nils-herrmann/clean_scirepeval huggingface dataset:
Skeleton Optical Spectra-Based Action Recognition Using Convolutional Neural Networks

This letter presents an effective method to encode the spatiotemporal information of a skeleton sequence into color texture images, referred to as skeleton optical spectra, and employs convolutional neural networks (ConvNets) to learn the discriminative features for action recognition. Such spectrum representation makes it possible to use a standard ConvNet architecture to learn suitable “dynamic” features from skeleton sequences without training millions of parameters afresh and it is especially valuable when there is insufficient annotated training video data. Specifically, the encoding consists of four steps: mapping of joint distribution, spectrum coding of joint trajectories, spectrum coding of body parts, and joint velocity weighted saturation and brightness. Experimental results on three widely used datasets have demonstrated the efficacy of the proposed method.
Bayesian Hierarchical Reinforcement Learning

We describe an approach to incorporating Bayesian priors in the MAXQ framework for hierarchical reinforcement learning (HRL). We define priors on the primitive environment model and on task pseudo-rewards. Since models for composite tasks can be complex, we use a mixed model-based/model-free learning approach to find an optimal hierarchical policy. We show empirically that (i) our approach results in improved convergence over non-Bayesian baselines, (ii) using both task hierarchies and Bayesian priors is better than either alone, (iii) taking advantage of the task hierarchy reduces the computational cost of Bayesian reinforcement learning and (iv) in this framework, task pseudo-rewards can be learned instead of being manually specified, leading to hierarchically optimal rather than recursively optimal policies.
Organizational behavior: affect in the workplace.

The study of affect in the workplace began and peaked in the 1930s, with the decades that followed up to the 1990s not being particularly fertile. Whereas job satisfaction generally continues to be loosely but not carefully thought of and measured as an affective state, critical work in the 1990s has raised serious questions about the affective status of job satisfaction in terms of its causes as well as its definition and measurement. Recent research has focused on the production of moods and emotions at work, with an emphasis, at least conceptually, on stressful events, leaders, work groups, physical settings, and rewards/punishment. Other recent research has addressed the consequences of workers' feelings, in particular, a variety of performance outcomes (e.g., helping behaviors and creativity). Even though recent interest in affect in the workplace has been intense, many theoretical and methodological opportunities and challenges remain.
Why Share Knowledge? The Influence of ICT on the Motivation for Knowledge Sharing

Information and communication technology (ICT) can enhance knowledge sharing by lowering temporal and spatial barriers between knowledge workers, and improving access to information about knowledge. Looking at ICT for knowledge sharing in this light, however, has limited value, because it ignores when and how the quality of knowledge sharing will be enhanced. A more encompassing perspective will come about if ICT is studied with relation to the motivation for knowledge sharing. The article explores this perspective by developing a theoretical model identifying and linking the variables involved. By presenting the outcomes of an empirical investigation, it also illustrates the differential effects of ICT on the motivation for knowledge sharing in different settings.
Effects of playing a violent video game as male versus female avatar on subsequent aggression in male and female players.

Previous research has shown that violent video games can increase aggression in players immediately after they play. The present research examines the effects of one subtle cue within violent video games that might moderate these effects-whether the avatar is male or female. One common stereotype is that males are more aggressive than females. Thus, playing a violent video game as a male avatar, compared to a female avatar, should be more likely to prime aggressive thoughts and inclinations in players and lead to more aggressive behavior afterwards. Male and female university students (N = 242) were randomly assigned to play a violent video game as a male or female avatar. After gameplay, participants gave an ostensible partner who hated spicy food hot sauce to eat. The amount of hot sauce given was used to measure aggression. Consistent with priming theory, results showed that both male and female participants who played a violent game as a male avatar behaved more aggressively afterwards than those who played as female avatar. The priming effects of the male avatar were somewhat stronger for male participants than for female participants, suggesting that male participants identified more with the male avatar than did the female participants. These results are particularly noteworthy because they are consistent with another recent experiment showing that playing a violent game as an avatar with a different stereotypically aggressive attribute (black skin color) stimulates more aggression than playing as an avatar without the stereotypically aggressive attribute (Yang et al., 2014,
FREEFORM ORIGAMI TESSELLATIONS BY GENERALIZING RESCH ’ S PATTERNS

In this research, we study a method to produce families of origami tessellations from given polyhedral surfaces. The resulting tessellated surfaces generalize the patterns proposed by Ron Resch and allow the construction of an origami tessellation that approximates a given surface. We will achieve these patterns by first constructing an initial configuration of the tessellated surfaces by separating each facets and inserting folded parts between them based on the local configuration. The initial configuration is then modified by solving the vertex coordinates to satisfy geometric constraints of developability, folding angle limitation, and local non-intersection. We propose a novel robust method for avoiding intersections between facets sharing vertices. Such generated polyhedral surfaces are not only applied to folding paper but also sheets of metal that does not allow 180◦ folding.
Analysis and Design of a Low-Cost Dual-Band Compact Circularly Polarized Antenna for GPS Application

A compact dual-coupled shorting probe (DCSP)-loaded patch antenna for dual-band global positioning system (GPS) application is presented. Due to the use of shorting loaded technique, the overall size of the antenna is only λo/8 · 8 × λo/8 · 8 × λo/19 , and high-permittivity substrate is replaced by low-cost F4b substrate. The DCSP technique that this communication proposed enables this antenna to resonate at L1/L2 GPS bands. Simulated and measured voltage standing-wave ratio (VSWR) is below 1.5 over both the bands, and boresight RHCP gain is 4.49 and 4.12 dBic over a large ground plane with 41 and 57 MHz 3-dB gain bandwidth at the L2 and L1 band, respectively. Therefore, the proposed antenna is a good candidate for low-cost, dual-band, and compact patch antenna.
Towards secure mobile cloud computing: A survey

Mobile cloud computing is gaining popularity among mobile users. The ABI Research predicts that the number of mobile cloud computing subscribers is expected to grow from 42.8 million (1.1% of total mobile users) in 2008 to 998 million (19% of total mobile users) in 2014. Despite the hype achieved by mobile cloud computing, the growth of mobile cloud computing subscribers is still below expectations. According to the recent survey conducted by the International Data Corporation, most IT Executives and CEOs are not interested in adopting such services due to the risks associatedwith security and privacy. The security threats have become a hurdle in the rapid adaptability of the mobile cloud computing paradigm. Significant efforts have been devoted in research organizations and academia to build securemobile cloud computing environments and infrastructures. In spite of the efforts, there are a number of loopholes and challenges that still exist in the security policies of mobile cloud computing. This literature review: (a)highlights the current state of the artwork proposed to securemobile cloud computing infrastructures, (b) identifies the potential problems, and (c) provides a taxonomy of the state of the art.
Can encrypted traffic be identified without port numbers, IP addresses and payload inspection?

Identifying encrypted application traffic represents an important issue for many network tasks including quality of service, firewall enforcement and security. Solutions should ideally be both simple – therefore efficient to deploy – and accurate. This paper presents a machine learning based approach employing simple Packet Header feature sets and statistical flow feature sets without using the IP addresses, source/destination ports and payload information to unveil encrypted application tunnels in network traffic. We demonstrate the effectiveness of our approach as a forensic analysis tool on two encrypted applications, Secure SHell (SSH) and Skype, using traces captured from entirely different networks. Results indicate that it is possible to identify encrypted traffic tunnels with high accuracy without inspecting payload, IP addresses and port numbers. Moreover, it is also possible to identify which services run in encrypted tunnels.
Sample Selection Bias as a Specification Error

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DRAFT: COMMENTS WELCOME BUT PLEASE DO NOT QUOTE

The Experimental Study of Adaptive User Interfaces Pat Langley (langley@isle.org) Institute for the Study of Learning and Expertise 2164 Staunton Court, Palo Alto, CA 94306 Michael Fehling (fehling@odc.stanford.edu) Organizational Dynamics Center, EES/OR Department Stanford University, Stanford, CA 94305  In this paper we examine some issues that arise in the experimental evaluation of adaptive user interfaces, which are computational decision aids that use machine learning to improve their interaction with users. We begin by reviewing the notion of an adaptive interface and presenting examples for a number of application areas. After this, we discuss plausible dependent measures of their behavior, including solution speed, solution quality, user satisfaction, and predictive accuracy. Next we turn to independent variables that are likely to in uence these measures, including the number of user interactions and characteristics of the system, the user, and the task at hand. In closing, we comment on the role that experimentation plays in the larger scienti c process.
Output Feedback Control of a Quadrotor UAV Using Neural Networks

In this paper, a new nonlinear controller for a quadrotor unmanned aerial vehicle (UAV) is proposed using neural networks (NNs) and output feedback. The assumption on the availability of UAV dynamics is not always practical, especially in an outdoor environment. Therefore, in this work, an NN is introduced to learn the complete dynamics of the UAV online, including uncertain nonlinear terms like aerodynamic friction and blade flapping. Although a quadrotor UAV is underactuated, a novel NN virtual control input scheme is proposed which allows all six degrees of freedom (DOF) of the UAV to be controlled using only four control inputs. Furthermore, an NN observer is introduced to estimate the translational and angular velocities of the UAV, and an output feedback control law is developed in which only the position and the attitude of the UAV are considered measurable. It is shown using Lyapunov theory that the position, orientation, and velocity tracking errors, the virtual control and observer estimation errors, and the NN weight estimation errors for each NN are all semiglobally uniformly ultimately bounded (SGUUB) in the presence of bounded disturbances and NN functional reconstruction errors while simultaneously relaxing the separation principle. The effectiveness of proposed output feedback control scheme is then demonstrated in the presence of unknown nonlinear dynamics and disturbances, and simulation results are included to demonstrate the theoretical conjecture.
On the Control of the Berkeley Lower Extremity Exoskeleton (BLEEX)

The first functional load-carrying and energetically autonomous exoskeleton was demonstrated at U.C. Berkeley, walking at the average speed of 1.3 m/s while carrying a 34 kg (75 lb) payload. Four fundamental technologies associated with the Berkeley Lower Extremity Exoskeleton (BLEEX) were tackled during the course of this project. These four core technologies include: the design of the exoskeleton architecture, control schemes, a body local area network (bLAN) to host the control algorithm and an on-board power unit to power the actuators, sensors and the computers. This article gives an overview of one of the control schemes. The analysis here is an extension of the classical definition of the sensitivity function of a system: the ability of a system to reject disturbances or the measure of system robustness. The control algorithm developed here increases the closed loop system sensitivity to its wearer’s forces and torques without any measurement from the wearer (such as force, position, or electromyogram signal). The control method has little robustness to parameter variations and therefore requires a relatively good dynamic model of the system. The tradeoffs between having sensors to measure human variables and the lack of robustness to parameter variation are described.
Do Deep Nets Really Need to be Deep?

Currently, deep neural networks are the state of the art on problems such as speech recognition and computer vision. In this paper we empirically demonstrate that shallow feed-forward nets can learn the complex functions previously learned by deep nets and achieve accuracies previously only achievable with deep models. Moreover, in some cases the shallow neural nets can learn these deep functions using the same number of parameters as the original deep models. On the TIMIT phoneme recognition and CIFAR-10 image recognition tasks, shallow nets can be trained that perform similarly to complex, well-engineered, deeper convolutional architectures.
Smartwatch-based activity recognition: A machine learning approach

Smartwatches and smartphones contain accelerometers and gyroscopes that sense a user's movements, and can help identify the activity a user is performing. Research into smartphone-based activity recognition has exploded over the past few years, but research into smartwatch-based activity recognition is still in its infancy. In this paper we compare smartwatch and smartphone-based activity recognition, and smartwatches are shown to be capable of identifying specialized hand-based activities, such as eating activities, which cannot be effectively recognized using a smartphone (e.g., smartwatches can identify the "drinking" activity with 93.3% accuracy while smartphones achieve an accuracy of only 77.3%). Smartwatch-based activity recognition can form the basis of new biomedical and health applications, including applications that automatically track a user's eating habits.
A comprehensive study on security attacks on SSL/TLS protocol

Secure Socket Layer (SSL) protocol was introduced in 1994 and was later renamed as transport layer security (TLS) protocol for securing transport layer. SSL/TLS protocol is used for securing communication on the network by ensuring data confidentiality, data integrity and authenticity between the communicating party. Authentication of the communicating party and securing transfer of data is done through certificates, key exchange and cipher suites. Security issues were found during evolutionary development of SSL/TLS protocol. The paper gives a detailed chronological order of attacks of past 22 years on SSL/TLS protocol.
Word Spotting in Cursive Handwritten Documents using Modified Character Shape Codes

There is a large collection of Handwritten English paper documents of Historical and Scientific importance. But paper documents are not recognised directly by computer. Hence the closest way of indexing these documents is by storing their document digital image. Hence a large database of document images can replace the paper documents. But the document and data corresponding to each image cannot be directly recognised by the computer. This paper applies the technique of word spotting using Modified Character Shape Code to Handwritten English document images for quick and efficient query search of words on a database of document images. It is different from other Word Spotting techniques as it implements two level of selection for word segments to match search query. First based on word size and then based on character shape code of query. It makes the process faster and more efficient and reduces the need of multiple pre-processing.
Learning to rank for information retrieval

This tutorial is concerned with a comprehensive introduction to the research area of learning to rank for information retrieval. In the first part of the tutorial, we will introduce three major approaches to learning to rank, i.e., the pointwise, pairwise, and listwise approaches, analyze the relationship between the loss functions used in these approaches and the widely-used IR evaluation measures, evaluate the performance of these approaches on the LETOR benchmark datasets, and demonstrate how to use these approaches to solve real ranking applications. In the second part of the tutorial, we will discuss some advanced topics regarding learning to rank, such as relational ranking, diverse ranking, semi-supervised ranking, transfer ranking, query-dependent ranking, and training data preprocessing. In the third part, we will briefly mention the recent advances on statistical learning theory for ranking, which explain the generalization ability and statistical consistency of different ranking methods. In the last part, we will conclude the tutorial and show several future research directions.
Punica granatum (pomegranate) and its potential for prevention and treatment of inflammation and cancer.

The last 7 years have seen over seven times as many publications indexed by Medline dealing with pomegranate and Punica granatum than in all the years preceding them. Because of this, and the virtual explosion of interest in pomegranate as a medicinal and nutritional product that has followed, this review is accordingly launched. The pomegranate tree, Punica granatum, especially its fruit, possesses a vast ethnomedical history and represents a phytochemical reservoir of heuristic medicinal value. The tree/fruit can be divided into several anatomical compartments: (1) seed, (2) juice, (3) peel, (4) leaf, (5) flower, (6) bark, and (7) roots, each of which has interesting pharmacologic activity. Juice and peels, for example, possess potent antioxidant properties, while juice, peel and oil are all weakly estrogenic and heuristically of interest for the treatment of menopausal symptoms and sequellae. The use of juice, peel and oil have also been shown to possess anticancer activities, including interference with tumor cell proliferation, cell cycle, invasion and angiogenesis. These may be associated with plant based anti-inflammatory effects, The phytochemistry and pharmacological actions of all Punica granatum components suggest a wide range of clinical applications for the treatment and prevention of cancer, as well as other diseases where chronic inflammation is believed to play an essential etiologic role.
Optimisation of the mover kinetic energy of a miniature linear actuator

The linear actuator presented in this paper is a core component of an electronically-controlled linear escapement mechanism. Its role is to unlock mechanical parts, its mover being used as a hammer. In this situation, the kinetic energy acquired by the mover at the position of the impact is a defining factor. The multiobjective optimisation presented in this paper targets the maximisation of said kinetic energy and the minimisation of the overall size of the actuator. In addition to the objective, the originality of this paper is that the control strategy as well as the behaviour of the guide of the mover are directly taken into account in the optimisation process.
A NOVEL DUAL-POLARIZED DOUBLE-RIDGED HORN ANTENNA FOR WIDEBAND APPLICATIONS

Dual-polarized antenna is widely used in communication systems such as ECM and DF systems. In this paper a novel doubleridged horn antenna with dual polarizations is introduced for frequency range of 8–18 GHz. Common double ridged horn antennas have single polarization over the operating frequency. We have used five layers polarizer to provide dual polarizations performance of the doubleridged horn antenna. In order to achieve dual polarizations the strips width, strips spacing and layers distances are optimized. It is worth mentioning that the corresponding VSWR of the antenna during the optimization process should be maintain below a certain value (VSWR< 2). Simulation results show that the proposed antenna yields dual polarizations performance and low VSWR over the operating frequency. We have used CST software for antenna simulation which is based on the finite integral technique.
Educating women about normal female genital appearance variation.

The study investigated the effectiveness of two online resources aimed at improving women's knowledge of the variation in normal female genital appearance and their attitudes towards their own genitals. The first consisted of a photographic array of normal female genitals and the second consisted of a video addressing digital airbrushing of women's genitals in media images. A sample of 136 female undergraduate students were randomly assigned to view the photographs, video, both the photographs and video, or neither. The video significantly increased women's perceptions of genital appearance diversity as well as awareness of digital airbrushing of genital images. Owing to relatively low levels of genital appearance concern, there was no effect of either resource on women's attitudes towards their own genitals; however, women who viewed the video indicated they would pass on their knowledge to help other women. Our results suggest that an educational video could be a useful tool.
Redefining e-learning readiness model

In order to bring out the highest advantages of e-learning, e-learning implementation need well-prepared strategic plan. It is expected that the implementation of E-learning is considered not only limited to investment and technology adoption, the use of e-learning should also be sustainable in the long term. Therefore, institutions need instruments and guideline in preparing all aspects towards e-learning implementation success. E-learning readiness becomes the answer to guide institutions in preparing the implementation. E-learning readiness cannot be separated from the maturity of all factors affecting its implementation. This study proposed model that not only identified factors to be prepared, but also provided a different view and a new perspective in determining prioritized factors in e-learning readiness. The model categorizes e-learning readiness factors into five domains and three layers based on levels of importance for institutions. Core layer includes organizations and academic domains, supporting layer covers the financial domain and the presentation layer consists of technology and content domain.