Miracle-dz/UniFAR-FTUs huggingface dataset:
GraphLab: A Distributed Framework for Machine Learning in the Cloud

Machine Learning (ML) techniques are indispensable in a wide range of fields. Unfortunately, the exponential increase of dataset sizes are rapidly extending the runtime of sequential algorithms and threatening to slow future progress in ML. With the promise of affordable large-scale parallel computing, Cloud systems offer a viable platform to resolve the computational challenges in ML. However, designing and implementing efficient, provably correct distributed ML algorithms is often prohibitively challenging. To enable ML researchers to easily and efficiently use parallel systems, we introduced the GraphLab abstraction which is designed to represent the computational patterns in ML algorithms while permitting efficient parallel and distributed implementations. In this paper we provide a formal description of the GraphLab parallel abstraction and present an efficient distributed implementation. We conduct a comprehensive evaluation of GraphLab on three state-of-the-art ML algorithms using real large-scale data and a 64 node EC2 cluster of 512 processors. We find that GraphLab achieves orders of magnitude performance gains over Hadoop while performing comparably or superior to hand-tuned MPI implementations.
Involvement of an “Antizyme’ in the Inactivation of Ornithine Decarboxylase

Abstract: DL‐Allylglycine causes a marked increase in mouse brain ornithine decarboxylase (ODC) activity. The amount of immunoreactive enzyme protein increases concomitantly with the activity, but the enzyme protein decreases more slowly than that of the activity. The amount of immunoreactive ODC in brain is many hundred times that of the catalytically active enzyme. The fact that mouse brain cytosol contains high amounts of dissociable antizyme (an inactivating protein) indicates the existence of an inactive, immunoreactive ODC‐antizyme pool. The total antizyme content does not change markedly, but instead there are significant changes in different antizyme pools. Putrescine concentrations start to increase 8 h after treatment with allylglycine and concomitantly with this increase, antizyme is released to inhibit enzyme activity. These results indicate the involvement of antizyme in the inactivation process of ODC.
Sensor Localization and Camera Calibration in Distributed Camera Sensor Networks

Camera sensors constitute an information rich sensing modality with many potential applications in sensor networks. Their effectiveness in a sensor network setting however greatly relies on their ability to calibrate with respect to each other, and other sensors in the field. This paper examines node localization and camera calibration using the shared field of view of camera pairs. Using a new distributed camera sensor network we compare two approaches from computer vision and propose an algorithm that combines a sparse set of distance measurements with image information to accurately localize nodes in 3D. Our algorithms are evaluated using a network of iMote2 nodes equipped with COTS camera modules. The sensor nodes identify themselves to cameras using modulated LED emissions. Our indoor experiments yielded a 2-7cm error in a 6x6m room. Our outdoor experiments in a 30x30m field resulted in errors 20-80cm, depending on the method used.
STUDY OF MUTUAL INFORMATION IN PERCEPTUAL CODING WITH APPLICATION FOR LOW BIT-RATE COMPRESSION

In this paper we analyze this aspect of redundancy reduc- tion as it appears in MPEG1-Layer 1 codec. Specifically, we consider the mutual information that exists between fil- ter bank coefficients and show that the normalization opera- tion indeed reduces the amount of dependency between the various channels. Next, the effect of masking normalization is considered in terms of its compression performance and is compared to linear, reduced rank short term ICA analysis. Specifically we show that a local linear ICA representation outperforms the traditional compression at low bit rates. A comparison of MPEG1 Layer 1 and a new ICA based au- dio compression method are reported in the paper. Certain aspects of ICA quantization and its applicability for low- bitrate compression are discussed. Specifically, we measure the amount of Mutual Information (MI) between the different filter bank subbands on a natu- ral sound. We show that the psychoacoustic model indeed helps remove some redundancies between the coefficients. Next, we use the idea of minimization of MI in order to de- sign a new architecture for a low bit-rate audio coder. One of the open research questions regarding ICA is whether it can be used for data compression. It is well known that PCA is optimal for data reduction in terms of reconstruc- tion error. Further more if the source is gaussian then opti- mal bit allocation can be achieved by using PCA. However, for non-gaussian variables where PCA is not optimal, ICA might give better resultsSpecifically, we consider the ques- tion of low bit-rate quantization using a combined PCA and low rank ICA representation. In our method of low bit-rate quantization we use a com- bined PCA and low rank ICA representation. This achieves several advantages for the compression task: 1). Coarse first step quantization by rank reduction gives a lower over- all error compared to low bit-rate quantization of the com- plete set of coefficients. 2) The reduced rank representa- tion is very sparse and allows an adaptive transmission of the transform coefficients without increasing the overall bi- trate. 3). The bit allocation is performed on approximately independent channels, a situation which is required by rate- distortion theory. It should be noted that no psychoacoustic model is employed since the ICA vectors do not correspond to the masking properties of the human ear. The superior performance of our method suggests that the the classical psychoacoustical masking of pure tones could be a special case of a more general redundancy reduction mechanism of the auditory pathway (3).
Identifying associations between smartphone usage and mental health during depression, anxiety and stress

Reality mining in behavioral studies is one of the highly researched topics in computational science. The reason behind this great deal of experimentation is the particularly dynamic and potentially latent nature of human behavior. In this work, we have showcased our efforts in analyzing the associations between the smartphone usage and the mental state of the person during depression, stress and anxiety. We have particularly focused on descriptive modeling of data using multiple linear regression to find correlations between the passive smartphone data stream and the user filled survey. Finally we estimate the predictive capability and outline the major challenges of such a system.
A Modified Dual-Baseline PolInSAR Method for Forest Height Estimation

This paper investigates the potentials and limitations of a simple dual-baseline PolInSAR (DBPI) method for forest height inversion. This DBPI method follows the classical three-stage inversion method’s idea used in single baseline PolInSAR (SBPI) inversion, but it avoids the assumption of the smallest ground-to-volume amplitude ratio (GVR) by employing an additional baseline to constrain the inversion procedure. In this paper, we present for the first time an assessment of such a method on real PolInSAR data over boreal forest. Additionally, we propose an improvement on the original DBPI method by incorporating the sloped random volume over ground (S-RVoG) model in order to reduce the range terrain slope effect. Therefore, a digital elevation model (DEM) is needed to provide the slope information in the proposed method. Three scenes of P-band airborne PolInSAR data acquired by E-SAR and light detection and ranging (LIDAR) data available in the BioSAR2008 campaign are employed for testing purposes. The performance of the SBPI, DBPI, and modified DBPI methods is compared. The results show that the DBPI method extracts forest heights with an average root mean square error (RMSE) of 4.72 m against LIDAR heights for trees of 18 m height on average. It presents a significant improvement of forest height accuracy over the SBPI method (with a stand-level mean improvement of 42.86%). Concerning the modified DBPI method, it consistently improves the accuracy of forest height inversion over sloped areas. This improvement reaches a stand-level mean of 21.72% improvement (with a mean RMSE of 4.63 m) for slopes greater than 10°.
Management of bullous pemphigoid: the European Dermatology Forum consensus in collaboration with the European Academy of Dermatology and Venereology

Bullous pemphigoid is the most common autoimmune subepidermal blistering disease of the skin and mucous membranes. This disease typically affects the elderly and presents with itch and localized or generalized bullous lesions. In up to 20% of affected patients, bullae may be completely absent, and only excoriations, prurigo‐like lesions, eczematous lesions, urticated lesions and/or infiltrated plaques are observed. The disease is significantly associated with neurological disorders. The morbidity of bullous pemphigoid and its impact on quality of life are significant. So far, a limited number of national treatment guidelines have been proposed, but no common European consensus has emerged. Our consensus for the treatment of bullous pemphigoid has been developed under the guidance of the European Dermatology Forum in collaboration with the European Academy of Dermatology and Venereology. It summarizes evidence‐based and expert‐based recommendations.
DOES ONE SIZE FIT ALL? COST UTILITY ANALYSES OF ALTERNATIVE MAMMOGRAPHIC FOLLOW-UP SCHEDULES, BY RISK OF RECURRENCE

Objectives: International guidelines recommend annual mammography after early breast cancer, but there is no randomized controlled trial evidence to support this schedule over any other. Given that not all women have the same risk of recurrence, it is possible that, by defining different risk profiles, we could tailor mammographic schedules that are more effective and efficient. Methods: A discrete event simulation model was developed to describe the progression of early breast cancer after completion of primary treatment. Retrospective data for 1,100 postmenopausal women diagnosed with early breast cancer in South Australia from 2000 to 2008 were used to calibrate the model. Women were divided into four prognostic subgroups based on the Nottingham Prognostic Index of their primary tumor. For each subgroup, we compared the cost-effectiveness of three different mammographic schedules for two different age groups. Results: Annual mammographic follow-up was not cost-effective for most postmenopausal women. Two yearly mammography was cost-effective for all women with excellent prognosis tumors; and for women with good prognosis tumors if high compliance rates can be achieved. Annual mammography for 5 years and 2 yearly surveillance thereafter (a mixed schedule) may be cost-effective for 50- to 69-year-old women with moderate prognosis tumors, and for women aged 70–79 years with poor prognosis tumors. For younger women with poor prognosis tumors, annual mammography is potentially cost-effective. Conclusions: Our results suggest that mammographic follow-up could be tailored according to risk of recurrence. If validated with larger datasets, this could potentially set the stage for personalized mammographic follow-up after breast cancer.
Measuring of diffusion coefficient of liquids using Fresnel diffraction from phase step

۳522 تیاس رد هک تسا رابتعا یاراد یتروص رد هلاقم نیا www.opsi. ir . دشاب یسرتسد لباق هزادنا یزاف هلپ زا لنرف شارپ زا هدافتسا اب عیام رد عیام شخپ بیرض هشیش هغیت کی . تسا هدش یریگ ،یروبع یزاف هلپ ناونع هب یا یم رارق شخپ نزخم لخاد دریگ . رزیل یزاوم و مافکت هکیراب مویله – نوئن هغیت حطس رب دومع یم هدنابات دوش و لنرف شارپ هدش لیکشت هحفص رد ومع یا ر رب د ا شبات یاتس طسوت CCD یم تبث دوش . شخپ عورش زا سپ ، رییغت نامز اب نزخم لخاد تسکش بیرض عیزوت یم و دنک هلپ هبل زا هتفای شارپ تدش عیزوت رییغت ار یم هد . د ،هیروف لیدبت شور زا هدافتسا اب هیامن هجیتن رد و زاف هیامن تسکش بیرض اد یم تسدب نزخم لخ یم هبساحم شخپ بیرض و دیآ دوش .
A Field Theory Approach to Natural Language

Automatic text understanding is a complex task, best broken into several steps. One essential step is a parser that identiies dependencies between words of a sentence. Such a parser should take into account both syntactic and semantic evidence and should be easily tuned to new domains and new writing styles. We present a new parsing paradigm. Rather than treating words as passive objects of grammar rules, the eld theory parser views words as particles exerting forces of attraction towards other particles. This force is estimated by a statistical model that is indexed by syntactic and semantic features of the words involved. The parser achieves high performance from relatively small training sets. Information extraction (IE) systems that automatically identify selected facts from free text are are beginning to achieve high enough performance to be of practical use. IE systems are knowledge intensive and must be trained for each domain, however. One challenge facing IE is to develop eeective statistical or machine learning tools to avoid expensive knowledge engineering when adapting a system to a new domain or new writing genre. Another challenge is to move in the direction of full understanding of texts. Deep understanding of free text is too complex for a system to go immediately from the text to its meaning in one step. The problem is typically divided into several steps that include syntactic parsing, followed by semantic interpretation of the resulting parse graph. The parser presented here is part of an IE system for medical reports, which we are initially developing for the domain of radiology reports. These are free text narratives in which a physician describes ndings in a chest x-ray. The goal of our system is to extract all information from these reports about the medical ndings: their attributes and anatomical location, and the interpretation of the ndings. Figure 1 gives a sample sentence from a thoracic radiology report. The nding \mass" has attributes of The large mass within the posterior segments of the right upper lobe has increased in size. Figure 1: A sample sentence from a radiology report size, location, and clinical trend (\increased in size"). The parser identiies which words are modiiers of other words and produces a dependency graph. This is equivalent to a parse tree is which the head of each constituent is designated. Figure 2 shows the dependency graph for the sample sentence. A directed arc from word A …
combinFormation: a mixed-initiative system for representing collections as compositions of image and text surrogates

We develop combinFormation, a mixed-initiative system for representing collections as compositions of image and text surrogates. The system provides a set of direct manipulation facilities for forming, editing, organizing, and distributing collections as compositions. Additionally, to assist users in sifting through the vast expanse of potentially relevant information resources, the system also includes a generative agent that can proactively engage in processes of collecting information resources and forming image and text surrogates. A generative temporal visual composition agent develops the collection and its visual representation over time, enabling users to see more possibilities. To keep the user in control, we develop interactive techniques that enable the user to direct the agent. For evaluation, we conducted a field study in an undergraduate general education course offered in the architecture department. Alternating groups of students used combinFormation as an aid in preparing one of two major assignments involving information discovery to support processes of invention. The students that used combinFormation were found to perform better
A real-time background subtraction method with camera motion compensation

Background subtraction algorithms are critical to many video recognition/analysis systems and have been studied for decades. Most of the algorithms assume that the camera is fixed. We propose a background subtraction algorithm that works when a shaking camera is present. In this algorithm, the input frames are compensated and compared with the given reference frame to separate foreground objects from the background. Experimental results show that the proposed method outperforms the widely used Gaussian mixture model based method in both fixed camera and shaking camera scenarios with respect to accuracy, robustness, and efficiency.
[Research on differential genes related with qi stagnation constitution].

OBJECTIVE To investigate the differential genes between the qi-stagnation constitution (QSC) and non-QSC, for the sake of disclose the hereditary essence of QSC. METHODS The constitution of 3 patients was judged as QSC by criteria for QSC and that of 2 patients was determined as non-QSC by experts according to the gentle constitution related treatise. The differential genes between them were studied using the mRNA differential display revers transcription polymerase chain reaction (DD-RT-PCR). RESULTS Some differential genes were found (part of them not found in non-QSC, and part was highly expressed in QSC). Among the differential genes, homology was shown between plexin A2-human chromosomal 1q32 (in 98%), notch pre-proteinogen-chromosomal 1q11 (98%), nuclear prelamin A-chromosomal 17q25 (100%), T-cell receptor delta chain-chromosomal 1q24 (99%), neuronal PAS domain protein 3-chromosomal 14q13 (98%), S-phase kinase-associated protein 2-chromosomal 5p12 (99%). CONCLUSIONS Some differential genes may be existed between QSC and non-QSC.
On the utility of sixth-order cyclic cumulants for RF signal classification

Several researchers have recently proposed the use of higher-order cumulants as features for automatic communication-signal classification. Cumulants can be associated with a stationary signal model or with a cyclostationary signal model, in which case they are periodically time-varying with Fourier components called cyclic cumulants. These researchers limit the maximum order to four, and it is commonly believed that sixth- and higher-order cumulants provide no additional benefit due to their relatively large measurement-error variance. However, we have observed experimentally that classification performance can be improved by the use of sixth-order cyclic cumulants. In this paper, we present the results of a simulation study of the cumulant variance for signals corrupted by cochannel interference and AWGN. Situations in which the use of sixth-order cumulants provides a classification benefit are provided and the benefit is quantified.
Optimization of Complex Systems with OptQuest

⎯ Optimization of complex systems has been for many years limited to problems that could be formulated as mathematical programming models of linear, nonlinear and integer types. Problemspecific heuristics that do not require a mathematical formulation of the problem have been also used for optimizing complex systems, however, they generally must be developed in a case-by-case basis. Recent research in the area of metaheuristics has placed the ambitious goal of building a general-purpose optimizer within reach. Specifically, population-based metaheuristics have made possible the development of general-purpose optimizers for which the solution process is context independent. Two of the best known population-based metaheuristics are genetic algorithms and scatter search. In this paper we described the implementation and functionality of OptQuest, a general-purpose optimizer that was developed using the scatter search methodology. We illustrate the system’s features with applications in stochastic, nonlinear and combinatorial optimization. 2 Optimization with OptQuest
Outcomes and patient satisfaction after presbyopic bilateral lens exchange with the ResTOR IOL in emmetropic patients.

PURPOSE To assess efficacy, safety, predictability, stability, and patient satisfaction after presbyopic lens exchange in emmetropic patients. METHODS A prospective, nonrandomized, masked, observational case series (self-controlled) of 46 emmetropic eyes of 23 consecutive patients (age range: 50 to 60 years) after presbyopic lens exchange with bilateral AcrySof ReSTOR Natural (SN60D3) intraocular lens (IOL) (Alcon Laboratories Inc) implantation were evaluated. Mean spherical equivalent refraction (SE) was -0.04±0.14 diopters (D) (range: +0.25 to -0.25 D). Monocular and binocular uncorrected distance visual acuity (UDVA), corrected distance visual acuity (CDVA), uncorrected near visual acuity (UNVA), distance-corrected near visual acuity (DCNVA), and patient satisfaction were recorded preoperatively and 6 months after surgery. RESULTS At 6 months postoperative, efficacy index at distance was 1.00. No eye lost ≥2 lines of CDVA, 5 eyes lost 1 line, 24 eyes did not change after surgery, 14 eyes gained 1 line, and 3 eyes gained 2 lines of visual acuity. Safety index at distance was 1.03. All eyes had a manifest SE within ±0.50 D of emmetropia. Mean postoperative SE was +0.14±0.22 D (range: -0.25 to +0.37 D). No eye lost >2 lines of DCNVA, 1 eye lost 2 lines, 3 eyes lost 1 line, 34 eyes did not change after surgery, and 8 eyes gained 1 line of visual acuity. Uncorrected near visual acuity was 0.95±0.07. Safety and efficacy indexes at near were 1.01 and 1.03, respectively. A patient satisfaction questionnaire showed that patients had a high level of satisfaction after presbyopic lens exchange surgery. CONCLUSIONS Presbyopic lens exchange with implantation of the ReSTOR multifocal IOL in emmetropic eyes is an effective and safe procedure for presbyopia correction.
WEB Image Classification Based on the Fusion of Image and Text Classifiers

This paper presents a novel method for the classification of images that combines information extracted from the images and contextual information. The main hypothesis is that contextual information related to an image can contribute in the image classification process. First, independent classifiers are designed to deal with images and text. From the images color, shape and texture features are extracted. These features are used with a neural network (NN) classifier to carry out image classification. On the other hand, contextual information is processed and used with a Naive Bayes (NB) classifier. At the end, the outputs of both classifiers are combined through heuristic rules. Experimental results on a database of more than 5,000 HTML documents have shown that the combination of classifiers provides a meaningful improvement (about 16%) in the correct image classification rate relative to the results provided by the NN classifier alone.