nils-herrmann/clean_scirepeval huggingface dataset:
FingerCode: A Filterbank for Fingerprint Representation and Matching

With the ident i ty fraud in o u r society reaching u n precedented proportions and wi th a n increasing emphas i s o n the emerging automat ic posit ive personal ident i f ication applications, biometrics-based identif ication, especially fingerprint-based identif ication, i s receiving a lot of a t ten t ion . There are t w o m a j o r shortcomings of t he traditional approaches t o f ingerpr in t representa t ion . For a significant f rac t ion of population, the . representations based o n explicit detection of complete ridge structures in the f ingerpr in t are d i f i cu l t t o extract automatically. T h e widely used minutiae-based representation does n o t uti l ize a significant component of the..riCh discriminatory in format ion available in the f ingerprints. T h e proposed filter-based algorithm uses a bank of Gabor f i l ters t o capture both the local and the global details in a f ingerpr in t as a compact 640byte fixed length FingerCode. T h e f ingerpr in t ma tch ing i s based o n the Eucl idean distance between the t w o corresponding F ingercodes and hence i s extremely fa s t . Our init ial results show identif ication accuracies comparable t o the best results of minutiae-based algorithms published in the open literature [ . I . Finally, w e show that t he matching per formance can be improved by combining the decisions of the ma tchers based o n complementary f ingerprint in format ion .
Scaffolds in tissue engineering bone and cartilage.

Musculoskeletal tissue, bone and cartilage are under extensive investigation in tissue engineering research. A number of biodegradable and bioresorbable materials, as well as scaffold designs, have been experimentally and/or clinically studied. Ideally, a scaffold should have the following characteristics: (i) three-dimensional and highly porous with an interconnected pore network for cell growth and flow transport of nutrients and metabolic waste; (ii) biocompatible and bioresorbable with a controllable degradation and resorption rate to match cell/tissue growth in vitro and/or in vivo; (iii) suitable surface chemistry for cell attachment, proliferation, and differentiation and (iv) mechanical properties to match those of the tissues at the site of implantation. This paper reviews research on the tissue engineering of bone and cartilage from the polymeric scaffold point of view.
The job satisfaction-job performance relationship: a qualitative and quantitative review.

A qualitative and quantitative review of the relationship between job satisfaction and job performance is provided. The qualitative review is organized around 7 models that characterize past research on the relationship between job satisfaction and job performance. Although some models have received more support than have others, research has not provided conclusive confirmation or disconfirmation of any model, partly because of a lack of assimilation and integration in the literature. Research devoted to testing these models waned following 2 meta-analyses of the job satisfaction-job performance relationship. Because of limitations in these prior analyses and the misinterpretation of their findings, a new meta-analysis was conducted on 312 samples with a combined N of 54,417. The mean true correlation between overall job satisfaction and job performance was estimated to be .30. In light of these results and the qualitative review, an agenda for future research on the satisfaction-performance relationship is provided.
Performance Comparison of Cholesky Decomposition on GPUs and FPGAs

Cholesky decomposition has been widely utilized for positive symmetric matrix factorization in solving least square problems. Various parallel accelerators including GPUs and FPGAs have been explored to improve performance. In this paper, Cholesky decomposition is implemented on both FPGAs and GPUs by designing a dedicated architecture for FPGAs and exploiting massively parallel computation for GPUs. Performance of the Cholesky decomposition on GPUs, CPUs, FPGAs, and hybrid systems are compared in both single and double precision. Results show that the FPGA implementation has the highest efficiency with respect to clock cycles compared with our pure GPU implementation, a hybrid system with MAGMA, and a CPU with LAPACK. The GPU implementation is better than other implementations using MAGMA and LAPACK library for small matrices, and the hybrid system with MAGMA is the best for larger matrices.
Low-complexity image denoising based on statistical modeling of wavelet coefficients

We introduce a simple spatially adaptive statistical model for wavelet image coefficients and apply it to image denoising. Our model is inspired by a recent wavelet image compression algorithm, the estimation-quantization (EQ) coder. We model wavelet image coefficients as zero-mean Gaussian random variables with high local correlation. We assume a marginal prior distribution on wavelet coefficients variances and estimate them using an approximate maximum a posteriori probability rule. Then we apply an approximate minimum mean squared error estimation procedure to restore the noisy wavelet image coefficients. Despite the simplicity of our method, both in its concept and implementation, our denoising results are among the best reported in the literature.
Prospective Investigation of Video Game Use in Children and Subsequent Conduct Disorder and Depression Using Data from the Avon Longitudinal Study of Parents and Children

There is increasing public and scientific concern regarding the long-term behavioural effects of video game use in children, but currently little consensus as to the nature of any such relationships. We investigated the relationship between video game use in children, degree of violence in games, and measures of depression and a 6-level banded measure of conduct disorder. Data from the Avon Longitudinal Study of Parents and Children were used. A 3-level measure of game use at age 8/9 years was developed, taking into account degree of violence based on game genre. Associations with conduct disorder and depression, measured at age 15, were investigated using ordinal logistic regression, adjusted for a number of potential confounders. Shoot-em-up games were associated with conduct disorder bands, and with a binary measure of conduct disorder, although the strength of evidence for these associations was weak. A sensitivity analysis comparing those who play competitive games to those who play shoot-em-ups found weak evidence supporting the hypothesis that it is violence rather than competitiveness that is associated with conduct disorder. However this analysis was underpowered, and we cannot rule out the possibility that increasing levels of competition in games may be just as likely to account for the observed associations as violent content. Overall game exposure as indicated by number of games in a household was not related to conduct disorder, nor was any association found between shoot-em-up video game use and depression.
Privacy-preserving Network Provenance

Network accountability, forensic analysis, and failure diagnosis are becoming increasingly important for network management and security. Network provenance significantly aids network administrators in these tasks by explaining system behavior and revealing the dependencies between system states. Although resourceful, network provenance can sometimes be too rich, revealing potentially sensitive information that was involved in system execution. In this paper, we propose a cryptographic approach to preserve the confidentiality of provenance (sub)graphs while allowing users to query and access the parts of the graph for which they are authorized. Our proposed solution is a novel application of searchable symmetric encryption (SSE) and more generally structured encryption (SE). Our SE-enabled provenance system allows a node to enforce access control policies over its provenance data even after the data has been shipped to remote nodes (e.g., for optimization purposes). We present a prototype of our design and demonstrate its practicality, scalability, and efficiency for both provenance maintenance and querying.
Stakeholder engagement, social auditing and corporate sustainability

To identify the applicability of social auditing as an approach of engaging stakeholders in assessing and reporting on corporate sustainability and its performance.  Drawing upon the framework of AA1000 and the social auditing studies, this paper links stakeholder engagement, social auditing and corporate sustainability with a view to applying dialogue-based social auditing to address corporate sustainability.  This paper identifies a “match” between corporate sustainability and social auditing, as both aim at improving the social, environmental and economic performance of an organisation, considering the well-being of a wider range of stakeholders and requiring the engagement of stakeholders in the process. This paper suggests that social auditing through engaging stakeholders via dialogue could be applied to build trusts, identify commitment and promote co-operation amongst stakeholders and corporations.  This research requires further empirical research into the practicality of social auditing in addressing corporate sustainability and the determination of the limitations of dialogue-based social auditing.  Social auditing has been identified as a useful mechanism of balancing differing interests among stakeholders and corporations in a democratic business society. The application of social auditing in developing and achieving corporate sustainability has apparently practical implications.  This paper examines the applicability of dialogue-based social auditing in helping business to move towards sustainability. Social auditing as a process of assessing and reporting on corporate social and environmental performance through engaging stakeholders via dialogue could be applied to build trusts, identify commitment and promote cooperation amongst stakeholders and corporations.
Retail Bank Services Strategy: A Model of Traditional, Electronic, and Mixed Distribution Choices

Design of a retail banking distribution strategy is an important issue in that industry. This paper shows the effect of new electronic distribution technologies such as PC banking on the choice of a bank’s distribution strategy. We present a competitive model of distribution strategy choice, including heterogeneous consumers and banks, that allows a rich variety of customer preference and technology cost parameters. Sensitivity analysis shows how several parameters affect the competitive outcome. This analysis suggests that changing consumer behavior and attitudes, instead of banks’ cost structure with new technologies significantly affects the bank’s distribution strategy choice. If the segment of consumers that prefers PC banking remains small relative to the segment that prefers branches, then there will still be a market for specialized branch banks. Branch banking without PC banking services will be a viable strategy until the segment that prefers PC banking grows larger (amounting to about 40 percent of all transactions). Banks offering both branch and PC banking services can prevent successful and profitable entry by virtual banks (Internet banks offering only PC banking services) as long as the segment of customers that prefer PC banking remains relatively small (less than two-thirds of all transactions). Beyond this fraction, virtual banks will be profitable. This analysis suggests that it may be a long time (if ever) before virtual banks turn a profit.
Comparison of 3D Joint Angles Measured With the Kinect 2.0 Skeletal Tracker Versus a Marker-Based Motion Capture System.

The Microsoft Kinect is becoming a widely used tool for inexpensive, portable measurement of human motion, with the potential to support clinical assessments of performance and function. In this study, the relative osteokinematic Cardan joint angles of the hip and knee were calculated using the Kinect 2.0 skeletal tracker. The pelvis segments of the default skeletal model were reoriented and 3-dimensional joint angles were compared with a marker-based system during a drop vertical jump and a hip abduction motion. Good agreement between the Kinect and marker-based system were found for knee (correlation coefficient = 0.96, cycle RMS error = 11°, peak flexion difference = 3°) and hip (correlation coefficient = 0.97, cycle RMS = 12°, peak flexion difference = 12°) flexion during the landing phase of the drop vertical jump and for hip abduction/adduction (correlation coefficient = 0.99, cycle RMS error = 7°, peak flexion difference = 8°) during isolated hip motion. Nonsagittal hip and knee angles did not correlate well for the drop vertical jump. When limited to activities in the optimal capture volume and with simple modifications to the skeletal model, the Kinect 2.0 skeletal tracker can provide limited 3-dimensional kinematic information of the lower limbs that may be useful for functional movement assessment.
"Easy" Cooking Recipe Recommendation Considering User's Conditions

It is natural to think that couples who work at a company or a person who lives by her/himself want to cook food for themselves as quickly and easily as possible when they are busy. However, to keep having the same food they can easily cook fed them up, therefore, it should be preferable for them to be recommended a variety of food that they can cook "easily". Currently, there are so many Web sites for cooking recipes, and there are also recipes regarded as "easy" to cook. However, those recipes are not estimated as "easy" by taking user's conditions into account. Therefore, in this study, we aim to propose a method to recommend "easy" cooking recipes by analyzing the content of recipes and considering user's conditions and then develop a recommendation system with the proposed method.
Web evaluation: heuristic evaluation vs. user testing.

It is very important that designers recognize the benefits and limitations of different usability inspection methods. This is because the quality of the usability evaluation is dependent on the method used. Two of the most popular usability evaluation techniques are user testing and heuristic analysis. The main objective of this study was to compare the efficiency and effectiveness between user testing and heuristic analysis in evaluating four different commercial web sites. The results showed that both user testing and heuristic analysis addressed different usability problems. Analysis by severity of problems found and diminishing return analysis model on the relationship between the number of new problems discovered with users and evaluators used showed that both methods are equally efficient and effective in addressing different categories of usability problems. These significant differences found between these two methods suggested that the two methods are complimentary and should not be competing. In order for better evaluation results, both user testing and heuristic analysis are still needed.  The research findings from this study will be of particular value to the web development industry and communities. Knowledge regarding the differences between user testing and heuristic evaluation will enable appropriate business decisions to be made on when and how to apply these methods to improve the overall efficiency of the design process.
Thermodynamics and NMR of internal G.T mismatches in DNA.

Thermodynamics of 39 oligonucleotides with internal G.T mismatches dissolved in 1 M NaCl were determined from UV absorbance versus temperature profiles. These data were combined with literature values of six sequences to derive parameters for 10 linearly independent trimer and tetramer sequences with G.T mismatches and Watson-Crick base pairs. The G.T mismatch parameters predict DeltaG degrees 37, DeltaH degrees , DeltaS degrees , and TM with average deviations of 5.1%, 7.5%, 8.0%, and 1.4 degrees C, respectively. These predictions are within the limits of what can be expected for a nearest-neighbor model. The data show that the contribution of a single G.T mismatch to helix stability is context dependent and ranges from +1.05 kcal/mol for AGA/TTT to -1.05 kcal/mol for CGC/GTG. Several tests of the applicability of the nearest-neighbor model to G.T mismatches are described. Analysis of imino proton chemical shifts show that structural perturbations from the G.T mismatches are highly localized. One-dimensional NOE difference spectra demonstrate that G.T mismatches form stable hydrogen-bonded wobble pairs in diverse contexts. Refined nearest-neighbor parameters for Watson-Crick base pairs are also presented.
A Design Space Exploration Framework for Convolutional Neural Networks Implemented on Edge Devices

Deploying convolutional neural networks (CNNs) in embedded devices that operate at the edges of Internet of Things (IoT) networks provides various advantages in terms of performance, energy efficiency, and security in comparison with the alternative approach of transmitting large volumes of data for processing to the cloud. However, the implementation of CNNs on low power embedded devices is challenging due to the limited computational resources they provide and to the large resource requirements of state-of-the-art CNNs. In this paper, we propose a framework for the efficient deployment of CNNs in low power processor-based architectures used as edge devices in IoT networks. The framework leverages design space exploration (DSE) techniques to identify efficient implementations in terms of execution time and energy consumption. The exploration parameter is the utilization of hardware resources of the edge devices. The proposed framework is evaluated using a set of 6 state-of-the-art CNNs deployed in the Intel/Movidius Myriad2 low power embedded platform. The results show that using the maximum available amount of resources is not always the optimal solution in terms of performance and energy efficiency. Fine-tuned resource management based on DSE, reduces the execution time up to 3.6% and the energy consumption up to 7.7% in comparison with straightforward implementations.
Learning Discriminative Representation with Signed Laplacian Restricted Boltzmann Machine

We investigate the potential of a restricted Boltzmann Machine (RBM) for discriminative representation learning. By imposing the class information preservation constraints on the hidden layer of the RBM, we propose a Signed Laplacian Restricted Boltzmann Machine (SLRBM) for supervised discriminative representation learning. The model utilizes the label information and preserves the global data locality of data points simultaneously. Experimental results on the benchmark data set show the effectiveness of our method.
Secure Logging as a Service—Delegating Log Management to the Cloud

Securely maintaining log records over extended periods of time is very important to the proper functioning of any organization. Integrity of the log files and that of the logging process need to be ensured at all times. In addition, as log files often contain sensitive information, confidentiality and privacy of log records are equally important. However, deploying a secure logging infrastructure involves substantial capital expenses that many organizations may find overwhelming. Delegating log management to the cloud appears to be a viable cost saving measure. In this paper, we identify the challenges for a secure cloud-based log management service and propose a framework for doing the same.
A Hidden Semi-Markov Model-Based Speech Synthesis System

Recently, a statistical speech synthesis system based on the hidden Markov model (HMM) has been proposed. In this system, spectrum, excitation, and duration of human speech are modeled simultaneously by context-dependent HMMs and speech parameter vector sequences are generated from the HMMs themselves. This system defines a speech synthesis problem in a generative model framework and solves it using the maximum likelihood (ML) criterion. However, there is an inconsistency: although state duration models are explicitly used in the synthesis part of the system, they have not been incorporated in its training part. This inconsistency may degrade the naturalness of synthesized speech. In the present paper, a statistical speech synthesis system based on a hidden semi-Markov model (HSMM), which can be viewed as an HMM with explicit state duration models, is developed and evaluated. The use of HSMMs allows us to incorporate the state duration models explicitly not only in the synthesis part but also in the training part of the system and resolves the inconsistency in the HMM-based speech synthesis system. Subjective listening test results show that the use of HSMMs improves the reported naturalness of synthesized speech. key words: hidden Markov model, hidden semi-Markov model, HMMbased speech synthesis
Class-DE Ultrasound Transducer Driver for HIFU Therapy

This paper presents a practical implementation of an integrated MRI-compatible CMOS amplifier capable of directly driving a piezoelectric ultrasound transducer suitable for high-intensity focused ultrasound (HIFU) therapy. The amplifier operates in Class DE mode without the need for an output matching network. The integrated amplifier has been implemented with the AMS AG H35 CMOS process. A class DE amplifier design methodology for driving unmatched piezoelectric loads is presented along with simulation and experimental results. The proposed design achieves approximately 90% efficiency with over 800 mW of output power at 1010 kHz. The total die area including pads is 2 mm2. Compatibility with MRI was validated with B1 imaging of a phantom and the amplifier circuit.
The role of chronotype, gender, test anxiety, and conscientiousness in academic achievement of high school students.

Previous findings have demonstrated that chronotype (morningness/intermediate/eveningness) is correlated with cognitive functions, that is, people show higher mental performance when they do a test at their preferred time of day. Empirical studies found a relationship between morningness and higher learning achievement at school and university. However, only a few of them controlled for other moderating and mediating variables. In this study, we included chronotype, gender, conscientiousness and test anxiety in a structural equation model (SEM) with grade point average (GPA) as academic achievement outcome. Participants were 158 high school students and results revealed that boys and girls differed in GPA and test anxiety significantly, with girls reporting better grades and higher test anxiety. Moreover, there was a positive correlation between conscientiousness and GPA (r = 0.17) and morningness (r = 0.29), respectively, and a negative correlation between conscientiousness and test anxiety (r = -0.22). The SEM demonstrated that gender was the strongest predictor of academic achievement. Lower test anxiety predicted higher GPA in girls but not in boys. Additionally, chronotype as moderator revealed a significant association between gender and GPA for evening types and intermediate types, while intermediate types showed a significant relationship between test anxiety and GPA. Our results suggest that gender is an essential predictor of academic achievement even stronger than low or absent test anxiety. Future studies are needed to explore how gender and chronotype act together in a longitudinal panel design and how chronotype is mediated by conscientiousness in the prediction of academic achievement.