nils-herrmann/clean_scirepeval huggingface dataset:
Hand Gesture Recognition using Computer Vision

The use of the gesture system in our daily life as a natural human-human interaction has inspired the researchers to simulate and utilize this gift in human-machine interaction which is appealing and can take place the bore interaction ones that existed such as television, radio, and various home appliances as well as virtual reality will worth and deserve its name. This kind of interaction ensures promising and satisfying outcomes if applied in systematic approach, and supports unadorned human hand when transferring the message to these devices which is easiest, comfort and desired rather than the communication that requires frills to deliver the message to such devices. With the rapid emergence of 3d applications and virtual environments in computer system the need for a new type of interaction device arises. This is because the traditional devices such as mouse, keyboard and joystick become inefficient and cumbersome within this virtual environments.in other words evolution of user interfaces shapes the change in the HumanComputer Interaction (HCI).Intuitive and naturalness characteristics of “Hand Gestures” in the HCI have been the driving force and motivation to develop an interaction device which can replace current unwieldy tools. A survey on the methods of analysing, modelling and recognizing hand gestures in the context of the HCI is provided in this paper.
Robust Semisupervised Graph Classifier Learning With Negative Edge Weights

In a semisupervised learning scenario, (possibly noisy) partially observed labels are used as input to train a classifier in order to assign labels to unclassified samples. In this paper, we construct a complete graph-based binary classifier given only samples’ feature vectors and partial labels. Specifically, we first build appropriate similarity graphs with positive and negative edge weights connecting all samples based on internode feature distances. By viewing a binary classifier as a piecewise constant graph signal, we cast classifier learning as a signal restoration problem via a classical maximum <italic>a posteriori</italic> (MAP) formulation. One unfortunate consequence of negative edge weights is that the graph Laplacian matrix <inline-formula><tex-math notation="LaTeX"> $\mathbf {L}$</tex-math></inline-formula> can be indefinite, and previously proposed graph-signal smoothness prior <inline-formula><tex-math notation="LaTeX">$\mathbf {x}^T \mathbf {L}\mathbf {x}$</tex-math></inline-formula> for candidate signal <inline-formula><tex-math notation="LaTeX">$\mathbf {x}$</tex-math></inline-formula> can lead to pathological solutions. In response, we derive a minimum-norm perturbation matrix <inline-formula> <tex-math notation="LaTeX">$\boldsymbol{\Delta }$</tex-math></inline-formula> that preserves <inline-formula> <tex-math notation="LaTeX">$\mathbf {L}$</tex-math></inline-formula>'s eigen-structure—based on a fast lower-bound computation of <inline-formula><tex-math notation="LaTeX">$\mathbf {L}$</tex-math></inline-formula>'s smallest negative eigenvalue via a novel application of the Haynsworth inertia additivity formula—so that <inline-formula><tex-math notation="LaTeX">$\mathbf {L}+ \boldsymbol{\Delta }$</tex-math></inline-formula> is positive semidefinite, resulting in a stable signal prior. Further, instead of forcing a hard binary decision for each sample, we define the notion of generalized smoothness on graphs that promotes ambiguity in the classifier signal. Finally, we propose an algorithm based on iterative reweighted least squares that solves the posed MAP problem efficiently. Extensive simulation results show that our proposed algorithm outperforms both SVM variants and previous graph-based classifiers using positive-edge graphs noticeably.
Optimization of Belt-Type Electrostatic Separation of Triboaerodynamically Charged Granular Plastic Mixtures

Electrostatic separation is frequently employed for the selective sorting of conducting and insulating materials for waste electric and electronic equipment. In a series of recent papers, the authors have presented several novel triboelectrostatic separation installations for the recycling of the main categories of plastics contained in information technology wastes. The aim of the present work is to optimize the design and the operation of such an installation, composed of a belt-type electrostatic separator associated to a propeller-type tribocharging device. The experimental design method is employed for modeling and optimizing the separation of a mixture of high-impact polystyrene and acrylonitrile butadiene styrene granules originating from shredded out-of-use computer cases. A distinct experiment is carried out on three synthetic mixtures of virgin plastic granules: 75% polyamide (PA)+ 25% polycarbonate (PC), 50% PA+ 50% PC, and 25% PA + 75% PC. The best results are obtained for the mixtures containing equal quantities of the two constituents.
Smart foot device for women safety

In this paper, an attempt has been made to develop a smart device that can assist women when they feel unsafe. This smart device will be clipped to the footwear of the user and can be triggered discreetly. On tapping one foot behind the other four times, an alert is sent via Bluetooth Low Energy communication to an application on the victim's phone, programmed to generate a message seeking help with the location of the device attached. The results obtained were analysed using Naïve Bayes classifier and this low cost device showed an overall accuracy of 97.5%.
Assessment of Unmanned Aerial Vehicles Imagery for Quantitative Monitoring of Wheat Crop in Small Plots

This paper outlines how light Unmanned Aerial Vehicles (UAV) can be used in remote sensing for precision farming. It focuses on the combination of simple digital photographic cameras with spectral filters, designed to provide multispectral images in the visible and near-infrared domains. In 2005, these instruments were fitted to powered glider and parachute, and flown at six dates staggered over the crop season. We monitored ten varieties of wheat, grown in trial micro-plots in the South-West of France. For each date, we acquired multiple views in four spectral bands corresponding to blue, green, red, and near-infrared. We then performed accurate corrections of image vignetting, geometric distortions, and radiometric bidirectional effects. Afterwards, we derived for each experimental micro-plot several vegetation indexes relevant for vegetation analyses. Finally, we sought relationships between these indexes and field-measured biophysical parameters, both generic and date-specific. Therefore, we established a robust and stable generic relationship between, in one hand, leaf area index and NDVI and, in the other hand, nitrogen uptake and GNDVI. Due to a high amount of noise in the data, it was not possible to obtain a more accurate model for each date independently. A validation protocol showed that we could expect a precision level of 15% in the biophysical parameters estimation while using these relationships.
Relationship between Organizational Commitment and EFQM Business Excellence Model : A Study on Turkish Quality Award Winners

Excellence models affect performance and help organizations achieve organizational excellence. Furthermore, organizational commitment is another concern of organizational excellence. The measurement of organizational commitment has become an important issue in TQM. In this respect, the extent to which employees are committed to what they are responsible for may directly influence the level of customer satisfaction with services and products. The main purpose of the study is to determine the relationship between an excellence model and organizational commitment. In order to achieve this goal, a survey that contains Meyer & Allen’s Organizational Commitment scale and EFQM Criteria are applied to Turkish Quality Awards winners’ employees in 2004. Data obtained in the study have been analyzed at the level of multivariate data analysis and the results show that the relationship between organizational commitment and EFQM Excellence Model was significant. Findings suggest that leadership, partnerships and resources, policy and strategy, affective commitment, processes, results, people development and involvement and continuance commitment are the determinants of the organizational commitment and EFQM Excellence Model respectively. Theoretical and practical implications of the findings are also discussed in the paper.
Optimizing Surface Electromyography Acquisition without Right Leg Drive Circuit

The right leg drive (RLD) is a circuit associated with electrocardiography acquisition circuits. For electromyography (EMG), the RLD circuit is used to a lesser degree. In general, the RLD circuit provides better noise reduction. This study compares the output of the EMG with and without the RLD circuit. The results indicate that with a good filter design, the direct grounding method can match the RLD in terms of noise reduction. As a result, EMG application, the RLD drive can be omitted.
A randomized, efficient, and distributed protocol for the detection of node replication attacks in wireless sensor networks

Wireless sensor networks are often deployed in hostile environments, where anadversary can physically capture some of the nodes. Once a node is captured, the attackercan re-program it and replicate the node in a large number of clones, thus easily taking over the network. The detection of node replication attacks in a wireless sensor network is therefore a fundamental problem. A few distributed solutions have recently been proposed. However, these solutions are not satisfactory. First, they are energy and memory demanding: A serious drawback for any protocol that is to be used in resource constrained environment such as a sensor network. Further, they are vulnerable to specific adversary models introduced in this paper.
 The contributions of this work are threefold. First, we analyze the desirable properties of a distributed mechanism for the detection of node replication attacks. Second, we show that the known solutions for this problem do not completely meet our requirements. Third, we propose a new Randomized, Efficient, and Distributed (RED) protocol for the detection of node replication attacks and we show that it is completely satisfactory with respect to the requirements. Extensive simulations also show that our protocol is highly efficient in communication, memory, and computation, that it sets out an improved attack detection probability compared to the best solutions in the literature, and that it is resistant to the new kind of attacks we introduce in this paper, while other solutions are not.
A new deep spatial transformer convolutional neural network for image saliency detection

In this paper we propose a novel deep spatial transformer convolutional neural network (Spatial Net) framework for the detection of salient and abnormal areas in images. The proposedmethod is general and has threemain parts: (1) context information in the image is captured by using convolutional neural networks (CNN) to automatically learn high-level features; (2) to better adapt the CNN model to the saliency task, we redesign the feature sub-network structure to output a 6-dimensional transformation matrix for affine transformation based on the spatial transformer network. Several local features are extracted, which can effectively capture edge pixels in the salient area, meanwhile embedded into the above model to reduce the impact of highlighting background regions; (3) finally, areas of interest are detected by means of the linear combination of global and local feature information. Experimental results demonstrate that Spatial Nets obtain superior detection performance over state-of-the-art algorithms on two popular datasets, requiring less memory and computation to achieve high performance.
IT Governance Practices For Improving Strategic And Operational Business-IT Alignment

The literature suggests that business-IT alignment is an important antecedent of IS success, business process performance, and competitive advantage. Additionally, IT governance practices are highlighted as being instrumental to fostering business-IT alignment. In this paper, we derive various IT governance practices (in terms of structures, processes, relational mechanisms, and enterprise architecture characteristics) from literature and expert interviews. While prior investigations only considered the effect of such practices on strategic business-IT alignment, we also incorporate alignment at operational level. Using results from a case study in the IT services division of a large multi-national, multi-divisional company acting in diverse industries we highlight the effect of various IT governance practices and offer new insights by showing which mechanisms are effective in facilitating strategic or operational business-IT alignment. Our results indicate the most important practices for both strategic and operational alignment.
The simple sacral dimple: diagnostic yield of ultrasound in neonates

Although spinal cord tethering is known to be associated with certain clinical syndromes and cutaneous stigmata, its incidence in healthy infants with simple sacral dimples has not been thoroughly evaluated. Our objective was to determine the frequency of tethered cord in otherwise healthy patients with simple sacral dimples. We reviewed the lumbar spine US reports of all healthy neonates referred for a simple sacral dimple during a 12-year period at two children’s hospitals. A sonogram was considered abnormal for a conus medullaris terminating below the L2–L3 disc space, decreased conus or nerve root motion, an abnormal filum terminale, or for the presence of an intraspinal mass, osseous dysraphism, or a sinus leading to the thecal sac. The medical records of patients with abnormal screening sonograms were reviewed to determine the final clinical outcome. During the study period 3,991 infants underwent screening sonography. Of these, 107 were excluded because of the presence of other medical conditions. Of the remaining 3,884 healthy infants, 133 (3.4%) had an abnormal sonogram. Five (0.13%) of these infants were lost to follow-up; 52 subsequently had normal follow-up imaging; 49 had a low conus without other signs of tethering; 18 had a fatty filum; 2 had decreased conus motion; 2 had both a low conus and a fatty filum. None of these infants underwent surgery. Only the remaining 5/3,884 (0.13%) infants underwent surgical intervention (95% CI: 0–0.27%), and 4/5 were found to have a tethered cord intraoperatively. The risk of significant spinal malformations in asymptomatic, healthy infants with an isolated simple sacral dimple is exceedingly low.
On Software Implementation of High Performance GHASH Algorithms

There have been several modes of operations available for symmetric key block ciphers, among which Galois Counter Mode (GCM) of operation is a standard. GCM mode of operation provides con dentiality with the help of symmetric key block cipher operating in counter mode. The authentication component of GCM comprises of Galois hash (GHASH) computation which is a keyed hash function. The most important component of GHASH computation is carry-less multiplication of 128bit operands which is followed by a modulo reduction. There have been a number of schemes proposed for e cient software implementation of carry-less multiplication to improve performance of GHASH by increasing the speed of multiplications. This thesis focuses on providing an e cient way of software implementation of high performance GHASH function as being proposed by Meloni et al., and also on the implementation of GHASH using a carry-less multiplication instruction provided by Intel on their Westmere architecture. The thesis work includes implementation of the high performance GHASH and its comparison to the older or standard implementation of GHASH function. It also includes comparison of the two implementations using Intel's carry-less multiplication instruction. This is the rst time that this kind of comparison is being done on software implementations of these algorithms. Our software implementations suggest that the new GHASH algorithm, which was originally proposed for the hardware implementations due to the required parallelization, can't take advantage of the Intel carry-less multiplication instruction PCLMULQDQ. On the other hand, when implementations are done without using the PCLMULQDQ instruction the new algorithm performs better, even if its inherent parallelization is not utilized. This suggest that the new algorithm will perform better on embedded systems that do not support PCLMULQDQ.
American Sign Language Recognition System Using Image Processing Method

The paper aims to propose a novel technique that recognizes finger spelled American Sign Language (ASL) gestures. The external characteristic of hand, i.e. shape based algorithm is being used for recognition. Since almost all of the alphabets have a unique shape, each alphabet is characterized on the basis landmark points marked on the boundary of the hand shown by the signer. A training set is made by training several images of each alphabet and the landmark points of each alphabet which produces a 72 point descriptor are stored in database. The descriptor of test image is then matched with the ones in database. Finally, Euclidean distance classifies the test images to the recognized alphabet. By increasing the number of sampling points there was an increase in accuracy rate. Thus a 180 point descriptor results in better recognition. Index Terms — Fingerspelling ASL, external characteristics, landmark, training set, descriptor, Euclidean distance.
High performance active gate drive for high power IGBTs

This paper deals with an active gate drive (AGD) technology for high power IGBTs. It is based on an optimal combination of several requirements necessary for good switching performance under hard switching conditions. The scheme specifically combines together the slow drive requirements for low noise and switching stress and the fast drive requirements for high speed switching and low switching energy loss. The gate drive can also effectively dampen oscillations during low current turn-on transients in the IGBT. This paper looks at the conflicting requirements of the conventional gate drive circuit design and demonstrates, using experimental results, that the proposed three-stage active gate drive technique can be an effective solution.
Deep learning enhanced mobile-phone microscopy

Mobile-phones have facilitated the creation of field-portable, cost-effective imaging and sensing technologies that approach laboratory-grade instrument performance. However, the optical imaging interfaces of mobile-phones are not designed for microscopy and produce spatial and spectral distortions in imaging microscopic specimens. Here, we report on the use of deep learning to correct such distortions introduced by mobile-phone-based microscopes, facilitating the production of high-resolution, denoised and colour-corrected images, matching the performance of benchtop microscopes with high-end objective lenses, also extending their limited depth-of-field. After training a convolutional neural network, we successfully imaged various samples, including blood smears, histopathology tissue sections, and parasites, where the recorded images were highly compressed to ease storage and transmission for telemedicine applications. This method is applicable to other low-cost, aberrated imaging systems, and could offer alternatives for costly and bulky microscopes, while also providing a framework for standardization of optical images for clinical and biomedical applications.
Manual Evaluation of the Pelvic Floor : State of the Art and Evaluative Hypothesis

The pelvic floor is an anatomical area where the balance of different visceral, muscular and liquid pressures play a fundamental role in the physiological pursuit of the functions of all the structures contained therein. When the balance is broken, multiple disorders and pathologies arise, requiring conservative or surgical multidisciplinary treatments. The focus of this article is to propose a manual evaluation of the musculoskeletal structures of the pelvic floor since a complete palpatory examination taking into account the muscular, articular and ligamentous aspect of the pelvic area is currently missing. The detection of the abnormal area is a determining factor to organize properly the therapeutic work because, potentially resulting in better results. According to the Authors' knowledge, this is the first article in the current scientific landscape proposing a complete manual evaluation.
Bandwidth Enhancement of a Single-Feed Circularly Polarized Antenna Using a Metasurface: Metamaterial-based wideband CP rectangular microstrip antenna.

In this article, the authors use a 7 x 7 rectangular-ring unit metasurface and a single-feed, CP, rectangular, slotted patch antenna to enhance bandwidth. The antenna consists of a rectangular, slotted patch radiator, a metasurface with an array of rectangular-ring cells, and a coaxial feed. Using the metasurface results in a wide CP bandwidth sevenfold the size of a conventional antenna. The measured 3-dB-AR bandwidth of an antenna prototype printed onto an FR4 substrate is 28.3% (3.62 GHz-4.75 GHz) with 2:1-voltage standing wave ratio (VSWR) bandwidth of 36%. A 6.0-dBic, boresight gain with a variation of 1.5 dB is achieved across the frequency band of 3.35 GHz-4.75 GHz, with the maximum gain of 7.4 dBic at 4.1 GHz. We measure and compare the antenna prototype with a simulation using CST Microwave Studio. Parametric studies aid in understanding the proposed antenna's operation mechanism.