the recognizer of the noisy band, which is less reliable, can be given less weight in the recombination process. An accurate decision on which bands can be considered as reliable and which bands are less reliable due to corruption by noise is usually hard to take. We investigate a maximum-likelihood (ML) approach to adapting the combination weights of a multi-band system. The Gaussian mixture model parameters are kept constant, while the combination weights are iteratively updated to maximize the data likelihood. Unsupervised offline and online weights adaptation are compared to the use of equal weights, and 'cheating' weights where the noisy band is known, as well as to the fullband system. Initial tests show that both ML-weighting strategies show a robustness gain on band-limited noise.
A hierarchical agent assisted MIPv6 handover scheme with QoS support

This paper proposes a hierarchical mobility management architecture providing adaptive QoS control to improve the performance during mobile handovers, especially break-before-make handovers. In the proposed scheme, the information for QoS configuration and location management is carried by the same set of messages. The interactions between the QoS Agents (QA) enable smooth handover, with better performance in terms of IP layer handover latency and QoS configuration latency when the MN is away from the home network.
The Coverage of Error Diagnosis in Logic Programming Using Weighted Constraints - The Case of an Ill-Defined Domain

Programming should be considered as an ill-defined domain because for a given programming problem there might be many alternative solution strategies and for each of them a wide spectrum of solutions can be created. Most programming problems, which are used to tutor beginners, are simple and might have well-defined start and goal states. The task statement can be well specified and a solution can easily be checked for being correct or not. However, the activity of solving a programming task is a design problem. One can not only apply different programming techniques to create a solution, but also modularize a program to make the code clear, easy maintainable and reusable. In this paper, we demonstrate how we applied weighted constraints to build a diagnosis component which serves the student model of an intelligent tutoring system (ITS) for logic programming. This technology has been integrated into a web-based ITS. We evaluated the coverage of error diagnosis with 221 student solutions of past examinations and the system was able to produce a correct analysis for 87.9% of collected solutions.
Research on the Data Storage and Access Model in Distributed Environment

In order to improve the data access efficiency and enhance the security in IT systems, a layered access control model with classified distributed storage in distributed environment is presented[1,2]. In the model, information is stored in numbers of physical distributed storage nodes. The storage architecture is logically organized into four classes, which includes active data storage, static data storage, backup data storage and data warehouse. Data access efficiency is increased because most applications will concentrate on active data storage or static data storage where the most recently and frequently used data are stored. Data security access is controlled through a 3-layered access control model based on RBAC model[3,4]. The three layers include operation layer, data logic security shield layer and application layer. Operation layer and application layer are to control the authorized access for system managers and application end users respectively. The data logic security shield layer is to shield the difference among the database safety control organizations. It is appreciated after the model has been applied to Zhejiang Fuchunjiang Limited Company.
Integration themes in multimodal human-computer interaction

This research examines how people integrate spoken and written input during multimodal human-computer interaction. Three studies used a semi-automatic simulation technique to collect data on people's free use of spoken and written input. Within-subject repeated-measures studies were designed, with data analyzed from 44 subjects and 240 tasks. The primary factors that govern people's selection to write versus speak at given points during a human-computer exchange were evaluated. Analyses revealed that people write digits more often than textual content, and proper names more often than other text. A form-based presentation, in comparison with an unconstrained format, also increased the likelihood of writing. However, the most in uential factor in patterning people's integrated use of speech and writing is contrastive functionality, or the use of spoken and written input in a contrastive way to designate a shift in content or functionality, such as original versus corrected input, data versus command, and digits versus text. Di erent patterns of contrastive mode use accounted for approximately 57% of the integrated pen/voice use observed in these studies. Information also is summarized on preferential mode use, and simultaneity of pen/voice input. One long-term goal of this research is the development of quantitative predictive models of natural modality integration, which could provide guidance on the strategic design of robust multimodal systems.
Relationship Dynamics of Burnout, Turnover Intentions and Workplace Incivility Perceptions

Building upon the relational perspective of employee attitudes and behaviors, we built and tested a causal model to demonstrate the relationship dynamics of burnout, turnover intentions and workplace incivility perceptions. A sample of 237 professionals from 6 major telecom companies participated in this cross-sectional study. A self-reported questionnaire was administered to guage participants’ perceptions regarding burnout, turnover intentions and workplace incivility. This study concludes that the perceptions of burnout, through workplace invility, provoke turnover intentions. This finding is a significant addition to existing body of literature on burnout, turnover intentions and workplace incivility.