nils-herrmann/clean_scirepeval huggingface dataset:
Efficient Tempo and Beat Tracking in Audio Recordings *

Estimating the tempo of a musical piece is a complex problem, which has received an increasing amount of attention in the past few years. The problem consists of estimating the number of beats per minute (bpm) at which the music is played and identifying exactly when these beats occur. Commercial devices already exist that attempt to extract a musical instrument digital interface (MIDI) clock from an audio signal, indicating both the tempo and the actual location of the beat. Such MIDI clocks can then be used to synchronize other devices (such as drum machines and audio effects) to the audio source, enabling a new range of " beat-synchronized " audio processing. Beat detection can also simplify the usually tedious process of manipulating audio material in audio-editing software. Cut and paste operations are made considerably easier if markers are positioned at each beat or at bar boundaries. Looping a drum track over two bars becomes trivial once the location of the beats is known. A third range of applications is the fairly new area of automatic playlist generation, where a computer is given the task to choose a series of audio tracks from a track database in a way similar to what a human deejay would do. The track tempo is a very important selection criterion in this context , as deejays will tend to string tracks with similar tempi back to back. Furthermore, deejays also tend to perform beat-synchronous crossfading between successive tracks manually, slowing down or speeding up one of the tracks so that the beats in the two tracks line up exactly during the crossfade. This can easily be done automatically once the beats are located in the two tracks. The tempo detection systems commercially available appear to be fairly unsophisticated, as they rely mostly on the presence of a strong and regular bass-drum kick at every beat, an assumption that holds mostly with modern musical genres such as techno or drums and bass. For music with a less pronounced tempo such techniques fail miserably and more sophisticated algorithms are needed. This paper describes an off-line tempo detection algorithm , able to estimate a time-varying tempo from an audio track stored, for example, on an audio CD or on a computer hard disk. The technique works in three successive steps: 1) an " energy flux " signal is extracted from the track, 2) at each tempo-analysis time, several …
Pedestrian behavior analysis using 110-car naturalistic driving data in USA

The research objective of this work was to understand pedestrians’ behavior and interaction with vehicles during pre-crash scenarios that provides critical information on how to improve pedestrian safety. In this study, we recruited 110 cars and their drivers in the greater Indianapolis area for a one year naturalistic driving study starting in March 2012. The drivers were selected based on their geographic, demographic, and driving route representativeness. We used off-the-shelf vehicle black boxes for data recording, which are installed at the front windshield behind the rear-view mirrors. It records highresolution forward-view videos (recording driving views outside of front windshield), GPS information, and G-sensor information. We developed category-based multi-stage pedestrian detection and behavior analysis tools to efficiently process this large scale driving dataset. To ensure the accuracy, we incorporated the human-in-loop process to verify the automatic pedestrian detection results. For each pedestrian event, we generate a 5-second video to further study potential conflicts between pedestrians and vehicle. For each detected potential conflict event, we generate a 15second video to analyze pedestrian behavior. We conduct in-depth analysis of pedestrian behavior in regular and near-miss scenarios using the naturalistic data. We observed pedestrian and vehicle interaction videos and studied what scenarios might be more dangerous and could more likely to result in potential conflicts. We observed: 1) Children alone as pedestrians is an elevated risk; 2) three or more adults may be more likely to result in potential conflicts with vehicles than one or two adults; 3) parking lots, communities, school areas, shopping malls, etc. could have more potential conflicts than regular urban/rural driving environments; 4) when pedestrian is crossing road, there is much higher potential conflict than pedestrian walking along/against traffic; 5) There is an elevated risk for pedestrians walking in road (where vehicles can drive by); 6) when pedestrians are jogging, it is much more likely to have potential conflict than walking or standing.; and 7) it is more likely to have potential conflict at cross walk and junction than other road types. Furthermore, we estimated the pedestrian appearance points of all potential conflict events and time to collision (TTC). Most potential conflict events have a TTC value ranging from 1 second to 6 seconds, with the range of 2 seconds to 4 seconds being associated with highest percentages of all the cases. The mean value of TTC is 3.84 seconds with standard deviation of 1.74 seconds. To date, we have collected about 65TB of driving data with about 1.1 million miles. We have processed about 50% of the data. We are continuously working on the data collection and processing. There could be some changes in our observation results after including all data. But the existing analysis is based on a quite large-scale data and would provide a good estimation.
3-D Thin film interposer based on TGV (Through Glass Vias): An alternative to Si-interposer

Interposers for SiP will become more and more important for advanced electronic systems. But through substrate vias are essential for the 3-D integration. Being a standard for laminate based materials this is much more complex for Si-wafers: High speed etching has to be combined with complex electrical isolation, diffusion barriers and void-free Cu-filling. Without doubt this can be solved in lab-scale but for high production scale cost is a tremendous barrier. Glass wafers with W-plugs have been intensively investigated in this paper. A new acronym has been posted to high-light this technology: TGV for Through Glass Vias. The results of modeling and simulation of TGV at RF/Microwave frequencies showed a very good compromise between wafer thickness, TGV-shape and via diameter for vertical metal plugs with 100 μm diameters in 500 μm thick glass wafer still very stable for thin film wafer processing without costly temporary wafer bonding processes. Therefore the HermeS® from Schott was chosen as the basis for a prototype of a bidirectional 4 × 10 Gbps electro-optical transceiver module. Thin film RDL and bumping of these wafers was possible without any modifications to Si-wafer. First thermal cycles showed very promising results for the reliability of this concept.
A Low-Jitter 1.8-kV 100-ps Rise-Time 50-kHz Repetition-Rate Pulsed-Power Generator

A 1.8-kV 100-ps rise-time pulsed-power generator operating at a repetition frequency of 50 kHz is presented. The generator consists of three compression stages. In the first stage, a power MOSFET produces high voltage by breaking an inductor current. In the second stage, a 3-kV drift-step-recovery diode cuts the reverse current rapidly to create a 1-ns rise-time pulse. In the last stage, a silicon-avalanche shaper is used as a fast 100-ps closing switch. Experimental investigation showed that, by optimizing the generator operating point, the shot-to-shot jitter can be reduced to less than 13 ps. The theoretical model of the pulse-forming circuit is presented.
A 200-V 98.16%-Efficiency Buck LED Driver Using Integrated Current Control to Improve Current Accuracy for Large-Scale Single-String LED Backlighting Applications

This paper presents an average current mode buck dimmable light-emitting diode (LED) driver for large-scale single-string LED backlighting applications. The proposed integrated current control technique can provide exact current control signals by using an autozeroed integrator to enhance the accuracy of the average current of LEDs while driving a large number of LEDs. Adoption of discontinuous low-side current sensing leads to power loss reduction. Adoption of a fast-settling technique allows the LED driver to enter into the steady state within three switching cycles after the dimming signal is triggered. Implemented in a 0.35-μm HV CMOS process, the proposed LED driver achieves 1.7% LED current error and 98.16% peak efficiency over an input voltage range of 110 to 200 V while driving 30 to 50 LEDs.
What Motivates Consumers to Write Online Travel Reviews?

The Web provides a fertile ground for word-of-mouth communication and more and more consumers write about and share product-related experiences online. Given the experiential nature of tourism, such first-hand knowledge communicated by other travelers is especially useful for travel decision making. However, very little is known about what motivates consumers to write online travel reviews. A Web-based survey using an online consumer panel was conducted to investigate consumers’ motivations to write online travel reviews. Measurement scales to gauge the motivations to contribute online travel reviews were developed and tested. The results indicate that online travel review writers are mostly motivated by helping a travel service provider, concerns for other consumers, and needs for enjoyment/positive self-enhancement. Venting negative feelings through postings is clearly not seen as an important motive. Motivational differences were found for gender and income level. Implications of the findings for online travel communities and tourism marketers are discussed.
A Planar MICS Band Antenna Combined With a Body Channel Communication Electrode for Body Sensor Network

A 2.5 times 1.8 cm2 medical implant communication service band antenna is combined with an electrode for body channel communication. The proposed design enables a body sensor network controller to communicate with health-care devices located on and inside a patient's body. The spiral microstrip antenna with its radiating body and ground plane placed side-by-side has the thickness of 2 mm and can be attached to human skin conveniently. The propagation loss of the body channel is measured when the proposed antenna is used as the skin interface for BCC in the 10-70-MHz band, and the results are compared with the cases of Ag/AgCl and circular dry electrodes. The equivalent-circuit model of the antenna as the electrode is also derived from the measured impedance characteristics. The LC resonance structure to drive the on-body antenna with its capacitance increased due to the skin contact reduces the power consumption of the TX buffer by >50%. TheS 11-parameter of the on-body antenna, its radiation pattern, and the signal loss inside the human body are investigated.
A Trustless Privacy-Preserving Reputation System

Reputation systems are crucial for distributed applications in which users have to be made accountable for their actions, such as ecommerce websites. However, existing systems often disclose the identity of the raters, which might deter honest users from submitting reviews out of fear of retaliation from the ratees. While many privacy-preserving reputation systems have been proposed, we observe that none of them is simultaneously truly decentralized, trustless, and suitable for real world usage in, for example, e-commerce applications. In this paper, we present a blockchain based decentralized privacy-preserving reputation system. We demonstrate that our system provides correctness and security while eliminating the need for users to trust any third parties or even fellow users.
Multiview Convolutional Neural Networks for Multidocument Extractive Summarization

Multidocument summarization has gained popularity in many real world applications because vital information can be extracted within a short time. Extractive summarization aims to generate a summary of a document or a set of documents by ranking sentences and the ranking results rely heavily on the quality of sentence features. However, almost all previous algorithms require hand-crafted features for sentence representation. In this paper, we leverage on word embedding to represent sentences so as to avoid the intensive labor in feature engineering. An enhanced convolutional neural networks (CNNs) termed multiview CNNs is successfully developed to obtain the features of sentences and rank sentences jointly. Multiview learning is incorporated into the model to greatly enhance the learning capability of original CNN. We evaluate the generic summarization performance of our proposed method on five Document Understanding Conference datasets. The proposed system outperforms the state-of-the-art approaches and the improvement is statistically significant shown by paired  $t$ -test.
Research on warehouse operation: A comprehensive review

An extensive review on warehouse operation planning problems is presented. The problems are classified according to the basic warehouse functions, i.e., receiving, storage, order picking, and shipping. The literature in each category is summarized with an emphasis on the characteristics of various decision support models and solution algorithms. The purpose is to provide a bridge between academic researchers and warehouse practitioners, explaining what planning models and methods are currently available for warehouse operations, and what are the future research opportunities.
Content Based Color Image Classification using SVM

We propose a novel approach for content based color image classification using Support Vector Machine (SVM). Traditional classification approaches deal poorly on content based image classification tasks being one of the reasons of high dimensionality of the feature space. In this paper, color image classification is done on features extracted from histograms of color components. The benefit of using color image histograms are better efficiency, and insensitivity to small changes in camera view-point i.e. translation and rotation. As a case study for validation purpose, experimental trials were done on a database of about 500 images divided into four different classes has been reported and compared on histogram features for RGB, CMYK, Lab, YUV, YCBCR, HSV, HVC and YIQ color spaces. Results based on the proposed approach are found encouraging in terms of color image classification accuracy.
CMOS current reference with temperature compensation

Current reference is an essential building block in all analog-mixed signal integrated circuits. Basic current references are sensitive to temperature variations, and may vary up to ±30% for a temperature range -30 °C to 135°C. This paper, suggests a technique of combining two current reference models with complementary temperature characteristics, to improve stability of the reference current to 1.14% for the full range of temperature variation; and a dynamic variation which is below 57ppm/ °C. The circuit is designed for a current reference of 5μA for 180nm CMOS technology and Physical design (Layout) is simulated for a temperature range of -30°C to 135 °C across process corners.
Intrusion Detection and Prevention in Cloud Environment: A Systematic Review

The traditional intrusion detection system is not flexible in providing security in cloud computing because of the distributed structure of cloud computing. This paper surveys the intrusion detection and prevention techniques and possible solutions in Host Based and Network Based Intrusion Detection System. It discusses DDoS attacks in Cloud environment. Different Intrusion Detection techniques are also discussed namely anomaly based techniques and signature based techniques. It also surveys different approaches of Intrusion Prevention System.
Multi-modal control framework for a semi-autonomous wheelchair using modular sensor designs

This paper presents the hardware and software control framework for a semi-autonomous wheelchair. The hardware design incorporates modular and reconfigurable sensors and corresponding low-level software architecture. Two control schemes are discussed. Assisted control that augments the user inputs by providing functionalities such as obstacle avoidance and wall following. And, semi-autonomous navigation which takes higher level destination goals and executes a SLAM algorithm. We also propose an adaptive motion control with a online parameter estimation. The paper presents both experimental and simulation results.
Objects and attention: the state of the art

What are the units of attention? In addition to standard models holding that attention can select spatial regions and visual features, recent work suggests that in some cases attention can directly select discrete objects. This paper reviews the state of the art with regard to such 'object-based' attention, and explores how objects of attention relate to locations, reference frames, perceptual groups, surfaces, parts, and features. Also discussed are the dynamic aspects of objecthood, including the question of how attended objects are individuated in time, and the possibility of attending to simple dynamic motions and events. The final sections of this review generalize these issues beyond vision science, to other modalities and fields such as auditory objects of attention and the infant's 'object concept'.
Customer Perceived Value , Satisfaction , and Loyalty : The Role of Switching Costs

It is a marketplace reality that marketing managers sometimes inflict switching costs on their customers, to inhibit them from defecting to new suppliers. In a competitive setting, such as the Internet market, where competition may be only one click away, has the potential of switching costs as an exit barrier and a binding ingredient of customer loyalty become altered? To address that issue, this article examines the moderating effects of switching costs on customer loyalty through both satisfaction and perceived-value measures. The results, evoked from a Web-based survey of online service users, indicate that companies that strive for customer loyalty should focus primarily on satisfaction and perceived value. The moderating effects of switching costs on the association of customer loyalty and customer satisfaction and perceived value are significant only when the level of customer satisfaction or perceived value is above average. In light of the major findings, the article sets forth strategic implications for customer loyalty in the setting of electronic commerce.  In the consumer marketing community, customer loyalty has long been regarded as an important goal (Reichheld & Schefter, 2000). Both marketing academics and professionals have attempted to uncover the most prominent antecedents of customer loyalty. Numerous studies have Psychology & Marketing, Vol. 21(10):799–822 (October 2004) Published online in Wiley InterScience (www.interscience.wiley.com)
Traffic sign segmentation and classification using statistical learning methods

Traffic signs are an essential part of any circulation system, and failure detection by the driver may significantly increase the accident risk. Currently, automatic traffic sign detection systems still have some performance limitations, specially for achromatic signs and variable lighting conditions. In this work, we propose an automatic traffic-sign detection method capable of detecting both chromatic and achromatic signs, while taking into account rotations, scale changes, shifts, partial deformations, and shadows. The proposed system is divided into three stages: (1) Segmentation of chromatic and achromatic scene elements using L∗a∗b∗ and HSI spaces, where two machine learning techniques (k-Nearest Neighbors and Support Vector Machines), are benchmarked; (2) Post-processing in order to discard non-interest regions, to connect fragmented signs, and to separate signs located at the same post; (3) Sign-shape classification by using Fourier Descriptors, which yield significant advantage in comparison to other contour-based methods, and subsequent shape recognition with machine learning techniques. Experiments with two databases of real-world images captured with different cameras yielded a sign detection rate of about 97% with a false alarm rate between 3% and 4%, depending on the database. ∗Corresponding author Email addresses: josemaria.lillo@urjc.es (J.M. Lillo-Castellano), inmaculada.mora@urjc.es (I. Mora-Jiménez), carlos.figuera@urjc.es (C. Figuera-Pozuelo), joseluis.rojo@urjc.es (J.L. Rojo-Álvarez)  2014 Our method can be readily used for maintenance, inventory, or driver support system applications.
Graphene-Flakes Printed Wideband Elliptical Dipole Antenna for Low-Cost Wireless Communications Applications

This letter presents the design, manufacturing, and operational performance of a graphene-flakes-based screen-printed wideband elliptical dipole antenna operating from 2 up to 5 GHz for low-cost wireless communications applications. To investigate radio frequency (RF) conductivity of the printed graphene, a coplanar waveguide (CPW) test structure was designed, fabricated, and tested in the frequency range from 1 to 20 GHz. Antenna and CPW were screen-printed on Kapton substrates using a graphene paste formulated with a graphene-to-binder ratio of 1:2. A combination of thermal treatment and subsequent compression rolling is utilized to further decrease the sheet resistance for printed graphene structures, ultimately reaching 4 Ω/□ at 10-μ m thicknesses. For the graphene-flakes printed antenna, an antenna efficiency of 60% is obtained. The measured maximum antenna gain is 2.3 dBi at 4.8 GHz. Thus, the graphene-flakes printed antenna adds a total loss of only 3.1 dB to an RF link when compared to the same structure screen-printed for reference with a commercial silver ink. This shows that the electrical performance of screen-printed graphene flakes, which also does not degrade after repeated bending, is suitable for realizing low-cost wearable RF wireless communication devices.
Survey on Credit Card Fraud Detection Techniques

The credit card has become the most popular mode of payment for both online as well as regular purchase, in cases of fraud associated with it are also rising. Credit card frauds are increasing day by day regardless of various techniques developed for its detection. Fraudsters are so experts that they generate new ways of committing fraudulent transactions each day which demands constant innovation for its detection techniques. Most of the techniques based on Artificial Intelligence, Fuzzy Logic, Neural Network, Logistic Regression, Naïve Bayesian, Machine Learning, Sequence Alignment, Decision tree, Bayesian network, meta learning, Genetic programming etc., these are evolved in detecting various credit card fraudulent transactions. This paper presents a survey of various techniques used in various credit card fraud detection mechanisms.