nils-herrmann/clean_scirepeval huggingface dataset:
Survey: Visual Navigation for Mobile Robot

There has been countless researches for vision based navigation and control in the field of autonomous mobile robot. Vision which was costlier in terms of processing power was not good enough for real time application in early days of robotics. But with new approaches, better computational power and effective algorithm, vision was area of interest for many researches for better navigation of robot which produced numerous research opportunities. For localization, automatic map construction, autonomous navigation, path following, inspection,
The Dual-Tree Complex Wavelet Transform – A Coherent Framework for Multiscale Signal and Image Processing

The dual-tree complex wavelet transform ( CWT) is a relatively recent enhancement of the discrete wavelet transform (DWT) with important additional properties: It is nearly shift-invariant and directionally selective in two and higher dimensions. It achieves this with a redundancy factor of only2 for d-dimensional signals, which is substantially lower than the undecimated DWT. The multidimensional dual-tree CWT is non-separable but is based on a computationally efficient, separable filter bank. This tutorial discusses the theory behind the dual-tree transform, shows how complex wavelets with good properties can be designed, and illustrates a range of applications in signal and image processing.
Pixel- and region-based image fusion with complex wavelets

A number of pixel-based image fusion algorithms (using averaging, contrast pyramids, the discrete wavelet transform and the dualtree complex wavelet transform (DT-CWT) to perform fusion) are reviewed and compared with a novel region-based image fusion method which facilitates increased flexibility with the definition of a variety of fusion rules. The DT-CWT method could dissolve an image into simpler data so we could analyze the characteristic which contained within the image and then fused it with other image that had already been decomposed and DT-CWT could reconstruct the image into its original form without losing its original data. The pixel-based and region-based rules are compared to know each of their capability and performance. Region-based methods have a number of advantages over pixel-based methods. These include: the ability to use more intelligent semantic fusion rules; and for regions with certain properties to be attenuated or accentuated.
Diagnosing and understanding the maxillary lip-tie (superior labial, the maxillary labial frenum) as it relates to breastfeeding.

Successful breastfeeding is dependent upon an infant's ability to correctly latch onto a mother's breast. If an infant is born with oral soft tissue abnormalities such as tongue-tie or lip-tie, breastfeeding may become challenging or impossible. During the oral evaluation of an infant presenting with breastfeeding problems, one area that is often overlooked and undiagnosed and, thus, untreated is the attachment of the upper lip to the maxillary gingival tissue. Historically, this tissue has been described as the superior labial frenum, median labial frenum, or maxillary labial frenum. These terms all refer to a segment of the mucous membrane in the midline of the upper lip containing loose connective tissue that inserts into the maxillary arch's loose, unattached gingival or tight, attached gingival tissue. There is no muscle contained within this tissue. In severe instances, this tissue may extend into the area behind the upper central incisors and incisive papilla. The author has defined and identified the restrictions of mobility of this tissue as a lip-tie, which reflects the clinical attachment of the upper lip to the maxillary arch. This article discusses the diagnosis and classifications of the lip-tie, as it affects an infant's latch onto the mother's breast. As more and more women choose to breastfeed, lip-ties must be considered as an impediment to breastfeeding, recognizing that they can affect a successful, painless latch and milk transfer.
Coding-based energy minimization for Phase Change Memory

We devise new coding methods to minimize Phase Change Memory write energy. Our method minimizes the energy required for memory rewrites by utilizing the differences between PCM read, set, and reset energies. We develop an integer linear programming method and employ dynamic programming to produce codes for uniformly distributed data. We also introduce data-aware coding schemes to efficiently address the energy minimization problem for stochastic data. Our evaluations show that the proposed methods result in up to 32% and 44% reduction in memory energy consumption for uniform and stochastic data respectively.
Mining Overlapping Communities and Inner Role Assignments through Bayesian Mixed-Membership Models of Networks with Context-Dependent Interactions

Community discovery and role assignment have been recently integrated into an unsupervised approach for the exploratory analysis of overlapping communities and inner roles in networks. However, the formation of ties in these prototypical research efforts is not truly realistic, since it does not account for a fundamental aspect of link establishment in real-world networks, i.e., the explicative reasons that cause interactions among nodes. Such reasons can be interpreted as generic requirements of nodes, that are met by other nodes and essentially pertain both to the nodes themselves and to their interaction contexts (i.e., the respective communities and roles).
 In this article, we present two new model-based machine-learning approaches, wherein community discovery and role assignment are seamlessly integrated and simultaneously performed through approximate posterior inference in Bayesian mixed-membership models of directed networks. The devised models account for the explicative reasons governing link establishment in terms of node-specific and contextual latent interaction factors. The former are inherently characteristic of nodes, while the latter are characterizations of nodes in the context of the individual communities and roles. The generative process of both models assigns nodes to communities with respective roles and connects them through directed links, which are probabilistically governed by their node-specific and contextual interaction factors. The difference between the proposed models lies in the exploitation of the contextual interaction factors. More precisely, in one model, the contextual interaction factors have the same impact on link generation. In the other model, the contextual interaction factors are weighted by the extent of involvement of the linked nodes in the respective communities and roles.
 We develop MCMC algorithms implementing approximate posterior inference and parameter estimation within our models.
 Finally, we conduct an intensive comparative experimentation, which demonstrates their superiority in community compactness and link prediction on various real-world and synthetic networks.
Correlated Q-Learning

There have been several attempts to design multiagent Q-learning algorithms capable of learning equilibrium policies in general-sum Markov games, just as Q-learning learns optimal policies in Markov decision processes. We introduce correlated Q-learning, one such algorithm based on the correlated equilibrium solution concept. Motivated by a fixed point proof of the existence of stationary correlated equilibrium policies in Markov games, we present a generic multiagent Q-learning algorithm of which many popular algorithms are immediate special cases. We also prove that certain variants of correlated (and Nash) Qlearning are guaranteed to converge to stationary correlated (and Nash) equilibrium policies in two special classes of Markov games, namely zero-sum and common-interest. Finally, we show empirically that correlated Q-learning outperforms Nash Q-learning, further justifying the former beyond noting that it is less computationally expensive than the latter.
Abstract linguistic structure correlates with temporal activity during naturalistic comprehension

Neurolinguistic accounts of sentence comprehension identify a network of relevant brain regions, but do not detail the information flowing through them. We investigate syntactic information. Does brain activity implicate a computation over hierarchical grammars or does it simply reflect linear order, as in a Markov chain? To address this question, we quantify the cognitive states implied by alternative parsing models. We compare processing-complexity predictions from these states against fMRI timecourses from regions that have been implicated in sentence comprehension. We find that hierarchical grammars independently predict timecourses from left anterior and posterior temporal lobe. Markov models are predictive in these regions and across a broader network that includes the inferior frontal gyrus. These results suggest that while linear effects are wide-spread across the language network, certain areas in the left temporal lobe deal with abstract, hierarchical syntactic representations.
Semimicro determination of cellulose in biological materials.

The quantitative determination of cellulose in biological materials presents some difficult problems. The moisture con~ent of cellulose varies with the relative humidity, so that accurate analyses require that moisture determinations be made under carefully standardized conditions. Cellulose ordinarily occurs in association with lignin, polyuronide hemicelluloses, and xylan cellulosans. Matrone, Ellis, and Maynard (4), who were interested primarily in the nutrition of ruminants, pointed ou~ that the xylan cellulosans are probably digested to the same extent by animals as true cellulose, and therefore recommended a modification of the method of Norman and Jenkins (5), which determines true cellulose and xylan eellulosans together, over the method of Kiirschner and Hanak (3) or the Crampton and Maynard (1) modification of this method, in which xylan cellulosans are partially or completely removed, so that cellulose is determined alone. All of these methods are laborious gravimetrie procedures in which the sample, ground to 40 mesh or finer, is repeatedly extracted with a series of hot solvent mixtures which remove lipides, proteins, lignin, and hemicelluloses. The residue is then dried at 105 ° to 110°C, and weighed, and cellulose is determined by the weight~ loss on ignition. Our objective was to develop a simple, rapid, colorimetric method for the determination of cellulose in a large number of cultures of cellulolytic bacteria and fungi. Since the procedure of Crampton and Maynard required much less time for extractions than that of Matrone, Ellis, and Maynard, it was chosen as a starting point. The sedimentation of the cellulose, extraction with the acetic acid/nitric acid reagent of Crampton and Maynard to remove lignin, hemicellulose, and xylosans, and final solution of ~he sample in 67% tt~SQ (v/v) were all carried out in a single 15 ml centrifuge tube. Cellulose was then determined on an appropriate dilution of the sulfuric acid solution by the anthrone method of Scott and Melvin (7).
Quantitative Assessment of Player Performance and Winner Prediction in ODI Cricket

The statistics of professional sports, including players and teams, provide numerous opportunities for research. Cricket is one of the most popular team sports, with billions of fans all over the world. In this thesis, we address two problems related to the One Day International (ODI) format of the game. First, we propose a novel method to predict the winner of ODI cricket matches using a team-composition based approach at the start of the match. Second, we present a method to quantitatively assess the performances of individual players in a match of ODI cricket which incorporates the game situations under which the players performed. The player performances are further used to predict the player of the match award. Players are the fundamental unit of a team. Players of one team work against the players of the opponent team in order to win a match. The strengths and abilities of the players of a team play a key role in deciding the outcome of a match. However, a team changes its composition depending on the match conditions, venue, and opponent team, etc. Therefore, we propose a novel dynamic approach which takes into account the varying strengths of the individual players and reflects the changes in player combinations over time. Our work suggests that the relative team strength between the competing teams forms a distinctive feature for predicting the winner. Modeling the team strength boils down to modeling individual players’ batting and bowling performances, forming the basis of our approach. We use career statistics as well as the recent performances of a player to model him. Using the relative strength of one team versus the other, along with two player-independent features, namely, the toss outcome and the venue of the match, we evaluate multiple supervised machine learning algorithms to predict the winner of the match. We show that, for our approach, the k-Nearest Neighbor (kNN) algorithm yields better results as compared to other classifiers. Players have multiple roles in a game of cricket, predominantly as batsmen and bowlers. Over the generations, statistics such as batting and bowling averages, and strike and economy rates have been used to judge the performance of individual players. These measures, however, do not take into consideration the context of the game in which a player performed across the course of a match. Further, these types of statistics are incapable of comparing the performance of players across different roles. Therefore, we present an approach to quantitatively assess the performances of individual players in a single match of ODI cricket. We have developed a new measure, called the Work Index, which represents the amount of work that is yet to be done by a team to achieve its target. Our approach incorporates game situations and the team strengths to measure the player contributions. This not only helps us in
Tutoring Robots - Multiparty Multimodal Social Dialogue with an Embodied Tutor

This project explores a novel experimental setup towards building spoken, multi-modally rich, and human-like multiparty tutoring agent. A setup is developed and a corpus is collected that targets the development of a dialogue system platform to explore verbal and nonverbal tutoring strategies in multiparty spoken interactions with embodied agents. The dialogue task is centered on two participants involved in a dialogue aiming to solve a card-ordering game. With the participants sits a tutor that helps the participants perform the task and organizes and balances their interaction. Different multimodal signals captured and auto-synchronized by different audio-visual capture technologies were coupled with manual annotations to build a situated model of the interaction based on the participants personalities, their temporally-changing state of attention, their conversational engagement and verbal dominance, and the way these are correlated with the verbal and visual feedback, turn-management, and conversation regulatory actions generated by the tutor. At the end of this chapter we discuss the potential areas of research and developments this work opens and some of the challenges that lie in the road ahead.
Flexibility in 21st Century Power Systems

All power systems have some inherent level of flexibility— designed to balance supply and demand at all times. Variability and uncertainty are not new to power systems because loads change over time and in sometimes unpredictable ways, and conventional resources fail unexpectedly. Variable renewable energy supply, however, can make this balance harder to achieve. Both wind and solar generation output vary significantly over the course of hours to days, sometimes in a predictable fashion, but often imperfectly forecasted.
An extremely wideband tapered balun for application in tightly coupled arrays

This paper presents the design of a single layer, compact, tapered balun with a >20:1 bandwidth and less than λ/17 in length at the lowest frequency of operation. The balun operates from 0.7GHz to over 15GHz. It can provide both impedance transformation as well as a balanced feed for tightly coupled arrays. Its performance is compared with that of a full-length balun operating over the same frequency band. There is a high degree of agreement between the two baluns.
Timeline trees: visualizing sequences of transactions in information hierarchies

In many applications transactions between the elements of an information hierarchy occur over time. For example, the product offers of a department store can be organized into product groups and subgroups to form an information hierarchy. A market basket consisting of the products bought by a customer forms a transaction. Market baskets of one or more customers can be ordered by time into a sequence of transactions. Each item in a transaction is associated with a measure, for example, the amount paid for a product.
 In this paper we present a novel method for visualizing sequences of these kinds of transactions in information hierarchies. It uses a tree layout to draw the hierarchy and a timeline to represent progression of transactions in the hierarchy. We have developed several interaction techniques that allow the users to explore the data. Smooth animations help them to track the transitions between views. The usefulness of the approach is illustrated by examples from several very different application domains.
Depression and poor glycemic control: a meta-analytic review of the literature.

Depression is common among patients with diabetes, but its relationship to glycemic control has not been systematically reviewed. Our objective was to determine whether depression is associated with poor glycemic control.



Medline and PsycINFO databases and published reference lists were used to identify studies that measured the association of depression with glycemic control. Meta-analytic procedures were used to convert the findings to a common metric, calculate effect sizes (ESs), and statistically analyze the collective data.



A total of 24 studies satisfied the inclusion and exclusion criteria for the meta-analysis. Depression was significantly associated with hyperglycemia (Z = 5.4, P < 0.0001). The standardized ES was in the small-to-moderate range (0.17) and was consistent, as the 95% CI was narrow (0.13-0.21). The ES was similar in studies of either type 1 or type 2 diabetes (ES 0.19 vs. 0.16) and larger when standardized interviews and diagnostic criteria rather than self-report questionnaires were used to assess depression (ES 0.28 vs. 0.15).



Depression is associated with hyperglycemia in patients with type 1 or type 2 diabetes. Additional studies are needed to establish the directional nature of this relationship and to determine the effects of depression treatment on glycemic control and the long-term course of diabetes.
Opinion Mining and Sentiment Polarity on Twitter and Correlation between Events and Sentiment

Twitter, as a social media is a very popular way of expressing opinions and interacting with other people in the online world. When taken in aggregation tweets can provide a reflection of public sentiment towards events. In this paper, we provide a positive or negative sentiment on Twitter posts using a well-known machine learning method for text categorization. In addition, we use manually labeled (positive/negative) tweets to build a trained method to accomplish a task. The task is looking for a correlation between twitter sentiment and events that have occurred. The trained model is based on the Bayesian Logistic Regression (BLR) classification method. We used external lexicons to detect subjective or objective tweets, added Unigram and Bigram features and used TF-IDF (Term Frequency-Inverse Document Frequency) to filter out the features. Using the FIFA World Cup 2014 as our case study, we used Twitter Streaming API and some of the official world cup hashtags to mine, filter and process tweets, in order to analyze the reflection of public sentiment towards unexpected events. The same approach, can be used as a basis for predicting future events.
[Prenatal and clinicopathological study of 6 cases of Pallister-Killian syndrome and review].

In multidisciplinary prenatal diagnosis centers, the search for a tetrasomy 12p mosaic is requested following the discovery of a diaphragmatic hernia in the antenatal period. Thus, the series of Pallister Killian syndromes (PKS: OMIM 601803) probably overestimate the prevalence of diaphragmatic hernia in this syndrome to the detriment of other morphological abnormalities.



A multicenter retrospective study was conducted with search for assistance from members of the French society for Fetal Pathology. For each identified case, we collected all antenatal and postnatal data. Antenatal data were compared with data from the clinicopathological examination to assess the adequacy of sonographic signs of PKS. A review of the literature on antenatal morphological anomalies in case of PKS completed the study.



Ten cases were referred to us: 7 had cytogenetic confirmation and 6 had ultrasound screening. In the prenatal as well as post mortem period, the most common sign is facial dysmorphism (5 cases/6). A malformation of limbs is reported in half of the cases (3 out of 6). Ultrasound examination detected craniofacial dysmorphism in 5 cases out of 6. We found 1 case of left diaphragmatic hernia. Our results are in agreement with the malformation spectrum described in the literature.



Some malformation associations could evoke a SPK without classical diaphragmatic hernia.
Hepta-band CPW bow-tie aperture antenna for WiFi (2.4 GHz and 5.5 GHz) and other bands

A Hepta-band Bowtie Antenna is proposed to function at two Wi-Fi bands and other bands. The following seven frequency bands are operational for the proposed antenna: 2.4, 3.9, 5.5, 6.7, 8.4, 10.2 and 12.8 GHz. The antenna structure consists of six loaded metallic strips in addition to interconnected loaded parasitic rectangular components near to the edge of the left side of the antenna. The loaded metallic strips resulted in five frequency bands and the interconnected parasitic components resulted in the remaining additional two frequency bands. The four metallic strips that are near the center of the antenna are symmetric while the remaining two metallic strips have different heights. All the metallic strips have the same width. The hepta-band antenna is simulated with HFSS to obtain the results of the return loss, radiation patterns and other antenna parameters. It will be shown from the simulation results that the antenna has seven operational frequency bands including the two Wi-Fi bands 2.4 and 5.5 GHz.