Miracle-dz/UniFAR-FTUs huggingface dataset:
Point-Based Global Illumination for Movie Production

This course note describes a fast point-based method for computing diffuse and glossy global illumination, area light illumination and soft shadows, HDRI environment map illumination, multiple diffuse reﬂection bounces, ﬁnal gathering for photon mapping, ambient occlusion, reﬂection occlusion, and volume scattering. The results are free of noise and the run-time does not increase due to displacement maps on surfaces, complex shaders, or dozens of complex light sources. These properties make the method suitable for movie production. The ﬁrst step generates a point cloud (surfel) representation of the directly illuminated geometry in the scene. The surfels in the point cloud are organized in an octree, and the power from the surfels in each octree node is approximated either as a single large surfel or using spherical harmonics. To compute the indirect illumination at a receiving point, we rasterize the light from all surfels using three degrees of accuracy: ray tracing, disk approximation, and clusters. Huge point clouds are handled by reading the octree nodes and surfels on demand and caching them. The method is integrated into Pixar’s RenderMan renderer (PRMan) and has been used in the production of more than 35 feature ﬁlms to date.
Cardiovascular disease prognosis using effective classification and feature selection technique

Cardiovascular disease is a worldwide health problem and according to American Heart Association (AHA), it also causes an approximate death of 17.3 million each year. Therefore early detection and treatment of asymptomatic cardiovascular disease which can significantly reduce the chances of death. An important fact regarding such life-threatening disease prognosis is to identify the patient's physical state (healthy or sick) based on the analysis of health checkup data. This paper aims at optimized cardiovascular disease prognosis using different data mining techniques. We also provide a technique to improve the accuracy of proposed classifier models using feature selection technique. Patient's data were collected from Department of Computing of Goldsmiths University of London. This dataset contains total 14 attributes in which we applied SMO (SVM - Support Vector Machine), C4.5 (J48 - Decision Tree) and Naïve Bayes classification algorithms and calculated their prediction accuracy. An efficient feature selection algorithm helped us to improve the accuracy of each model by reducing some lower ranked attributes. Which helped us to gain an accuracy of 87.8%, 86.80% & 79.9% in case of SMO, Naïve Bayes and C4.5 Decision Tree algorithms respectively.
HKUST statistical machine translation experiments for IWSLT 2007

This paper describes the HKUST experiments in the IWSLT 2007 evaluation campaign on spoken language translation. Our primary objective was to compare the open-source phrase-based statistical machine translation toolkit Moses against Pharaoh. We focused on Chinese to English translation, but we also report results on the Arabic to English, Italian to English, and Japanese to English tasks.
SELF-ESTEEM, PAIN AND SUICIDAL THOUGHTS IN A SAMPLE OF CANCER PATIENTS

Objective: Our primary aim was to assess the relationship between self-esteem and pain and suicidal thoughts in a sample of patients with various kinds of cancer. Method: A total of 117 adult cancer patients were assessed with respect to several sociodemographic variables, the severity of pain, depression, and anxiety, current suicidal thoughts, hopelessness and self-esteem. Turkish versions of Visual Analog Scale, Hospital Anxiety and Depression Scale, Beck Hopelessness Scale, Beck Scale for Suicide Ideation, Rosenberg Self-Esteem Scale were used in this study. Results: The severity of depression, anxiety, hopelessness, and current suicidal thoughts were significantly higher in patients with pain compared to patients without pain. Self-esteem was significantly reduced in subjects with pain. Previous history of psychiatric disorder and pain significantly predicted current suicidal thoughts status. Reduced self-esteem was significantly correlated with depression, anxiety, hopelessness, pain, and current suicidal thoughts. Conclusions: Reduced self-esteem among cancer patients was particularly associated with a more severe pain, higher levels of depression, stronger feelings of hopelessness and current suicidal thoughts. Our findings might indicate that pain in cancer patients might have a negative influence on self-esteem leading to suicidal thoughts along with depression, anxiety, and hopelessness. Therefore, reduced self-esteem in cancer patients might be associated with suicidal ideations through pain, depression, anxiety, and hopelessness.
On the analysis of QoE-based performance degradation in YouTube traffic

YouTube is the most popular service in today's Internet. Google relies on its massive Content Delivery Network (CDN) to push YouTube videos as close as possible to the end-users to improve their Quality of Experience (QoE), using dynamic server selection strategies. Such traffic delivery policies can have a relevant impact on the traffic routed through the Internet Service Providers (ISPs) providing the access, but most importantly, they can have negative effects on the end-user QoE. In this paper we shed light on the problem of diagnosing QoE-based performance degradation events in YouTube's traffic. Through the analysis of one month of YouTube flow traces collected at the network of a large European ISP, we particularly identify and drill down a Google's CDN server selection policy negatively impacting the watching experience of YouTube users during several days at peak-load times. The analysis combines both the user-side perspective and the CDN perspective of the end-to-end YouTube delivery service to diagnose the problem. The main contributions of the paper are threefold: firstly, we provide a large-scale characterization of the YouTube service in terms of traffic characteristics and provisioning behavior of the Google CDN servers. Secondly, we introduce simple yet effective QoE-based KPIs to monitor YouTube videos from the end-user perspective. Finally and most important, we analyze and provide evidence of the occurrence of QoE-based YouTube anomalies induced by CDN server selection policies, which are somehow normally hidden from the common knowledge of the end-user. This is a main issue for ISPs, who see their reputation degrade when such events occur, even if Google is the culprit.
A general scheme for noise-tolerant logic design based on probabilistic and DCVS approaches

The performance of logic function could be affected significantly by the noise effect as the dimension of CMOS devices scales to nanometers. Thus, many pertinent researches about noise-tolerant logic gate have received growing attention. Considering the randomness as the noise's nature, probabilistic-based approach proves better noise-immunity and three design schemes with the technique of Markov Random Field (MRF) have been proposed in [1]-[3]. In this paper, a general circuit scheme for noise-tolerant logic design based on MRF theory and Differential Cascode Voltage Switch (DCVS) technique has been proposed, which is an extension of the work in [3], [4]. A DCVS block with only four transistors has been successfully inserted to the original circuit scheme from [3] and extensive simulation results based on HSPICE show that our proposed design can operate correctly with the input signal of 1dB SNR. When using the Kullback-Leibler Distance (KLD) [5] as the evaluation parameter, the KLD value of our design decreases by 76.5% on average than [3] which means that superior noise-immunity could be obtained through our work.
Video Stabilization by Feature-Block Motion Estimation

This paper presents a real-time video stabilization method for adjusting unstable frames captured by a vibrating camera. The basic idea is to calculate the vibration degree for compensating the vibration area by block motion detection and analyzing vibration type. A feature block is selected to obtain the vibration vector for checking if the frame is vibrant, and then the missing area is compensated and the overlapping area is adjusted. Experimental results show that the proposed algorithm can effectively reduce the frame vibration in real-time for the general vibration situations of moderate degree and compensate more than 21 pixels.
An alternative single-image super resolution framework employing high frequency prediction using a robust huber rational function

In general prospective, SI-SR or Single-Image Super-Resolution, which is one of the most useful algorithms of Super Resolution-Reconstruction (SRR) algorithms, is a mathematical procedure for acquiring a high-resolution image from only one coarse-resolution image, which is usually computed by Digital Image Processing (DIP). Even thought there have been substantially researched during the last decade, Single - Image Super-Resolution for applying on real implementations still keeps throw down the gauntlet. One of the practical Single-Image Super-Resolution is the resolution enhancement using prediction of the high-frequency image because of its high performance and its less complexity however the rational function C(x, y) of high-frequency image prediction process of this technique is depend upon three parameters (b, h, k) therefore the parameter turning is difficult for maximizing its performance. From this problem prospective, this paper presents the alternative SI-SR framework employing robust rational function based on Huber function, which is depend upon only one parameter (T), instead of three parameters like the rational function C(x, y). Using up to fourteen standard images, which are crooked by varied noise models, in analysis testing section, the proposed SI-SR is demonstrated to be somewhat simper than the original SI-SR with equivalent efficiency because the saving in parameter turning time will be very important for SI-SR in real implementations.
SCCharts: sequentially constructive statecharts for safety-critical applications: HW/SW-synthesis for a conservative extension of synchronous statecharts

We present a new visual language, SCCharts, designed for specifying safety-critical reactive systems. SCCharts use a statechart notation and provide determinate concurrency based on a synchronous model of computation (MoC), without restrictions common to previous synchronous MoCs. Specifically, we lift earlier limitations on sequential accesses to shared variables, by leveraging the sequentially constructive MoC. The semantics and key features of SCCharts are defined by a very small set of elements, the Core SCCharts, consisting of state machines plus fork/join concurrency. We also present a compilation chain that allows efficient synthesis of software and hardware.
Chronic Renal Failure Resistance of Bone to PTH Shift in Set Point for Calcium Decreased

Hyperplasia of the parathyroid glands and increased concentrations of immunoreactive parathyroid hormone are among the earlier alterations of mineral metabolism in patients with chronic renal failure. In the past five years several investigators have demonstrated that phosphorus retention plays a key role in the development of secondary hyperparathyroidism and chief cell hyperplasia of the parathyroid glands. Since phosphorus regulates the production of 1,25D3 by altering the enzyme 1-a-hydroxylase it is possible that the effect of phosphorus retention is mediated by a decrease in the synthesis of 1,25D3. This has been shown in patients with early renal insufficiency. However, in patients with advanced renal failure the reduced renal mass may limit the production of 1,25D3. It is clear now that phosphorus per se independent of the levels of ionized calcium and 1,25D3 can increase the synthesis and secretion of PTH in vivo and in vitro. The abnormalities in vitamin D metabolism are not only characterized by low levels 1,25D3 but by low number of vitamin D receptors. Thus, the parathyroid glands are resistant to the action of 1,25D3 and high pharmacological concentrations of 1,25D3 in blood are necessary to suppress the levels of parathyroid hormone in advanced renal failure. The development of monoclonal changes in glands obtained from patients with secondary hyperparathyroidism further complicates the treatment of secondary hyperparathyroidism in patients maintained on haemodialysis. Thus, correction of serum phosphorus is imperative for the success of 1,25D3 to control the levels of parathyroid hormone. Currently several laboratories are studying at the molecular level the mechanisms by which dietary phosphorus induces chief cell hyperplasia.
Regulation of the Actin Cytoskeleton Organization in Yeast by a Novel Serine/Threonine Kinase Prk1p

Normal actin cytoskeleton organization in budding yeast requires the function of the Pan1p/ End3p complex. Mutations in PAN1 and END3 cause defects in the organization of actin cytoskeleton and endocytosis. By screening for mutations that can suppress the temperature sensitivity of a pan1 mutant (pan1-4), a novel serine/threonine kinase Prk1p is now identified as a new factor regulating the actin cytoskeleton organization in yeast. The suppression of pan1-4 by prk1 requires the presence of mutant Pan1p. Although viable, the prk1 mutant is unable to maintain an asymmetric distribution of the actin cytoskeleton at 37°C. Consistent with its role in the regulation of actin cytoskeleton, Prk1p localizes to the regions of cell growth and coincides with the polarized actin patches. Overexpression of the PRK1 gene in wild-type cells leads to lethality and actin cytoskeleton abnormalities similar to those exhibited by the pan1 and end3 mutants. In vitro phosphorylation assays demonstrate that Prk1p is able to phosphorylate regions of Pan1p containing the LxxQxTG repeats, including the region responsible for binding to End3p. Based on these findings, we propose that the Prk1 protein kinase regulates the actin cytoskeleton organization by modulating the activities of some actin cytoskeleton-related proteins such as Pan1p/End3p.
Design and implementation of the PLUG architecture for programmable and efficient network lookups

This paper proposes a new architecture called Pipelined LookUp Grid (PLUG) that can perform data structure lookups in network processing. PLUGs are programmable and through simplicity achieve power efficiency. We draw upon the insights that data structure lookups have natural structure that can be statically determined and exploited. The PLUG execution model transforms data-structure lookups into pipelined stages of computation and associates small code-blocks with data. The PLUG architecture is a tiled architecture with each tile consisting predominantly of SRAMs, a lightweight no-buffering router, and an array of lightweight computation cores. Using a principle of fixed delays in the execution model, the architecture is contention-free and completely statically scheduled thus achieving high energy efficiency. The architecture enables rapid deployment of new network protocols and generalizes as a data-structure accelerator. This paper describes the PLUG architecture, the compiler, and evaluates our RTL prototype PLUG chip synthesized on a 55nm technology library. We evaluate six diverse high-end network processing workloads including IPv4, IPv6, and Ethernet forwarding. We show that at a 55nm technology, a 16-tile PLUG occupies 58mm2, provides 4MB on-chip storage, and sustains a clock frequency of 1 GHz. This translates to 1 billion lookups per second, a latency of 18ns to 219ns, and average power less than 1 watt.
Classification of n-butanol concentrations with k-NN algorithm and ANN in electronic nose

Electronic nose (e-nose) is a machine used for sensing and recognizing odors by using chemical sensors. E-nose has wide fields of applications and it is used for sensing special odors. Also performance of e-nose depends on choosing correct sensor and choosing correct pattern recognition algorithm according to field of application and kinds of odors. In this study, different n-butanol concentrations sensed by 12 metal oxide gas sensors are classified by using artificial neural network (ANN) and k-nearest neighbor (k-NN) algorithm. 100 % success rate is obtained with k-NN classifier for this application. Simultaneously results of k-NN classifier are compared with ANN results. To recognize the different concentrations of n-butanol sample which is component of farm odors is first stage of the study. Advanced stage of the study recognizes the farm odors.
Distributed Reset

A reset subsystem is designed that can be embedded in an arbitrary distributed system in order to allow the system processes to reset the system when necessary. Our design is layered, and comprises three main components: a leader election, a spanning tree construction, and a diffusing computation. Each of these components is self-stabilizing in the following sense: if the coordination between the up-processes in the system is ever lost (due to failures or repairs of processes and channels), then each component eventually reaches a state where coordination is regained. This capability makes our reset subsystem very robust: it can tolerate fail-stop failures and repairs of processes and channels, even when a reset is in progress. >
Pilot hopping in massive MIMO systems with MMSE channel estimation

Next generation wireless promises high data rate using advanced MIMO techniques. Large-Scale antenna system, or massive MIMO, has been proposed as a strong candidate for broadband next generation wireless applications. However, pilot contamination is one of the major challenges that limits the promised massive gains. In this paper, a new pilot assignment procedure is proposed to mitigate the pilot contamination problem. The assignment algorithm performs pilot reuse strategy and pilot hopping across multiple time slots during the channel coherence time. The goal is to randomize the contaminating users experienced by each user so that the interferences (and noise) are averaged out and thus increase the cell throughput. We show that this randomization can be made in a structured manner and that pilot reuse strategy has to be carefully designed in order to achieve high throughput. The covariance matrix of the channel estimation error using MMSE channel estimation is obtained.
Performance Analysis of FIR filter in frequency Domain and Time Domain for Wireless Communication System

This Paper gives design the methodology for implementation of FIR filter in the frequency domain and time domain. The filter coefficients for these two implementation are taken by sampling the time representation and frequency representation of RRC filter. The RRC filter transfer function is used to obtain Raised Cosine filter which is a pulse shaping filter. Then the performance evaluation is made by comparing the simulation results of the two filter implementation on the basis of computational complexity, inter symbol interference rejection depending on average gain in immunity against ISI, Error Vector Magnitude (EVM), Peak distortion and AWGN rejection. Then it is shown that by choosing frequency domain filter coefficients as the samples of the ideal frequency transfer function can boost the performances of such a filters mainly in terms of immunity against inter symbol interference. Keywords—FIR, RRC, WCDMA, IIR, UMTS, ISI
Spotfire: an information exploration environment

In this paper we examine the issues involved in developing information visualisation systems and present a framework for their construction. The framework addresses the components which must be considered in providing effective visualisations. The framework is specified using a declarative object oriented language; the resulting object model may be mapped to a variety of graphical user interface development platforms. This provides general support to developers of visualisation systems. A prototype system exists which allows the investigation of alternative visualisations for a range of data sources.
The atomic detail of an evaporating meniscus

Atomistic simulations of a simple Lennard-Jones fluid are used to investigate the very near-wall dynamics and thermodynamics of evaporating menisci. The specific configuration considered is a two-dimensional (in the mean) liquid drop centered on a cold spot on an atomically smooth solid wall with evaporating menisci extending from it onto hotter regions of the wall. In the four cases simulated, the interaction energy between the solid atoms, which make up the wall, and the fluid atoms, which are equilibrated in liquid and vapor phases, is varied by a factor of about 5. Results are interpreted in the context of a recently proposed continuum model [V. S. Ajaev and G. M. Homsy, “Steady vapor bubbles in rectangular microchannels,” J. Colloid. Interface Sci. 240, 259 (2001)], which is based on a low-capillary-number asymptotic analysis of the flow and heat equations. In this model, the nonlocal influence of the wall is modeled by a disjoining pressure, a common linearized nonequilibrium model is assumed for ev.
Teaching for developmental growth: learning partnerships and student development in graduate education in China

ABSTRACT Teaching and learning in higher education can integrate and accomplish student developmental goals in addition to promoting student learning of subject matter knowledge and transferrable skills. Drawn from the theoretical concept of self-authorship, the Learning Partnerships Model was implemented in teaching a graduate-level course on social research methodology. This paper describes the conceptualization and implementation of the developmentally attuned course, and reports a qualitative study that examined student development as its result. Qualitative data were collected from five cohorts of course participants, in the forms of reflective essays, student interviews, and the instructor’s teaching journal. Seven themes were identified that reflected student development throughout the course. The seven themes fall into three dimensions of epistemological, intrapersonal, and interpersonal development that are interconnected, and the epistemological dimension stands out as a strong partner among the three. These findings may help university faculty understand and integrate student development into their teaching practices.
Aspirin for prophylaxis against headache at high altitudes: randomised, double blind, placebo controlled trial

At altitudes of 3000-5000 m about 20-50% of skiers and mountaineers experience headache, the main symptom of acute mountain sickness.1 Although most mountaineers know that they should avoid climbing great heights too early on and too fast, they may not always act accordingly. The use of drugs to prevent and treat headaches at high altitudes is therefore widespread, aspirin being one of the most commonly taken. We tested the efficacy of aspirin as prophylaxis against headache at high altitudes. Twenty nine volunteers with a history of headache at high altitude were randomly assigned in a double blind fashion to receive placebo (eight men, six women, mean age 38 (SD 12) years) or 320 mg aspirin (nine men, six women, mean age 38 (14) years). After examination at low altitude (600 m), subjects were transported to high altitude (3480 m) …
Study on Classification Algorithm of Multi-subject Text

One text may belong to multi-class, but it can not be classified by standard SVM and other approaches. In this paper, a multi-subject text classification algorithm based on fuzzy support vector machines is proposed, 1-a-1 method is used to train sub-classifiers. For the sample to be classified, the sub-classifiers are used to obtain membership matrix, and then according to the sum of every line of membership matrix, the subjects that the sample belongs to can be confirmed. The algorithm was tested on Reuters 21578, the experimental results show that the algorithm has higher performance on recall, precision, and Fl.