nils-herrmann/clean_scirepeval huggingface dataset:
Solving the team orienteering problem using effective multi-start simulated annealing

The team orienteering problem (TOP) is known as an NP-complete problem. A set of locations is provided and a score is collected from the visit to each location. The objective is to maximize the total score given a fixed time limit for each available tour. Given the computational complexity of this problem, a multi-start simulated annealing (MSA) algorithm which combines a simulated annealing (SA) based meta-heuristic with a multi-start hill climbing strategy is proposed to solve TOP. To verify the developed MSA algorithm, computational experiments are performed on well-known benchmark problems involving numbers of locations ranging between 42 and 102. The experimental results demonstrate that the multi-start hill eta-heuristics ulti-start simulated annealing climbing strategy can significantly improve the performance of the traditional single-start SA. Meanwhile, the proposed MSA algorithm is highly effective compared to the state-of-the-art meta-heuristics on the same benchmark instances. The proposed MSA algorithm obtained 135 best solutions to the 157 benchmark problems, including five new best solutions. In terms of both solution quality and computational expense, this study successfully constructs a high-performance method for solving this challenging problem.
Learning to Detect Misleading Content on Twitter

The publication and spread of misleading content is a problem of increasing magnitude, complexity and consequences in a world that is increasingly relying on user-generated content for news sourcing. To this end, multimedia analysis techniques could serve as an assisting tool to spot and debunk misleading content on the Web. In this paper, we tackle the problem of misleading multimedia content detection on Twitter in real time. We propose a number of new features and a new semi-supervised learning event adaptation approach that helps generalize the detection capabilities of trained models to unseen content, even when the event of interest is of different nature compared to that used for training. Combined with bagging, the proposed approach manages to outperform previous systems by a significant margin in terms of accuracy. Moreover, in order to communicate the verification process to end users, we develop a web-based application for visualizing the results.
Asian rhinoplasty.

Asian rhinoplasty is one of the most challenging ethnic rhinoplasties that plastic surgeons perform because of the thick skin and soft-tissue envelope. There are three goals: pleasing the patient, achieving an aesthetically appealing result, and preserving a natural look. Of these goals, the most arduous is to satisfy the patient, as many patients have unrealistic goals and may desire an extremely narrow Western nose. Furthermore, patients may bring in celebrity or model photographs and expect that outcome, even though it may not be suitable for their face or appear over-resected and pinched. The surgeon's most important task is to attempt to persuade the patient that this result is nonfunctional, esthetically unfit, and difficult to achieve with their skin. For ethnic surgery, a clear and thorough grasp of nasal anatomy, function, and surgical techniques is paramount. An extensive preoperative discussion, including expectations, outcomes, and a detailed list of potential complications with the patient can prevent physician-patient miscommunication. Before surgery, it is essential to review the office examination, previous operative summary, photographs, nasal analysis sheet, problem list, and plan before proceeding with the surgical treatment.
A unified theory of development: a dialectic integration of nature and nurture.

The understanding of nature and nurture within developmental science has evolved with alternating ascendance of one or the other as primary explanations for individual differences in life course trajectories of success or failure. A dialectical perspective emphasizing the interconnectedness of individual and context is suggested to interpret the evolution of developmental science in similar terms to those necessary to explain the development of individual children. A unified theory of development is proposed to integrate personal change, context, regulation, and representational models of development.
Hand Movements and Gestures Characterization Using Quaternion Dynamic Time Warping Technique

Trends show that wearable devices with high-range sensors offer new business opportunities in enriching user experience in swing-based outdoor games, such as tennis, golf, and/or indoor gaming applications. Such applications providing insights into a player's abilities to play these games require methods that efficiently distinguish and capture intricacies of hand movements and/or gestures. In this paper, we show that quaternions-based dynamic time warping (QDTW) technique provides an efficient means for characterizing different arm/hand movements and gestures. A complete methodology and results for the pursued case study of outdoor tennis game are provided in this paper. We propose a new and unique approach for training data for various tennis shots and then using DTW and QDTW at the two levels of a hierarchical classifier for classification of an incoming tennis shot. The achieved accuracy for tennis shots detection is more than 99% and that for classification is 90%. Furthermore, the concept of consistency in a player's shots and how a played shot differs from a professional's similar shot are considered to suggest recommendations for improvement to the player.
Ka-Band Rectangular Waveguide to Suspended Stripline Transition

A Ka-band transition between a rectangular waveguide and a suspended stripline (SSL) is proposed. It uses a configuration in which the SSL substrate is perpendicular to the waveguide main axis. A patch printed on the SSL substrate is used to match the characteristic impedance of the waveguide. A set of formulas to facilitate the design of the element is presented. A prototype of the transition was fabricated and the experimental results agree well with the simulations. The proposed element can have the input matching below -15 dB in a 13% bandwidth while maintaining the insertion loss below 0.22 dB.
Hierarchical Prosody Conversion Using Regression-Based Clustering for Emotional Speech Synthesis

This paper presents an approach to hierarchical prosody conversion for emotional speech synthesis. The pitch contour of the source speech is decomposed into a hierarchical prosodic structure consisting of sentence, prosodic word, and subsyllable levels. The pitch contour in the higher level is encoded by the discrete Legendre polynomial coefficients. The residual, the difference between the source pitch contour and the pitch contour decoded from the discrete Legendre polynomial coefficients, is then used for pitch modeling at the lower level. For prosody conversion, Gaussian mixture models (GMMs) are used for sentence- and prosodic word-level conversion. At subsyllable level, the pitch feature vectors are clustered via a proposed regression-based clustering method to generate the prosody conversion functions for selection. Linguistic and symbolic prosody features of the source speech are adopted to select the most suitable function using the classification and regression tree for prosody conversion. Three small-sized emotional parallel speech databases with happy, angry, and sad emotions, respectively, were designed and collected for training and evaluation. Objective and subjective evaluations were conducted and the comparison results to the GMM-based method for prosody conversion achieved an improved performance using the hierarchical prosodic structure and the proposed regression-based clustering method.
Railway accidents analysis based on the improved algorithm of the maximal information coefficient

The maximal information coefficient (MIC), a measure of dependence for two-variable relationships, can be used to discover the relationships between two variables in big data. This paper proposes a new mathematical program model for calculating the value of MIC. A corresponding efficient algorithm is designed to solve the model in big data environment. In order to illustrate the validity of the proposed algorithm, the proposed algorithm is applied into the analysis of railway accidents data. Experimental results show that the proposed algorithm could find important relationships between two variables from big data. And some factors influencing accidents are identified from many factors. In addition, compared with the algorithm proposed by Reshef et al. in 2011, the proposed algorithm has lower time complexity and needs less computation time. Hence the proposed algorithm is more suitable for big data environment.
Probabilistic models in noisy environments : and their application to a visual prosthesis for the blind/

In recent years, probabilistic models have become fundamental techniques in machine learning. They are successfully applied in various engineering problems, such as robotics, biometrics, brain-computer interfaces or artificial vision, and will gain in importance in the near future. This work deals with the difficult, but common situation where the data is, either very noisy, or scarce compared to the complexity of the process to model. We focus on latent variable models, which can be formalized as probabilistic graphical models and learned by the expectation-maximization algorithm or its variants (e.g., variational Bayes). After having carefully studied a non-exhaustive list of multivariate kernel density estimators, we established that in most applications locally adaptive estimators should be preferred. Unfortunately, these methods are usually sensitive to outliers and have often too many parameters to set. Therefore, we focus on finite mixture models, which do not suffer from these drawbacks provided some structural modifications. Two questions are central in this dissertation: (i) how to make mixture models robust to noise, i.e. deal efficiently with outliers, and (ii) how to exploit side-channel information, i.e. additional information intrinsic to the data. In order to tackle the first question, we extend the training algorithms of the popular Gaussian mixture models to the Student-t mixture models. The Student-t distribution can be viewed as a heavy-tailed alternative to the Gaussian distribution, the robustness being tuned by an extra parameter, the degrees of freedom. Furthermore, we introduce a new variational Bayesian algorithm for learning Bayesian Student-t mixture models. This algorithm leads to very robust density estimators and clustering. To address the second question, we introduce manifold constrained mixture models. This new technique exploits the information that the data are living on a manifold of lower dimension than the dimension of the feature space. Taking the implicit geometrical data arrangement into account results in better generalization on unseen data. Finally, we show that the latent variable framework used for learning mixture models can be extended to construct probabilistic regularization networks, such as the Relevance Vector Machines. Subsequently, we make use of these methods in the context of an optic nerve visual prosthesis to restore partial vision to blind people of whom the optic nerve is still functional. Although visual sensations
A Novel BiQuad Antenna for 2 . 4 GHz Wireless Link Application : A Proposed Design

An ISM Band (2.4GHz) Design for a Biquad Antenna with Reflector base is presented for satisfying the ISM Band point-to-point link Applications in this paper. This proposed design can be used for Reception as well as Transmission in Wi-Fi's, WLAN, Bluetooth and even Zigbee links. The proposed antenna consists of two squares of the same size of 1⁄4 wavelength as a radiating element and a metallic plate or grid as reflector. This antenna has a beam width of about 70 degrees and a gain in the order of 10-12 dBi. A Prototype of this Antenna is designed and constructed. Parametric study is performed to understand the characterstics of the proposed antenna. Almost good antenna performances such as radiation patterns and antenna gains over the operating bands have been observed and simulated peak gain of the antenna is 10.7 dBi at 2439MHz. The simulated return loss is-35dB, whereas simulated SWR is 1.036 over the operating bands. The Biquad antenna is simple to build and offers good directivity and gain for Point-to-Point communications . It consists of two squares of the same size of 1⁄4 wavelength as a radiating element and a metallic plate or grid as reflector. This antenna has a beam width of about 70 degrees and a gain in the order of 10-12 dBi. It can be used as stand-alone antenna or as feeder for a Parabolic Dish . The polarization is such that looking at the antenna from the front, if the squares are placed side by side the polarization is vertical. The element is made from a length of 2mm thick copper wire, bent into the appropriate shape. Note that the length of each " side " should be close to 31 mm as possible, when measured from center to center of the wire [4-5]. The Details of the proposed antenna design are described in the paper, and simulated results are presented and discussed in the following sections.
OpenMM: An Open-Source Multimodal Feature Extraction Tool

The primary use of speech is in face-to-face interactions and situational context and human behavior therefore intrinsically shape and affect communication. In order to usefully model situational awareness, machines must have access to the same streams of information humans have access to. In other words, we need to provide machines with features that represent each communicative modality: face and gesture, voice and speech, and language.  an open-source multimodal feature extraction tool. We build upon existing open-source repositories to present the first publicly available tool for multimodal feature extraction. The tool provides a pipeline for researchers to easily extract visual and acoustic features. In addition, the tool also performs automatic speech recognition (ASR) and then uses the transcripts to extract linguistic features. We evaluate the OpenMM’s multimodal feature set on deception, depression and sentiment classification tasks and show its performance is very promising. This tool provides researchers with a simple way of extracting multimodal features and consequently a richer and more robust feature representation for machine learning tasks.
LTSG: Latent Topical Skip-Gram for Mutually Improving Topic Model and Vector Representations

Topic models have been widely used in discovering latent topics which are shared across documents in text mining. Vector representations, word embeddings and topic embeddings, map words and topics into a low-dimensional and dense real-value vector space, which have obtained high performance in NLP tasks. However, most of the existing models assume the results trained by one of them are perfect correct and used as prior knowledge for improving the other model. Some other models use the information trained from external large corpus to help improving smaller corpus. In this paper, we aim to build such an algorithm framework that makes topic models and vector representations mutually improve each other within the same corpus. An EM-style algorithm framework is employed to iteratively optimize both topic model and vector representations. Experimental results show that our model outperforms state-of-the-art methods on various NLP tasks.
Superstrate-Enhanced Ultrawideband Tightly Coupled Array With Resistive FSS

An efficient low-profile ultrawideband tightly coupled array employing a resistive frequency selective surface (FSS) and a superstrate is introduced. The FSS suppresses destructive ground plane interference, resulting in an increase in the array bandwidth by a factor greater than two. A superstrate is used to alleviate losses due to the resistive FSS. It is shown that a properly designed superstrate reduces losses by about 2.5 dB. The proposed array, which employs tightly coupled bowtie elements, achieves very low profile (0.055λlow) , 21:1 bandwidth, and radiation efficiency greater than 73% across the band. This paper presents the analysis and design of the array, particularly the FSS and superstrate. To validate the design, measurements of a prototype array are presented as well.
The Perspective-3-Point Problem When Using a Planar Mirror

The Perspective-3-Point problem (P3P) is a classical and fundamental problem in computer vision. All possible solution sets for the P3P problem are from 1 to 4 solutions. In this paper, we propose a very simple way to reduce the ambiguity of numbers of possible solutions in P3P using a planar mirror. For three reference points, if they and their reflections in a planar mirror are both observed, we may obtain two P3P problems: One is from the three original reference points, and the other is from their reflections. A trivial procedure may be suggested: Solve for each of the two P3P problems, and then find the intersections of the two solution sets. Different from the trivial case, we propose an efficient method which employs the ratio relations of the unknowns in the two P3P problems. The ratio relations are arise from mirror reflection, and can be easily determined before solving the two P3P problems. With the ratio relations, a system of 6 equations with 3 unknowns can be determined. To solve the over-constraint problem, we utilize an efficient algorithm by finding all local minima of least-squares residual. Experiments validate our approach.
Achieving high navigation accuracy using inertial navigation systems in autonomous underwater vehicles

This paper presents a summary of the current state-of-the-art in INS-based navigation systems in AUVs manufactured by Bluefin Robotics Corporation. A detailed description of the successful integrations of the Kearfott T-24 Ring Laser Gyro and the IXSEA PHINS III Fiber Optic Gyro into recent Bluefin Robotics AUVs is presented. Both systems provide excellent navigation accuracy for high quality data acquisition. This paper provides a comprehensive assessment of the primary advantages and disadvantages of each INS, paying particular attention to navigation accuracy, power draw, physical size, and acoustic radiated noise. Additionally, a brief presentation of a recently integrated Synthetic Aperture Sonar system will be used to highlight how critical a high-performance INS is to hydrographic, mine countermeasures, and other SAS applications.
Neural measures of the causal role of observers’ facial mimicry on visual working memory for facial expressions

Simulation models of facial expressions propose that sensorimotor regions may increase the clarity of facial expressions representations in extrastriate areas. We monitored the event-related potential marker of visual working memory (VWM) representations, namely the sustained posterior contralateral negativity (SPCN), also termed contralateral delay activity, while participants performed a change detection task including to-be-memorized faces with different intensities of anger. In one condition participants could freely use their facial mimicry during the encoding/VWM maintenance of the faces while in a different condition participants had their facial mimicry blocked by a gel. Notably, SPCN amplitude was reduced for faces in the blocked mimicry condition when compared to the free mimicry condition. This modulation interacted with the empathy levels of participants such that only participants with medium-high empathy scores showed such reduction of the SPCN amplitude when their mimicry was blocked. The SPCN amplitude was larger for full expressions when compared to neutral and subtle expressions, while subtle expressions elicited lower SPCN amplitudes than neutral faces. These findings provide evidence of a functional link between mimicry and VWM for faces and further shed light on how this memory system may receive feedbacks from sensorimotor regions during the processing of facial expressions.
Unpacking Spear Phishing Susceptibility

We report the results of a field experiment where we sent to over 1200 university students an email or a Facebook message with a link to (non-existing) party pictures from a non-existing person, and later asked them about the reasons for their link clicking behavior. We registered a significant difference in clicking rates: 20% of email versus 42.5% of Facebook recipients clicked. The most frequently reported reason for clicking was curiosity (34%), followed by the explanations that the message fit recipient’s expectations (27%). Moreover, 16% thought that they might know the sender. These results show that people’s decisional heuristics are relatively easy to misuse in a targeted attack, making defense especially challenging.
A localization and tracking scheme for target gangs based on big data of Wi-Fi locations

The modeling and analysis of target gangs’ usual haunts plays a very important role in law enforcement and supervision. Existing localization and tracking schemes usually need to deploy a large number of monitoring devices or continue to move with the target, which lead to high cost. In this paper, a localization and tracking scheme based on big data of Wi-Fi locations is proposed. Firstly, the characteristic of the smart mobile device that continuously broadcasts probe request frames is used to obtain its MAC address and Wi-Fi connection history. Secondly, the service set identifier (SSID) in the Wi-Fi connection history of smart mobile devices held by the target gangs are queried from the Wi-Fi location database, and the target gangs’ usual haunts are gained by statistical analysis. Lastly, monitoring devices are deployed in these places, and most of the target gangs’ activity pattern are known with only a small number of monitoring devices. The results of the related experimental tests demonstrate the feasibility of the proposed scheme.
Dual current control scheme for PWM converter under unbalanced input voltage conditions

Voltage unbalance in a three-phase system causes performance deterioration of a pulsewidth modulation (PWM) converter by producing the 120-Hz voltage ripples in the dc link and by increasing the reactive power. To eliminate the dc-link voltage ripple and the dc component of the reactive power, both positiveand negative-sequence currents should be controlled simultaneously, according to the paper by Rioualet al. We used two synchronous reference frames: a positive-sequence current regulated by a proportional integral (PI) controller in a positive synchronous reference frame (SRF), and a negativesequence current regulated by a PI controller in a negative SRF. In the positive SRF, which rotates counterclockwise, the positive sequence appears as dc, while the negative sequence appears as 120 Hz. In contrast, in the negative SRF, which rotates clockwise, the negative sequence appears as dc, while the positive sequence appears as 120 Hz. By deleting 120-Hz components using a notch filter in each SRF, one can measure positiveand negativesequence currents separately, and use them for constructing two feedback controllers. Since the negative-sequence current is also controlled in its own SRF by a dc command, this approach yields better performance without increasing the control gain. Note that, since the controller is implemented by a software routine in the digital signal processor chip, using two SRF’s does not require additional hardware. We demonstrated the effectiveness of the proposed control scheme by using computer simulation and experiments.