Miracle-dz/UniFAR-FTUs huggingface dataset:
Providing Memory QoS Guarantees for Real-Time Applications

Nowadays, systems often integrate a variety of applications whose service requirements are heterogeneous. Consequently, systems must be able to concurrently serve applications which rely on different constraints. This raises the problem of the dynamic distribution of the system resources (CPU, memory, network, etc.). Therefore, an integrated Quality of Service (QoS) management is needed so as to efficiently assign resources according to the various application demands. Within this paper, we focus on a dynamic approach of QoS management for memory resource allocation based on the Skip-Over model. We detail our solution and we show how it improves the service of task memory requests while providing them guarantees. Quantitative results using the TLSF allocator have been performed in order to evaluate the memory failure probability with and without memory QoS manager.
Database of homology‐derived protein structures and the structural meaning of sequence alignment

The database of known protein three‐dimensional structures can be significantly increased by the use of sequence homology, based on the following observations. (1) The database of known sequences, currently at more than 12,000 proteins, is two orders of magnitude larger than the database of known structures. (2) The currently most powerful method of predicting protein structures is model building by homology. (3) Structural homology can be inferred from the level of sequence similarity. (4) The threshold of sequence similarity sufficient for structural homology depends strongly on the length of the alignment. Here, we first quantify the relation between sequence similarity, structure similarity, and alignment length by an exhaustive survey of alignments between proteins of known structure and report a homology threshold curve as a function of alignment length. We then produce a database of homology‐derived secondary structure of proteins (HSSP) by aligning to each protein of known structure all sequences deemed homologous on the basis of the threshold curve. For each known protein structure, the derived database contains the aligned sequences, secondary structure, sequence variability, and sequence profile. Tertiary structures of the aligned sequences are implied, but not modeled explicity. The database effectively increases the number of known protein structures by a factor of five to more than 1800. The results may be useful in assessing the structural significance of matches in sequence database searches, in deriving preferences and patterns for structure prediction, in elucidating the structural role of conserved residues, and in modeling three‐dimensional detail by homology.
Approaches for practical BitTorrent traffic control

As practical ways to control BitTorrent traffic, we examine two basic approaches that exploit existing features of BitTorrent instead of modifying BitTorrent system. Based on PEX that allows BitTorrent clients to exchange their neighboring peer information directly, we propose topology-aware PEX, tPEX to inject some local peers to each local peer in the target network domain for the traffic localization. We also try to redirect the unavoidable inter-domain traffic from the transit links to the peering links by affecting tit-for-tat (TFT) strategy through the delay insertion (indirectly guided TFT, gTFT). Through simulations, we show that tPEX increases the intra-domain traffic volume by up to 316% and reduces the charging volume by up to 32.2% and the download completion time by up to 43.3%. gTFT reduces the inter-domain traffic volume of the transit links by up to 11.1% and increases the inter-domain traffic volume of the peering links by 9.2%. gTFT reduces the charging volume by up to 9.7%. Even though gTFT does not much affect the average download completion time, gTFT increases the performance difference among peers by up to 28.6% by adding the artificial delay selectively. tPEX+gTFT shows almost similar performance to that of tPEX, since gTFT loses its ability to redirect the inter-domain traffic once tPEX is applied. Above results show that tPEX can be the practical win-win approach to satisfy both ISP and users.
Statistical language modeling using a variable context length

In this paper we investigate statistical language models with a variable context length. For such models the number of relevant words in a context is not fixed as in conventional M-gram models but depends on the context itself. We develop a measure for the quality of variable-length models and present a pruning algorithm for the creation of such models, based on this measure. Further we address the question how the use of a special backing-off distribution can improve the language models. Experiments were performed on two data bases, the ARPANAB corpus and the German Verbmobil corpus, respectively. The results show that variable-length models outperform conventional models of the same size. Furthermore it can be seen that if a moderate loss in performance is acceptable, the size of a language model can be reduced drastically by using the presented pruning algorithm.
Bayesian Galaxy Shape Measurement for Weak Lensing Surveys -II. Application to Simulations

In this paper, we extend the Bayesian model fitting shape measurement method presented in Miller et al., and use the method to estimate the shear from the Shear TEsting Programme simulations (STEP). The method uses a fast model fitting algorithm that uses realistic galaxy profiles and analytically marginalizes over the position and amplitude of the model by doing the model fitting in Fourier space. This is used to find the full posterior probability in ellipticity. The shear is then estimated in a Bayesian way from this posterior probability surface. The Bayesian estimation allows measurement bias arising from the presence of random noise to be removed. In this paper, we introduce an iterative algorithm that can be used to estimate the intrinsic ellipticity prior and show that this is accurate and stable. We present results using the STEP parametrization that relates the input shear γ T to the estimated shear γ M by introducing a bias m and an offset c: γ M - γ T = my T + c. The average number density of galaxies used in the STEP1 analysis was 9 per square arcminute, for STEP2 the number density was 30 per square arcminute. By using the method to estimate the shear from the STEP1 simulations we find the method to have a shear bias of m = 0.006 ± 0.005 and a variation in shear offset with point spread function type of σ = 0.0002. Using the method to estimate the shear from the STEP2 simulations we find that the shear bias and offset are m = 0.002 ± 0.016 and c = -0.0007 ± 0.0006, respectively. In addition, we find that the bias and offset are stable to changes in the magnitude and size of the galaxies. Such biases should yield any cosmological constraints from future weak lensing surveys robust to systematic effects in shape measurement. Finally, we present an alternative to the STEP parametrization by using a quality factor that relates the intrinsic shear variance in a simulation to the variance in shear that is measured and show that the method presented has an average of Q ≥ 100 which is at least a factor of 10 times better than other shape measurement methods.
Percutaneous coronary intervention in treatment of multivessel coronary artery disease in patients with non-ST-segment elevation acute coronary syndrome

Among patients with non-ST-elevated acute coronary syndromes (NSTE-ACS) the estimated percentage of single vessel coronary artery disease (SV-CAD) observed during coronarography is about 20-40%, while multivessel coronary artery disease (MV-CAD) is found in about 40-60%. Further treatment in patients with both SV CAD and MV CAD is usually culprit vessel percutaneous coronary intervention (CV-PCI). Nevertheless, in the group of patients with MV-CAD there is still a problematic decision whether the non-infarct related arteries (non-IRA) should be treated with PCI. According to the European Society of Cardiology (ESC) guidelines on myocardial revascularization this decision should be based on the overall clinical and angiographic status of the patient; simultaneously they suggest performing ad hoc CV-PCI. The decision of performing intervention in the rest of the narrowed coronary arteries should be made after consultation with the heart team or according to the protocols adopted in the specific clinic. Furthermore, there is a question of whether the procedure should be performed immediately after culprit vessel revascularization or it should be postponed until the patient is stabilized. Due to the lack of specific recommendations we decided to perform an analysis of existing studies which compared culprit versus multivessel revascularization in patients with MV-CAD and non-ST-elevated acute coronary syndromes.
Using Control Theory for Self-Tuning Database Systems A Position Paper

Current studies on self-tuning databases tend to adapt a static view of problems by focusing on long-term performance. We argue that a more important issue is to maintain transient performance in such systems due to the inevitable fluctuations in workloads and environmental factors. We propose the idea of using feedback control theory to deal with such dynamics and maintain performance in self-tuning databases. We discuss how relevant control-theoretical techniques can be used to solve typical problems in this field. One of the major difficulties in using formal methods to study such problems is the lack of accurate analytical models for complex database systems. This can be partially solved by system identification techniques. Concrete examples and preliminary results support our proposal. We also identify the major challenges in applying control theory to self-tuning database study.
A method for estimation of lightness of objects with intensity data from SOKUIKI sensor

Recently, SOKUIKI sensor is used in various fields including robotics. SOKUIKI sensor ldquoURG-04LXrdquo can take distances by measurement. And by using special mode of the firmware, Received Light Intensity and AGC Voltage Level can be obtained. This paper describes a method to estimate Gray Level of scanned objects by using Received Light Intensity. The method uses AGC Voltage Level for accurate estimation.
Yaw Estimation Using Cylindrical and Ellipsoidal Face Models

Accurate head yaw estimation is necessary for detecting driver inattention in forward collision warning systems. In this paper, we propose three geometric models under the ellipsoidal framework for accurate head yaw estimation. We present theoretical analysis of the cylindrical and ellipsoidal face models used for yaw angle estimation of head rotation. The relationship between cylindrical, ellipsoidal, and proposed models is derived. We provide error functions for all models. Furthermore, for each model, over/under estimation of angle, zero crossings of error, bounds on yaw angle estimate, and bounds on error are presented. Experimental results of the proposed models on four standard head pose data sets yielded a mean absolute error between 4° and 8° demonstrating the efficacy of the proposed models over the state-of-the-art methods.
Why Functional Programming Matters

As software becomes more and more complex, it is more and more important to structure it well. Well-structured software is easy to write and to debug, and provides a collection of modules that can be reused to reduce future programming costs. In this paper we show that two features of functional languages in particular, higher-order functions and lazy evaluation, can contribute significantly to modularity. As examples, we manipulate lists and trees, program several numerical algorithms, and implement the alpha-beta heuristic (an algorithm from Artificial Intelligence used in game-playing programs). We conclude that since modularity is the key to successful programming, functional programming oers important advantages for software development.
D-LITe: Distributed Logic for Internet of Things Services

Smart phones, PDA, Sensors, Actuators, Phidgets and Smart Objects (i.e. objects with processing and networking capabilities) are more and more present in everyday's life. Merging all these technologies with the Internet is often described as 'Internet of Things' (IoT). In the IoT vision, Things around us provide a pervasive network of interacting and interconnected devices. However building IoT applications is a long and arduous work, reserved for specialists, requiring specific knowledge's in terms of network protocols and programming languages. The lack of widespread and easy-to-configure solutions is an obstacle for the development of this area. A universal framework, offering simplification and standardization, could facilitate the emergence of this promising field in terms of applications and business. IoT needs a solid foundation for rapid, simple development and deployment of new services. In this paper, we present D-LITe, a universal framework for building IoT applications over heterogeneous sets of small devices. D-LITe offers solutions for deploying application's logic, and executing it on Smart Objects despite their heterogeneity. An implementation of D-LITe on tiny devices, such as TelosB motes, allows to show that our framework is realistic even with the constraints of such devices.
Mining individual access patterns by the time preference of a web user

Mining a web user's access patterns can efficiently reveal the traits of personal behavior, e.g. the user's interest and inherent surfing habits. According to a user's access sequences which generate residence time and time intervals, a novel data structure called parent index tree of users' frequent access patterns (UFAP-PIT) is developed for mining individual access patterns. Furthermore, the residence time of personal access pages in Web page classes which are extracted from UFAP-PIT is processed by K-means clustering. Meanwhile, the time interval between a pair of Web page classes is processed in the same way. Finally, our algorithm can effectively construct personalized user access patterns by the time preference. The experimentation has shown that the proposed algorithm presents a marked difference in personal behavior patterns by time attributes.
Reference Node Selection Algorithm Based on Trilateration and Performance Analysis in Indoor Sensor Networks

In indoor sensor networks, due to resource limitation of the sensor nodes, some of the traditional positioning algorithms, such as two-phase positioning (TPP) algorithm, are too complicated to be implemented and they can't satisfy the real-time localization of the mobile node. We analyze the localization error and draw the conclusion that the localization error is the least when three reference nodes form an equilateral triangle. Therefore, we improve the TPP algorithm and propose reference node selection algorithm based on trilateration (RNST). Our proposed algorithm is verified by the simulation experiment. The simulation results show that our algorithm can meet real-time localization requirement of the mobile nodes in indoor environment, and make the localization error less than that of the traditional algorithm.
Enhancing the zone of keratinized tissue around implants

Presence or absence of a minimal zone of keratinized tissue around dental implants has been a matter of controversy. However, a consensus exists that a thick zone of keratinized zone around implants provides a prosthetic friendly environment, facilitates precise prosthetic procedures, allows oral hygiene maintenance, resists recession, and enhances esthetic blending. The aim of the present case series was to increase the zone of keratinized soft tissue around dental implants supporting overdentures. Three different surgical techniques modified palatal roll technique with and without apical positioning and connective tissue graft (CTG) were used to achieve this goal. There was a significant gain of keratinized soft tissue with all the three techniques, which remained stable over a period of 6 months. Modified palatal roll technique with and without apical positioning and CTG are simpler surgical techniques, which can be successfully and predictably used for increasing the zone of keratinized tissue around implants.
Improved image denoising method based on Curvelet transform

An improved image denoising method based on Curvelet transform is proposed in this article. Considering characteristic of Wavelet transform and traditional Curvelet transform, this method divides image up via window neighbourhood processing. It fuses two denoising images based Wavelet and Curvelet transform according to segmentation information and obtains higher quality and better effect image. Experiments show that with noise variance, the method in this paper can not only obtain higher PSNR but also keep more edge details. And it reduces “nick” and “ring” of restoration images.
Optical Emission Spectroscopy of Plasma Formation in a Xenon Theta-Pinch

Analyses of xenon spectral emission data in the IR range from excited neutral xenon transitions and estimations of electron temperature are performed on a theta-pinch test article. Estimations are based on a collisional-radiative model originally written for Hall-effect thrusters utilizing apparent collisional cross-sections. Tests performed on a pulsed xenon plasma at an energy of 80 J, neutral back-fill pressures of 10-100 mtorr, and vacuum discharge frequency of 462 kHz yield time-averaged electron temperatures of 6.4-11.2 eV for spectra integrated over the entire 20 μs. Time-resolved Te estimations are done using charge coupled device gate widths of 0.25 μs and yield estimates of up to 68 eV during peak spectral activity. Results show that back-fill pressures of 30 and 50 mtorr appear to generate plasma earlier and remain cooler than 10 and 100 mtorr. Poor signal-to-noise ratios produce substantial fluctuation in time-resolved intensities and thus estimation errors, while not quantified here, are assumed high for the time-resolved studies. Additionally, spectra acquired in the UV band verify: 1) the presence of second-order diffraction in the near-IR band from singly ionized xenon transitions and 2) the absence of air (contaminant) spectra.
Noise Injection Techniques to Expose Subtle and Unintended Message Races

Debugging intermittently occurring bugs within MPI applications is challenging, and message races, a condition in which two or more sends race to match with a receive, are one of the common root causes. Many debugging tools have been proposed to help programmers resolve them, but their runtime interference perturbs the timing such that subtle races often cannot be reproduced with debugging tools. We present novel noise injection techniques to expose message races even under a tool's control. We first formalize this race problem in the context of non-deterministic parallel applications and use this analysis to determine an effective noise-injection strategy to uncover them. We codified these techniques in NINJA (Noise INJection Agent) that exposes these races without modification to the application. Our evaluations on synthetic cases as well as a real-world bug in Hypre-2.10. 1 show that NINJA significantly helps expose races.
Language Impairment and Working Memory

In recent years, there has been much interest in the cognitive profile of children who have what has been termed specific language impairment (SLI), developmental language impairment (DLI), or primary language impairment (PLI). These children fail to make adequate progress in language development (phonology, vocabulary, grammar, morphology) despite the absence of underlying intellectual, neurological, social, or emotional impairment (e.g., Leonard, 2014). Use of the term specific language impairment is being discouraged, because research is showing that language impairment is rarely specific or an isolated deficit. In this article, the authors use the term developmental language impairment. Children with DLI can have very different language profiles (e.g., phonology, syntax, receptive/expressive language skills) that may change with age and development. The role of nonlinguistic factors in DLI has been of increasing interest, and this is reflected in emerging evidence that working memory (WM) difficulties are important for many of these children, alongside their structural language deficits. This approach to consider wider factors has affected theoretical ideas regarding DLI stances (Botting & Marshall, 2017), the diagnostic descriptions of children with language impairment (Bishop, 2014; Reilly et al., 2014), and the types of intervention evidence that is available (Holmes et al., 2015; Wener & Archibald, 2011). The authors of this article review the current state of knowledge regarding WM and DLI.
Equivalency of fecal immunochemical tests and colonoscopy in familial colorectal cancer screening.

BACKGROUND & AIMS Colonoscopy is the recommended screening procedure for first-degree relatives of patients with colorectal cancer (CRC), but few studies have compared its efficacy for CRC detection with that of other screening strategies. We conducted a controlled randomized trial to compare the efficacy of repeated fecal immunochemical tests (FITs) and colonoscopy in detecting advanced neoplasia (advanced adenoma or CRC) in family members of patients with CRC. METHODS In a prospective study, 1918 first-degree relatives of patients with CRC were randomly assigned (1:1 ratio) to receive a single colonoscopy examination or 3 FITs (1/year for 3 years; OC-Sensor; cutoff ≥10 μg hemoglobin/g feces, corresponding to 50 ng hemoglobin/mL buffer). The strategies were considered to be equivalent if the 95% confidence interval of the difference for the detection of advanced neoplasia was ±3%. Follow-up analyses were performed to identify false-negative FIT results and interval CRCs. RESULTS Of all eligible asymptomatic first-degree relatives, 782 were included in the colonoscopy group and 784 in the FIT group. In the intention-to-screen analysis, advanced neoplasia was detected in 33 (4.2%) and 44 (5.6%) first-degree relatives in the FIT and colonoscopy groups, respectively (odds ratio = 1.41; 95% confidence interval: 0.88-2.26; P = .14). In the per-protocol analysis, 28 first-degree relatives (3.9%) in the FIT group and 43 (5.8%) in the colonoscopy group had advanced neoplasia (odds ratio = 1.56; 95% confidence interval: 0.95-2.56; P = .08). FIT missed 16 of 41 advanced adenomas but no CRCs. The FIT strategy required endoscopic evaluation of 4-fold fewer individuals to detect 1 advanced neoplasia than the colonoscopy strategy. CONCLUSIONS Repeated FIT screening (1/year for 3 years) detected all CRCs and proved equivalent to colonoscopy in detecting advanced neoplasia in first-degree relatives of patients with CRC. This strategy should be considered for populations where compliance with FITs is higher than with colonoscopy. ClinicalTrials.gov number: NCT01075633 (COLONFAM Study).
Enhanced Attribute-Based Proxy Re-Encryption for Home Network

This paper studies security on home network to apply access control and encryption. It is difficult to implement and run a database server for access control as individual. For both access control and encryption, home network employs a series of Attribute-Based Encryption (ABE) schemes. In a string of the encryption schemes, we apply Attribute-Based Proxy Re-Encryption (ABPRE) to the network. In our scheme, authenticated people can encrypt all the data, control access to the data and temporarily delegate their permission to another they trust implicitly. A framework we propose for the security of the network use a ticket, an arbitrary bit sequence, to protect a key to decrypt the data and to decide whether the people have been fully allowed by home gateway or authorized people. The members of the family can obtain the ticket by decrypting security message in home gateway or delegate it by re-encrypting the ticket. Periodically updated by the gateway, the ticket would be automatically expired. The representative can search and control the data by using the delegated ticket up to when the ticket is valid.