nils-herrmann/clean_scirepeval huggingface dataset:
Pose-Free Facial Landmark Fitting via Optimized Part Mixtures and Cascaded Deformable Shape Model

This paper addresses the problem of facial landmark localization and tracking from a single camera. We present a two-stage cascaded deformable shape model to effectively and efficiently localize facial landmarks with large head pose variations. For face detection, we propose a group sparse learning method to automatically select the most salient facial landmarks. By introducing 3D face shape model, we use procrustes analysis to achieve pose-free facial landmark initialization. For deformation, the first step uses mean-shift local search with constrained local model to rapidly approach the global optimum. The second step uses component-wise active contours to discriminatively refine the subtle shape variation. Our framework can simultaneously handle face detection, pose-free landmark localization and tracking in real time. Extensive experiments are conducted on both laboratory environmental face databases and face-in-the-wild databases. All results demonstrate that our approach has certain advantages over state-of-the-art methods in handling pose variations.
Advanced Persistent Threats - detection and defense

The term “Advanced Persistent Threat” refers to a well-organized, malicious group of people who launch stealthy attacks against computer systems of specific targets, such as governments, companies or military. The attacks themselves are long-lasting, difficult to expose and often use very advanced hacking techniques. Since they are advanced in nature, prolonged and persistent, the organizations behind them have to possess a high level of knowledge, advanced tools and competent personnel to execute them. The attacks are usually preformed in several phases - reconnaissance, preparation, execution, gaining access, information gathering and connection maintenance. In each of the phases attacks can be detected with different probabilities. There are several ways to increase the level of security of an organization in order to counter these incidents. First and foremost, it is necessary to educate users and system administrators on different attack vectors and provide them with knowledge and protection so that the attacks are unsuccessful. Second, implement strict security policies. That includes access control and restrictions (to information or network), protecting information by encrypting it and installing latest security upgrades. Finally, it is possible to use software IDS tools to detect such anomalies (e.g. Snort, OSSEC, Sguil).
Research on immunity-based intrusion detection technology for the Internet of Things

To detect the security threat in the Internet of Things (IoT), the mechanisms of artificial immune system are applied to the IoT environment. The application method of immune theory to the IoT environment is constructed. A method of intrusion detection for the IoT is proposed. Antigen, self and non-self in the IoT are simulated. Immature detector, mature detector and memory detector are defined to detect attacks in the IoT. To adapt the complicated and changeful environment of the IoT, detectors evolve dynamically to detect mutated, even new IoT attacks. The attack information library is defined. Attacks detected by detectors in the IoT are combined with the attack information library to alarm the manager of the IoT.
Reducing Click and Skip Errors in Search Result Ranking

Search engines provide result summaries to help users quickly identify whether or not it is worthwhile to click on a result and read in detail. However, users may visit non-relevant results and/or skip relevant ones. These actions are usually harmful to the user experience, but few considered this problem in search result ranking. This paper optimizes relevance of results and user click and skip activities at the same time. Comparing two equally relevant results, our approach learns to rank the one that users are more likely to click on at a higher position. Similarly, it demotes non-relevant web pages with high click probabilities. Experimental results show this approach reduces about 10%-20% of the click and skip errors with a trade off of 2.1% decline in nDCG@10.
Is Question Answering fit for the Semantic Web?: A survey

With the recent rapid growth of the Semantic Web (SW), the processes of searching and querying content that is both massive in scale and heterogeneous have become increasingly challenging. User-friendly interfaces, which can support end users in querying and exploring this novel and diverse, structured information space, are needed to make the vision of the SW a reality. We present a survey on ontology-based Question Answering (QA), which has emerged in recent years to exploit the opportunities offered by structured semantic information on the Web. First, we provide a comprehensive perspective by analyzing the general background and history of the QA research field, from influential works from the artificial intelligence and database communities developed in the 70s and later decades, through open domain QA stimulated by the QA track in TREC since 1999, to the latest commercial semantic QA solutions, before tacking the current state of the art in open userfriendly interfaces for the SW. Second, we examine the potential of this technology to go beyond the current state of the art to support end-users in reusing and querying the SW content. We conclude our review with an outlook for this novel research area, focusing in particular on the R&D directions that need to be pursued to realize the goal of efficient and competent retrieval and integration of answers from large scale, heterogeneous, and continuously evolving semantic sources. MODUL University of Vienna, Austria.
Search and Rescue Robotics

In order to summarize the status of rescue robotics, this chapter will cover the basic characteristics of disasters and their impact on robotic design, describe the robots actually used in disasters to date, promising robot designs (e.g., snakes, legged locomotion) and concepts (e.g., robot teams or swarms, sensor networks), methods of evaluation in benchmarks for rescue robotics, and conclude with a discussion of the fundamental problems and open issues facing rescue robotics, and their evolution from an interesting idea to widespread adoption. The Chapter will concentrate on the rescue phase, not recovery, with the understanding that capabilities for rescue can be applied to, and extended for, the recovery phase. The use of robots in the prevention and preparedness phases of disaster management are outside the scope of this chapter.
Subjectivity and Sentiment Analysis of Modern Standard Arabic and Arabic Microblogs

Though much research has been conducted on Subjectivity and Sentiment Analysis (SSA) during the last decade, little work has focused on Arabic. In this work, we focus on SSA for both Modern Standard Arabic (MSA) news articles and dialectal Arabic microblogs from Twitter. We showcase some of the challenges associated with SSA on microblogs. We adopted a random graph walk approach to extend the Arabic SSA lexicon using ArabicEnglish phrase tables, leading to improvements for SSA on Arabic microblogs. We used different features for both subjectivity and sentiment classification including stemming, part-of-speech tagging, as well as tweet specific features. Our classification features yield results that surpass Arabic SSA results in the literature.
Probabilistic reasoning by neurons

Our brains allow us to reason about alternatives and to make choices that are likely to pay off. Often there is no one correct answer, but instead one that is favoured simply because it is more likely to lead to reward. A variety of probabilistic classification tasks probe the covert strategies that humans use to decide among alternatives based on evidence that bears only probabilistically on outcome. Here we show that rhesus monkeys can also achieve such reasoning. We have trained two monkeys to choose between a pair of coloured targets after viewing four shapes, shown sequentially, that governed the probability that one of the targets would furnish reward. Monkeys learned to combine probabilistic information from the shape combinations. Moreover, neurons in the parietal cortex reveal the addition and subtraction of probabilistic quantities that underlie decision-making on this task.
Psilocybin can occasion mystical-type experiences having substantial and sustained personal meaning and spiritual significance

Although psilocybin has been used for centuries for religious purposes, little is known scientifically about its acute and persisting effects. This double-blind study evaluated the acute and longer-term psychological effects of a high dose of psilocybin relative to a comparison compound administered under comfortable, supportive conditions. The participants were hallucinogen-naïve adults reporting regular participation in religious or spiritual activities. Two or three sessions were conducted at 2-month intervals. Thirty volunteers received orally administered psilocybin (30 mg/70 kg) and methylphenidate hydrochloride (40 mg/70 kg) in counterbalanced order. To obscure the study design, six additional volunteers received methylphenidate in the first two sessions and unblinded psilocybin in a third session. The 8-h sessions were conducted individually. Volunteers were encouraged to close their eyes and direct their attention inward. Study monitors rated volunteers’ behavior during sessions. Volunteers completed questionnaires assessing drug effects and mystical experience immediately after and 2 months after sessions. Community observers rated changes in the volunteer’s attitudes and behavior. Psilocybin produced a range of acute perceptual changes, subjective experiences, and labile moods including anxiety. Psilocybin also increased measures of mystical experience. At 2 months, the volunteers rated the psilocybin experience as having substantial personal meaning and spiritual significance and attributed to the experience sustained positive changes in attitudes and behavior consistent with changes rated by community observers. When administered under supportive conditions, psilocybin occasioned experiences similar to spontaneously occurring mystical experiences. The ability to occasion such experiences prospectively will allow rigorous scientific investigations of their causes and consequences.
Evaluation for UV laser dicing process and its reliability for various designs of stack chip scale package

In the semiconductor market, the trend of packaging for die stacking technology moves to high density with thinner chips and higher capacity of memory devices. Moreover, the wafer sawing process is becoming more important for thin wafer, because its process speed tends to affect sawn quality and yield. ULK (Ultra low-k) device could require laser grooving application to reduce the stress during wafer sawing. Furthermore under 75um-thick thin low-k wafer is not easy to use the laser grooving application. So, UV laser dicing technology that is very useful tool for Si wafer was selected as full cut application, which has been being used on low-k wafer as laser grooving method.
Multi-sensor data fusion for hand tracking using Kinect and Leap Motion

Often presented as competing products on the market of low cost 3D sensors, the Kinect™ and the Leap Motion™ (LM) can actually be complementary in some scenario. We promote, in this paper, the fusion of data acquired by both LM and Kinect sensors to improve hand tracking performances. The sensor fusion is applied to an existing augmented reality system targeting the treatment of phantom limb pain (PLP) in upper limb amputees. With the Kinect we acquire 3D images of the patient in real-time. These images are post-processed to apply a mirror effect along the sagittal plane of the body, before being displayed back to the patient in 3D, giving him the illusion that he has two arms. The patient uses the virtual reconstructed arm to perform given tasks involving interactions with virtual objects. Thanks to the plasticity of the brain, the restored visual feedback of the missing arm allows, in some cases, to reduce the pain intensity. The Leap Motion brings to the system the ability to perform accurate motion tracking of the hand, including the fingers. By registering the position and orientation of the LM in the frame of reference of the Kinect, we make our system able to accurately detect interactions of the hand and the fingers with virtual objects, which will greatly improve the user experience. We also show that the sensor fusion nicely extends the tracking domain by supplying finger positions even when the Kinect sensor fails to acquire the depth values for the hand.
Ambiguity and Constraint in Mathematical Expression Recognition

The problem of recognizing mathematical expressions differs significantly from the recognition of standard prose. While in prose significant constraints can be put on the interpretation of a character by the characters immediately preceding and following it, few such simple constraints are present in a mathematical expression. In order to make the problem tractable, effective methods of recognizing mathematical expressions will need to put intelligent constraints on the possible interpretations. The authors present preliminary results on a system for the recognition of both handwritten and typeset mathematical expressions. While previous systems perform character recognition out of context, the current system maintains ambiguity of the characters until context can be used to disambiguate the interpretatiom In addition, the system limits the number of potentially valid interpretations by decomposing the expressions into a sequence of compatible convex regions. The system uses A-star to search for the best possible interpretation of an expression. We provide a new lower bound estimate on the cost to goal that improves performance significantly.
Classical Structured Prediction Losses for Sequence to Sequence Learning

There has been much recent work on training neural attention models at the sequencelevel using either reinforcement learning-style methods or by optimizing the beam. In this paper, we survey a range of classical objective functions that have been widely used to train linear models for structured prediction and apply them to neural sequence to sequence models. Our experiments show that these losses can perform surprisingly well by slightly outperforming beam search optimization in a like for like setup. We also report new state of the art results on both IWSLT’14 German-English translation as well as Gigaword abstractive summarization. On the large WMT’14 English-French task, sequence-level training achieves 41.5 BLEU which is on par with the state of the art.1
Treatment Algorithm of Complications after Filler Injection: Based on Wound Healing Process

Soft tissue filler injection has been a very common procedure worldwide since filler injection was first introduced for soft tissue augmentation. Currently, filler is used in various medical fields with satisfactory results, but the number of complications is increasing due to the increased use of filler. The complications after filler injection can occur at any time after the procedure, early and delayed, and they range from minor to severe. In this review, based on our experience and previously published other articles, we suggest a treatment algorithm to help wound healing and tissue regeneration and generate good aesthetic results with early treatment in response to the side effects of filler. Familiarity with the treatment of these rare complications is essential for achieving the best possible outcome.
Functional impact of global rare copy number variation in autism spectrum disorders

The autism spectrum disorders (ASDs) are a group of conditions characterized by impairments in reciprocal social interaction and communication, and the presence of restricted and repetitive behaviours. Individuals with an ASD vary greatly in cognitive development, which can range from above average to intellectual disability. Although ASDs are known to be highly heritable (∼90%), the underlying genetic determinants are still largely unknown. Here we analysed the genome-wide characteristics of rare (<1% frequency) copy number variation in ASD using dense genotyping arrays. When comparing 996 ASD individuals of European ancestry to 1,287 matched controls, cases were found to carry a higher global burden of rare, genic copy number variants (CNVs) (1.19 fold, P = 0.012), especially so for loci previously implicated in either ASD and/or intellectual disability (1.69 fold, P = 3.4 × 10-4). Among the CNVs there were numerous de novo and inherited events, sometimes in combination in a given family, implicating many novel ASD genes such as SHANK2, SYNGAP1, DLGAP2 and the X-linked DDX53–PTCHD1 locus. We also discovered an enrichment of CNVs disrupting functional gene sets involved in cellular proliferation, projection and motility, and GTPase/Ras signalling. Our results reveal many new genetic and functional targets in ASD that may lead to final connected pathways.
Stylized augmented reality for improved immersion

The ultimate goal of augmented reality is to provide the user with a view of the surroundings enriched by virtual objects. Practically all augmented reality systems rely on standard real-time rendering methods for generating the images of virtual scene elements. Although such conventional computer graphics algorithms are fast, they often fail to produce sufficiently realistic renderings. The use of simple lighting and shading methods, as well as the lack of knowledge about actual lighting conditions in the real surroundings, cause virtual objects to appear artificial. In this paper, we propose an entirely novel approach for generating augmented reality images in video see-through systems. Our method is based on the idea of applying stylization techniques for reducing the visual realism of both the camera image and the virtual graphical objects. A special painterly image filter is applied to the camera video stream. The virtual scene elements are generated using a non-photorealistic rendering method. Since both the camera image and the virtual objects are stylized in a corresponding "cartoon-like" or "sketch-like" way, they appear very similar. As a result, the graphical objects seem to be an actual part of the real surroundings. We describe both the new painterly filter for the camera image and the non-photorealistic rendering method for virtual scene elements, which has been adapted for this purpose. Both are fast enough for generating augmented reality images in real-time and are highly customizable. The results obtained using our method, are very promising and show that it improves immersion in augmented reality.
Calcium signaling in dendritic spines.

Calcium (Ca(2+)) is a ubiquitous signaling molecule that accumulates in the cytoplasm in response to diverse classes of stimuli and, in turn, regulates many aspects of cell function. In neurons, Ca(2+) influx in response to action potentials or synaptic stimulation triggers neurotransmitter release, modulates ion channels, induces synaptic plasticity, and activates transcription. In this article, we discuss the factors that regulate Ca(2+) signaling in mammalian neurons with a particular focus on Ca(2+) signaling within dendritic spines. This includes consideration of the routes of entry and exit of Ca(2+), the cellular mechanisms that establish the temporal and spatial profile of Ca(2+) signaling, and the biophysical criteria that determine which downstream signals are activated when Ca(2+) accumulates in a spine. Furthermore, we also briefly discuss the technical advances that made possible the quantitative study of Ca(2+) signaling in dendritic spines.
A new tunable SAW filter circuit for reconfigurable RF

In recent years, the mobile data traffic is increasing and many more frequency bands have been employed in cellular handsets. A simple π type tunable band elimination filter (BEF) with switching function has been developed using a wideband tunable surface acoustic wave (SAW) resonator circuit. The frequency of BEF is tuned approximately 31% by variable capacitors without spurious. In LTE low band, the arrangement of TX and RX frequencies is to be reversed in Band 13, 14 and 20 compared with the other bands. The steep edge slopes of the developed filter can be exchanged according to the resonance condition and switching. With combining the TX and RX tunable BEFs and the small sized broadband circulator, a new tunable duplexer has been fabricated, and its TX-RX isolation is proved to be more than 50dB in LTE low band operations.
An Approach for Using CMMI in Agile Software Development Assessments : Experiences from Three Case Studies

Software development organizations are increasingly interested in the possibility of adopting agile development methods. Organizations that have been employing the Capability Maturity Model (CMM/CMMI) for making improvements are now changing their software development processes towards agility. By deploying agile methods, these organizations are making an investment the success of which needs to be proven. However, CMMI does not always support interpretations in an agile context. Consequently, assessments should be implemented in a manner that takes the agile context into account, while still producing useful results. This paper proposes an approach for agile software development assessment using CMMI and describes how this approach was used for software process improvement purposes in organizations that had either been planning to use or were using agile software development methods.
Study on Sequential Feeding Networks for Subarrays of Circularly Polarized Elliptical Dielectric Resonator Antenna

Circularly polarized (CP) dielectric resonator antenna (DRA) subarrays have been numerically studied and experimentally verified. Elliptical CP DRA is used as the antenna element, which is excited by either a narrow slot or a probe. The elements are arranged in a 2 by 2 subarray configuration and are excited sequentially. In order to optimize the CP bandwidth, wideband feeding networks have been designed. Three different types of feeding network are studied; they are parallel feeding network, series feeding network and hybrid ring feeding network. For the CP DRA subarray with hybrid ring feeding network, the impedance matching bandwidth (S11<-10 dB) and 3-dB AR bandwidth achieved are 44% and 26% respectively
Mechanical design and motion control of a hand exoskeleton for rehabilitation

Hand injuries are a frequent problem. The great amount of hand injuries is not only a problem for the affected people but economic consequences follow because rehabilitation takes a long time. To improve therapy results and reduce cost of rehabilitation a hand exoskeleton was developed. For research on control algorithms and rehabilitation programs a prototype supporting all four degrees of freedom of one finger was built (s. . In view of the fact that a lot of hand injuries affect only one finger, this prototype could already be functional in physical therapy. A robust sliding mode controller was proposed for motion control of the hand exoskeleton. The performance of the controller was evaluated for step response. In a second experiment varied forces where applied during the sensor was set to hold a constant position. Finally the controller was set to follow a complete trajectory.