snu-aidas/HVMap-dataset huggingface dataset:
Using Spoken Language Benchmarks to Characterize the Expressive Language Skills of Young Children With Autism Spectrum Disorders.

PURPOSE
Spoken language benchmarks proposed by Tager-Flusberg et al. (2009) were used to characterize communication profiles of toddlers with autism spectrum disorders and to investigate if there were differences in variables hypothesized to influence language development at different benchmark levels.


METHOD
The communication abilities of a large sample of toddlers with autism spectrum disorders (N = 105) were characterized in terms of spoken language benchmarks. The toddlers were grouped according to these benchmarks to investigate whether there were differences in selected variables across benchmark groups at a mean age of 2.5 years.


RESULTS
The majority of children in the sample presented with uneven communication profiles with relative strengths in phonology and significant weaknesses in pragmatics. When children were grouped according to one expressive language domain, across-group differences were observed in response to joint attention and gestures but not cognition or restricted and repetitive behaviors.


CONCLUSION
The spoken language benchmarks are useful for characterizing early communication profiles and investigating features that influence expressive language growth.
Neuroticism as a mediator of treatment response to SSRIs in major depressive disorder.

BACKGROUND
Serotonin function has been implicated in both major depressive disorder and neuroticism. In the current investigation, we examined the hypothesis that any change in depression severity is mediated through the reduction of neuroticism, but only for those compounds which target serotonin receptors.


METHODS
Ninety-three outpatients in the midst of a major depressive episode received one of three antidepressant medications, classified into two broad types: selective serotonin reuptake inhibitors (SSRIs) and non-SSRIs (i.e. reversible monoamine oxidase inhibitors [RIMAs] and noradrenergic and dopaminergic reuptake blockers [NDMs]). Patients completed the Hamilton Rating Scale for Depression, Beck Depression Inventory II and Revised NEO Personality Inventory prior to and following approximately 16 weeks of treatment. Structural equation modeling was used to test two models: a mediation model, in which neuroticism change is the mechanism by which SSRIs exert a therapeutic effect upon depressive symptoms, and a complication model, in which neuroticism change is a mere epiphenomenon of depression reduction in response to SSRIs.


RESULTS
The mediation model provided a good fit to the data; the complication model did not. Patients treated with SSRIs demonstrated greater neuroticism change than those treated with non-SSRIs, and greater neuroticism change was associated with greater depressive symptom change. These effects held for both self-reported and clinician-rated depressive symptom severity.


LIMITATIONS
Replication within a randomized control trial with multiple assessment periods is required.


CONCLUSION
Neuroticism mediates changes in depression in response to treatment with SSRIs, such that any treatment effect of SSRIs occurs through neuroticism reduction.
Intrusion Detection System using K-means , PSO with SVM Classifier : A Survey

Intrusion detection is a process of identifying the Attacks. The main aim of IDS is to identify the Normal and Intrusive activities. In recent years, many researchers are using data mining techniques for building IDS. Here we propose a new approach using data mining technique such as SVM and Particle swarm optimization for attaining higher detection rate. The propose technique has major steps: Preprocessing, Training using PSO, clustering using K-means to generate different training subsets. Then based on the subsequent training subsets a vector for SVM classification is formed and in the end, classification using PSO is performed to detect Intrusion has happened or not. This paper contains summarization study and identification of the drawbacks of formerly surveyed works. Keywords-Intrusion detection system; Neuro-fuzzy; Support Vector Machine (SVM); PSO; K-means
The Zachman Framework and the OMG''s Model Driven Architecture

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Video summarisation: A conceptual framework and survey of the state of the art

Video summaries provide condensed and succinct representations of the content of a video stream through a combination of still images, video segments, graphical representations and textual descriptors. This paper presents a conceptual framework for video summarisation derived from the research literature and used as a means for surveying the research literature. The framework distinguishes between video summarisation techniques (the methods used to process content from a source video stream to achieve a summarisation of that stream) and video summaries (outputs of video summarisation techniques). Video summarisation techniques are considered within three broad categories: internal (analyse information sourced directly from the video stream), external (analyse information not sourced directly from the video stream) and hybrid (analyse a combination of internal and external information). Video summaries are considered as a function of the type of content they are derived from (object, event, perception or feature based) and the functionality offered to the user for their consumption (interactive or static, personalised or generic). It is argued that video summarisation would benefit from greater incorporation of external information, particularly user based information that is unobtrusively sourced, in order to overcome longstanding challenges such as the semantic gap and providing video summaries that have greater relevance to individual users. 2007 Elsevier Inc. All rights reserved.
PKLot - A robust dataset for parking lot classification

http://dx.doi.org/10.1016/j.eswa.2015.02.009 0957-4174/ 2015 Elsevier Ltd. All rights reserved. ⇑ Corresponding author. E-mail addresses: prlalmeida@inf.ufpr.br (P.R.L. de Almeida), lesoliveira@inf. ufpr.br (L.S. Oliveira), alceu@ppgia.pucpr.br (A.S. Britto Jr.), eunelson@ppgia.pucpr. br (E.J. Silva Jr.), alessandro.koerich@etsmtl.ca (A.L. Koerich). Paulo R.L. de Almeida , Luiz S. Oliveira , Alceu S. Britto Jr. b,⇑, Eunelson J. Silva Jr. b Alessandro L. Koerich b,c
Irregularities in the Distribution of Primes and Twin Primes By

The maxima and minima of sL(x)) — n(x), iR(x)) — n(x), and sL2(x)) — n2(x) in various intervals up to x = 8 x 10 are tabulated. Here n(x) and n2(x) are respectively the number of primes and twin primes not exceeding x, L(x) is the logarithmic integral, R(x) is Riemann's approximation to ir(x), and L2(x) is the Hardy-Littlewood approximation to ti"2(;c). The computation of the sum of inverses of twin primes less than 8 x 10 gives a probable value 1.9021604 ± 5 x 10~7 for Brun's constant. 1. Approximations to nix). Let P= {2, 3, 5, • • • } be the set of primes, and let 7r(x) be the number of primes not exceeding x. Two well-known approximations to 7t(x) for x > 1 are the logarithmic integral: rx dt (1.1) L{x) = \v ; J o log t O-2) =T + log(logx)+Í: ^> k=\ k-k and Riemann's approximation: (1.3) R{x)=Z^L{xi'k) k=i k (1.4) =1 + ¿Jtó_ fz. k\kl{k + 1) Note that (1.1) differs by 1(2) = 1.04516378... from the frequently used approximation f2 dt/log t. We are interested in the errors O-5) r.{x) = (L(x)> n{x) and (1 6) r2(x) = (Rix)) n{x), where <y> denotes the integer closest to y {i.e., the integer part of (y + W)). k Received July 5, 1974. AMS (MOS) subject classifications (1970). Primary 10-04, 10H25, 10H15; Secondary 10A25, 10A40, 10H05, 65A05, 65B05.
A faceted approach to conceptualizing tasks in information seeking

0306-4573/$ see front matter Published by Elsevi doi:10.1016/j.ipm.2008.07.005 * Corresponding author. Tel.: +1 601 266 4035; fa E-mail addresses: Yuelin.Li@usm.edu (Y. Li), nick 1 Tel.: +1 732 932 7500x8271; fax: +1 732 932 69 The nature of the task that leads a person to engage in information interaction, as well as of information seeking and searching tasks, have been shown to influence individuals’ information behavior. Classifying tasks in a domain has been viewed as a departure point of studies on the relationship between tasks and human information behavior. However, previous task classification schemes either classify tasks with respect to the requirements of specific studies or merely classify a certain category of task. Such approaches do not lead to a holistic picture of task since a task involves different aspects. Therefore, the present study aims to develop a faceted classification of task, which can incorporate work tasks and information search tasks into the same classification scheme and characterize tasks in such a way as to help people make predictions of information behavior. For this purpose, previous task classification schemes and their underlying facets are reviewed and discussed. Analysis identifies essential facets and categorizes them into Generic facets of task and Common attributes of task. Generic facets of task include Source of task, Task doer, Time, Action, Product, and Goal. Common attributes of task includes Task characteristics and User’s perception of task. Corresponding sub-facets and values are identified as well. In this fashion, a faceted classification of task is established which could be used to describe users’ work tasks and information search tasks. This faceted classification provides a framework to further explore the relationships among work tasks, search tasks, and interactive information retrieval and advance adaptive IR systems design. Published by Elsevier Ltd.
RCD: Rapid Close to Deadline Scheduling for datacenter networks

Datacenter-based Cloud Computing services provide a flexible, scalable and yet economical infrastructure to host online services such as multimedia streaming, email and bulk storage. Many such services perform geo-replication to provide necessary quality of service and reliability to users resulting in frequent large inter-datacenter transfers. In order to meet tenant service level agreements (SLAs), these transfers have to be completed prior to a deadline. In addition, WAN resources are quite scarce and costly, meaning they should be fully utilized. Several recently proposed schemes, such as B4 [1], TEMPUS [2], and SWAN [3] have focused on improving the utilization of inter-datacenter transfers through centralized scheduling, however, they fail to provide a mechanism to guarantee that admitted requests meet their deadlines. Also, in a recent study, authors propose Amoeba [4], a system that allows tenants to define deadlines and guarantees that the specified deadlines are met, however, to admit new traffic, the proposed system has to modify the allocation of already admitted transfers. In this paper, we propose Rapid Close to Deadline Scheduling (RCD), a close to deadline traffic allocation technique that is fast and efficient. Through simulations, we show that RCD is up to 15 times faster than Amoeba, provides high link utilization along with deadline guarantees, and is able to make quick decisions on whether a new request can be fully satisfied before its deadline.
Scheduling and locking in multiprocessor real-time operating systems

BJÖRN B. BRANDENBURG: Scheduling and Locking in Multiprocessor Real-Time Operating Systems (Under the direction of James H. Anderson) With the widespread adoption of multicore architectures, multiprocessors are now a standard deployment platform for (soft) real-time applications. This dissertation addresses two questions fundamental to the design of multicore-ready real-time operating systems: (1) Which scheduling policies offer the greatest flexibility in satisfying temporal constraints; and (2) which locking algorithms should be used to avoid unpredictable delays? With regard to Question 1, LITMUSRT, a real-time extension of the Linux kernel, is presented and its design is discussed in detail. Notably, LITMUSRT implements link-based scheduling, a novel approach to controlling blocking due to non-preemptive sections. Each implemented scheduler (22 configurations in total) is evaluated under consideration of overheads on a 24-core Intel Xeon platform. The experiments show that partitioned earliest-deadline first (EDF) scheduling is generally preferable in a hard real-time setting, whereas global and clustered EDF scheduling are effective in a soft real-time setting. With regard to Question 2, real-time locking protocols are required to ensure that the maximum delay due priority inversion can be bounded a priori. Several spinlockand semaphore-based multiprocessor real-time locking protocols for mutual exclusion (mutex), reader-writer (RW) exclusion, and k-exclusion are proposed and analyzed. A new category of RW locks suited to worst-case analysis, termed phase-fair locks, is proposed and three efficient phase-fair spinlock implementations are provided (one with few atomic operations, one with low space requirements, and one with constant RMR complexity). Maximum priority-inversion blocking is proposed as a natural complexity measure for semaphore protocols. It is shown that there are two classes of schedulability analysis, namely suspensionoblivious and suspension-aware analysis, that yield two different lower bounds on blocking. Five
Swing-up and stabilization of a cart-pendulum system under restricted cart track length

This paper describes the swing-up and stabilization of a cart–pendulum system with a restricted cart track length and restricted control force using generalized energy control methods. Starting from a pendant position, the pendulum is swung up to the upright unstable equilibrium con5guration using energy control principles. An “energy well” is built within the cart track to prevent the cart from going outside the limited length. When su9cient energy is acquired by the pendulum, it goes into a “cruise” mode when the acquired energy is maintained. Finally, when the pendulum is close to the upright con5guration, a stabilizing controller is activated around a linear zone about the upright con5guration. The proposed scheme has worked well both in simulation and a practical setup and the conditions for stability have been derived using the multiple Lyapunov functions approach. c © 2002 Elsevier Science B.V. All rights reserved.
Depression as a risk factor for coronary artery disease: evidence, mechanisms, and treatment.

OBJECTIVE
The present paper reviews the evidence that depression is a risk factor for the development and progression of coronary artery disease (CAD).


METHODS
MEDLINE searches and reviews of bibliographies were used to identify relevant articles. Articles were clustered by theme: depression as a risk factor, biobehavioral mechanisms, and treatment outcome studies.


RESULTS
Depression confers a relative risk between 1.5 and 2.0 for the onset of CAD in healthy individuals, whereas depression in patients with existing CAD confers a relative risk between 1.5 and 2.5 for cardiac morbidity and mortality. A number of plausible biobehavioral mechanisms linking depression and CAD have been identified, including treatment adherence, lifestyle factors, traditional risk factors, alterations in autonomic nervous system (ANS) and hypothalamic pituitary adrenal (HPA) axis functioning, platelet activation, and inflammation.


CONCLUSION
There is substantial evidence for a relationship between depression and adverse clinical outcomes. However, despite the availability of effective therapies for depression, there is a paucity of data to support the efficacy of these interventions to improve clinical outcomes for depressed CAD patients. Randomized clinical trials are needed to further evaluate the value of treating depression in CAD patients to improve survival and reduce morbidity.
Complete discrete 2-D Gabor transforms by neural networks for image analysis and compression

A three-layered neural network is described for transforming two-dimensional discrete signals into generalized nonorthogonal 2-D “Gabor” representations for image analysis, segmentation, and compression. These transforms are conjoint spat iahpectral representations [lo], [15], which provide a complete image description in terms of locally windowed 2-D spectral coordinates embedded within global 2-D spatial coordinates. Because intrinsic redundancies within images a re extracted, the resulting image codes can be very compact. However, these conjoint transforms are inherently difficult to compute because t e elementary expansion functions a re not orthogonal. One o r t h o g o n k i n g approach developed for 1-D signals by Bastiaans [SI, based on biorthonormal expansions, is restricted by constraints on the conjoint sampling rates and invariance of the windowing function, as well as by the fact that the auxiliary orthogonalizing functions are nonlocal infinite series. In the present “neural network” approach, based upon interlaminar interactions involving two layers with fixed weights and one layer with adjustable weights, the network finds coefficients for complete conjoint 2-D Gabor transforms without these restrictive conditions. For arbitrary noncomplete transforms, in which the coefficients might be interpreted simply as signifying the presence of certain features in the image, the network finds optimal coefficients in the sense of minimal mean-squared-error in representing the image. I n one algebraically complete scheme permitting exact reconstruction, the network finds expansion coefficients that reduce entropy from 7.57 in the pixel representation to 2.55 in the complete 2-D Gabor transform. In “wavelet” expansions based on a biologically inspired log-polar ensemble of dilations, rotations, and translations of a single underlying 2-D Gabor wavelet template, image compression is illustrated with ratios up to 20: 1. Also demonstrated is image segmentation based on the clustering of coefficients in the complete 2-D Gabor transform. This coefficient-finding network for implementing useful nonorthogonal image transforms may also have neuroscientific relevance, because the network layers with fixed weights use empirical 2-D receptive field profiles obtained from orientation-selective neurons in cat visual cortex as the weighting functions, and the resulting transform mimics the biological visual strategy of embedding angular and spectral analysis within global spatial coordinates.
Vicious and virtuous cycles in ERP implementation: a case study of interrelations between critical success factors

• A submitted manuscript is the author's version of the article upon submission and before peer-review. There can be important differences between the submitted version and the official published version of record. People interested in the research are advised to contact the author for the final version of the publication, or visit the DOI to the publisher's website. • The final author version and the galley proof are versions of the publication after peer review. • The final published version features the final layout of the paper including the volume, issue and page numbers.
Nivolumab in previously untreated melanoma without BRAF mutation.

BACKGROUND
Nivolumab was associated with higher rates of objective response than chemotherapy in a phase 3 study involving patients with ipilimumab-refractory metastatic melanoma. The use of nivolumab in previously untreated patients with advanced melanoma has not been tested in a phase 3 controlled study.


METHODS
We randomly assigned 418 previously untreated patients who had metastatic melanoma without a BRAF mutation to receive nivolumab (at a dose of 3 mg per kilogram of body weight every 2 weeks and dacarbazine-matched placebo every 3 weeks) or dacarbazine (at a dose of 1000 mg per square meter of body-surface area every 3 weeks and nivolumab-matched placebo every 2 weeks). The primary end point was overall survival.


RESULTS
At 1 year, the overall rate of survival was 72.9% (95% confidence interval [CI], 65.5 to 78.9) in the nivolumab group, as compared with 42.1% (95% CI, 33.0 to 50.9) in the dacarbazine group (hazard ratio for death, 0.42; 99.79% CI, 0.25 to 0.73; P<0.001). The median progression-free survival was 5.1 months in the nivolumab group versus 2.2 months in the dacarbazine group (hazard ratio for death or progression of disease, 0.43; 95% CI, 0.34 to 0.56; P<0.001). The objective response rate was 40.0% (95% CI, 33.3 to 47.0) in the nivolumab group versus 13.9% (95% CI, 9.5 to 19.4) in the dacarbazine group (odds ratio, 4.06; P<0.001). The survival benefit with nivolumab versus dacarbazine was observed across prespecified subgroups, including subgroups defined by status regarding the programmed death ligand 1 (PD-L1). Common adverse events associated with nivolumab included fatigue, pruritus, and nausea. Drug-related adverse events of grade 3 or 4 occurred in 11.7% of the patients treated with nivolumab and 17.6% of those treated with dacarbazine.


CONCLUSIONS
Nivolumab was associated with significant improvements in overall survival and progression-free survival, as compared with dacarbazine, among previously untreated patients who had metastatic melanoma without a BRAF mutation. (Funded by Bristol-Myers Squibb; CheckMate 066 ClinicalTrials.gov number, NCT01721772.).