nils-herrmann/clean_scirepeval huggingface dataset:
3D Object Recognition and Pose Estimation for Multiple Objects Using Multi-Prioritized RANSAC and Model Updating

We present a feature-based framework that combines spatial feature clustering, guided sampling for pose generation, and model updating for 3D object recognition and pose estimation. Existing methods fails in case of repeated patterns or multiple instances of the same object, as they rely only on feature discriminability for matching and on the estimator capabilities for outlier rejection. We propose to spatially separate the features before matching to create smaller clusters containing the object. Then, hypothesis generation is guided by exploiting cues collected offand on-line, such as feature repeatability, 3D geometric constraints, and feature occurrence frequency. Finally, while previous methods overload the model with synthetic features for wide baseline matching, we claim that continuously updating the model representation is a lighter yet reliable strategy. The evaluation of our algorithm on challenging video sequences shows the improvement provided by our contribution.
Efficient parallel architecture of an intra-only scalable multi-layer HEVC encoder

The High Efficiency Video Coding (HEVC) standard enables meeting new video quality demands such as Ultra High Definition (UHD). Its scalable extension (SHVC) allows encoding simultaneously different representations of a video, organised in layers. Thanks to inter-layer predictions, SHVC provides bit-rate savings compared to the equivalent HEVC simulcast encoding. Therefore, SHVC seems a promising solution for both broadcast and storage applications. This paper proposes a multi-layer architecture of a pipelined software HEVC encoders with two main settings: a live setting for real-time encoding and a file setting for encoding with better fidelity. The proposed architecture provides a good trade-off between coding rate and coding efficiency achieving real-time performance of 1080p60 and 1600p30 sequences in 2× spatial scalability. Moreover, experimental results show more than a 26× and 300× speed-up for the file and live settings, respectively, with respect to the scalable reference software (SHM) in an intra-only configuration.
Computerized and virtual reality cognitive training for individuals at high risk of cognitive decline: systematic review of the literature.

The aim of this study was to assess the efficacy of cognitive training, specifically computerized cognitive training (CCT) and virtual reality cognitive training (VRCT), programs for individuals living with mild cognitive impairment (MCI) or dementia and therefore at high risk of cognitive decline. After searching a range of academic databases (CINHAL, PSYCinfo, and Web of Science), the studies evaluated (N = 16) were categorized as CCT (N = 10), VRCT (N = 3), and multimodal interventions (N = 3). Effect sizes were calculated, but a meta-analysis was not possible because of the large variability of study design and outcome measures adopted. The cognitive domains of attention, executive function, and memory (visual and verbal) showed the most consistent improvements. The positive effects on psychological outcomes (N = 6) were significant reductions on depressive symptoms (N = 3) and anxiety (N = 2) and improved perceived use of memory strategy (N = 1). Assessments of activities of daily living demonstrated no significant improvements (N = 8). Follow-up studies (N = 5) demonstrated long-term improvements in cognitive and psychological outcomes (N = 3), and the intervention groups showed a plateau effect of cognitive functioning compared with the cognitive decline experienced by control groups (N = 2). CCT and VRCT were moderately effective in long-term improvement of cognition for those at high risk of cognitive decline. Total intervention time did not mediate efficacy. Future research needs to improve study design by including larger samples, longitudinal designs, and a greater range of outcome measures, including functional and quality of life measures, to assess the wider effect of cognitive training on individuals at high risk of cognitive decline.
A Tutor Agent for MOBA Games

Digital games have become a key player in the entertainment industry, attracting millions of new players each year. In spite of that, novice players may have a hard time when playing certain types of games, such as MOBAs and MMORPGs, due to their steep learning curves and not so friendly online communities. In this paper, we present an approach to help novice players in MOBA games overcome these problems. An artificial intelligence agent plays alongside the player analysing his/her performance and giving tips about the game. Experiments performed with the game League of Legends show the potential of this approach.
Bioactive Components in Moringa Oleifera Leaves Protect against Chronic Disease

Moringa Oleifera (MO), a plant from the family Moringacea is a major crop in Asia and Africa. MO has been studied for its health properties, attributed to the numerous bioactive components, including vitamins, phenolic acids, flavonoids, isothiocyanates, tannins and saponins, which are present in significant amounts in various components of the plant. Moringa Oleifera leaves are the most widely studied and they have shown to be beneficial in several chronic conditions, including hypercholesterolemia, high blood pressure, diabetes, insulin resistance, non-alcoholic liver disease, cancer and overall inflammation. In this review, we present information on the beneficial results that have been reported on the prevention and alleviation of these chronic conditions in various animal models and in cell studies. The existing limited information on human studies and Moringa Oleifera leaves is also presented. Overall, it has been well documented that Moringa Oleifera leaves are a good strategic for various conditions associated with heart disease, diabetes, cancer and fatty liver.
A statistical study of magnetic tunnel junctions for high-density spin torque transfer-MRAM (STT-MRAM)

We have demonstrated a robust magnetic tunnel junction (MTJ) with a resistance-area product RA=8 Omega-mum2 that simultaneously satisfies the statistical requirements of high tunneling magnetoresistance TMR > 15sigma(Rp), write threshold spread sigma(Vw)/<Vw> <7.1%, breakdown-to-write voltage margin over 0.5 V, read-induced disturbance rate below 10-9, and sufficient write endurance, and is free of unwanted write-induced magnetic reversal. The statistics suggest that a 64 Mb chip at the 90-nm node is feasible.
Millimeter wave cellular channel models for system evaluation

The huge amount of (potentially) available spectrum makes millimeter wave (mmWave) a promising candidate for fifth generation cellular networks. Unfortunately, differences in the propagation environment as a function of frequency make it hard to make comparisons between systems operating at mmWave and microwave frequencies. This paper presents a simple channel model for evaluating system level performance in mmWave cellular networks. The model uses insights from measurement results that show mmWave is sensitive to blockages revealing very different path loss characteristics between line-of-sight (LOS) and non-line-of-sight (NLOS) links. The conventional path loss model with a single log-distance path loss function and a shadowing term is replaced with a stochastic path loss model with a distance-dependent LOS probability and two different path loss functions to account for LOS and NLOS links. The proposed model is used to compare microwave and mmWave networks in simulations. It is observed that mmWave networks can provide comparable coverage probability with a dense deployment, leading to much higher data rates thanks to the large bandwidth available in the mmWave spectrum.
Cross education and immobilisation: mechanisms and implications for injury rehabilitation.

Unilateral strength training produces an increase in strength of the contralateral homologous muscle group. This process of strength transfer, known as cross education, is generally attributed to neural adaptations. It has been suggested that unilateral strength training of the free limb may assist in maintaining the functional capacity of an immobilised limb via cross education of strength, potentially enhancing recovery outcomes following injury. Therefore, the purpose of this review is to examine the impact of immobilisation, the mechanisms that may contribute to cross education, and possible implications for the application of unilateral training to maintain strength during immobilisation.



Critical review of literature.



Search of online databases.



Immobilisation is well known for its detrimental effects on muscular function. Early reductions in strength outweigh atrophy, suggesting a neural contribution to strength loss, however direct evidence for the role of the central nervous system in this process is limited. Similarly, the precise neural mechanisms responsible for cross education strength transfer remain somewhat unknown. Two recent studies demonstrated that unilateral training of the free limb successfully maintained strength in the contralateral immobilised limb, although the role of the nervous system in this process was not quantified.



Cross education provides a unique opportunity for enhancing rehabilitation following injury. By gaining an understanding of the neural adaptations occurring during immobilisation and cross education, future research can utilise the application of unilateral training in clinical musculoskeletal injury rehabilitation.
Microstrip Antenna Array With Series Feeding Network Designed With the Use of Slot-Coupled Three-Way Power Divider

A novel concept of a series feeding network of a microstrip antenna array has been shown. The proposed feeding network utilizes a four-port slot coupler as a three-way power divider, which is composed of two microstrip lines appropriately coupled through a slot within a common ground plane. The proposed power divider is used for simultaneous power distribution between two consecutive linear subarrays and between two 4 × 1 linear arrays constituting a single 8 × 1 linear subarray, where equal-amplitude and out-of-phase signals are required. Such a solution allows for realization of antenna arrays, in which all linear subarrays designed with the use of the “through-element” series feeding technique are fed at their centers from single transmission lines. The theoretical analysis as well as measurement results of the 8 × 8 antenna array operating within 10.5-GHz frequency range are shown.
A Self-Correcting Projector

We describe a calibration and rendering technique for a projector that can render rectangular images under keystoned position. The projector utilizes a rigidly attached camera to form a stereo pair. We describe a very easy to use technique for calibration of the projector-camera pair using only black planar surfaces. We present an efficient rendering method to pre-warp images so that they appear correctly on the screen, and show experimental results.
Automatic classification of web images as UML diagrams

Our purpose in this research is to develop a methodology to automatically and efficiently classify web images as UML static diagrams, and to produce a computer tool that implements this function. The tool receives as input a bitmap file (in different formats) and tells whether the image corresponds to a diagram. The tool does not require that the images are explicitly or implicitly tagged as UML diagrams. The tool extracts graphical characteristics from each image (such as grayscale histogram, color histogram and elementary geometric forms) and uses a combination of rules to classify it. The rules are obtained with machine learning techniques (rule induction) from a sample of 19000 web images manually classified by experts. In this work we do not consider the textual contents of the images.
Challenges for Robust Trust and Reputation Systems

The purpose of trust and reputation systems is to strengthen the quality of markets and communities by providing an incentive for good behaviour and quality services, and by sanctioning bad behaviour and low quality services. However, trust and reputation systems will only be able to produce this effect when they are sufficiently robust against strategic manipulation or direct attacks. Currently, robustness analysis of TRSs is mostly done through simple simulated scenarios implemented by the TRS designers themselves, and this can not be considered as reliable evidence for how these systems would perform in a realistic environment. In order to set robustness requirements it is important to know how important robustness really is in a particular community or market. This paper discusses research challenges for trust and reputation systems, and proposes a research agenda for developing sound and reliable robustness principles and mechanisms for trust and reputation systems.
Developmental dyslexia: The visual attention span deficit hypothesis

The visual attention (VA) span is defined as the amount of distinct visual elements which can be processed in parallel in a multi-element array. Both recent empirical data and theoretical accounts suggest that a VA span deficit might contribute to developmental dyslexia, independently of a phonological disorder. In this study, this hypothesis was assessed in two large samples of French and British dyslexic children whose performance was compared to that of chronological-age matched control children. Results of the French study show that the VA span capacities account for a substantial amount of unique variance in reading, as do phonological skills. The British study replicates this finding and further reveals that the contribution of the VA span to reading performance remains even after controlling IQ, verbal fluency, vocabulary and single letter identification skills, in addition to phoneme awareness. In both studies, most dyslexic children exhibit a selective phonological or VA span disorder. Overall, these findings support a multi-factorial view of developmental dyslexia. In many cases, developmental reading disorders do not seem to be due to phonological disorders. We propose that a VA span deficit is a likely alternative underlying cognitive deficit in dyslexia.
A Software Product Line Process to Develop Agents for the IoT

One of the most important challenges of this decade is the Internet of Things (IoT), which aims to enable things to be connected anytime, anyplace, with anything and anyone, ideally using any path/network and any service. IoT systems are usually composed of heterogeneous and interconnected lightweight devices that support applications that are subject to change in their external environment and in the functioning of these devices. The management of the variability of these changes, autonomously, is a challenge in the development of these systems. Agents are a good option for developing self-managed IoT systems due to their distributed nature, context-awareness and self-adaptation. Our goal is to enhance the development of IoT applications using agents and software product lines (SPL). Specifically, we propose to use Self-StarMASMAS, multi-agent system) agents and to define an SPL process using the Common Variability Language. In this contribution, we propose an SPL process for Self-StarMAS, paying particular attention to agents embedded in sensor motes.
Design of the CMU sphinx-4 decoder

The decoder of the sphinx-4 speech recognition system incorporates several new design strategies which have not been used earlier in conventional decoders of HMM-based large vocabulary speech recognition systems. Some new design aspects include graph construction for multilevel parallel decoding with independent simultaneous feature streams without the use of compound HMMs, the incorporation of a generalized search algorithm that subsumes Viterbi and full-forward decoding as special cases, design of generalized language HMM graphs from grammars and language models of multiple standard formats, that toggles trivially from flat search structure to tree search structure etc. This paper describes some salient design aspects of the Sphinx-4 decoder and includes preliminary performance measures relating to speed and accu-
Combining Speech, Gaze, and Micro-gestures for the Multimodal Control of In-Car Functions

Modern cars are already incredibly smart environments today due to the sheer number of sensors and processors packed into a small space. Likewise, new technologies in human-computer interaction increasingly find their way inside, e.g. eye tracking, speech interaction and gesture recognition. The support of new modalities is promising a reduction of driver distraction and a better handling of an increasing number of functions offered by in-vehicle systems. With multiple modalities to choose from, which can be combined arbitrarily via multimodal fusion, drivers can make a free choice depending on the demands of the situation and their preferences. Our paper presents a prototype in-car system that allows car features (like turning lights and windows) to be controlled by combinations of speech, gaze, and micro-gestures. We propose an interaction concept, sketch our architecture based on a domain-independent multimodal dialogue platform, and draw some first conclusions on the outcome.
Design, Implementation, Simulation of a Pyramidal Horn Antenna Excited with Various Top-Hat Loaded Monopoles

This paper presents the design and simulation of a wideband, medium gain, light weight, wide bandwidth pyramidal horn antenna feed for microwave applications. The horn was designed using approximation method to calculate the gain in mat lab and simulated using CST microwave studio. The proposed antenna operates within 1-2 GHz (L-band). The horn is supported by a rectangular wave guide. It is linearly polarized and shows wide bandwidth with a gain of 15.3dB. The horn is excited with the monopole which is loaded with various top hat loading such as rectangular disc, circular disc, annular disc, L-type, T-type, Cone shape, U-shaped plates etc. and checked their performances for return loss as well as bandwidth. The circular disc and annular ring gives the low return loss and wide bandwidth as well as low VSWR. The annular ring gave good VSWR and return loss compared to the circular disc. The far field radiation pattern is obtained as well as Efield & H-field analysis for L-band pyramidal horn has been observed, simulated and optimized using CST Microwave Studio. The simulation results show that the pyramidal horn structure exhibits low VSWR as well as good radiation pattern over L-band.
Anxious or Angry? Effects of Discrete Emotions on the Perceived Helpfulness of Online Reviews

This paper explores the effects of emotions embedded in a seller review on its perceived helpfulness to readers. Drawing on frameworks in literature on emotion and cognitive processing, we propose that over and above a well-known negativity bias, the impact of discrete emotions in a review will vary, and that one source of this variance is reader perceptions of reviewers’ cognitive effort. We focus on the roles of two distinct, negative emotions common to seller reviews: anxiety and anger. In the first two studies, experimental methods were utilized to identify and explain the differential impact of anxiety and anger in terms of perceived reviewer effort. In the third study, seller reviews from Yahoo! Shopping web sites were collected to examine the relationship between emotional review content and helpfulness ratings. Our findings demonstrate the importance of examining discrete emotions in online word-of-mouth, and they carry important practical implications for consumers and online retailers.
Basal-like breast cancer: a critical review.

Recent gene expression profiling of breast cancer has identified specific subtypes with clinical, biologic, and therapeutic implications. The basal-like group of tumors is characterized by an expression signature similar to that of the basal/myoepithelial cells of the breast and is reported to have transcriptomic characteristics similar to those of tumors arising in BRCA1 germline mutation carriers. They are associated with aggressive behavior and poor prognosis, and typically do not express hormone receptors or HER-2 ("triple-negative" phenotype). Therefore, patients with basal-like cancers are unlikely to benefit from currently available targeted systemic therapy. Although basal-like tumors are characterized by distinctive morphologic, genetic, immunophenotypic, and clinical features, neither an accepted consensus on routine clinical identification and definition of this aggressive subtype of breast cancer nor a way of systematically classifying this complex group of tumors has been described. Different definitions are, therefore, likely to produce variable and contradictory results that may hamper consistent identification and development of treatment strategies for these tumors. In this review, we discuss definition, heterogeneity, morphologic spectrum, relation to BRCA1, and clinical significance of this important class of breast cancer.
Evolutionary Feature Selection

This thesis contains research on feature selection, in particular feature selection using evolutionary algorithms. Feature selection is motivated by increasing data-dimensionality and the need to construct simple induction models. A literature review of evolutionary feature selection is conducted. After that a abstract feature selection algorithm, capable of using many different wrappers, is constructed. The algorithm is configured using a low-dimensional dataset. Finally it is tested on a wide range of datasets, revealing both it’s abilities and problems. The main contribution is the revelation that classifier accuracy is not a sufficient metric for feature selection on high-dimensional data.
Stochastic modeling of a serial killer.

We analyze the time pattern of the activity of a serial killer, who during 12 years had murdered 53 people. The plot of the cumulative number of murders as a function of time is of "Devil's staircase" type. The distribution of the intervals between murders (step length) follows a power law with the exponent of 1.4. We propose a model according to which the serial killer commits murders when neuronal excitation in his brain exceeds certain threshold. We model this neural activity as a branching process, which in turn is approximated by a random walk. As the distribution of the random walk return times is a power law with the exponent 1.5, the distribution of the inter-murder intervals is thus explained. We illustrate analytical results by numerical simulation. Time pattern activity data from two other serial killers further substantiate our analysis.
Overexpression of Peptide-Encoding OsCEP6.1 Results in Pleiotropic Effects on Growth in Rice (O. sativa)

Plant peptide hormones play an important role in regulating plant developmental programs via cell-to-cell communication in a non-cell autonomous manner. To characterize the biological relevance of C-TERMINALLY ENCODED PEPTIDE (CEP) genes in rice, we performed a genome-wide search against public databases using a bioinformatics approach and identified six additional CEP members. Expression analysis revealed a spatial-temporal pattern of OsCEP6.1 gene in different tissues and at different developmental stages of panicle. Interestingly, the expression level of the OsCEP6.1 was also significantly up-regulated by exogenous cytokinin. Application of a chemically synthesized 15-amino acid OsCEP6.1 peptide showed that OsCEP6.1 had a negative role in regulating root and seedling growth, which was further confirmed by transgenic lines. Furthermore, the constitutive expression of OsCEP6.1 was sufficient to lead to panicle architecture and grain size variations. Scanning electron microscopy analysis revealed that the phenotypic variation of OsCEP6.1 overexpression lines resulted from decreased cell size but not reduced cell number. Moreover, starch accumulation was not significantly affected. Taken together, these data suggest that the OsCEP6.1 peptide might be involved in regulating the development of panicles and grains in rice.