nils-herrmann/clean_scirepeval huggingface dataset:
Vehicle number plate detection and recognition using bounding box method

The use of vehicles in our life is increasing exponentially day by day and as increasing vehicles are violating the traffic rules, theft of vehicles, entering in restricted areas, high number of accidents lead to increase in the crime rates linearly. For any vehicle to be recognized, vehicle license plate detection will play a major significant role in this active world. For finding vehicles commonly used in field of security and safety system, LPDR plays a significant role and we need to recognize vehicles registration number at a certain distance. This paper has four major steps as follows: Preprocessing of captured image, Extracting license number plate region, Segmentation and Character Recognition of license plate. In pre-processing the desired vehicle image is taken through the digital camera, brightness of image is adjusted, noise removal using filters and image is converted to gray scale. Exactions of license plate region consist of finding the edges in the image where exact location of licenses plate is located and crop it into rectangular frame. Segmentation plays a vital role in vehicle licenses plate recognition; the legibility of character recognition completely relies on the segmentation done. The approach which we have used is simple but appropriate. First we segmented all characters in the image (LP) using Bounding box method. Finally, recognition of each character is done. The template matching method is used for recognition each character in the vehicle license plate.
Force of Habit and Information Systems Usage: Theory and Initial Validation

Over the last two decades, information systems (IS) research has primarily focused on people’s conscious (intentional) behavior when trying to explain and predict IS usage. Consequently, almost no research has investigated the potential importance of subconscious (automatic) behaviors, also known as habits. This study represents a first step toward validating the idea that one can add explanatory power to a behavioral model such as Ajzen’s [1985] theory of planned behavior (TPB) by including the habit construct. We conducted a two-stage questionnaire-based survey involving two different groups of students who had access to a sophisticated internet-based communication tool (IBCT). These data were used to test a behavioral model integrating theoretical constructs of TPB and a relevant subset of Triandis’ [1980] behavioral framework. Our findings highlight the importance of considering both conscious (intentions) and subconscious (habits) factors in explaining usage behavior. Furthermore, we share our observations about antecedents of IBCT usage in the educational context. Implications for practice and research are discussed.
Neuroticism as a mediator of treatment response to SSRIs in major depressive disorder.

Serotonin function has been implicated in both major depressive disorder and neuroticism. In the current investigation, we examined the hypothesis that any change in depression severity is mediated through the reduction of neuroticism, but only for those compounds which target serotonin receptors.



Ninety-three outpatients in the midst of a major depressive episode received one of three antidepressant medications, classified into two broad types: selective serotonin reuptake inhibitors (SSRIs) and non-SSRIs (i.e. reversible monoamine oxidase inhibitors [RIMAs] and noradrenergic and dopaminergic reuptake blockers [NDMs]). Patients completed the Hamilton Rating Scale for Depression, Beck Depression Inventory II and Revised NEO Personality Inventory prior to and following approximately 16 weeks of treatment. Structural equation modeling was used to test two models: a mediation model, in which neuroticism change is the mechanism by which SSRIs exert a therapeutic effect upon depressive symptoms, and a complication model, in which neuroticism change is a mere epiphenomenon of depression reduction in response to SSRIs.



The mediation model provided a good fit to the data; the complication model did not. Patients treated with SSRIs demonstrated greater neuroticism change than those treated with non-SSRIs, and greater neuroticism change was associated with greater depressive symptom change. These effects held for both self-reported and clinician-rated depressive symptom severity.



Replication within a randomized control trial with multiple assessment periods is required.



Neuroticism mediates changes in depression in response to treatment with SSRIs, such that any treatment effect of SSRIs occurs through neuroticism reduction.
Undecidability of Static Analysis

Static analysis of programs is indispensable to any software tool, environment, or system that requires compile-time information about the semantics of programs. With the emergence of languages like C and LISP, static analysis of programs with dynamic storage and recursive data structures has become a field of active research. Such analysis is difficult, and the static-analysis community has recognized the need for simplifying assumptions and approximate solutions. However, even under the common simplifying assumptions, such analyses are harder than previously recognized. Two fundamental static-analysis problems are may alias and must alias. The former is not recursive (is undecidable), and the latter is not recursively enumerable (is uncomputable), even when all paths are executable in the program being analyzed for languages with if statements, loops, dynamic storage, and recursive data structures.
High-voltage high-frequency power supply using a phase-shifted PWM full bridge inverter fed ozone generator with constant applied electrode voltage

This paper proposes the high-voltage high-frequency power supply for an ozone generator using a phase-shift pulse width modulation (PWM) full bridge inverter with constant applied electrode voltage. The circuit operation is fully described. The high-frequency transformer and ozone generator mathematical models are also included for preliminarily calculating of instantaneous voltages and currents. The proposed system simulation using the MATLAB/SIMULINK software package is given. In order to ensure that the zero voltage switch (ZVS) is always operated over a certain range of a frequency variation, a series-compensated resonant inductor is included. The advantage of the proposed system is a capability of varying ozone gas production quantity by varying the frequency and phase shift angle of the converter whilst the applied voltage to the electrodes is kept constant. The correctness of the proposed system is verified by both simulation and experimental results.
Support vector machines versus fast scoring in the low-dimensional total variability space for speaker verification

This paper presents a new speaker verification system architecture based on Joint Factor Analysis (JFA) as feature extractor. In this modeling, the JFA is used to define a new low-dimensional space named the total variability factor space, instead of both channel and speaker variability spaces for the classical JFA. The main contribution in this approach, is the use of the cosine kernel in the new total factor space to design two different systems: the first system is Support Vector Machines based, and the second one uses directly this kernel as a decision score. This last scoring method makes the process faster and less computation complex compared to others classical methods. We tested several intersession compensation methods in total factors, and we found that the combination of Linear Discriminate Analysis and Within Class Covariance Normalization achieved the best performance. We achieved a remarkable results using fast scoring method based only on cosine kernel especially for male trials, we yield an EER of 1.12% and MinDCF of 0.0094 on the English trials of the NIST 2008 SRE dataset.
A Survey of Challenges and Applications of Wireless Body Area Network (WBAN) and Role of a Virtual Doctor Server in Existing Architecture

Wireless body area network has gained much interest and became emerging technology at health service facilities due to its wide range of utility and vital role to improve the human health. In this research paper, we are conducting a comprehensive survey of wireless Body Area Network (WBAN) and also introducing a virtual doctor server (VDS) in existing WBAN architecture. Existing architecture of WBAN consists of: wireless sensor, wireless actuator node , wireless central unit and wireless Personal Device (PD). Personal Digital Assistant (PDA) or smart phone can be used as PD. Based on the existing architecture mentioned above, we propose a design concept for a virtual doctor server (VDS) to support various patient health care services. VDS will keep the historical data about the patient, generate the daily tips and advices for him, call the doctor or emergency squad if required and can provide first aid assistance instructions on patient or any of his close relative's PDA's.
Interactive example-based urban layout synthesis

We present an interactive system for synthesizing urban layouts by example. Our method simultaneously performs both a structure-based synthesis and an image-based synthesis to generate a complete urban layout with a plausible street network and with aerial-view imagery. Our approach uses the structure and image data of real-world urban areas and a synthesis algorithm to provide several high-level operations to easily and interactively generate complex layouts by example. The user can create new urban layouts by a sequence of operations such as join, expand, and blend without being concerned about low-level structural details. Further, the ability to blend example urban layout fragments provides a powerful way to generate new synthetic content. We demonstrate our system by creating urban layouts using example fragments from several real-world cities, each ranging from hundreds to thousands of city blocks and parcels.
IoT based smart surveillance security system using raspberry Pi

Communication mainly is the transfer of whatever thing or exchanging of data, so that the Internet of things is naught but the transferring or exchanging of anything with several other things. The using of internet authorized system or devices roughly calculated as that by 2020 there will be nearly about billions. The purpose of the paper is to define a safekeeping alert device spending little handling power by Internet of things which help out to observer plus alerts when gestures or else motion are there then send images to a cloud server. Besides, internet of things centered use can be used tenuously to observe the action as well as acquire warning when gestures or else indication are there. The images are showed straight to a cloud attendant, when the cloud attendant is not accessible at that time the records are put in storage close by on a Raspberry Pi. A credit card size Raspberry Pi with a advantage of Open Source Computer Vision (Open-CV) software knobs the image processing, control algorithms used for the attentiveness then shows taken images to concern persons email by the use of Wi-Fi module. The system uses ordinary webcam.
Mitochondrial diseases in man and mouse.

Over the past 10 years, mitochondrial defects have been implicated in a wide variety of degenerative diseases, aging, and cancer. Studies on patients with these diseases have revealed much about the complexities of mitochondrial genetics, which involves an interplay between mutations in the mitochondrial and nuclear genomes. However, the pathophysiology of mitochondrial diseases has remained perplexing. The essential role of mitochondrial oxidative phosphorylation in cellular energy production, the generation of reactive oxygen species, and the initiation of apoptosis has suggested a number of novel mechanisms for mitochondrial pathology. The importance and interrelationship of these functions are now being studied in mouse models of mitochondrial disease.
Eventually Returning to Strong Consistency

Eventually and weakly consistent distributed systems have emerged in the past decade as an answer to scalability and availability issues associated with strong consistency semantics, such as linearizability. However, systems offering strong consistency semantics have an advantage over systems based on weaker consistency models, as they are typically much simpler to reason about and are more intuitive to developers, exhibiting more predictable behavior. Therefore, a lot of research and development effort is being invested lately into the re-engineering of strongly consistent distributed systems, as well as into boosting their scalability and performance. This paper overviews and discusses several novel directions in the design and implementation of strongly consistent systems in industries and research domains such as cloud computing, data center networking and blockchain. It also discusses a general trend of returning to strong consistency in distributed systems, when system requirements permit so.
The Trier Social Stress Test: Principles and practice

Researchers interested in the neurobiology of the acute stress response in humans require a valid and reliable acute stressor that can be used under experimental conditions. The Trier Social Stress Test (TSST) provides such a testing platform. It induces stress by requiring participants to make an interview-style presentation, followed by a surprise mental arithmetic test, in front of an interview panel who do not provide feedback or encouragement. In this review, we outline the methodology of the TSST, and discuss key findings under conditions of health and stress-related disorder. The TSST has unveiled differences in males and females, as well as different age groups, in their neurobiological response to acute stress. The TSST has also deepened our understanding of how genotype may moderate the cognitive neurobiology of acute stress, and exciting new inroads have been made in understanding epigenetic contributions to the biological regulation of the acute stress response using the TSST. A number of innovative adaptations have been developed which allow for the TSST to be used in group settings, with children, in combination with brain imaging, and with virtual committees. Future applications may incorporate the emerging links between the gut microbiome and the stress response. Future research should also maximise use of behavioural data generated by the TSST. Alternative acute stress paradigms may have utility over the TSST in certain situations, such as those that require repeat testing. Nonetheless, we expect that the TSST remains the gold standard for examining the cognitive neurobiology of acute stress in humans.
Tensors for Data Mining and Data Fusion: Models, Applications, and Scalable Algorithms

Tensors and tensor decompositions are very powerful and versatile tools that can model a wide variety of heterogeneous, multiaspect data. As a result, tensor decompositions, which extract useful latent information out of multiaspect data tensors, have witnessed increasing popularity and adoption by the data mining community. In this survey, we present some of the most widely used tensor decompositions, providing the key insights behind them, and summarizing them from a practitioner’s point of view. We then provide an overview of a very broad spectrum of applications where tensors have been instrumental in achieving state-of-the-art performance, ranging from social network analysis to brain data analysis, and from web mining to healthcare. Subsequently, we present recent algorithmic advances in scaling tensor decompositions up to today’s big data, outlining the existing systems and summarizing the key ideas behind them. Finally, we conclude with a list of challenges and open problems that outline exciting future research directions.
Survey on Fraud Detection Techniques Using Data Mining

Now a days, fraud is a million dollar business and every year it is increasing more and more. In a crime survey in 2009, tells that close to 30% of the company’s worldwide reported falling victim to fraud in the past year. Fraud involves individual or in a form of groups who intentionally act secretly to rob another of something of worth, for their own profit. Fraud is as against the humanity and it is unlimited variety of different forms. So in this paper, we introduce different methods and techniques to tackle the fraud and how to prevent the fraud into the organization, businesses, and hospital and insurance companies. Fraud prevention is a continuing battle. Many website owners must continually fight against many kinds of crime ranging from stealing identity theft and credit cards and many other types of fraud related to that. Internet Fraud is also very popular, where fraudster can steal the credit card number and buy thing from the different websites.
Design of a CMOS Broadband Transimpedance Amplifier With Active Feedback

In this paper, a novel current-mode transimpedance amplifier (TIA) exploiting the common gate input stage with common source active feedback has been realized in CHRT 0.18 ¿m -1.8 V RFCMOS technology. The proposed active feedback TIA input stage is able to achieve a low input impedance similar to that of the well-known regulated cascode (RGC) topology. The proposed TIA also employs series inductive peaking and capacitive degeneration techniques to enhance the bandwidth and the gain. The measured transimpedance gain is 54.6 dB¿ with a -3 dB bandwidth of about 7 GHz for a total input parasitic capacitance of 0.3 pF. The measured average input referred noise current spectral density is about 17.5 pA/¿{Hz} up to 7 GHz. The measured group delay is within 65 ± 10 ps over the bandwidth of interest. The chip consumes 18.6 mW DC power from a single 1.8 V supply. The mathematical analysis of the proposed TIA is presented together with a detailed noise analysis based on the van der Ziel MOSFET noise model. The effect of the induced gate noise in a broadband TIA is included.
AC Power Losses Model for Planar Windings With Rectangular Cross-Sectional Conductors

In this letter, a method to calculate the ac losses, including skin effect and proximity losses, in planar windings with rectangular cross-sectional conductors is proposed. The aim is proposing proper ac losses expressions similar to the formulas available for round cross-sectional wires, to be used for the calculation of the ac losses and the optimization of planar magnetic windings implemented in the printed circuit board. The proposed model is based on the decomposition into conduction and proximity losses. Conduction losses only depend on the properties of the conductor, whereas proximity losses are calculated by using the orthogonal decomposition of the magnetic fields in which the conductors are immersed. Functions including the frequency and geometrical dependences of the both types of losses are extracted by means of finite element method simulation. Finally, several prototypes are used to verify the proposed expressions and some design considerations are also outlined.
A computational study of cross-situational techniques for learning word-to-meaning mappings

This paper presents a computational study of part of the lexical-acquisition task faced by children, namely the acquisition of word-to-meaning mappings. It first approximates this task as a formal mathematical problem. It then presents an implemented algorithm for solving this problem, illustrating its operation on a small example. This algorithm offers one precise interpretation of the intuitive notions of cross-situational learning and the principle of contrast applied between words in an utterance. It robustly learns a homonymous lexicon despite noisy multi-word input, in the presence of referential uncertainty, with no prior knowledge that is specific to the language being learned. Computational simulations demonstrate the robustness of this algorithm and illustrate how algorithms based on cross-situational learning and the principle of contrast might be able to solve lexical-acquisition problems of the size faced by children, under weak, worst-case assumptions about the type and quantity of data available.
Real-time capable methods to determine the magnet temperature of permanent magnet synchronous motors — A review

The permanent magnet synchronous motor (PMSM) is widely used in highly utilised automotive traction drives and other industrial applications. With regards to the device life-time, safe operation and control performance, the magnet temperature is of great interest. Since a direct magnet temperature measurement is not feasible in most cases, this contribution gives a review on state-of-the-art model-based magnet temperature determination methods in PMSM. In this context, the existing publications can be classified into thermal models, flux observers and voltage signal injection approaches. Firstly, brief introductions of these methods are given, followed by a direct comparison regarding drawbacks and benefits. Finally, this contribution concludes with an outlook of potential further investigations in this research field.
Accurate and dense wide-baseline stereo matching using SW-POC

This paper proposes an accurate and dense wide-baseline stereo matching method using Scaled Window Phase-Only Correlation (SW-POC). The wide-baseline setting of the stereo camera can improve the accuracy of the 3D reconstruction compared with the short-baseline setting. However, it is difficult to find accurate and dense correspondence from wide-baseline stereo images due to its large perspective distortion. Addressing this problem, we employ the SW-POC, which is a correspondence matching method using 1D POC with the concept of Scale Window Matching (SWM). The use of SW-POC makes it possible to find the accurate and dense correspondence from a wide-baseline stereo image pair with low computational cost. We also apply the proposed method to 3D reconstruction using a moving and uncalibrated consumer digital camera.
A 5.8-GHz radar sensor chip in 0.18-μm CMOS for non-contact vital sign detection

This paper presents a 5.8-GHz radar sensor chip for non-contact vital sign detection. The sensor chip is designed and fabricated in TSMC 0.18 μm CMOS 1P6M process. Except for the low-noise amplifier, all the active and passive components of the radar system are fully integrated in a single CMOS chip. With packaging on the printed-circuit board and connecting transmitting and receiving antennas, the radar sensor chip has been successfully demonstrated to detect the respiration and heart beat rates of a human adult.
Proximity based IoT device authentication

Internet of Things (IoT) devices are largely embedded devices which lack a sophisticated user interface, e.g., touch screen, keyboard, etc. As a consequence, traditional Pre-Shared Key (PSK) based authentication for mobile devices becomes difficult to apply. For example, according to our study on home automation devices which leverage smartphone for PSK input, the current process does not protect against active impersonating attack and also leaks the Wi-Fi password to eavesdroppers, i.e., currently these IoT devices can be exploited to enter into critical infrastructures, e.g., home networks. Motivated by this real-world security vulnerability, in this paper we propose a novel proximity-based mechanism for IoT device authentication, called Move2Auth, for the purpose of enhancing IoT device security. In Move2Auth, we require user to hold smartphone and perform one of two hand-gestures (moving towards and away, and rotating) in front of IoT device. By combining (1) large RSS-variation and (2) matching between RSS-trace and smartphone sensor-trace, Move2Auth can reliably detect proximity and authenticate IoT device accordingly. Based on our implementation on Samsung Galaxy smartphone and commodity Wi-Fi adapter, we prove Move2Auth can protect against powerful active attack, i.e., the false-positive rate is consistently lower than 0.5%.