nils-herrmann/clean_scirepeval huggingface dataset:
Derivative Delay Embedding: Online Modeling of Streaming Time Series

The staggering amount of streaming time series coming from the real world calls for more efficient and effective online modeling solution. For time series modeling, most existing works make some unrealistic assumptions such as the input data is of fixed length or well aligned, which requires extra effort on segmentation or normalization of the raw streaming data. Although some literature claim their approaches to be invariant to data length and misalignment, they are too time-consuming to model a streaming time series in an online manner. We propose a novel and more practical online modeling and classification scheme, DDE-MGM, which does not make any assumptions on the time series while maintaining high efficiency and state-of-the-art performance. The derivative delay embedding (DDE) is developed to incrementally transform time series to the embedding space, where the intrinsic characteristics of data is preserved as recursive patterns regardless of the stream length and misalignment. Then, a non-parametric Markov geographic model (MGM) is proposed to both model and classify the pattern in an online manner. Experimental results demonstrate the effectiveness and superior classification accuracy of the proposed DDE-MGM in an online setting as compared to the state-of-the-art.
Do Convnets Learn Correspondence?

Convolutional neural nets (convnets) trained from massive labeled datasets [1] have substantially improved the state-of-the-art in image classification [2] and object detection . However, visual understanding requires establishing correspondence on a finer level than object category. Given their large pooling regions and training from whole-image labels, it is not clear that convnets derive their success from an accurate correspondence model which could be used for precise localization. In this paper, we study the effectiveness of convnet activation features for tasks requiring correspondence. We present evidence that convnet features localize at a much finer scale than their receptive field sizes, that they can be used to perform intraclass aligment as well as conventional hand-engineered features, and that they outperform conventional features in keypoint prediction on objects from PASCAL VOC 2011 .
System Dynamics Modeling for the Complexity of Knowledge Creation Within Adaptive Large Programs Management

This research is an attempt to illustrate the variables that are mentioned in the literature to deal with the unexpected future risks that are increasingly threatening the success of the large program. The research is a qualitative conceptualization using secondary data collection from the literature review and by criticizing it reaching a structural validation of the system dynamic simple model of how to increase the level of the stock of the unknown unknowns or the complexity chaotic knowledge for better risk management and creativity in achieving a competitive edge. The unknow-unknowns are still representing a black box and are under the control of the god act. This is a try only to concurrent and foreword adaptation with the unknown future. The manager can use this model to conceptualize the internal and external variables that can be linked to the business being objectives. By using this model the manager can minimized the side effects of the productivity and efficiency
Trace Ratio Optimization-Based Semi-Supervised Nonlinear Dimensionality Reduction for Marginal Manifold Visualization

Visualizing similarity data of different objects by exhibiting more separate organizations with local and multimodal characteristics preserved is important in multivariate data analysis. Laplacian Eigenmaps (LAE) and Locally Linear Embedding (LLE) aim at preserving the embeddings of all similarity pairs in the close vicinity of the reduced output space, but they are unable to identify and separate interclass neighbors. This paper considers the semi-supervised manifold learning problems. We apply the pairwise Cannot-Link and Must-Link constraints induced by the neighborhood graph to specify the types of neighboring pairs. More flexible regulation on supervised information is provided. Two novel multimodal nonlinear techniques, which we call trace ratio (TR) criterion-based semi-supervised LAE (S2LAE) and LLE (S2LLE), are then proposed for marginal manifold visualization. We also present the kernelized S2LAE and S2LLE. We verify the feasibility of S2LAE and S2LLE through extensive simulations over benchmark real-world MIT CBCL, CMU PIE, MNIST, and USPS data sets. Manifold visualizations show that S2LAE and S2LLE are able to deliver large margins between different clusters or classes with multimodal distributions preserved. Clustering evaluations show they can achieve comparable to or even better results than some widely used methods.
When Cellular Networks Met IPv6: Security Problems of Middleboxes in IPv6 Cellular Networks

Recently, cellular operators have started migrating to IPv6 in response to the increasing demand for IP addresses. With the introduction of IPv6, cellular middleboxes, such as firewalls for preventing malicious traffic from the Internet and stateful NAT64 boxes for providing backward compatibility with legacy IPv4 services, have become crucial to maintain stability of cellular networks. This paper presents security problems of the currently deployed IPv6 middleboxes of five major operators. To this end, we first investigate several key features of the current IPv6 deployment that can harm the safety of a cellular network as well as its customers. These features combined with the currently deployed IPv6 middlebox allow an adversary to launch six different attacks. First, firewalls in IPv6 cellular networks fail to block incoming packets properly. Thus, an adversary could fingerprint cellular devices with scanning, and further, she could launch denial-of-service or over-billing attacks. Second, vulnerabilities in the stateful NAT64 box, a middlebox that maps an IPv6 address to an IPv4 address (and vice versa), allow an adversary to launch three different attacks: 1) NAT overflow attack that allows an adversary to overflow the NAT resources, 2) NAT wiping attack that removes active NAT mappings by exploiting the lack of TCP sequence number verification of firewalls, and 3) NAT bricking attack that targets services adopting IP-based blacklisting by preventing the shared external IPv4 address from accessing the service. We confirmed the feasibility of these attacks with an empirical analysis. We also propose effective countermeasures for each attack.
7 Multisensory and sensorimotor maps

The parietal lobe plays a major role in sensorimotor integration and action. Recent neuroimaging studies have revealed more than 40 retinotopic areas distributed across five visual streams in the human brain, two of which enter the parietal lobe. A series of retinotopic areas occupy the length of the intraparietal sulcus and continue into the postcentral sulcus. On themedial wall, retinotopy extends across the parieto-occipital sulcus into the precuneus and reaches the cingulate sulcus. Full-body tactile stimulation revealed a multisensory homunculus lying along the postcentral sulcus just posterior to primary somatosensory cortical areas and overlapping with the anteriormost retinotopic maps. These topologically organized higher-level maps lay the foundation for actions in peripersonal space (e.g., reaching and grasping) aswell as navigation through space. A preliminary yet comprehensive multilayer functional atlas was constructed to specify the relative locations of cortical unisensory, multisensory, and action representations. We expect that those areal and functional definitions will be refined by future studies using more sophisticated stimuli and tasks tailored to regions with different specificity. The long-term goal is to construct an online surface-based atlas containing layered maps of multiple modalities that can be used as a reference to understand the functions and disorders of the parietal lobe.
Finding your voice: a singing lesson from functional imaging.

Vocal singing (singing with lyrics) shares features common to music and language but it is not clear to what extent they use the same brain systems, particularly at the higher cortical level, and how this varies with expertise. Twenty-six participants of varying singing ability performed two functional imaging tasks. The first examined covert generative language using orthographic lexical retrieval while the second required covert vocal singing of a well-known song. The neural networks subserving covert vocal singing and language were found to be proximally located, and their extent of cortical overlap varied with singing expertise. Nonexpert singers showed greater engagement of their language network during vocal singing, likely accounting for their less tuneful performance. In contrast, expert singers showed a more unilateral pattern of activation associated with reduced engagement of the right frontal lobe. The findings indicate that singing expertise promotes independence from the language network with decoupling producing more tuneful performance. This means that the age-old singing practice of 'finding your singing voice' may be neurologically mediated by changing how strongly singing is coupled to the language system.
Building Security Perimeters to Protect Network Systems Against Cyber Threats [Future Directions]

Due to the wide variety of devices used in computer network systems, cybersecurity plays a major role in securing and improving the performance of the network or system. Although cybersecurity has received a large amount of global interest in recent years, it remains an open research space. Current security solutions in network-based cyberspace provide an open door to attackers by communicating first before authentication, thereby leaving a black hole for an attacker to enter the system before authentication. This article provides an overview of cyberthreats, traditional security solutions, and the advanced security model to overcome current security drawbacks.
Sarcoptic mange in dogs: Its effect on liver, oxidative stress, trace minerals and vitamins.

The present study was aimed to determine the effect on liver, associated oxidative stress, trace element and vitamin alteration in dogs with sarcoptic mange. A total of 24 dogs with clinically established diagnosis of sarcoptic mange, divided into two groups, severely infested group (n=9) and mild/moderately infested group (n=15), according to the extent of skin lesions caused by sarcoptic mange and 6 dogs as control group were included in the present study. In comparison to healthy control hemoglobin, PCV, and TEC were significantly (P<0.05) decreased in dogs with sarcoptic mange however, significant increase in TLC along with neutrophilia and lymphopenia was observed only in severely infested dogs. The albumin, glucose and cholesterol were significantly (P<0.05) decreased and globulin, ALT, AST and bilirubin were significantly (P<0.05) increased in severely infested dogs when compared to other two groups. Malondialdehyde (MDA) levels were significantly (P<0.01) higher in dogs with sarcoptic mange, with levels highest in severely infested groups. Activity of superoxide dismutase (SOD) (P<0.05) and catalase were significantly (P<0.01) lower in sarcoptic infested dogs when compared with the healthy control group. Zinc and copper levels in dogs with sarcoptic mange were significantly (P<0.05) lower when compared with healthy control group with the levels lowest in severely infested group. Vitamin A and vitamin C levels were significantly (P<0.05) lower in sarcoptic infested dogs when compared to healthy control. From the present study, it was concluded that sarcoptic mange in dogs affects the liver and the infestation is associated with oxidant/anti-oxidant imbalance, significant alteration in trace elements and vitamins.
Connectivity-based parcellation of human cingulate cortex and its relation to functional specialization.

Whole-brain neuroimaging studies have demonstrated regional variations in function within human cingulate cortex. At the same time, regional variations in cingulate anatomical connections have been found in animal models. It has, however, been difficult to estimate the relationship between connectivity and function throughout the whole cingulate cortex within the human brain. In this study, magnetic resonance diffusion tractography was used to investigate cingulate probabilistic connectivity in the human brain with two approaches. First, an algorithm was used to search for regional variations in the probabilistic connectivity profiles of all cingulate cortex voxels with the whole of the rest of the brain. Nine subregions with distinctive connectivity profiles were identified. It was possible to characterize several distinct areas in the dorsal cingulate sulcal region. Several distinct regions were also found in subgenual and perigenual cortex. Second, the probabilities of connection between cingulate cortex and 11 predefined target regions of interest were calculated. Cingulate voxels with a high probability of connection with the different targets formed separate clusters within cingulate cortex. Distinct connectivity fingerprints characterized the likelihood of connections between the extracingulate target regions and the nine cingulate subregions. Last, a meta-analysis of 171 functional studies reporting cingulate activation was performed. Seven different cognitive conditions were selected and peak activation coordinates were plotted to create maps of functional localization within the cingulate cortex. Regional functional specialization was found to be related to regional differences in probabilistic anatomical connectivity.
Extensive unilateral nevus comedonicus without genetic abnormality.

Nevus comedonicus is considered a genodermatosis characterized by the presence of multiple groups of dilated pilosebaceous orifices filled with black keratin plugs, with sharply unilateral distribution mostly on the face, neck, trunk, upper arms. Lesions can appear at any age, frequently before the age of 10 years, but they are usually present at birth. We present a 2.7-year-old girl with a very severe form of nevus comedonicus. She exhibited lesions located initially at the left side of the body with a linear characteristic, following Blascko lines T1/T2, T5, T7, S1 /S2, but progressively developed lesions on the right side of the scalp and left gluteal area.
At-speed test for path delay faults using practical techniques

To detect the smallest delay faults at a fault site, the longest path(s) through it must be tested at full speed. Most existing test generation tools are either inefficient in automatically identifying the longest testable paths due to the high computational complexity or do not support at-speed test using existing practical design-for-testability structures, such as scan design. In this work a test generation methodology for scan-based synchronous sequential circuits is presented, under two at-speed test strategies used in industry. The two strategies are compared and the test generation efficiency is evaluated on the ISCAS89 benchmark circuits.
Improving Short Text Classification Using Unlabeled Background Knowledge

We describe a method for improving the classification of short text strings using a combination of labeled training data plus a secondary corpus of unlabeled but related longer documents. We show that such unlabeled background knowledge can greatly decrease error rates, particularly if the number of examples or the size of the strings in the training set is small. This is particularly useful when labeling text is a labor-intensive job and when there is a large amount of information available about a particular problem on the World Wide Web. Our approach views the task as one of information integration using WHIRL, a tool that combines database functionalities with techniques from the information-retrieval literature.
Non-Native Text-to-Speech Preserving Speaker Individuality Based on Partial Correction of Prosodic and Phonetic Characteristics

This paper presents a novel non-native speech synthesis technique that preserves the individuality of a non-native speaker. Crosslingual speech synthesis based on voice conversion or Hidden Markov Model (HMM)-based speech synthesis is a technique to synthesize foreign language speech using a target speaker’s natural speech uttered in his/her mother tongue. Although the technique holds promise to improve a wide variety of applications, it tends to cause degradation of target speaker’s individuality in synthetic speech compared to intra-lingual speech synthesis. This paper proposes a new approach to speech synthesis that preserves speaker individuality by using non-native speech spoken by the target speaker. Although the use of non-native speech makes it possible to preserve the speaker individuality in the synthesized target speech, naturalness is significantly degraded as the synthesized speech waveform is directly affected by unnatural prosody and pronunciation often caused by differences in the linguistic systems of the source and target languages. To improve naturalness while preserving speaker individuality, we propose (1) a prosody correction method based on model adaptation, and (2) a phonetic correction method based on spectrum replacement for unvoiced consonants. The experimental results using English speech uttered by native Japanese speakers demonstrate that (1) the proposed methods are capable of significantly improving naturalness while preserving the speaker individuality in synthetic speech, and (2) the proposed methods also improve intelligibility as confirmed by a dictation test. key words: cross-lingual speech synthesis, English-Read-by-Japanese, speaker individuality, HMM-based speech synthesis, prosody correction, phonetic correction
Behavioral and Psychosocial Health of New Mothers and Associations With Contextual Factors and Perceived Health.

To test the association of behavioral and psychosocial health domains with contextual variables and perceived health in ethnically and economically diverse postpartum women.



Mail survey of a stratified random sample.



Southwestern community in Texas.



Non-Hispanic White, African American, and Hispanic women (N = 168).



A questionnaire was sent to a sample of 600 women. The adjusted response rate was 32.8%. The questionnaire covered behavioral (diet, physical activity, smoking, and alcohol use) and psychosocial (depression symptoms and body image) health, contextual variables (race/ethnicity, income, perceived stress, and social support), and perceived health. Hypotheses were tested using linear and logistic regression.



Body image, dietary behaviors, physical activity behaviors, and depression symptoms were all significantly correlated (Spearman ρ = -.15 to .47). Higher income was associated with increased odds of higher alcohol use (more than 1 drink on 1 to 4 days in a 14-day period). African American ethnicity was correlated with less healthy dietary behaviors and Hispanic ethnicity with less physical activity. In multivariable regressions, perceived stress was associated with less healthy dietary behaviors, increased odds of depression, and decreased odds of higher alcohol use, whereas social support was associated with less body image dissatisfaction, more physical activity, and decreased odds of depression. All behavioral and psychosocial domains were significantly correlated with perceived health, with higher alcohol use related to more favorable perceived health. In regressions analyses, perceived stress was a significant contextual predictor of perceived health.



Stress and social support had more consistent relationships to behavioral and psychosocial variables than race/ethnicity and income level.
Chapter in Wiley Encyclopedia of Electrical and Electronics Engineering

unit of computation and a processor a piece of physical hardware In addition to reading to and writing from local memory a process can send and receive messages by making calls to a library of message passing routines The coordinated exchange of messages has the e ect of synchronizing processes This can be achieved by the synchronous exchange of messages in which the sending operation does not terminate until the receive operation has begun A di erent form of synchronization occurs when a message is sent asynchronously but the receiving process must wait or block until the data arrives Processes can be mapped to physical processors in various ways the mapping employed does not a ect the semantics of a program In particular multiple processes may be mapped to a single processor The message passing model provides a mechanism for talking about locality data contained in the local memory of a process are close and other data are remote We now examine some other properties of the message passing programming model performance mapping independence and modularity
Rule-Based Exploratory Testing of Graphical User Interfaces

This paper introduces rule-based exploratory testing, an approach to GUI testing that combines aspects of manual exploratory testing with rule-based test automation. This approach uses short, automated rules to increase the bug-detection capability of recorded exploratory test sessions. A preliminary evaluation found that this approach can be used to detect both general and application-specific bugs, but that rules for general bugs are easier to transfer between applications. Also, despite the advantages of keyword-based testing, it interferes with the transfer of rules between applications.
Islamic star patterns in absolute geometry

We present Najm, a set of tools built on the axioms of absolute geometry for exploring the design space of Islamic star patterns. Our approach makes use of a novel family of tilings, called "inflation tilings," which are particularly well suited as guides for creating star patterns. We describe a method for creating a parameterized set of motifs that can be used to fill the many regular polygons that comprise these tilings, as well as an algorithm to infer geometry for any irregular polygons that remain. Erasing the underlying tiling and joining together the inferred motifs produces the star patterns. By choice, Najm is build upon the subset of geometry that makes no assumption about the behavior of parallel lines. As a consequence, star patterns created by Najm can be designed equally well to fit the Euclidean plane, the hyperbolic plane, or the surface of a sphere.
Low Rank Representation on Grassmann Manifolds

Low-rank representation (LRR) has recently attracted great interest due to its pleasing efficacy in exploring low-dimensional subspace structures embedded in data. One of its successful applications is subspace clustering which means data are clustered according to the subspaces they belong to. In this paper, at a higher level, we intend to cluster subspaces into classes of subspaces. This is naturally described as a clustering problem on Grassmann manifold. The novelty of this paper is to generalize LRR on Euclidean space into the LRR model on Grassmann manifold. The new method has many applications in computer vision tasks. The paper conducts the experiments over two real world examples, clustering handwritten digits and clustering dynamic textures. The experiments show the proposed method outperforms a number of existing methods.