Miracle-dz/UniFAR-FTUs huggingface dataset:
QualityRank: assessing quality of wikipedia articles by mutually evaluating editors and texts

In this paper, we propose a method to identify high-quality Wikipedia articles by mutually evaluating editors and texts. A major approach for assessing articles using edit history is a text survival ratio based approach. However, the problem is that many high-quality articles are identified as low quality, because many vandals delete high-quality texts, then the survival ratios of high-quality texts are decreased by vandals. Our approach's strongest point is its resistance to vandalism. Using our method, if we calculate text quality values using editor quality values, vandals do not affect any quality values of the other editors, then the accuracy of text quality values should improve. However, the problem is that editor quality values are calculated by text quality values, and text quality values are calculated by editor quality values. To solve this problem, we mutually calculate editor and text quality values until they converge. Using this method, we can calculate a quality value of a text that takes into consideration that of its editors.
EEG-based microsleep detector using microcontroller

Drowsiness has symptoms which are itchy eyes, slow eye blink movement, smaller pupils, yawning and even trembling body. But the driver ignores it when the body send one of those signals often. The impacts which can occur to the driver, such as make incorrect decision while driving, could happen and lead to the most car accident reason. Therefore, the system which can provide an alarm when the driver feels drowsiness, fatigue or even microsleep is required. The way to detect microsleep when it occurs is to use the Electroencephalograph (EEG) brainwave. The system uses the one channel EEG Sensor device developed by Neurosky Mindwave which can provide eight brainwave signal such as Delta, Theta, Low Alpha, High Alpha, Low Beta, High Beta, Low Gamma, and Mid Gamma. On the other hand, attention and relaxation value can be generated as well. This prototype system tested by the car driver achieved its purpose of detecting microsleep event and alerting the driver by the alarm.
A Novel Particle Swarm Optimization-based Algorithm for the Optimal Centralized Wireless Access Network

The wireless access networks design problem is formulated as a constrained optimization problem, where the goal is to find a network topology such that an objective function is optimized, subject to a set of constraints. The objective function may be the total cost, or some performance measure like utilization, call blocking or throughput. The constraints may be bounds on link capacities, cost elements, or some network performance measure. However, the optimization problem is too complex. In this paper, we propose a novel Particle Swarm Optimization (PSO) algorithm to finding the total cost of connecting the BSs to the MSCs, and connecting the MSCs to the LE called by the optimal centralized wireless access network. Numerical results show that performance of our proposed algorithm is much better than previous studies.
Multispectral demosaicking using adaptive kernel upsampling

Multispectral demosaicking, which estimates full multispectral images from raw data observed using a single image sensor with a color filter array (CFA), is a challenging task because each spectral component is severely undersampled. In this paper, we propose a novel multispectral demosaicking algorithm. We extend existing upsampling algorithms to adaptive kernel upsampling algorithms using an adaptive kernel as a spatial weight and apply them to multispectral demosaicking. We also propose a new CFA and a direct adaptive kernel estimation from the raw data of the proposed CFA. Experimental results with real multispectral images demonstrate the effectiveness of the proposed algorithm.
Multi-Histogram Equalization Methods for Contrast Enhancement and Brightness Preserving

Histogram equalization (HE) has proved to be a simple and effective image contrast enhancement technique. However, it tends to change the mean brightness of the image to the middle level of the gray-level range, which is not desirable in the case of images from consumer electronics products. In the latter case, preserving the input brightness of the image is required to avoid the generation of non-existing artifacts in the output image. To surmount this drawback, Bi- HE methods for brightness preserving and contrast enhancement have been proposed. Although these methods preserve the input brightness on the output image with a significant contrast enhancement, they may produce images with do not look as natural as the input ones. In order to overcome this drawback, this work proposes a novel technique called Multi-HE, which consists of decomposing the input image into several sub-images, and then applying the classical HE process to each one. This methodology performs a less intensive image contrast enhancement, in a way that the output image presents a more natural look. We propose two discrepancy functions for image decomposing, conceiving two new Multi-HE methods. A cost function is also used for automatically deciding in how many sub-images the input image will be decomposed on. Experiments show that our methods preserve more the brightness and produce more natural looking images than the other HE methods.
Theory and practice of I/O-efficient algorithms for multidimensional batched searching problems

We describe a powerful framework for designing efficient batch algorithms for certain large-scale dynamic problems that must be solved using external memory. The class of problems we consider, which we call colorable eztemaldecomposable problems, include rectangle intersection, orthogonal line segment intersection, range searching, and point location. We are particularly interested in these problems in two and higher dimensions. They have numerous applications in geographic information systems (GIS), spatial databases, and VLSI and CAD design. We present simplied algorithms for problems previously solved by more complicated approaches (such as rectangle intersection), and we present efficient algorithms for problems not previously solved in an efficient way (such as point location and higherdimensional versions of range searching and rectangle intersection). communication is the bottleneck in many large-scale applications such as those arising in VLSI and CAD design, spatial databases, and geographic information systems (GIS). In this paper we consider I/O-efficient algorithms for batched searching problems. We consider both batched static and batched dynamic problems, and use the correspondence which often exists between a ddimensional static problem and a (dl)-dimensional dynamic problem to obtain a number of new d-dimensional algorithms. We give experimental results concerning the running time for our approach applied to the red-blue rectangle intersection problem, which is a key component of the extremely important database operation spatial join. Our algorithm scales well with the problem size, and for large problems sizes it greatly outperforms the well-known sweepline approach. One prominent example of the problems we consider is the rectangle intersection problem, which is a key component in VLSI design rule checking [31] and in the extremely important database operation spatial join [34]. We illustrate the practical significance of our algorithms by comparing the empirical performance of our algorithm for this problem with the well-known sweepline algorithm developed for internal memory. 1.1 Problem definition and memory model
Clonal Analysis of Bilateral Breast Cancer1

Forty-nine pairs of bilateral breast tumors (41 synchronous and 8 asynchronous cases) were examined for X-chro-mosome inactivation status andp53 mutations to address the issue of their clonality. Among 12 cases that were informa-five for the trinucleotide repeat polymorphism in exon 1 of the androgen receptor gene on the X chromosome, 3 cases were found to have different alleles of the locus inactivated in the right and left breast tumors, indicating that the two tumors arose from distinct transformed cells. Thirteen tumors (13%) from 11 women (22%) contained somatic mutations in exons 5-8 of the p5.3 gene. In two cases, both breast tumors harbored p53 mutations, but the specific mutations were not identical. Seven synchronous and two asynchronous cases had p53 mutations in one tumor only. A germ line p53 mutation at codon 248, one of the most common p53 mutations in Li-Fraumeni syndrome, was observed in one case. Immunohistochemical analysis of p53 protein with a monoclonal antihuman p53 antibody showed concordant positivity between the right and left tumors in three bilateral breast cancer cases. Our results suggest that at least some bilateral breast tumors originate from distinct cells, but that some bilateral breast tumors may he related through a common p5.3 abnormality.
A Feature Extraction Method for Recognition of Petechia Dot in Tongue Image

Petechia Dot ranks itself among the most significant pathological features utilized in the practice of the Tongue Diagnosis because it can reveal the existence of tiny hemorrhage in some organ inside the body. In this paper, a feature extraction method aiming for recognition of the Petechia Dot in tongue image is proposed employing graylevel-height based thresholding, Top-hat high-pass filtering, and Gaussian histogram specification. Graylevel contrast-stretch and morphological filters are designed as preprocessing method to make Petechia Dot more apparent. Finally, algorithm erasing falsely selected pixel is presented to avoid misjudgment with help of region growing and Hit-or-Miss transform. Experiments to test correctness of these methods are carried out, and result is proved to be satisfactory.
Category: Genetic Algorithms Interactive Genetic Algorithms for the Traveling Salesman Problem

We use an interactive genetic algorithm to divide and conquer large traveling salesper-son problems. Current genetic algorithm approaches are computationally intensive and may not produce acceptable tours within the time available. Instead of applying a genetic algorithm to the entire problem, we let the user interactively decompose a problem into subproblems, let the genetic algorithm separately solve these subproblems and then interactively connect subproblem solutions to get a global tour for the original problem. Our approach signiicantly reduces the computing time to nd high quality solutions for large traveling salesperson problems. We believe that an interactive approach can be extended to other visually decomposable problems .
Quantum Probability in Operant Conditioning - Behavioral Uncertainty in Reinforcement Learning

An implicit assumption in the study of operant conditioning and reinforcement learning is that behavior is stochastic, in that it depends on the probability that an outcome follows a response and on how the presence or absence of the output affects the frequency of the response. In this paper we argue that classical probability is not the right tool to represent uncertainty operant conditioning and propose an interpretation of behavioral states in terms of quantum probability instead.
A Modern Cohort of Duodenal Obstruction Patients: Predictors of Delayed Transition to Full Enteral Nutrition

Background. A common site for neonatal intestinal obstruction is the duodenum. Delayed establishment of enteral nutritional autonomy continues to challenge surgeons and, since early institution of nutritional support is critical in postoperative newborns, identification of patients likely to require alternative nutritional support may improve their outcomes. Therefore, we aimed to investigate risk factors leading to delayed establishment of full enteral nutrition in these patients. Methods. 87 patients who were surgically treated for intrinsic duodenal obstructions from 1998 to 2012 were reviewed. Variables were tested as potential risk factors. Median time to full enteral nutrition was estimated using the Kaplan-Meier method. Independent risk factors of delayed transition were identified using the multivariate Cox proportional hazards regression model. Results. Median time to transition to full enteral nutrition was 12 days (interquartile range: 9–17 days). Multivariate Cox analysis identified three significant risk factors for delayed enteral nutrition: gestational age (GA) ≤ 35 weeks (P < .001), congenital heart disease (CHD) (P = .02), and malrotation (P = .03). Conclusions. CHD and Prematurity are most commonly associated with delayed transition to full enteral nutrition. Thus, in these patients, supportive nutrition should strongly be considered pending enteral nutritional autonomy.
32 Intuitive Multimodal Interaction with Communication Robot

One of the most important motivations for many humanoid robot projects is that robots with a human-like body and human-like senses could in principle be capable of intuitive multimodal communication with people. The general idea is that by mimicking the way humans interact with each other, it will be possible to transfer the efficient and robust communication strategies that humans use in their interactions to the man-machine interface. This includes the use of multiple modalities, such as speech, facial expressions, gestures, body language, etc. If successful, this approach yields a user interface that leverages the evolution of human communication and that is intuitive to naïve users, as they have practiced it since early childhood. We work towards intuitive multimodal communication in the domain of a museum guide robot. This application requires interacting with multiple unknown persons. The testing of communication robots in science museums and on science fairs is popular, because the robots encounter there many new interaction partners, which have a general interest in science and technology. Here, we present the humanoid communication robot Fritz that we developed as successor to the communication robot Alpha (Bennewitz et al., 2005). Fritz uses speech, facial expressions, eye-gaze, and gestures to interact with people. Depending on the audio-visual input, our robot shifts its attention between different persons in order to involve them into an interaction. He performs human-like arm gestures during the conversation and also uses pointing gestures generated with eyes, its head, and arms to direct the attention of its communication partners towards the explained exhibits. To express its emotional state, the robot generates facial expressions and adapts the speech synthesis. The remainder of the chapter is organized as follows. The next section reviews some of the related work. The mechanical and electrical design of Fritz is covered in Sec. 3. Sec. 4 details the perception of the human communication partners. Sec. 5 explains the robot's attentional system. The generation of arm gestures and of facial expressions is presented in Sec. 6 and 7, respectively. Finally, in the experimental section, we discuss experiences made during public demonstrations of our robot.
Characterization of α1(IV) Collagen Mutations in Caenorhabditis elegans and the Effects of α1 and α2(IV) Mutations on Type IV Collagen Distribution

Type IV collagen is a major component of basement membranes. We have characterized 11 mutations in emb-9, the α1(IV) collagen gene of Caenorhabditis elegans, that result in a spectrum of phenotypes. Five are substitutions of glycines in the Gly-X-Y domain and cause semidominant, temperature-sensitive lethality at the twofold stage of embryogenesis. One is a glycine substitution that causes recessive, non–temperature-sensitive larval lethality. Three putative null alleles, two nonsense mutations and a deletion, all cause recessive, non–temperature-sensitive lethality at the threefold stage of embryogenesis. The less severe null phenotype indicates that glycine substitution containing mutant chains dominantly interfere with the function of other molecules. The emb-9 null mutants do not stain with anti–EMB-9 antisera and show intracellular accumulation of the α2(IV) chain, LET-2, indicating that LET-2 assembly and/or secretion requires EMB-9. Glycine substitutions in either EMB-9 or LET-2 cause intracellular accumulation of both chains. The degree of intracellular accumulation differs depending on the allele and temperature and correlates with the severity of the phenotype. Temperature sensitivity appears to result from reduced assembly/secretion of type IV collagen, not defective function in the basement membrane. Because the dominant interference of glycine substitution mutations is maximal when type IV collagen secretion is totally blocked, this interference appears to occur intracellularly, rather than in the basement membrane. We suggest that the nature of dominant interference caused by mutations in type IV collagen is different than that caused by mutations in fibrillar collagens.
Asymptotics of a quantum random walk driven by an optical cavity

We investigate a novel quantum random walk (QRW) model, of possible use in quantum algorithm implementation, that achieves a quadratically faster diffusion rate compared to its classical counterpart. We evaluate its asymptotic behaviour expressed in the form of a limit probability distribution of a double-horn shape. Questions of robustness and control of that limit distribution are addressed by introducing a quantum optical cavity in which a resonant Jaynes–Cummings type of interaction between the quantum walk coin system realized in the form of a two-level atom and a laser field is taking place. Driving the optical cavity by means of the coin–field interaction time and the initial quantum coin state, we determine two types of modification of the asymptotic behaviour of the QRW. In the first one the limit distribution is robustly reproduced up to a scaling, while in the second one the quantum features of the walk, exemplified by an enhanced diffusion rate, are washed out and Gaussian asymptotics prevail. Verification of these findings in an experimental set-up that involves two quantum optical cavities that implement the driven QRW and its quantum to classical transition is discussed.
Human activity recognition based on the blob features

In this paper, we present a novel approach for human activities recognition in the video. We analyze human activities in the sequential frames because human activities can be considered as a temporal object which contains a series of frames. Firstly, we establish a statistical background model and extract foreground object through background subtraction in the video stream. Then, we use foreground blobs of the current frame and a series of frames before the current frame to form a new feature image in certain rules. Finally, we combine the non-zero pixels in the feature image into blobs using the connected component method. Then each blob corresponds to an activity which is characterized by the blob appearance. By recognizing blob features we can recognize activities. We use Gaussian Mixture to model features for each type of human activities and employ Mahalanobis distance to measure the similarity.
HRED: a simple and efficient active queue management algorithm

Active queue management (AQM) is an area of critical importance for the operation of networks. In this paper, we propose a minimal adjustment to the classic random early detection (RED) algorithm, called hyperbola RED (HRED), that uses the hyperbola as the drop probability curve. The control law of HRED can regulate the queue size close to the reference queue size which is settable by the user. As a result, it is expected that HRED is no longer sensitive to the level of network load, its behavior shows low dependence on the parameter settings, and it can achieve higher network utilization. Additionally, very little work needs to be done to migrate from RED to HRED on Internet routers because only the drop profile is adjusted. We implemented HRED on a real Internet router to examine and compare its performance with the classic RED and parabola RED that are currently deployed on Internet routers. From experiments on the real network, we conclude that HRED is insensitive to the network conditions and parameter settings, and can achieve higher network utilization than the other RED schemes
Heuristic for resources allocation on utility computing infrastructures

The use of utility on-demand computing infrastructures, such as Amazon's Elastic Clouds [1], is a viable solution to speed lengthy parallel computing problems to those without access to other cluster or grid infrastructures. With a suitable middleware, bag-of-tasks problems could be easily deployed over a pool of virtual computers created on such infrastructures. In bag-of-tasks problems, as there is no communication between tasks, the number of concurrent tasks is allowed to vary over time. In a utility computing infrastructure, if too many virtual computers are created, the speedups are high but may not be cost effective; if too few computers are created, the cost is low but speedups fall below expectations. Without previous knowledge of the processing time of each task, it is difficult to determine how many machines should be created. In this paper, we present an heuristic to optimize the number of machines that should be allocated to process tasks so that for a given budget the speedups are maximal. We have simulated the proposed heuristics against real and theoretical workloads and evaluated the ratios between number of allocated hosts, charged times, speedups and processing times. With the proposed heuristics, it is possible to obtain speedups in line with the number of allocated computers, while being charged approximately the same predefined budget.
Dirichlet Process with Mixed Random Measures: A Nonparametric Topic Model for Labeled Data

We describe a nonparametric topic model for labeled data. The model uses a mixture of random measures (MRM) as a base distribution of the Dirichlet process (DP) of the HDP framework, so we call it the DP-MRM. To model labeled data, we define a DP distributed random measure for each label, and the resulting model generates an unbounded number of topics for each label. We apply DP-MRM on single-labeled and multi-labeled corpora of documents and compare the performance on label prediction with MedLDA, LDA-SVM, and Labeled-LDA. We further enhance the model by incorporating ddCRP and modeling multi-labeled images for image segmentation and object labeling, comparing the performance with nCuts and rddCRP.
Distributed under Creative Commons Cc-by 4.0 the Oral Microbiome of Patients with Axial Spondyloarthritis Compared to Healthy Individuals

Background. A loss of mucosal tolerance to the resident microbiome has been postulated in the aetiopathogenesis of spondyloarthritis, thus the purpose of these studies was to investigate microbial communities that colonise the oral cavity of patients with axial spondyloarthritis (AxSpA) and to compare these with microbial profiles of a matched healthy population. Methods. Thirty-nine participants, 17 patients with AxSpA and 22 age and gender-matched disease-free controls were recruited to the study. For patients with AxSpA, disease activity was assessed using the Bath Ankylosing Spondylitis Disease Activity Index (BASDAI). All participants underwent a detailed dental examination to assess oral health, including the presence of periodontal disease assessed using probing pocket depth (PPD). Plaque samples were obtained and their bacterial populations were profiled using Ion Torrent sequencing of the V6 region of the 16S rRNA gene. Results. Patients with AxSpA had active disease (BASDAI 4.1 ± 2.1 [mean ± SD]), and a significantly greater prevalence of periodontitis (PPD ≥ 4 mm at ≥4 sites) than controls. Bacterial communities did not differ between the two groups with multiple metrics of α and β diversity considered. Analysis of operational taxonomic units (OTUs) and