Miracle-dz/UniFAR-FTUs huggingface dataset:
Variance shadow maps

Shadow maps are a widely used shadowing technique in real time graphics. One major drawback of their use is that they cannot be filtered in the same way as color textures, typically leading to severe aliasing. This paper introduces variance shadow maps, a new real time shadowing algorithm. Instead of storing a single depth value, we store the mean and mean squared of a distribution of depths, from which we can efficiently compute the variance over any filter region. Using the variance, we derive an upper bound on the fraction of a shaded fragment that is occluded. We show that this bound often provides a good approximation to the true occlusion, and can be used as an approximate value for rendering. Our algorithm is simple to implement on current graphics processors and solves the problem of shadow map aliasing with minimal additional storage and computation.
Azimuthal elastic inversion for fracture characterization

In this paper, we investigated azimuthal elastic inversion problem using Monte Carlo type methods: Simulated Annealing (SA) and Markov Chain Monte Carlo (MCMC). It is demonstrated in numerical simulation that these two approaches are capable of resolving 5 and even 6 parameters in the forward model, which is considered complicated for its non-linearity ([2]).
Hybrid side-channel/machine-learning attacks on PUFs: A new threat?

Machine Learning (ML) is a well-studied strategy in modeling Physical Unclonable Functions (PUFs) but reaches its limits while applied on instances of high complexity. To address this issue, side-channel attacks have recently been combined with modeling techniques to make attacks more efficient [25][26]. In this work, we present an overview and survey of these so-called “hybrid modeling and side-channel attacks” on PUFs, as well as of classical side channel techniques for PUFs. A taxonomy is proposed based on the characteristics of different side-channel attacks. The practical reach of some published side-channel attacks is discussed. Both challenges and opportunities for PUF attackers are introduced. Countermeasures against some certain side-channel attacks are also analyzed. To better understand the side-channel attacks on PUFs, three different methodologies of implementing side-channel attacks are compared. At the end of this paper, we bring forward some open problems for this research area.
Influence of Underground Coal Mining on Surface Morphology and Soil Erosion

This paper uses FLAC 3D numerical simulation software to establish the model of concave slope, convex slope, mixed slope and uniform slope to simulate the influence of underground coal mining on surface morphology. The modified universal soil loss equation (RUSLE) was used to estimate the amount of soil erosion caused by underground coal mining. The results show that underground mining will cause the increase of surface slope, the decrease of slope length and the increase of soil erosion. The soil erosion is uniform slope, concave slope, mixed slope, convex slope, and uniform slope (straight slope) is the key prevention and control slope of soil erosion in underground mining.
Development of a virtual audience concept for public speaking training in immersive virtual environments

Public speaking is common in today's work and study environment, yet many people dread giving presentations and sometimes even avoid them altogether. A frequent solution is to take up public speaking courses where speakers can learn presentation skills from speech trainers and rehearse in front of other trainees. By combining the opportunities of virtual reality with the characteristics and challenges of training sessions, the dissertation proposes a design concept for a virtual audience that can serve as speech training tool in immersive virtual environments. Through this approach the research addresses public speaking from a training angle - a novel view that wishes to complement the existing speech anxiety treatment studies in virtual reality. The work rests on a multidisciplinary ground and includes perspectives from interpersonal communication, virtual reality, human-computer interaction, and design of virtual learning environments.
Emotional speech classification using Gaussian mixture models

The classification of utterances into five basic emotional states is studied. A total of 87 statistical characteristics of pitch, energy, and formants is extracted from 500 utterances of the Danish emotional speech database. An evaluation of the classification capability of each feature is performed with respect to the probability of correct classification achieved by the Bayes classifier that models the feature probability density function as a mixture of Gaussian densities. Next, the feature subset that yields the highest probability of correct classification is found using the sequential floating forward selection algorithm. The probability of correct classification is estimated via cross-validation and the probability density functions are modelled as mixtures of 2 or 3 Gaussian densities. The results demonstrate that the Bayes classifier which employs mixtures of 2 Gaussian densities can achieve a probability of correct classification equal to 0.55, whereas the human classification score is 0.67 for the database considered and random classification would give a probability of correct classification equal to 0.20.
Eigenvalue translation based preconditioners for the GMRES(k) method

The paper considers a possible approach to the construction of high-quality preconditionings for solving large sparse unsymmetric offdiagonally dominant, possibly indefinite linear systems. We are interested in the construction of an efficient iterative method which does not require from the user a prescription of several problem-dependent parameters to ensure the convergence, which can be used in the case when only a procedure for multiplying the coefficient matrix by a vector is available and which allows for an efficient parallel/vector implementation with only one additional assumption that the most of eigenvalues of the coefficient matrix are condensed in a vicinity of the point 1 of the complex plane. The suggested preconditioning strategy is based on consecutive translations of groups of spread eigenvalues into a vicinity of the point 1. Approximations to eigenvalues to be translated are computed by the Arnoldi procedure at several GMRES(k) iterations. We formulate the optimization problem to find optimal translations, present its suboptimal solution and prove the numerical stability of consecutive translations. The results of numerical experiments with the model CFD problem show the efficiency of the suggested preconditioning strategy.
Dual function of TGFβ in lens epithelial cell fate: implications for secondary cataract

TGFβ signaling is linked to posterior capsule opacification (PCO), the most common complication of cataract surgery. TGFβ can induce primary lens epithelial cells to differentiate into two disparate, PCO-causing abnormal cell phenotypes, a variation of the TGFβ paradox. Analysis of the signaling pathways downstream of TGFβ reveals novel therapeutic targets for PCO.
A joint signal processing and cryptographic approach to multimedia encryption

In recent years, there has been an increasing trend for multimedia applications to use delegate service providers for content distribution, archiving, search, and retrieval. These delegate services have brought new challenges to the protection of multimedia content confidentiality. This paper discusses the importance and feasibility of applying a joint signal processing and cryptographic approach to multimedia encryption, in order to address the access control issues unique to multimedia applications. We propose two atomic encryption operations that can preserve standard compliance and are friendly to delegate processing. Quantitative analysis for these operations is presented to demonstrate that a good tradeoff can be made between security and bitrate overhead. In assisting the design and evaluation of media security systems, we also propose a set of multimedia-oriented security scores to quantify the security against approximation attacks and to complement the existing notion of generic data security. Using video as an example, we present a systematic study on how to strategically integrate different atomic operations to build a video encryption system. The resulting system can provide superior performance over both generic encryption and its simple adaptation to video in terms of a joint consideration of security, bitrate overhead, and friendliness to delegate processing.
Which psychiatric patients board on the medical service?

OBJECTIVES Patients who require psychiatric hospitalization may be admitted to a medical service only because there are no available inpatient psychiatric beds. These patients are psychiatric "boarders. " The goals of this study were to describe the extent of the boarder problem and to compare the characteristics of patients who are placed successfully into psychiatric facilities from the emergency department (ED) with those who require admission to the medical service as a boarder. METHODS A retrospective cohort study of a large pediatric ED was conducted. Included were patients who required inpatient psychiatric admission between July 1, 1999, and June 30, 2000. Patients were excluded when they needed inpatient medical treatment before psychiatric placement. The main outcome measured was placement into a psychiatric facility or boarding on medical service. RESULTS Of the 315 patients who presented to the ED and required psychiatric admission, 103 (33%) were boarded on the medical service. Multivariate logistic regression demonstrated an increased odds of boarding for age 10 to 13 years (adjusted odds ratio [AOR]: 3.5; 95% confidence interval [CI]: 1.8-6.6), black race (AOR: 2.3; 95% CI: 1.1-4.8), presenting on a weekend or holiday (AOR: 3.8; 95% CI: 1.6-8.8), and presenting from October to June (October-December 1999 [AOR: 4.7; 95% CI: 1.7-13.4], January-March 2000 [AOR: 14.5; 95% CI: 4.9-42.6], and April-June 2000 [AOR: 10.4; 95% CI: 3.5-30.2]) but a decreased odds for 1 insurance company (AOR: 0.08; 95% CI: 0.02-0.4). There was a linear increase in odds of boarding as severity of homicidal ideation increased from none to mild (AOR: 1.5; 95% CI: 1.2-1.8) to moderate (AOR: 2.3; 95% CI: 2.0-2.6) to severe (AOR: 3.5; 95% CI: 3.2-3.8). Suicidal patients also had increased risk of boarding (AOR: 2.2; 95% CI: 1.2-4.3). CONCLUSIONS Boarders are a problem in pediatrics, and this study identifies multiple characteristics that were associated with increasing a youth's odds of becoming a boarder at this institution. The suicidal and homicidal symptom results suggest a reverse triage system in which sicker patients are not necessarily given priority by psychiatric facilities. These data highlight mental health practices that need to be reassessed to ensure optimal care for youths with acute mental illness.
Detection of G Proteins in Purified Bovine Brain Myelin

Abstract: Following a previous report on detection of muscarinic receptors in myelin with the implied presence of G proteins, we now demonstrate by more direct means the presence of such proteins and their quantification. Using [35S]guanosine 5′‐O‐(3‐thiotriphosphate) ([35S]GTPγS) as the binding ligand, purified myelin from bovine brain was found to contain approximately half the binding activity of whole white matter (138 ± 9 vs. 271 ± 18 pmol/mg of protein). Scatchard analysis of saturation binding data revealed two slopes, a result suggesting at least two binding populations. This binding was inhibited by GTP and its analog but not by 5′‐adenylylimidodiphosphate [App(NH)p], GMP, or UTP. Following sodium dodecyl sulfate (SDS)polyacrylamide gel electrophoresis (PAGE) of myelin proteins and blotting on nitrocellulose, [α‐32P]GTP bound to three bands in the 21–27‐kDa range in a manner inhibited by GTP and GTPγS but not App(NH)p. ADP‐ribosylation of myelin with [32P]NAD+ and cholera toxin labeled a protein of 43 kDa, whereas reaction with pertussis toxin labeled two components of 40 kDa. Cholatc extract of myelin subjected to chromatography on a column of phenyl‐Sepharose gave at least three major peaks of [35S]GTPγS binding activity. SDS‐PAGE and immunoblot analyses of peak I indicated the presence of Goα, Giα, and Gsα. Further fractionation of peak II by diethyl‐aminoethyl‐Sephacel chromatography gave one [35S]GTPγS binding peak with the low‐molecular‐mass (21–27 kDa) proteins and a second showing two major protein bands of 36 and 40 kDa on SDS‐PAGE. Immunoblot analysis of this material identified the 36‐kDa protein as the β subunit, whereas the fraction containing 40‐kDa polypeptides reacted with specific antibodies to Goα and Giα. Thus, purified myelin from bovine brain has been shown to contain several GTP‐binding proteins resembling in broad outline the G proteins of whole brain and potentially able to transduce signals received by muscarinic (and perhaps other) receptors in this membrane.
Immersive virtual aquarium with real-walking navigation

In this paper, we propose a new immersive virtual aquarium system that comprises enhanced navigation, shared user experience, and manipulation in virtual reality. The system utilizes a large studio that allows users to walk around naturally and operates as a surrogate for navigation in the virtual aquarium. It also provides an additional view that shows what is happening in the virtual aquarium to observers. The system can be regarded as a form of augmented virtuality as it superimposes a live video avatar of users into the virtual aquarium. In addition, each user can interact with virtual fishes via 3D gestures because the system also utilizes a gesture recognition method that is suitable for the physically large space. These features enable our proposed system to give users and observers a more immersive and novel experience than conventional virtual reality systems.
A Novel Network Intrusion Detection System (NIDS) Based on Signatures Search of Data Mining

Network security has been a very important issue, since the rising evolution of the Internet. There has been an increasing need for security systems against the external attacks from the hackers. One important type is the intrusion detection system (IDS). There are two major categories of the analysis techniques of IDS: the anomaly detection and the misuse detection. Here we forcus on misuse detection, the misuse detection collected the attack signatures in a database as the same as virus protection software to detect the relate attacks, we propose an algorithm to use the known signature to find the signature of the related attack quickly.
Live Broadcast With Community Interactions: Bottlenecks and Optimizations

Recent years have witnessed the rapid growth of new live broadcast services, represented by Twitch.tv and YouTube live events, where videos are crowdsourced from amateur users (e.g., game players), rather than from commercial and professional TV broadcaster or content providers. The viewers also actively contribute to the content through embedded open-chat channels. Such community interactions among viewers, or even between broadcasters and viewers, make content generation highly diversified and engaging, particularly for the young generation. In this context, cross-viewer synchronization is highly desirable; otherwise the viewers with shorter broadcast latency may act as spoilers, significantly affecting the user experience of other viewers. In this paper, we show that the end-to-end delay has a dramatically amplified impact on the broadcast latency for individual viewers. We suggest smart rate adaptation to achieve cross-viewer synchronization, and develop distributed algorithms based on dual decomposition. We further extend our solution to the cloud environment, and present the concept of ShadowCast, which moves broadcasters to the cloud to provide high-quality streams beyond broadcasters’ network bandwidth constraint. Its practicability and effectiveness is demonstrated by our implementation and test bed experiments.
The design of a DSP-based PFN trigger timing control system and the experimental study

At the present, most of the electromagnetic gun in the research use multilevel capacitance energy storage power as incentive. The electromagnetic gun uses the PFN discharge network to form the expected discharge waveform and reach the purpose of controlling the emitting muzzle velocity of the electromagnetic gun. So it's important to control all the power modules discharge timing precisely before the launch. This paper puts forward a trigger timing control system based on TMS320F2812. The main circuit includes four parts which are timing controlling, pulse generation, high voltage trigger and energy free-wheeling. In the circuit, the anti-interference measures have been taken. The system can output multiple control pulse signal and the delay time of the pulse signals can be changed through the computer directly. In the paper, the hardware design method and the software implementation of the DSP control system are given out. The control circuit with the TVS, spark switch and SCR as the switches is presented and the best switch is chosen by comparison. The feasibility and reliability of the system are verified through the experiment. The paper also gives the PFN discharge current figures under the simulation and experiment with different discharge timings. The optimal PFN discharge timing is drawn when the discharge waveform is suitable. In the end, it analyzes the influence of the high voltage pulse on the crowbar diode during the discharge process with different discharge timings and different positions of the switch.
Effect of Solution pH and Chloride Concentration on Akaganeite Precipitation: Implications for Akaganeite Formation on Mars

Akaganeite, a chloride‐bearing Fe(III) (hydr)oxide, has been reported on Mars in Yellowknife Bay in Gale crater by X‐ray diffraction (XRD), in Robert Sharp crater by Compact Reconnaissance Imaging Spectrometer for Mars, and possibly at the Gusev crater and Meridiani Planum by combined Mössbauer and bulk chemistry analyses. Because formation conditions remain unknown, we investigated akaganeite precipitation as a function of solution pH and chloride concentration. Akaganeite was synthesized through hydrolysis of Fe(III) perchlorate in the presence of 0.02, 0.05, and 0.1 M chloride and at initial solution pH of 1.6, 4, 6, and 8 at 90 °C. Mineralogy of the precipitated Fe(III) (hydr)oxides was characterized by XRD, infrared spectroscopy, and Mössbauer spectroscopy. Total chloride and perchlorate contents were determined by ion chromatography. XRD revealed that akaganeite formed alone or in mixtures with ferrihydrite, hematite, and/or goethite at initial pH 1.6 with 0.02, 0.05, and 0.1 M Cl− and at initial pH from 4 to 8 with 0.05 and 0.1 M Cl−. Infrared analysis showed that akaganeite bands at ~2 and ~2.45 μm were sensitive to amount of akaganeite, total chloride content, and presence of other Fe(III) (hydr)oxides. The results indicate that akaganeite in Yellowknife Bay in Gale crater likely formed under acidic to alkaline (1.6 < pH < 8) oxidizing conditions in solutions containing >0.05 M Cl− by the dissolution of basaltic minerals. Akaganeite in Robert Sharp crater may have formed in acidic (pH < 4) solutions with ~0.1 M Cl− through oxidative dissolution of Fe(II) sulfides and/or acidic oxidizing dissolution of basalts.
Comparing one-class and two-class SVM classifiers for normal mammogram detection

X-ray mammograms are one of the most common techniques used by radiologists for breast cancer detection and diagnosis. Early detection is important, which raised the importance of developing Computer-Aided Detection and Diag-nosis(CAD) systems. Although most(CAD)systems were designed to help radiologists in their diagnosis by providing useful insight, the accuracy of CAD systems remains below the level that would lead to an improvement in the overall radiologists' performance. Unlike other CAD systems who aim to detect abnormal mammograms, we are designing a pre-CAD system that aims to detect normal mammograms instead of abnormal ones. The pre-CAD system works as a "first look" and screens-out normal mammograms, leaving the radiologists and other conventional CAD systems to focus on the suspicious cases. Support Vector Machine classifiers are used to detect normal mammograms. We are comparing the effect of using 1-class and 2-class SVMs when normal mammogram, instead of abnormal, is detected. Results showed that our pre-CAD system performance for 1-class outperformed 2-class SVM classifiers almost always. Using our set of features, 1-class SVM achieved a specificity of (99.2%), while the two-class SVM achieved (86.71%) respectively.
Surface modification of biomaterials using plasma immersion ion implantation and deposition

Although remarkable progress has been made on biomaterial research, the ideal biomaterial that satisfies all the technical requirements and biological functions is not available up to now. Surface modification seems to be a more economic and efficient way to adjust existing conventional biomaterials to meet the current and ever-evolving clinical needs. From an industrial perspective, plasma immersion ion implantation and deposition (PIII&D) is an attractive method for biomaterials owing to its capability of treating objects with irregular shapes, as well as the control of coating composition. It is well acknowledged that the physico-chemical characteristics of biomaterials are the decisive factors greatly affecting the biological responses of biomaterials including bioactivity, haemocompatibility and antibacterial activity. Here, we mainly review the recent advances in surface modification of biomaterials via PIII&D technology, especially titanium alloys and polymers used for orthopaedic, dental and cardiovascular implants. Moreover, the variations of biological performances depending on the physico-chemical properties of modified biomaterials will be discussed.
Estimating traffic correlations from sampling and active network probing

An extensive body of research deals with estimating the correlation and the Hurst parameter of Internet traffic traces. The significance of these statistics is due to their fundamental impact on network performance. The coverage of Internet traffic traces is, however, limited since acquiring such traces is challenging with respect to, e.g., confidentiality, logging speed, and storage capacity. In this work, we investigate how the correlation of Internet traffic can be reliably estimated from random traffic samples. These samples are observed either by passive monitoring within the network, or otherwise by active packet probes at end systems. We analyze random sampling processes with different inter-sample distributions and show how to obtain asymptotically unbiased estimates from these samples. We quantify the inherent limitations that are due to limited observations and explore the influence of various parameters, such as sampling intensity, network utilization, or Hurst parameter on the estimation accuracy. We design an active probing method which enables simple and lightweight traffic sampling without support from the network. We verify our approach in a controlled network environment and present comprehensive Internet measurements. We find that the correlation exhibits properties such as long range dependence as well as periodicities and that it differs significantly across Internet paths and observation times.