nils-herrmann/clean_scirepeval huggingface dataset:
The high-conductance state of neocortical neurons in vivo

Intracellular recordings in vivo have shown that neocortical neurons are subjected to an intense synaptic bombardment in intact networks and are in a 'high-conductance' state. In vitro studies have shed light on the complex interplay between the active properties of dendrites and how they convey discrete synaptic inputs to the soma. Computational models have attempted to tie these results together and predicted that high-conductance states profoundly alter the integrative properties of cortical neurons, providing them with a number of computational advantages. Here, we summarize results from these different approaches, with the aim of understanding the integrative properties of neocortical neurons in the intact brain.
GazeTouchPass: Multimodal Authentication Using Gaze and Touch on Mobile Devices

We propose a multimodal scheme, GazeTouchPass, that combines gaze and touch for shoulder-surfing resistant user authentication on mobile devices. GazeTouchPass allows passwords with multiple switches between input modalities during authentication. This requires attackers to simultaneously observe the device screen and the user's eyes to find the password. We evaluate the security and usability of GazeTouchPass in two user studies. Our findings show that GazeTouchPass is usable and significantly more secure than single-modal authentication against basic and even advanced shoulder-surfing attacks.
From Adjective Glosses to Attribute Concepts: Learning Different Aspects That an Adjective Can Describe

Adjectives are one of the major contributors to conveying subjective meaning to sentences. Understanding the semantics of adjectives is essential for understanding natural language sentences. In this paper we propose a novel approach for learning different properties that an adjective can describe, corresponding to the ‘attribute concepts’, which is not currently available in existing linguistic resources. We accomplish this by reading adjective glosses and bootstrapping attribute concepts from a seed of adjectives. We show that we can learn new attribute concepts using adjective glosses of WordNet adjectives with high accuracy as compared with human annotation on a test set.
Low Latency Live Video Streaming over HTTP 2.0

Hypertext Transfer Protocol (HTTP) has been widely adopted as a scalable and efficient protocol for streaming video content over the Internet. HTTP streaming clients receive a manifest file, download the referred video segments over HTTP, and play them back seamlessly emulating video streaming. This introduces at least one segment duration latency making HTTP streaming unsuitable for live video streaming use cases that require low latencies. The straightforward solution to lower live latency that reduces segment duration leads to an explosion in the number of HTTP requests, as well as inefficient deployment of assets in HTTP caches. To solve this problem, we develop a low latency live video streaming technique over HTTP 2.0. In particular, we employ the new server push feature in HTTP 2.0 to stream the live video actively from the web server to the client, as soon as the video segments become available. We implement this server push based low latency mechanism in a MPEG Dynamic Adaptive Streaming over HTTP (DASH) prototype. Our experimental results indicate performance gains in live latency using the server push scheme. More importantly, by leveraging the server push feature in HTTP 2.0, we are able to avoid the request explosion problem while lowering latency by reducing the segment duration.
High-Frequency Behavior of Graphene-Based Interconnects—Part I: Impedance Modeling

This paper presents the first detailed methodology for the accurate evaluation of high-frequency impedance of graphene-based structures relevant to on-chip interconnect and inductor applications. Going beyond the simplifying assumptions of Ohm's law, the effects of electric-field variation within a mean free path and current dependency on the nonlocal electric-field are taken into account to accurately capture the high-frequency behavior of graphene ribbons (GRs). At the same time, a simplified approach that may be adopted at lower frequencies is also explained. Starting from the basic Boltzmann equation and combining with the unique dispersion relation for graphene in its hexagonal Brillouin zone, the current density across the GR structure is derived. First, a semi-infinite slab of GR is analyzed using the theory of Fourier integrals, which is followed by the development of a rigorous methodology for practical finite structures based on a self-consistent numerical calculation of the derived current density using the Green's function approach.
Denoising autoencoder with modulated lateral connections learns invariant representations of natural images

Suitable lateral connections between encoder and decoder are shown to allow higher layers of a denoising autoencoder (dAE) to focus on invariant representations. In regular autoencoders, detailed information needs to be carried through the highest layers but lateral connections from encoder to decoder relieve this pressure. It is shown that abstract invariant features can be translated to detailed reconstructions when invariant features are allowed to modulate the strength of the lateral connection. Three dAE structures with modulated and additive lateral connections, and without lateral connections were compared in experiments using real-world images. The experiments verify that adding modulated lateral connections to the model 1) improves the accuracy of the probability model for inputs, as measured by denoising performance; 2) results in representations whose degree of invariance grows faster towards the higher layers; and 3) supports the formation of diverse invariant poolings.
Energy big data: A survey

As a significant application of energy, smart grid is a complicated interconnected power grid that involves sensors, deployment strategies, smart meters, and real-time data processing. It continuously generates data with large volume, high velocity, and diverse variety. In this paper, we first give a brief introduction on big data, smart grid, and big data application in the smart grid scenario. Then, recent studies and developments are summarized in the context of integrated architecture and key enabling technologies. Meanwhile, security issues are specifically addressed. Finally, we introduce several typical big data applications and point out future challenges in the energy domain.
City, self, network: transnational migrants and online identity work

This paper uses qualitative interviews with 26 transnational migrants in New York City to analyze socio-technical practices related to online identity work. We focus specifically on the use of Facebook, where benefits included keeping in touch with friends and family abroad and documenting everyday urban life. At the same time, many participants also reported experiences of fatigue, socio-cultural tensions and concerns about maintaining a sense of personal privacy. These experiences highlight how transnational practices complicate context collapse, where the geographic dispersal of participants' personal networks renders visible conflicts of 'flattened' online networks. Our findings also suggest a kind of technology-enabled code-switching, where transnational migrants leverage social media to perform identities that alternate between communities, nationalities and geographies. This analysis informs HCI research on transnationalism and technological practices, as well as the complexities of online identity work in terms of shifting social and spatial contexts.
Large Scale Cloudlets Deployment for Efficient Mobile Cloud Computing

Interest in using Mobile Cloud Computing (MCC) for compute intensive mobile devices jobs such as multimedia applications has been growing. In fact, many new research efforts were invested to maximize the mobile intensive jobs offloading to the cloud within the cloud system coverage area. However, a large scale MCC deployment challenges and limitations are not considered. In this paper, a large scale Cloudlet-based MCC system deployment is introduced, aiming at reducing the power consumption and the network delay of multimedia applications while using MCC. The proposed deployment offers a large coverage area that can be used by mobile devices while they are moving from one location to another to reduce broadband communication needs. Practical experimental results and simulated results using show that using the proposed model reduces the power consumption of the mobile devices as well as reducing the communication latency when the mobile device requests a job to be performed remotely while satisfying the high quality of service requirements of mobile users.
Response and Habituation of the Human Amygdala during Visual Processing of Facial Expression

We measured amygdala activity in human volunteers during rapid visual presentations of fearful, happy, and neutral faces using functional magnetic resonance imaging (fMRI). The first experiment involved a fixed order of conditions both within and across runs, while the second one used a fully counterbalanced order in addition to a low level baseline of simple visual stimuli. In both experiments, the amygdala was preferentially activated in response to fearful versus neutral faces. In the counterbalanced experiment, the amygdala also responded preferentially to happy versus neutral faces, suggesting a possible generalized response to emotionally valenced stimuli. Rapid habituation effects were prominent in both experiments. Thus, the human amygdala responds preferentially to emotionally valenced faces and rapidly habituates to them.
Investigation of Locked Rotor Test for Estimation of Magnet PWM Carrier Eddy Current Loss in Synchronous Machines

The measurement method on the basis of locked rotor tests has been developed for the estimation of magnet PWM carrier eddy current loss in synchronous machines. In the measurement, the magnet eddy current loss is separated from the other losses by subtracting the loss of the machine without the magnets from that with the magnets under the appropriate control of armature currents and voltages. The 3-D finite element analysis is also carried out in order to confirm the validity of the proposed measurement method. The measured and calculated results are found to be in good agreement. It is clarified that the magnet eddy current loss of the machine can be predicted from the results of the proposed measurement method.
3D human pose estimation from depth maps using a deep combination of poses

Many real-world applications require the estimation of human body joints for higher-level tasks as, for example, human behaviour understanding. In recent years, depth sensors have become a popular approach to obtain three-dimensional information. The depth maps generated by these sensors provide information that can be employed to disambiguate the poses observed in two-dimensional images. This work addresses the problem of 3D human pose estimation from depth maps employing a Deep Learning approach. We propose a model, named Deep Depth Pose (DDP), which receives a depth map containing a person and a set of predefined 3D prototype poses and returns the 3D position of the body joints of the person. In particular, DDP is defined as a ConvNet that computes the specific weights needed to linearly combine the prototypes for the given input. We have thoroughly evaluated DDP on the challenging ‘ITOP’ and ‘UBC3V’ datasets, which respectively depict realistic and synthetic samples, defining a new state-of-the-art on them.
A WIDEBAND TWIN-DIAMOND-SHAPED CIRCULARLY POLARIZED PATCH ANTENNA WITH GAP-COUPLED FEED

A novel twin-diamond-shaped antenna is presented for wideband circularly polarized (CP) radiation. By introducing a twin-diamond-shaped patch and a gap-coupled feed structure, a lefthanded circularly polarized (LHCP) antenna in bore-sight direction is obtained. The gap-coupled feed structure consists of a horizontal microstrip arm of approximately 0.285λ0 at the centre frequency and two small diamonds, which greatly contributes to wideband characteristics. The experimental bandwidths of 10-dB return loss and 3-dB axial ratio (AR) for the antenna prototype are about 20% and 9.2%, respectively. The measured gain is more than 6.8 dBi over the entire bandwidth.
AutoISES: Automatically Inferring Security Specification and Detecting Violations

The importance of software security cannot be overstated. In the past, researchers have applied program analysis techniques to automatically detect security vulnerabilities and verify security properties. However, such techniques have limited success in reality because they require manually provided code-level security specifications. Manually writing and generating these code-level security specifications are tedious and error-prone. Additionally, they seldom exist in production software. In this paper, we propose a novel method and tool, called AutoISES, which Automatically Infers Security Specifications by statically analyzing source code, and then directly use these specifications to automatically detect security violations. Our experiments with the Linux kernel and Xen demonstrated the effectiveness of this approach – AutoISES automatically generated 84 security specifications and detected 8 vulnerabilities in the Linux kernel and Xen, 7 of which have already been confirmed by the corresponding developers.
Scalable Modified Kneser-Ney Language Model Estimation

We present an efficient algorithm to estimate large modified Kneser-Ney models including interpolation. Streaming and sorting enables the algorithm to scale to much larger models by using a fixed amount of RAM and variable amount of disk. Using one machine with 140 GB RAM for 2.8 days, we built an unpruned model on 126 billion tokens. Machine translation experiments with this model show improvement of 0.8 BLEU point over constrained systems for the 2013 Workshop on Machine Translation task in three language pairs. Our algorithm is also faster for small models: we estimated a model on 302 million tokens using 7.7% of the RAM and 14.0% of the wall time taken by SRILM. The code is open source as part of KenLM.
Culture and the categorization of emotions.

Some writers assume--and others deny--that all human beings distinguish emotions from nonemotions and divide the emotions into happiness, anger, fear, and so on. A review of ethnographic and cross-cultural studies on (a) emotion lexicons, (b) the emotions inferred from facial expressions, and (c) dimensions implicit in comparative judgments of emotions indicated both similarities and differences in how the emotions are categorized in different languages and cultures. Five hypotheses are reviewed: (a) Basic categories of emotion are pancultural, subordinate categories culture specific; (b) emotional focal points are pancultural, boundaries culture specific; (c) emotion categories evolved from a single primitive category of physiological arousal; (d) most emotion categories are culture specific but can be defined by pancultural semantic primitives; and (e) an emotion category is a script with both culture-specific and pancultural components.
DSP Implementation in the Loop of the Vector Control Drive of a Permanent Magnet Synchronous Machine

The aim of this work is to design and implement the FOC (Field Oriented Control) of the permanent magnet synchronous machine (PMSM) on DSP in Hardware In the Loop (HIL). The MATLAB /Simulink, the IDE Code Composer Studio and the DSP TMS320F28335 platform will be used to perform the simulation, the code generation and the HIL.
 The obtained performances of this command (a speed response time of 10 ms and a zero static error vis-à-vis the setpoint and disruption) converge to those obtained with conventional simulation on SIMULINK
Conditional Random Fields and Support Vector Machines for Disorder Named Entity Recognition in Clinical Texts

We present a comparative study between two machine learning methods, Conditional Random Fields and Support Vector Machines for clinical named entity recognition. We explore their applicability to clinical domain. Evaluation against a set of gold standard named entities shows that CRFs outperform SVMs. The best F-score with CRFs is 0.86 and for the SVMs is 0.64 as compared to a baseline of 0.60.
Early sport specialization: roots, effectiveness, risks.

Year-round training in a single sport beginning at a relatively young age is increasingly common among youth. Contributing factors include perceptions of Eastern European sport programs, a parent's desire to give his or her child an edge, labeling youth as talented at an early age, pursuit of scholarships and professional contracts, the sporting goods and services industry, and expertise research. The factors interact with the demands of sport systems. Limiting experiences to a single sport is not the best path to elite status. Risks of early specialization include social isolation, overdependence, burnout, and perhaps risk of overuse injury. Commitment to a single sport at an early age immerses a youngster in a complex world regulated by adults, which is a setting that facilitates manipulation - social, dietary, chemical, and commercial. Youth sport must be kept in perspective. Participants, including talented young athletes, are children and adolescents with the needs of children and adolescents.
Convergent and discriminant validation by the multitrait-multimethod matrix.

Content Memory (Learning Ability) As Comprehension 82 Vocabulary Cs .30 ( ) .23 .31 ( ) .31 .31 .35 ( ) .29 .48 .35 .38 ( ) .30 .40 .47 .58 .48 ( ) As judged against these latter values, comprehension (.48) and vocabulary (.47), but not memory (.31), show some specific validity. This transmutability of the validation matrix argues for the comparisons within the heteromethod block as the most generally relevant validation data, and illustrates the potential interchangeability of trait and method components. Some of the correlations in Chi's (1937) prodigious study of halo effect in ratings are appropriate to a multitrait-multimethod matrix in which each rater might be regarded as representing a different method. While the published report does not make these available in detail because it employs averaged values, it is apparent from a comparison of his Tables IV and VIII that the ratings generally failed to meet the requirement that ratings of the same trait by different raters should correlate higher than ratings of different traits by the same rater. Validity is shown to the extent that of the correlations in the heteromethod block, those in the validity diagonal are higher than the average heteromethod-heterotrait values. A conspicuously unsuccessful multitrait-multimethod matrix is provided by Campbell (1953, 1956) for rating of the leadership behavior of officers by themselves and by their subordinates. Only one of 11 variables (Recognition Behavior) met the requirement of providing a validity diagonal value higher than any of the heterotrait-heteromethod values, that validity being .29. For none of the variables were the validities higher than heterotrait-monomethod values. A study of attitudes toward authority and nonauthority figures by Burwen and Campbell (1957) contains a complex multitrait-multimethod matrix, one symmetrical excerpt from which is shown in Table 6. Method variance was strong for most of the procedures in this study. Where validity was found, it was primarily at the level of validity diagonal values higher than heterotrait-heteromethod values. As illustrated in Table 6, attitude toward father showed this kind of validity, as did attitude toward peers to a lesser degree. Attitude toward boss showed no validity. There was no evidence of a generalized attitude toward authority which would include father and boss, although such values as the VALIDATION BY THE MULTITRAIT-MULTIMETHOD MATRIX
Malaria parasite identification on thick blood film using genetic programming

Thin blood film is used to know type and phase of the malaria parasite, but which is widely used in Indonesia is the thick blood film. Therefore we need a method that can identify parasites in thick blood film image with a high percentage of accuracy. This research aims to establish a more objective classification system and reduce the subjective factors of medical personnel in diagnosing the type of malaria parasite include its phase. It has three main stages, there are preprocessing, feature extraction, and classification. Preprocessing aims to eliminate the noise, feature extraction using red-green-blue channel color histogram, hue channel HSV histogram, and hue channel HSI histogram, classification using Genetic Programming to identify parasites and also to detect type and phase of the parasite. Experiment was conducted on 180 thick blood film images that classiffied into two classes. The classification has an average accuracy of 95.49% for non-parasites and 95.58% for parasites. Meanwhile when system is used to classified into six classes, testing result have an average accuracy of 90.25% not parasites, 82.25% vivax thropozoit, 75.83% vivax schizont, 81.75% vivax gametocytes, 90.75% falciparum thropozoit, 86.75% falciparum gametocytes. This research confirm that identifying malaria parasite in thick blood film is possible.
Singularity detection and processing with wavelets

Most of a signal information is often carried by irregular structures and transient phenomena. The mathematical characterization of singularities with Lipschitz exponents is explained. Theorems are reviewed that estimate local Lipschitz exponents of functions from the evolution across scales of their wavelet transform. It is then proven that the local maxima of the wavelet transform modulus detect the locations of irregular structures and provide numerical procedures to compute their Lipschitz exponents. The wavelet transform of singularities with fast oscillations have a particular behavior that is studied separately. The local frequency of such oscillations are measured from the wavelet transform modulus maxima. It has been shown numerically that oneand two-dimensional signals can be reconstructed, with a good approximation, from the local maxima of their wavelet transform modulus. As an application, an algorithm is developed that removes white noises from signals by analyzing the evolution of the wavelet transform maxima across scales. In two-dimensions, the wavelet transform maxima indicate the location of edges in images. The denoising algorithm is extended for image enhancement.
Evaluation of Hardware Performance for the SHA-3 Candidates Using SASEBO-GII

As a result of extensive analyses on cryptographic hash functions, NIST started an open competition for selecting a new standard hash function SHA-3. One important aspect of this competition is in evaluating hardware implementations and in collecting much attention of researchers in this area. For a fair comparison of the hardware performance, we propose an evaluation platform, a hardware design strategy, and evaluation criteria that must be consistent for all SHA-3 candidates. First, we define specifications of interface for the SASEBO-GII platform that are suitable for evaluating the performance in real-life hash applications, while one can also evaluate the performance of the SHA-3 core function that has an ideal interface. Second, we discuss the design strategy for high-throughput hardware implementations. Lastly, we explain the evaluation criteria to compare the cost and speed performance of eight SHA-3 candidates out of fourteen.