nils-herrmann/clean_scirepeval huggingface dataset:
A modelling approach to multi-domain traceability

Traceability is an important concern in projects that span different engineering domains. Traceability can also be mandated, exploited and managed across the engineering lifecycle, and may involve defining connections between heterogeneous models. As a result, traceability can be considered to be multi-domain. This thesis introduces the concept and challenges of multi-domain traceability and explains how it can be used to support typical traceability scenarios. It proposes a model-based approach to develop a traceability solution which effectively operates across multiple engineering domains. The approach introduced a collection of tasks and structures which address the identified challenges for a traceability solution in multi-domain projects. The proposed approach demonstrates that modelling principles and MDE techniques can help to address current challenges and consequently improve the effectiveness of a multi-domain traceability solution. A prototype of the required tooling to support the approach is implemented with EMF and atop Epsilon; it consists of an implementation of the proposed structures (models) and model management operations to support traceability. Moreover, the approach is illustrated in the context of two safety-critical projects where multi-domain traceability is required to underpin certification arguments.
Review analyzer analysis of product reviews on WEKA classifiers

E-transactions have become promising and very much convenient due to worldwide and usage of the internet. The consumer reviews are increasing rapidly in number on various products. These large numbers of reviews are beneficial to manufacturers and consumers alike. It is a big task for a potential consumer to read all reviews to make a good decision of purchasing. It is beneficial to mine available consumer reviews for popular products from various product review sites of consumer. The first step is performing sentiment analysis to decide the polarity of a review. On the basis of polarity, we can then classify the review. Comparison is made among the different WEKA classifiers in the form of charts and graphs.
The anatomy of the medial part of the knee.

While the anatomy of the medial part of the knee has been described qualitatively, quantitative descriptions of the attachment sites of the main medial knee structures have not been reported. The purpose of the present study was to verify the qualitative anatomy of medial knee structures and to perform a quantitative evaluation of their anatomic attachment sites as well as their relationships to pertinent osseous landmarks.



Dissections were performed and measurements were made for eight nonpaired fresh-frozen cadaveric knees with use of an electromagnetic three-dimensional tracking sensor system.



In addition to the medial epicondyle and the adductor tubercle, a third osseous prominence, the gastrocnemius tubercle, which corresponded to the attachment site of the medial gastrocnemius tendon, was identified. The average length of the superficial medial (tibial) collateral ligament was 94.8 mm. The superficial medial collateral ligament femoral attachment was 3.2 mm proximal and 4.8 mm posterior to the medial epicondyle. The superficial medial collateral ligament had two separate attachments on the tibia. The distal attachment of the superficial medial collateral ligament on the tibia was 61.2 mm distal to the knee joint. The deep medial collateral ligament consisted of meniscofemoral and meniscotibial portions. The posterior oblique ligament femoral attachment was 7.7 mm distal and 6.4 mm posterior to the adductor tubercle and 1.4 mm distal and 2.9 mm anterior to the gastrocnemius tubercle. The medial patellofemoral ligament attachment on the femur was 1.9 mm anterior and 3.8 mm distal to the adductor tubercle.



The medial knee ligament structures have a consistent attachment pattern.
Coverage and Its Discontents

Everyone wants to know one thing about a test suite: will it detect enough bugs? Unfortunately, in most settings that matter, answering this question directly is impractical or impossible. Software engineers and researchers therefore tend to rely on various measures of code coverage (where mutation testing is considered a form of syntactic coverage). A long line of academic research efforts have attempted to determine whether relying on coverage as a substitute for fault detection is a reasonable solution to the problems of test suite evaluation. This essay argues that the profusion of coverage-related literature is in part a sign of an underlying uncertainty as to what exactly it is that measuring coverage should achieve, as well as how we would know if it can, in fact, achieve it. We propose some solutions and mitigations, but the primary focus of this essay is to clarify the state of current confusions regarding this key problem for effective software testing.
Flexible Primitives for Distributed Deep Learning in Ray

Distributed computation is increasingly important for deep learning, and many deep learning frameworks provide built-in support for distributed training. This results in a tight coupling between the neural network computation and the underlying distributed execution, which poses a challenge for the implementation of new communication and aggregation strategies. We argue that decoupling the deep learning framework from the distributed execution framework enables the flexible development of new communication and aggregation strategies. Furthermore, we argue that Ray  provides a flexible set of distributed computing primitives that, when used in conjunction with modern deep learning libraries, enable the implementation of a wide range of gradient aggregation strategies appropriate for different computing environments. We show how these primitives can be used to address common problems, and demonstrate the performance benefits empirically.
Complex regional pain syndrome is a disease of the central nervous system

Complex regional pain syndrome (CRPS) is clinically characterized by pain, abnormal regulation of blood flow and sweating, edema of skin and subcutaneous tissues, trophic changes of skin, appendages of skin and subcutaneous tissues, and active and passive movement disorders. It is classified into type I (previously reflex sympathetic dystrophy) and type II (previously causalgia). Based on multiple evidence from clinical observations, experimentation on humans, and experimentation on animals, the hypothesis has been put forward that CRPS is primarily a disease of the central nervous system. CRPS patients exhibit changes which occur in somatosensory systems processing noxious, tactile and thermal information, in sympathetic systems innervating skin (blood vessels, sweat glands), and in the somatomotor system. This indicates that the central representations of these systems are changed and data show that CRPS, in particular type I, is a systemic disease involving these neuronal systems. This way of looking at CRPS shifts the attention away from interpreting the syndrome conceptually in a narrow manner and to reduce it to one system or to one mechanism only, e. g., to sympathetic-afferent coupling. It will further our understanding why CRPS type I may develop after a trivial trauma, after a trauma being remote from the affected extremity exhibiting CRPS, and possibly after immobilization of an extremity. It will explain why, in CRPS patients with sympathetically maintained pain, a few temporary blocks of the sympathetic innervation of the affected extremity sometimes lead to long-lasting (even permanent) pain relief and to resolution of the other changes observed in CRPS. This changed view will bring about a diagnostic reclassification and redefinition of CRPS and will have bearings on the therapeutic approaches. Finally it will shift the focus of research efforts.
Multimodality image registration by maximization of mutual information

A new approach to the problem of multimodality medical image registration is proposed, using a basic concept from information theory, mutual information (MI), or relative entropy, as a new matching criterion. The method presented in this paper applies MI to measure the statistical dependence or information redundancy between the image intensities of corresponding voxels in both images, which is assumed to be maximal if the images are geometrically aligned. Maximization of MI is a very general and powerful criterion, because no assumptions are made regarding the nature of this dependence and no limiting constraints are imposed on the image content of the modalities involved. The accuracy of the MI criterion is validated for rigid body registration of computed tomography (CT), magnetic resonance (MR), and photon emission tomography (PET) images by comparison with the stereotactic registration solution, while robustness is evaluated with respect to implementation issues, such as interpolation and optimization, and image content, including partial overlap and image degradation. Our results demonstrate that subvoxel accuracy with respect to the stereotactic reference solution can be achieved completely automatically and without any prior segmentation, feature extraction, or other preprocessing steps which makes this method very well suited for clinical applications.
ESD Protection Design With On-Chip ESD Bus and High-Voltage-Tolerant ESD Clamp Circuit for Mixed-Voltage I/O Buffers

Considering gate-oxide reliability, a new electrostatic discharge (ESD) protection scheme with an on-chip ESD bus (ESD_BUS) and a high-voltage-tolerant ESD clamp circuit for 1.2/2.5 V mixed-voltage I/O interfaces is proposed. The devices used in the high-voltage-tolerant ESD clamp circuit are all 1.2 V low-voltage N- and P-type MOS devices that can be safely operated under the 2.5-V bias conditions without suffering from the gate-oxide reliability issue. The four-mode (positive-to-VSS, negative-to-VSS, positive-to-VDD, and negative-to-VDD) ESD stresses on the mixed-voltage I/O pad and pin-to-pin ESD stresses can be effectively discharged by the proposed ESD protection scheme. The experimental results verified in a 0.13-mum CMOS process have confirmed that the proposed new ESD protection scheme has high human-body model (HBM) and machine-model (MM) ESD robustness with a fast turn-on speed. The proposed new ESD protection scheme, which is designed with only low- voltage devices, is an excellent and cost-efficient solution to protect mixed-voltage I/O interfaces.
A video analysis framework for soft biometry security surveillance

We propose a distributed, multi-camera video analysis paradigm for aiport security surveillance. We propose to use a new class of biometry signatures, which are called soft biometry including a person's height, built, skin tone, color of shirts and trousers, motion pattern, trajectory history, etc., to ID and track errant passengers and suspicious events without having to shut down a whole terminal building and cancel multiple flights. The proposed research is to enable the reliable acquisition, maintenance, and correspondence of soft biometry signatures in a coordinated manner from a large number of video streams for security surveillance. The intellectual merit of the proposed research is to address three important video analysis problems in a distributed, multi-camera surveillance network: sensor network calibration, peer-to-peer sensor data fusion, and stationary-dynamic cooperative camera sensing.
A compiler framework for mapping applications to a coarse-grained reconfigurable computer architecture

The rapid growth of silicon densities has made it feasible to deploy reconfigurable hardware as a highly parallel computing platform. However, in most cases, the application needs to be programmed in hardware description or assembly languages, whereas most application programmers are familiar with the algorithmic programming paradigm. SA-C has been proposed as an expression-oriented language designed to implicitly express data parallel operations. Morphosys is a reconfigurable system-on-chip architecture that supports a data-parallel, SIMD computational model. This paper describes a compiler framework to analyze SA-C programs, perform optimizations, and map the application onto the Morphosys architecture. The mapping process involves operation scheduling, resource allocation and binding and register allocation in the context of the Morphosys architecture. The execution times of some compiled image-processing kernels can achieve up to 42x speed-up over an 800 MHz Pentium III machine.
Binding of intrinsic and extrinsic features in working memory.

There is ongoing debate concerning the mechanisms of feature binding in working memory. In particular, there is controversy regarding the extent to which these binding processes are automatic. The present article demonstrates that binding mechanisms differ depending on whether the to-be-integrated features are perceived as forming a coherent object. We presented a series of experiments that investigated the binding of color and shape, whereby color was either an intrinsic feature of the shape or an extrinsic feature of the shape's background. Results show that intrinsic color affected shape recognition, even when it was incidentally studied and irrelevant for the recognition task. In contrast, extrinsic color did not affect shape recognition, even when the association of color and shape was encoded and retrievable on demand. This strongly suggests that binding of intrinsic intra-item information but not extrinsic contextual information is obligatory in visual working memory. We highlight links to perception as well as implicit and explicit long-term memory, which suggest that the intrinsic-extrinsic dimension is a principle relevant to multiple domains of human cognition.
Lifestyle for Brain Health (LIBRA): a new model for dementia prevention.

Modifiable risk factors for dementia were recently identified and compiled in a systematic review. The 'Lifestyle for Brain Health' (LIBRA) score, reflecting someone's potential for dementia prevention, was studied in a large longitudinal population-based sample with respect to predicting cognitive change over an observation period of up to 16 years.



Lifestyle for Brain Health was calculated at baseline for 949 participants aged 50-81 years from the Maastricht Ageing Study. The predictive value of LIBRA for incident dementia and cognitive impairment was examined by using Cox proportional hazard models and by testing its relation with cognitive decline.



Lifestyle for Brain Health predicted future risk of dementia, as well as risk of cognitive impairment. A one-point increase in LIBRA score related to 19% higher risk for dementia and 9% higher risk for cognitive impairment. LIBRA predicted rate of decline in processing speed, but not memory or executive functioning.



Lifestyle for Brain Health (LIBRA) may help in identifying and monitoring risk status in dementia-prevention programmes, by targeting modifiable, lifestyle-related risk factors.
Complexity of system configuration management

System administration has often been considered to be a “practice” with no theoretical underpinnings. In this thesis, we begin to define a theory of system administration, based upon two activities of system administrators: configuration management and dependency analysis. We formalize and explore the complexity of these activities, and demonstrate that they are intractable in the general case. We define the concepts of system behavior, kinds of configuration operations, a model of configuration management, a model of reproducibility, and proofs that several parts of the process are NP-complete or NP-hard. We also explore how system administrators keep these tasks tractable in practice. This is a first step toward a theory of system administration and a common language for discussing the theoretical underpinnings of the practice.
Some expectations of a non-central chi-square distribution with an even number of degrees of freedom

The non-central chi-square distribution plays an important role in communications, for example in the analysis of mobile and wireless communication systems. It not only includes the important cases of a squared Rayleigh distribution and a squared Rice distribution, but also the generalizations to a sum of independent squared Gaussian random variables of identical variance with or without mean, i.e., a "squared MIMO Rayleigh" and "squared MIMO Rice" distribution. In this paper closed-form expressions are derived for the expectation of the logarithm and for the expectation of the n-th power of the reciprocal value of a non-central chi-square random variable. It is shown that these expectations can be expressed by a family of continuous functions gm(ldr) and that these families have nice properties (monotonicity, convexity, etc.). Moreover, some tight upper and lower bounds are derived that are helpful in situations where the closed-form expression of gm(ldr) is too complex for further analysis.
A survey on software cost estimation in the chinese software industry

Although a lot of attention has been paid to software cost estimation since 1960, making accurate effort and schedule estimation is still a challenge. To collect evidence and identify potential areas of improvement in software cost estimation, it is important to investigate the estimation accuracy, the estimation method used, and the factors influencing the adoption of estimation methods in current industry. This paper analyzed 112 projects from the Chinese software project benchmarking dataset and conducted questionnaire survey on 116 organizations to investigate the above information. The paper presents the current situations related to software project estimation in China and provides evidence-based suggestions on how to improve software project estimation. Our survey results suggest, e.g., that large projects were more prone to cost and schedule overruns, that most computing managers and professionals were neither satisfied nor dissatisfied with the project estimation, that very few organizations (15%) used model-based methods, and that the high adoption cost and insignificant benefit after adoption were the main causes for low use of model-based methods.
Batched Gauss-Jordan Elimination for Block-Jacobi Preconditioner Generation on GPUs

In this paper, we design and evaluate a routine for the efficient generation of block-Jacobi preconditioners on graphics processing units (GPUs). Concretely, to exploit the architecture of the graphics accelerator, we develop a batched Gauss-Jordan elimination CUDA kernel for matrix inversion that embeds an implicit pivoting technique and handles the entire inversion process in the GPU registers. In addition, we integrate extraction and insertion CUDA kernels to rapidly set up the block-Jacobi preconditioner.
 Our experiments compare the performance of our implementation against a sequence of batched routines from the MAGMA library realizing the inversion via the LU factorization with partial pivoting. Furthermore, we evaluate the costs of different strategies for the block-Jacobi extraction and insertion steps, using a variety of sparse matrices from the SuiteSparse matrix collection. Finally, we assess the efficiency of the complete block-Jacobi preconditioner generation in the context of an iterative solver applied to a set of computational science problems, and quantify its benefits over a scalar Jacobi preconditioner.
Generic User Modeling Systems

The paper reviews the development of generic user modeling systems over the past twenty years. It describes their purposes, their services within user-adaptive systems, and the different design requirements for research prototypes and commercially deployed servers. It discusses the architectures that have been explored so far, namely shell systems that form part of the application, central server systems that communicate with several applications, and possible future user modeling agents that physically follow the user. Several implemented research prototypes and commercial systems are briefly described.
A scalable content-addressable network

Hash tables - which map "keys" onto "values" - are an essential building block in modern software systems. We believe a similar functionality would be equally valuable to large distributed systems. In this paper, we introduce the concept of a Content-Addressable Network (CAN) as a distributed infrastructure that provides hash table-like functionality on Internet-like scales. The CAN is scalable, fault-tolerant and completely self-organizing, and we demonstrate its scalability, robustness and low-latency properties through simulation.
The SUMMA Platform Prototype

We present the first prototype of the SUMMA Platform: an integrated platform for multilingual media monitoring. The platform contains a rich suite of low-level and high-level natural language processing technologies: automatic speech recognition of broadcast media, machine translation, automated tagging and classification of named entities, semantic parsing to detect relationships between entities, and automatic construction / augmentation of factual knowledge bases. Implemented on the Docker platform, it can easily be deployed, customised, and scaled to large volumes of incoming media streams.
Biology's response to dieting: the impetus for weight regain.

Dieting is the most common approach to losing weight for the majority of obese and overweight individuals. Restricting intake leads to weight loss in the short term, but, by itself, dieting has a relatively poor success rate for long-term weight reduction. Most obese people eventually regain the weight they have worked so hard to lose. Weight regain has emerged as one of the most significant obstacles for obesity therapeutics, undoubtedly perpetuating the epidemic of excess weight that now affects more than 60% of U.S. adults. In this review, we summarize the evidence of biology's role in the problem of weight regain. Biology's impact is first placed in context with other pressures known to affect body weight. Then, the biological adaptations to an energy-restricted, low-fat diet that are known to occur in the overweight and obese are reviewed, and an integrative picture of energy homeostasis after long-term weight reduction and during weight regain is presented. Finally, a novel model is proposed to explain the persistence of the "energy depletion" signal during the dynamic metabolic state of weight regain, when traditional adiposity signals no longer reflect stored energy in the periphery. The preponderance of evidence would suggest that the biological response to weight loss involves comprehensive, persistent, and redundant adaptations in energy homeostasis and that these adaptations underlie the high recidivism rate in obesity therapeutics. To be successful in the long term, our strategies for preventing weight regain may need to be just as comprehensive, persistent, and redundant, as the biological adaptations they are attempting to counter.
Deformable GANs for Pose-Based Human Image Generation

In this paper we address the problem of generating person images conditioned on a given pose. Specifically, given an image of a person and a target pose, we synthesize a new image of that person in the novel pose. In order to deal with pixel-to-pixel misalignments caused by the pose differences, we introduce deformable skip connections in the generator of our Generative Adversarial Network. Moreover, a nearest-neighbour loss is proposed instead of the common L1 and L2 losses in order to match the details of the generated image with the target image. We test our approach using photos of persons in different poses and we compare our method with previous work in this area showing state-of-the-art results in two benchmarks. Our method can be applied to the wider field of deformable object generation, provided that the pose of the articulated object can be extracted using a keypoint detector.