nils-herrmann/clean_scirepeval huggingface dataset:
Design of Low Voltage Unsaturated Ring Oscillator for a Sigma Delta Time to Digital Converter

This thesis investigates the phase noise of two different 2-stage cross-coupled pair unsaturated ring oscillators with no tail current source. One oscillator consists of top crosscoupled pair delay cells, and the other consists of top cross-coupled pair and bottom crosscoupled pair delay cells. Under a low supply voltage restriction, a phase noise model is developed and applied to both ring oscillators. Both top cross-coupled pair and top and bottom cross-coupled pair oscillators are fabricated with 0.13 μm CMOS technology. Phase noise measurements of -92 dBc/Hz and -89 dBc/Hz ,respectively, at 1 MHz offset is obtained from the chip, which agree with theory and simulations. Top cross-coupled ring oscillator, with phase noise of -92 dBc/Hz at 1 MHz offset, is implemented in a second order sigma-delta time to digital converter. System level and transistor level functional simulation and timing jitter simulation are obtained.
Feature Fusion for Scene Text Detection

A significant challenge in scene text detection is the large variation in text sizes. In particular, small text are usually hard to detect. This paper presents an accurate oriented text detector based on Faster R-CNN. We observe that Faster R-CNN is suitable for general object detection but inadequate for scene text detection due to the large variation in text size. We apply feature fusion both in RPN and Fast R-CNN to alleviate this problem and furthermore, enhance model's ability to detect relatively small text. Our text detector achieves comparable results to those state of the art methods on ICDAR 2015 and MSRA-TD500, showing its advantage and applicability.
A framework for classifying semantic relationships

Recently, the NLP community has shown a renewed interest in lexical semantics in the extent of automatic recognition of semantic relationships between pairs of words in text. Lexical semantics has become increasingly important in many natural language applications, this approach to semantics is concerned with psychological facts associated with meaning of words and how these words can be connected in semantic relations to build ontologies that provide a shared vocabulary to model a specified domain. And represent a structural framework for organizing information across fields of Artificial Intelligence (AI), Semantic Web, systems engineering and information architecture. But current systems mainly concentrate on classification of semantic relations rather than to give solutions for how these relations can be created . At the same time, systems that do provide methods for creating the relations tend to ignore the context in which the conceptual relationships occur. Furthermore, methods that address semantic (non-taxonomic) relations are yet to come up with widely accepted ways of enhancing the process of classifying and extracting semantic relations. In this research we will focus on the learning of semantic relations patterns between word meanings by taking into consideration the surrounding context in the general domain. We will first generate semantic patterns in domain independent environment depending on previous specific semantic information, and a set of input examples. Our case of study will be causation relations. Then these patterns will classify causation in general domain texts taking into consideration the context of the relations, and then the classified relations will be used to learn new causation semantic patterns.
A neuroprotective function for the hematopoietic protein granulocyte-macrophage colony stimulating factor (GM-CSF).

Granulocyte-macrophage colony-stimulating factor (GM-CSF) is a hematopoietic cytokine responsible for the proliferation, differentiation, and maturation of cells of the myeloid lineage, which was cloned more than 20 years ago. Here we uncovered a novel function of GM-CSF in the central nervous system (CNS). We identified the GM-CSF alpha-receptor as an upregulated gene in a screen for ischemia-induced genes in the cortex. This receptor is broadly expressed on neurons throughout the brain together with its ligand and induced by ischemic insults. In primary cortical neurons and human neuroblastoma cells, GM-CSF counteracts programmed cell death and induces BCL-2 and BCL-Xl expression in a dose- and time-dependent manner. Of the signaling pathways studied, GM-CSF most prominently induced the PI3K-Akt pathway, and inhibition of Akt strongly decreased antiapoptotic activity. Intravenously given GM-CSF passes the blood-brain barrier, and decreases infarct damage in two different experimental stroke models (middle cerebral artery occlusion (MCAO), and combined common carotid/distal MCA occlusion) concomitant with induction of BCL-Xl expression. Thus, GM-CSF acts as a neuroprotective protein in the CNS. This finding is remarkably reminiscent of the recently discovered functionality of two other hematopoietic factors, erythropoietin and granulocyte colony-stimulating factor in the CNS. The identification of a third hematopoietic factor acting as a neurotrophic factor in the CNS suggests a common principle in the functional evolution of these factors. Clinically, GM-CSF now broadens the repertoire of hematopoietic factors available as novel drug candidates for stroke and neurodegenerative diseases.
Learning Structure and Strength of CNN Filters for Small Sample Size Training

Convolutional Neural Networks have provided state-of-the-art results in several computer vision problems. However, due to a large number of parameters in CNNs, they require a large number of training samples which is a limiting factor for small sample size problems. To address this limitation, we propose SSF-CNN which focuses on learning the "structure" and "strength" of filters. The structure of the filter is initialized using a dictionary based filter learning algorithm and the strength of the filter is learned using the small sample training data. The architecture provides the flexibility of training with both small and large training databases, and yields good accuracies even with small size training data. The effectiveness of the algorithm is first demonstrated on MNIST, CIFAR10, and NORB databases, with varying number of training samples. The results show that SSF-CNN significantly reduces the number of parameters required for training while providing high accuracies on the test databases. On small sample size problems such as newborn face recognition and Omniglot, it yields state-of-the-art results. Specifically, on the IIITD Newborn Face Database, the results demonstrate improvement in rank-1 identification accuracy by at least 10%.
A data model of theses and dissertations compatible with CERIF, Dublin Core and EDT-MS

The aim of this research is to define a data model of theses and dissertations that enables data exchange with CERIF-compatible CRIS systems and data exchange according to OAI-PMH protocol in different metadata formats (Dublin Core, EDT-MS, etc.).  Various systems that contain metadata about theses and dissertations are analyzed. There are different standards and protocols that enable the interoperability of those systems: CERIF standard, AOI-PMH protocol, etc. A physical data model that enables interoperability with almost all of those systems is created using the PowerDesigner CASE tool.  A set of metadata about theses and dissertations that contain all the metadata required by CERIF data model, Dublin Core format, EDT-MS format and all the metadata prescribed by the University of Novi Sad is defined. Defined metadata can be stored in the CERIF-compatible data model based on the MARC21 format. UNS is a CRIS which has been developed at the University of Novi Sad since 2008. The system is based on the proposed data model, which enables the system’s interoperability with other CERIF-compatible CRIS systems. Also, the system based on the proposed model can become a member of NDLTD.  A system based on the proposed model increases the availability of theses and dissertations, and thus encourages the development of the knowledge-based society.  A data model of theses and dissertations that enables interoperability with CERIF-compatible CRIS systems is proposed. A software system based on the proposed model could become a member of NDLTD and exchange metadata with institutional repositories. The proposed model increases the availability of theses and dissertations.
What have we learned about treating child physical abuse? A literature review of the last decade.

A literature review of articles on treatment of physically abused children and treatment of physically abused parents was undertaken. Only articles that had more than five subjects in the sample, at least 15% of the children in the sample having been physically abused and either pretest, posttest; comparison group; or randomization between different treatments used in the design were selected. Twelve papers meeting these criteria for abusive parents and 13 for treatment of abused children were found. Treatment duration ranged from 4 weeks to 12 months for parents and 4 weeks to 24 months for children. A wide range of treatments were used, the most popular for children being therapeutic daycare, with emphasis on improving developmental skills. While most programs showed some improvement with treatment, many had no, or very short, follow-up to see if improvement was sustained. More emphasis needs to be placed on rigorous evaluation and longer-term follow-up of children in physical abuse treatment programs.
Tinea Capitis in Two Sisters of a Wooly Hair Family

Wooly hair is usually present at birth or infancy with a genetic linkage of autosomal dominant or recessive. Hair is curly, thick and often heavily pigmented. This condition has been reported with eye, teeth, cardiac anomalies. Also, keratosis pilaris atrophicans, ichtiyosis and deafness, palmoplantar keratoderma and Noonan syndrome may accompany wooly hair. We report two sisters with wooly hair, simultaneously developed an inflammatory tinea capitis (kerion). Our patients have neither a systemic disease nor eye, dental and other skin disorders. In their family; mother, two sisters, and one brother of them have also wooly hair without any other clinical associations. To our knowledge, this is the second, describes the association of wooly hair with tinea capitis. However, in the first report, mother and her son, also had keratosis follicularis spinulosa decalvans. As a result, presence of tinea capitis in both patients may be explained by the enhanced susceptibility to fungal infection in keratinizing disorders.
Enslaving the Algorithm: From a “Right to an Explanation” to a “Right to Better Decisions”?

As concerns about unfairness and discrimination in “black box” machine learning systems rise, a legal “right to an explanation” has emerged as a compellingly attractive approach for challenge and redress. We outline recent debates on the limited provisions in European data protection law, and introduce and analyze newer explanation rights in French administrative law and the draft modernized Council of Europe Convention 108. While individual rights can be useful, in privacy law they have historically unreasonably burdened the average data subject. “Meaningful information” about algorithmic logics is more technically possible than commonly thought, but this exacerbates a new “transparency fallacy”—an illusion of remedy rather than anything substantively helpful. While rights-based approaches deserve a firm place in the toolbox, other forms of governance, such as impact assessments, “soft law,” judicial review, and model repositories deserve more attention, alongside catalyzing agencies acting for users to control algorithmic system design.
Spatial accessibility of primary health care utilising the two step floating catchment area method: an assessment of recent improvements

The two step floating catchment area (2SFCA) method has emerged in the last decade as a key measure of spatial accessibility, particularly in its application to primary health care access. Many recent 'improvements' to the original 2SFCA method have been developed, which generally either account for distance-decay within a catchment or enable the usage of variable catchment sizes. This paper evaluates the effectiveness of various proposed methods within these two improvement groups. Moreover, its assessment focuses on how well these improvements operate within and between rural and metropolitan populations over large geographical regions.



Demonstrating these improvements to the whole state of Victoria, Australia, this paper presents the first comparison between continuous and zonal (step) decay functions and specifically their effect within both rural and metropolitan populations. Especially in metropolitan populations, the application of either type of distance-decay function is shown to be problematic by itself. Its inclusion necessitates the addition of a variable catchment size function which can enable the 2SFCA method to dynamically define more appropriate catchments which align with actual health service supply and utilisation.



This study assesses recent 'improvements' to the 2SFCA when applied over large geographic regions of both large and small populations. Its findings demonstrate the necessary combination of both a distance-decay function and variable catchment size function in order for the 2SFCA to appropriately measure healthcare access across all geographical regions.
Left-insular cortex lesions perturb cardiac autonomic tone in humans

The insular cortex is involved in cardiac regulation. The left insula is predominantly responsible for parasympathetic cardiovascular effects. Damage to this area could shift cardiovascular balance towards increased basal sympathetic tone (a proarrhythmic condition) and contribute to the excess cardiac mortality following stroke. Acute left insular stroke increased basal cardiac sympathetic tone and was associated with a decrease in randomness of heart rate variability. In addition, phase relationships between heart rate and blood pressure were disturbed, implying a disruption of oscillators involved in cardiovascular control. The insula appears to be involved in human heart rate regulation and damage to it may encourage a pro-arrhythmic state.
Sensory reflex control for humanoid walking

Since a biped humanoid inherently suffers from instability and always risks tipping itself over, ensuring high stability and reliability of walk is one of the most important goals. This paper proposes a walk control consisting of a feedforward dynamic pattern and a feedback sensory reflex. The dynamic pattern is a rhythmic and periodic motion, which satisfies the constraints of dynamic stability and ground conditions, and is generated assuming that the models of the humanoid and the environment are known. The sensory reflex is a simple, but rapid motion programmed in respect to sensory information. The sensory reflex we propose in this paper consists of the zero moment point reflex, the landing-phase reflex, and the body-posture reflex. With the dynamic pattern and the sensory reflex, it is possible for the humanoid to walk rhythmically and to adapt itself to the environmental uncertainties. The effectiveness of our proposed method was confirmed by dynamic simulation and walk experiments on an actual 26-degree-of-freedom humanoid.
A data locality optimizing algorithm (with retrospective)

This paper proposes an algorithm that improves the locality of a loop nest by transforming the code via interchange, reversal, skewing and tiling. The loop transformation algorithm is based on two concepts: a mathematical formulation of reuse and locality, and a loop transformation theory that unifies the various transforms as unimodular matrix transformations.The algorithm has been implemented in the SUIF (Stanford University Intermediate Format) compiler, and is successful in optimizing codes such as matrix multiplication, successive over-relaxation (SOR), LU decomposition without pivoting, and Givens QR factorization. Performance evaluation indicates that locality optimization is especially crucial for scaling up the performance of parallel code.
CLASSIFICATION OF SKIN DISEASE USING MULTI SVM CLASSIFIER

Skin diseases are most common form of infections occurring in people of all ages. A patient can recover from severe skin diseases if it is detected and treated in the early stages and this can achieve cure ratios of over 95%. Early diagnosis is dependent upon patient attention and accurate assessment by a medical practitioner. Due to the costs of dermatologists to monitor every patient, there is a need for a computerized system to evaluate patient‘s risk of skin disease using images of their skin lesions captured using a standard digital camera. The traditional diagnosis technique comprised of a recording of what the human eye can see using a digital camera whereas this idea aims at improving the quality of existing diagnostic systems by proposing advanced feature extraction and classification methods. In the Proposed method, 45 digital images collected from MIT BMI unit and this database consists of warts, benign skin cancer and malignant skin cancer image apart from normal skin images. These images are subjected to various pre-processing techniques such as resizing, RGB to LAB conversion and contrast enhancement. Then these images are undergone image segmentation using c-means and watershed algorithms individually. Feature extraction is performed using Grey Level Co-occurrence Matrix (GLCM) and Image Quality Assessment (IQA) methods for examining texture which gave the statistical parameters of each algorithm respectively. These features are unitedly used to obtain better classification efficiency. In this work, different types of skin diseases are commonly classified as Benign Skin Cancer, Malignant Skin Cancer and Warts using multi-SVM (Support Vector Machine). Support Vector Machines (SVM) are supervised learning models with associated algorithms that analyze database images for classification analysis. The diagnosis system involves two stages of process such as training and testing. Features values of the training data set is compared to the testing data set of each type. C-means algorithm provides better segmentation and feature extraction compared to watershed algorithm
Analysis of the Power Factor of Stator DC-Excited Vernier Reluctance Machines

Stator dc-excited vernier reluctance machines (dc-VRMs) are a kind of a novel vernier reluctance synchronous machine that employs doubly salient structures; their innovations include stator concentrated dc windings to generate the exciting field. Compared with the rotor wound field machines or stator/rotor PM synchronous machines, these machines are characterized by low cost due to the absence of PMs, a robust rotor structure, and a wide speed range resulting from the flexible stator dc exciting field. In this paper, with the proposed phasor diagram, the power factor of dc-VRMs is analyzed analytically and with the finite-element analysis, and the analysis results are confirmed with the experiment. It is found that, with constant slot sizes and slot fill, the power factor is mainly dependent on the ratio of the dc current to the armature winding current and also the ratio of the armature synchronous inductance to the mutual inductance between the field winding and the armature winding. However, torque will be sacrificed if measures are taken to further improve the power factor.
CHARACTERIZATION OF ELECTRIC SOLID PROPELLANT PULSED MICROTHRUSTERS by MATTHEW SCOTT GLASCOCK

Electric solid propellants are an attractive option for space propulsion because they are ignited by applied electric power only. In this work, the behavior of pulsed microthruster devices utilizing such a material is investigated. These devices are similar in function and operation to the pulsed plasma thruster, which typically uses Teflon as propellant. A Faraday probe, Langmuir triple probe, residual gas analyzer, pendulum thrust stand and high speed camera are utilized as diagnostic devices. These thrusters are made in batches, of which a few devices were tested experimentally in vacuum environments. Results indicate a plume electron temperature of about 1.7 eV, with an electron density between 10 and 10 cm. According to thermal equilibrium and adiabatic expansion calculations, these relatively hot electrons are mixed with ~2000 K neutral and ion species, forming a non-equilibrium gas. From time-of-flight analysis, this gas mixture plume has an effective velocity of 1500-1650 m/s on centerline. The ablated mass of this plume is 215 μg on average, of which an estimated 0.3% is ionized species while 45±11% is ablated at negligible relative speed. This late-time ablation occurs on a time scale three times that of the 0.5 ms pulse discharge, and does not contribute to the measured 0.21 mN-s impulse per pulse. Similar values have previously been measured in pulsed plasma thrusters. These observations indicate the electric solid propellant material in this configuration behaves similar to Teflon in an electrothermal pulsed plasma
S-TunExSPEM: Towards an Extension of SPEM 2.0 to Model and Exchange Tunable Safety-Oriented Processes

Prescriptive process-based safety standards (e.g. EN 50128, DO-178B, etc.) incorporate best practices to be adopted to develop safety-critical systems or software. In some domains, compliance with the standards is required to get the certificate from the certification authorities. Thus, a well-defined interpretation of the processes to be adopted is essential for certification purposes. Currently, no satisfying means allows process engineers and safety managers to model and exchange safety-oriented processes. To overcome this limitation, this paper proposes S-TunExSPEM, an extension of Software & Systems Process Engineering MetaModel 2.0 (SPEM 2.0) to allow users to specify safety-oriented processes for the development of safety-critical systems in the context of safety standards according to the required safety level. Moreover, to enable exchange for simulation, monitoring, execution purposes, S-TunExSPEM concepts are mapped onto XML Process Definition Language 2.2 (XPDL 2.2) concepts. Finally, a case-study from the avionics domain illustrates the usage and effectiveness of the proposed extension.
Field measurement and analysis on the prestress loss of a long-span PC box Girder Bridge

The crack and large deflection of long-span PC box Girder Bridge is common in their service stage. The lower estimation for the loss of prestress is one of possible reasons. Combined with a long-span prestressed concrete box girder bridges, the loss of longitudinal and vertical prestress of a long-span PC box girder bridge is measured during the construction and service stage. Based on the measured results, the loss of the longitudinal and vertical prestress of the long-span PC box girder bridge is analyzed by GA-ANN method and the code of JTG D62-2004, respectively. The results demonstrate that the instantaneous loss of the longitudinal prestress is more than 40% of the designed value, and the total loss of the vertical prestress is about 40% more than the designed one as well. The value of the prestress loss is much higher than the expected one of the design. The reason lies in the inappropriate construction technology, such as not tension the prestress to the designed value, tension at an early age, and excessive different of the tube wobble and so on. Therefore, the engineering quality control must be strengthened during the construction stage of the long-span PC box girder bridge for avoiding excessive prestress loss.