nils-herrmann/clean_scirepeval huggingface dataset:
Business process composition based on meta models

Nowadays, Business Process Management (BPM) technology has been developed and widely applied in small and large scale. There are many companies and organizations implemented business process oriented information systems. Therefore, the flexibility issues become very important in managing large quantity of business processes because business processes are always changing overtime. There is a need of flexible business process models so that every possible changes can be done easily every time. Flexible business process models are represented by a reconfigurable model. In this paper, we proposed a method to manage business process model variations in order to efficiently develop the business process repository. The variation management is done by storing the common business processes and its variation in the repository. Then, we also propose meta models which contain information about the models stored in the repository. The results show that the meta models support the composition process of a new business process based on the common business process. The variation management has achieved to reduce storage redundancy up to 82%.
Attaining human-level performance for anatomical landmark detection in 3D CT data

We present an efficient neural network approach for locating anatomical landmarks, using a two-pass, two-resolution cascaded approach which leverages a mechanism we term atlas location autocontext. Location predictions are made by regression to Gaussian heatmaps, one heatmap per landmark. This system allows patchwise application of a shallow network, thus enabling the prediction of multiple volumetric heatmaps in a unified system, without prohibitive GPU memory requirements. Evaluation is performed for 22 landmarks defined on a range of structures in head CT scans and the neural network model is benchmarked against a previously reported decision forest model trained with the same cascaded system. Models are trained and validated on 201 scans. Over the final test set of 20 scans which was independently annotated by 2 observers, we show that the neural network reaches an accuracy which matches the annotator variability.
Extracting lines of curvature from noisy point clouds

We present a robust framework for extracting lines of curvature from point clouds. First, we show a novel approach to denoising the input point cloud using robust statistical estimates of surface normal and curvature which automatically rejects outliers and corrects points by energy minimization. Then the lines of curvature are constructed on the point cloud with controllable density. Our approach is applicable to surfaces of arbitrary genus, with or without boundaries, and is statistically robust to noise and outliers while preserving sharp surface features. We show our approach to be effective over a range of synthetic and real-world input datasets with varying amounts of noise and outliers. The extraction of curvature information can benefit many applications in CAD, computer vision and graphics for point cloud shape analysis, recognition and segmentation. Here, we show the possibility of using the lines of curvature for feature-preserving mesh construction directly from noisy point clouds.
LiveNet: Improving features generalization for face liveness detection using convolution neural networks

Performance of face liveness detection algorithms in cross-database face liveness detection tests is one of the key issues in face-biometric based systems. Recently, Convolution Neural Networks (CNN) classifiers have shown remarkable performance in intra-database face liveness detection tests. However, a little effort has been made to improve the generalization capability of CNN classifiers for cross-database and unconstrained face liveness detection tests. In this paper, we propose an efficient strategy for training deep CNN classifiers for face liveness detection task. We utilize continuous data-randomization (like bootstrapping) in the form of small mini-batches during training CNN classifiers on small scale face antispoofing database. Experimental results revealed that the proposed approach reduces the training time by 18.39%, while significantly lowering the HTER by 8.28% and 14.14% in cross-database tests on CASIAFASD and Replay-Attack database respectively as compared to state-of-the-art approaches. Additionally, the proposed approach achieves satisfactory results on intra-database and cross-database face liveness detection tests, claiming a good generality over other state-of-the-art face anti-spoofing approaches.
Influence of music on human electroencephalogram

This paper deals with a research of an influence of listening to sound sequence on changing of brain activity. Differences of human electroencephalogram (EEG) monitored by a four channel device on silent conditions and while listening to a sound sequence are described. Sound sequence consisted of fourteen tracks separated by five seconds of silence. This experiment was performed on four subjects sitting on a chair with closed eyes inside an audiology room. The average of four channels was used for additional processing. Signal of each subject was edited to fifteen parts representing EEG signals during listening to each track. All parts of EEG signal were filtered to delta, theta, alpha, beta and gamma activities. Energy of all these activities was calculated. For each activity the changeability of EEG during listening to the tracks was analyzed by analysis of variance.
Effects of small-sided games on physical conditioning and performance in young soccer players.

The purpose of this study was to examine, first, the movement actions performed during two different small-sided games and, second, their effects on a series of field endurance and technical tests. Thirty-four young soccer players (age: 13 ± 0.9 yrs; body mass: 62.3 ± 15.1 kg; height: 1.65 ± 0.06 m) participated in the study. Small-sided games included three-a-side (3 versus 3 players) and six-a-side (6 versus 6 players) games consisting of 10 bouts of 4 min duration with 3 min active recovery between bouts. Soccer player performance was evaluated using five field tests: a) 30m sprint, b) throw-in for distance, c) Illinois Agility Test, d) dribbling the ball and e) horizontal jump before, in the middle and after the implementation of both game situations. Heart rate was monitored during the entire testing session. Each game was also filmed to measure soccer movements within the game. The ANOVA analysis indicated that the three-a- side games displayed significantly higher heart rate values compared with the six-a-side games (p < 0.05). The number of short passes, kicks, tackles, dribbles and scoring goals were significantly higher during the three-a-side compared with the six-a-side game condition (p < 0. 05) while players performed more long passes and headed the ball more often during the six-a-side (p < 0.05). After the three-a-side games, there was a significant decline in sprint and agility performance (p < 0.05), while after both game conditions significant alterations in the throw-in and the horizontal jump performance were observed (p < 0.05). The results of the present study indicated that three-a-side games provide higher stimulus for physical conditioning and technical improvement than six-a-side games and their use for training young soccer players is recommended. -a-side games display higher HR compared with six-a-side games.In the three-a-side games players performed more short passes, kicks, dribbles, tackles and scored more goals compared with the six-a-side games.Impairment in endurance and field test performance was observed mainly after three-a-side games.The use of the three-a-side games to develop physical fitness and technique in young soccer players is recommended.
Tunable combline filter with continuous control of center frequency and bandwidth

A new combline filter structure with a continuous tunability for both the center frequency and bandwidth is presented in this paper. The passband-width tunability is achieved by placing variable coupling reducers between the filter resonators. The coupling reducers, operating as bandwidth control subnetworks, are designed as detuned resonators made up of a line segment ending in a variable capacitor. The proposed filter structure is experimentally validated with the design, construction in suspended stripline technology, and characterization of a low-cost filter prototype for terrestrial digital video broadcasting receivers operating in the UHF band (470-862 MHz). Other relevant factors, such as the intermodulation distortion produced by the varactors used to control the bandwidth electronically or the power-handling performance of the constructed filter, are also discussed. The reconfigurable filter module described in this paper is very suitable for the design of flexible multifunction receiver subsystems simultaneously supporting signals with a different bandwidth.
Toward Understanding How Early-Life Stress Reprograms Cognitive and Emotional Brain Networks

Vulnerability to emotional disorders including depression derives from interactions between genes and environment, especially during sensitive developmental periods. Adverse early-life experiences provoke the release and modify the expression of several stress mediators and neurotransmitters within specific brain regions. The interaction of these mediators with developing neurons and neuronal networks may lead to long-lasting structural and functional alterations associated with cognitive and emotional consequences. Although a vast body of work has linked quantitative and qualitative aspects of stress to adolescent and adult outcomes, a number of questions are unclear. What distinguishes ‘normal’ from pathologic or toxic stress? How are the effects of stress transformed into structural and functional changes in individual neurons and neuronal networks? Which ones are affected? We review these questions in the context of established and emerging studies. We introduce a novel concept regarding the origin of toxic early-life stress, stating that it may derive from specific patterns of environmental signals, especially those derived from the mother or caretaker. Fragmented and unpredictable patterns of maternal care behaviors induce a profound chronic stress. The aberrant patterns and rhythms of early-life sensory input might also directly and adversely influence the maturation of cognitive and emotional brain circuits, in analogy to visual and auditory brain systems. Thus, unpredictable, stress-provoking early-life experiences may influence adolescent cognitive and emotional outcomes by disrupting the maturation of the underlying brain networks. Comprehensive approaches and multiple levels of analysis are required to probe the protean consequences of early-life adversity on the developing brain. These involve integrated human and animal-model studies, and approaches ranging from in vivo imaging to novel neuroanatomical, molecular, epigenomic, and computational methodologies. Because early-life adversity is a powerful determinant of subsequent vulnerabilities to emotional and cognitive pathologies, understanding the underlying processes will have profound implications for the world’s current and future children.
GPS and GSM based Vehicle Tracing and Employee Security System

A GPS & GSM Based Vehicle Tracking and Employee Security System combine the installation of an electronic device in a vehicle, with purpose-designed computer software to enable the company to track the vehicle's location. In vehicle tracking systems we use Global Positioning System (GPS) technology for locating the vehicle. Vehicle information can be viewed on electronic maps via the Internet or specialized software. Due to recently happened mishaps such as burglary, rape cases etc., the employee safety, esp. for the women employees, has become a number one priority for most of the companies. Even though the companies take good precautions to ensure that its employees are safe, there are some serious loop holes in the existing system. Firstly there is no full proof mechanism to track the outsiders to avoid this kind of problem we are going to implement a system that provides more security to the employee. The car Unit is placed inside the car .When the car picks up the employee; he/she needs to swap the RFID card. The micro controller matches the RFID card no. with its database records and sends the employee’s id, cab id & the cab position co-ordinates to the company unit via GSM module. The GSM Modem will receive the message through GSM in the company unit. If employee finds himself/herself in a problem, he/she will press the button. Microcontroller will detect the action & sends a signal to the GSM which will coordinate with to the company unit and police. Microcontroller will also send a signal to the relay which will turn off the car ignition & stop the car. The GSM Modem will receive the message. This message will then be transferred to the computer through the serial port. The employee name, employee id & cab position coordinates (longitude and latitude) get displayed on computer. Once the data is obtained on the computer, it can be used for further analysis. In this way the company unit keeps a track of the vehicle. This will be a much simpler and low cost technique compared to others.
Mobile Manipulation in Unstructured Environments: Perception, Planning, and Execution

Unstructured human environments present a substantial challenge to effective robotic operation. Mobile manipulation in human environments requires dealing with novel unknown objects, cluttered workspaces, and noisy sensor data. We present an approach to mobile pick and place in such environments using a combination of two-dimensional (2-D) and three-dimensional (3-D) visual processing, tactile and proprioceptive sensor data, fast motion planning, reactive control and monitoring, and reactive grasping. We demonstrate our approach by using a two-arm mobile manipulation system to pick and place objects. Reactive components allow our system to account for uncertainty arising from noisy sensors, inaccurate perception (e.g., object detection or registration), or dynamic changes in the environment. We also present a set of tools that allows our system to be easily configured within a short time for a new robotic system.
Resilience as a Positive Youth Development Construct: A Conceptual Review

The concept of resilience is reviewed from a range of disciplinary perspectives in this paper. Both broad and narrow definitions of resilience are highlighted and a working definition of resilience is proposed to inform research, policy and practice. Different psychological, social and ecological protective factors, particularly competence, optimism, and bonding to family and cultural beliefs are highlighted. Theoretical relationships between resilience and positive youth development are examined with an attempt to erase misunderstandings. Finally, how schools can promote resilience among students is discussed.
Memo No . 90 June 29 , 2018 Theory IIIb : Generalization in Deep Networks

A main puzzle of deep neural networks (DNNs) revolves around the apparent absence of “overfitting”, defined in this paper as follows: the expected error does not get worse when increasing the number of neurons or of iterations of gradient descent. This is surprising because of the large capacity demonstrated by DNNs to fit randomly labeled data and the absence of explicit regularization. Recent results by Srebro et al. provide a satisfying solution of the puzzle for linear networks used in binary classification. They prove that minimization of loss functions such as the logistic, the cross-entropy and the exp-loss yields asymptotic, “slow” convergence to the maximum margin solution for linearly separable datasets, independently of the initial conditions. Here we prove a similar result for nonlinear multilayer DNNs near zero minima of the empirical loss. The result holds for exponential-type losses but not for the square loss. In particular, we prove that the normalized weight matrix at each layer of a deep network converges to a minimum norm solution (in the separable case). Our analysis of the dynamical system corresponding to gradient descent of a multilayer network suggests a simple criterion for predicting the generalization performance of different zero minimizers of the empirical loss. This material is based upon work supported by the Center for Brains, Minds and Machines (CBMM), funded by NSF STC award CCF-1231216.  Generalization in Deep Networks Tomaso Poggio ∗1, Qianli Liao1, Brando Miranda1, Andrzej Banburski1, Xavier Boix1, and Jack Hidary2 1Center for Brains, Minds and Machines, MIT 2Alphabet (Google) X
Music and Cognitive Abilities

Does music make you smarter? Music listening and music lessons have been claimed to confer intellectual advantages. Any association between music and intellectual functioning would be notable only if the benefits apply reliably to nonmusical abilities and if music is unique in producing the effects. The available evidence indicates that music listening leads to enhanced performance on a variety of cognitive tests, but that such effects are shortterm and stem from the impact of music on arousal level and mood, which, in turn, affect cognitive performance; experiences other than music listening have similar effects. Music lessons in childhood tell a different story. They are associated with small but general and long-lasting intellectual benefits that cannot be attributed to obvious confounding variables such as family income and parents’ education. The mechanisms underlying this association have yet to be determined. music cognition; intelligence; cognitive development People’s eagerness for quick fixes can be seen in the seemingly irrational appeal of crash diets, get-rich-quick schemes, and getsmart-fast programs. Is the claim of music as a route to enhanced intelligence yet another self-improvement fantasy? In the pages that follow, I outline the origins of the claim and evaluate the available evidence. Intellectual benefits of exposure to music would be noteworthy if (a) they extend to nonmusical abilities, (b) they are systematic and reliable, and (c) they are more likely to result from hearing or playing music than from other activities. Unlike in other cultures, where virtually everyone participates in music making, musical experiences in Western society typically involve listening and, only in some cases, lessons and performing. Music listening is ubiquitous, both purposefully (e.g., listening to the radio) and incidentally (e.g., background music in stores and restaurants). By contrast, relatively few individuals take music lessons for several years. The consequences of music listening are likely to differ quantitatively and qualitatively from those of music lessons.
Mature HIV-1 capsid structure by cryo-electron microscopy and all-atom molecular dynamics

Retroviral capsid proteins are conserved structurally but assemble into different morphologies. The mature human immunodeficiency virus-1 (HIV-1) capsid is best described by a ‘fullerene cone’ model, in which hexamers of the capsid protein are linked to form a hexagonal surface lattice that is closed by incorporating 12 capsid-protein pentamers. HIV-1 capsid protein contains an amino-terminal domain (NTD) comprising seven α-helices and a β-hairpin, a carboxy-terminal domain (CTD) comprising four α-helices, and a flexible linker with a 310-helix connecting the two structural domains. Structures of the capsid-protein assembly units have been determined by X-ray crystallography; however, structural information regarding the assembled capsid and the contacts between the assembly units is incomplete. Here we report the cryo-electron microscopy structure of a tubular HIV-1 capsid-protein assembly at 8 Å resolution and the three-dimensional structure of a native HIV-1 core by cryo-electron tomography. The structure of the tubular assembly shows, at the three-fold interface, a three-helix bundle with critical hydrophobic interactions. Mutagenesis studies confirm that hydrophobic residues in the centre of the three-helix bundle are crucial for capsid assembly and stability, and for viral infectivity. The cryo-electron-microscopy structures enable modelling by large-scale molecular dynamics simulation, resulting in all-atom models for the hexamer-of-hexamer and pentamer-of-hexamer elements as well as for the entire capsid. Incorporation of pentamers results in closer trimer contacts and induces acute surface curvature. The complete atomic HIV-1 capsid model provides a platform for further studies of capsid function and for targeted pharmacological intervention.
A Simple Edit-Time Metaobject Protocol

We present a simple edit-time metaobject protocol (ETMOP) which runs as part of a code editor and enables metadata annotations to customize the rendering and editing of code. The protocol is layered, so that simple render/edit customizations are easy to implement, while more substantial customizations are still manageable. Experiments with a prototype implementation of the protocol as an Eclipse plug-in show that the ETMOP is flexible enough to allow easy customization of the rendering and editing of a number of annotations being used in current practice. The flexibility and performance of the prototype suggest that the ETMOP approach is viable and warrants further study.
Web-STAR: A Visual Web-based IDE for a Story Comprehension System

We present Web-STAR, an online platform for story understanding built on top of the STAR reasoning engine for STory comprehension through ARgumentation. The platform includes a web-based IDE, integration with the STAR system, and a web service infrastructure to support integration with other systems that rely on story understanding functionality to complete their tasks. The platform also delivers a number of “social” features, including a community repository for public story sharing with a built-in commenting system, and tools for collaborative story editing that can be used for team development projects and for educational purposes. Under consideration in Theory and Practice of Logic Programming (TPLP).
A Dual-Mode Wideband MIMO Cube Antenna With Magneto-Electric Dipoles

A four-port wideband diversity antenna capable of radiating two broadside patterns and two omnidirectional patterns is realized. This antenna is composed of five dual-polarized magneto-electric dipole elements mounted on the five faces of a grounded metallic cubic structure. By rotationally combining the four dual-polarized elements in a ring-configuration, θ-and φ-polarized waves can be excited, whereas x-and y-polarized orthogonal waves are excited by another radiating element mounted on the top of the whole metallic cube. The simulated common impedance bandwidth for these four modes is 38.7% with SWR from 1.77 GHz to 2.62 GHz, while the measured one is 39.1% with SWR from 1.73 GHz to 2.57 GHz. The mutual coupling between any two modes is lower than -30 dB which is low enough for practical usage. This antenna is suitable for wireless communication systems with a hemispherical coverage requirement.
LSTM for punctuation restoration in speech transcripts

The output of automatic speech recognition systems is generally an unpunctuated stream of words which is hard to process for both humans and machines. We present a two-stage recurrent neural network based model using long short-term memory units to restore punctuation in speech transcripts. In the first stage, textual features are learned on a large text corpus. The second stage combines textual features with pause durations and adapts the model to speech domain. Our approach reduces the number of punctuation errors by up to 16.9% when compared to a decision tree that combines hidden-event language model posteriors with inter-word pause information, having largest improvements in period restoration.