nils-herrmann/clean_scirepeval huggingface dataset:
Wide Residual Networks
Venue: BMVC
Year: 2016

Deep residual networks were shown to be able to scale up to thousands of layers and still have improving performance. However, each fraction of a percent of improved accuracy costs nearly doubling the number of layers, and so training very deep residual networks has a problem of diminishing feature reuse, which makes these networks very slow to train. To tackle these problems, in this paper we conduct a detailed experimental study on the architecture of ResNet blocks, based on which we propose a novel architecture where we decrease depth and increase width of residual networks. We call the resulting network structures wide residual networks (WRNs) and show that these are far superior over their commonly used thin and very deep counterparts. For example, we demonstrate that even a simple 16 layer deep wide residual network outperforms in accuracy and efficiency all previous deep residual networks, including thousand layer deep networks, achieving new state of the art results on CIFAR, SVHN, COCO, and significant improvements on ImageNet. Our code and models are available at this https URL
"Kubla Khan" and Islamic Structures: Retracing Symbolism and Investigating Imagination
Venue: New Horizons in English Studies
Year: 2019

Samuel Taylor Coleridge'spoem "Kubla Khan" draws upon the historical Xanadu, the summer palace of Mongol ruler Kubla Khan, and presents an architectural space that uses a commixture of imagination and mimesis to present a space of historical and supernatural transactions and transcends geographical limits. The architectural characteristics of Kubla Khan's pleasure dome in Xanadu are replete with similarities with various elements of Islamic architecture. The walled in structure bears a great deal of resemblance to the layout of Islamic paradise gardens which are often found in the chaharbagh structure in mosques and Islamic sites. Further, the poem proposes a setting which has marked similarities with Kashmir and its geographical spaces and the same has been posited by several scholars. In this paper, I have aimed to present a coherent sequence of arguments in an attempt to relate the similarity of Xanadu with real geographical spaces and its intersection with elements of Islamic architecture through an examination of its actual history along with various tales of Xanadu found in the accounts of Marco Polo and other travellers. The paper also compares Xanadu with the structural compositions of the Taj Mahal in India and later, the Mecca, and also engages in discussing its allegorical significance in relation with the Islamic paradise or Jannah. The paper also discusses the possible sources for Coleridge's poem and how they might have influenced him and his dreams and investigates the poem's role in revisiting the fabled summer city of the Mongol ruler and its pleasure dome configuration that resembled his paradise.
Aritmetica e conhecimento simbolico: notas sobre o Tractatus Logico Philosophicus e o ensino de filosofia da matematica
Year: 2020

Departing from and closing with reflections on issues regarding teaching practices of philosophy of mathematics, I propose a comparison between the main features of the Leibnizian notion of symbolic knowledge and some pas sages from the Tractatus on arithmetic. I argue that this way of reading al lows (i) to shed a new light on the specificities of the Tractarian definition of number, compared to those of Frege and Russell; (ii) to highlight the under standing of the nature of mathematical knowledge as symbolic or formal knowledge that Wittgenstein mobilizes in his book; (iii) to offer reasons for the claim that Wittgenstein can be considered the philosopher of mathemati cal practice avant la lettre. The paper ends with an overview, a return to the initial reflection on the connections between research and teaching, and a de fense of the reading key used here in terms of its potential for the research in philosophy of mathematics.
Dynamic Behavior of Sand/Rubber Mixtures, Part II: Effect of Rubber Content on G/G O g DT Curves and Volumetric Threshold Strain
Year: 2012

This paper examines the strain dependent dynamic properties (G/GO logg DT curves) of dry and saturated sand recycled rubber mixtures in a range of shearing strain amplitudes from (5 x 10 4) to (6 x 10 1) using a fixed free torsional resonant column device. The effect of the rubber content on the pore water pressure buildup and volumetric threshold strain gtv of saturated mixtures, as well as the effect of specimens' geometry on the experimental data, are also presented and discussed. Based on a comprehensive set of experimental results, a modified hyperbolic model, frequently used in practice, has been proposed. An increase in the rubber content leads to a more linear shape of the G/GO logg and DT logg curves and a reduction in the pore water pressure buildup. Damping is expressed in terms of DT DTO, which eliminates the effect of the rubber content and the mean confining pressure. The final aim is to propose appropriate design G/GO logg DT curves for sand rubber mixtures currently used in practice.
Policy imperatives for diverting construction waste from landfill: Experts' recommendations for UK policy expansion
Year: 2017

Legislation and fiscal policies have remained the key drivers of construction waste minimization. It has often been suggested that reducing waste to the landfill does not only require improvement on existing waste management policies and fiscal framework; there is a need for adequate inputs from the construction professionals. As a means of engendering effective waste management policies, this study explores industry practitioners' viewpoints on effective policies for minimising waste landfilled by the UK construction industry. Using exploratory sequential mixed method approach, qualitative and quantitative methods were used. In the first phase of the study, data was collected through focus group discussions with 24 experts from the UK construction industry. Findings from the qualitative study served as an input into a questionnaire, which was used to elicit a wider opinion from 63 experts at the quantitative stage of the study. The study suggests that for waste management legislation and policies to effectively drive construction waste minimization, six key measures are important. These include (i) provision of tax breaks and incentives to good waste performers and waste management businesses; (ii) increased targeting of design stages in policies; (iii) Extension of sustainable design appraisal systems by allocating more points to proven waste performance measures; (iv) increased stringency of legislative measures by requiring use of proven waste efficient design, procurement and construction methods; (v) increased stringency of fiscal policies by increasing penalties for poor waste performance; and (vi) corroboration of policy requirements with enablers and facilitators. The strategies through which each of the legislative and fiscal measures could be tailored and enhanced are discussed in the paper. By embracing both stringent and palliative policy measures suggested in the study, substantial construction waste could be diverted from landfill.
Face Recognition Based Automated Student Attendance System
Year: 2020

Face recognition system is very beneficial in real time applications, concentrated in security control systems. Face Detection and Recognition is a vital area in the province of validation. In this project, the Open CV based face recognition strategy has been proposed. This model integrates a camera that captures an input image, an algorithm Haar Cascade Algorithm for detecting face from an input image, identifying the face and marking the attendance in an excel sheet. The proposed system implements features such as detection of faces, extraction of the features, exposure of extracted features, analysis of students' attendance, and monthly attendance report generation. Faces are recognized using advanced LBP using the database that contains images of students and is used to identify students using the captured image. Better precision is accomplished in results and the system takes into account the changes that occurs in the face over some time.
Metal ion removal using waste byssus from aquaculture
Venue: Scientific reports
Year: 2020

Byssus is a thread like seafood waste that has a natural high efficiency in anchoring many metal ions thanks to its richness of diverse functional groups. It also has structural stability in extreme chemical, physical and mechanical conditions. The combination of these properties, absent in other waste materials, has novelty suggested its use as matrix for water remediation. Thus, pristine byssus, upon de metalation, was studied to remove metal ions from ideal solutions at pH 4 and 7, as model chemical systems of industrial and environmental polluted waters, respectively. The byssus matrix's uptake of metal ions was determined by ICP OES and its surface microstructure investigated by SEM. The results showed that the byssus matrix excellently uptakes metal ions slightly reorganizing its surface micro structure. As example of its efficiency: 50 mg of byssus absorbed 21.7 mg*g 1 of Cd2+ from a 10 mM solution at pH 7. The adsorption isotherm models of Freundlich and Langmuir were mainly used to describe the system at pH 7 and pH 4, respectively. In conclusion, we showed that the byssus, a waste material that is an environmental issue, has the potential to purify polluted industrial and environmental waters from metal ions.
The relationship between adolescent academic stress and sleep quality: A multiple mediation model
Year: 2018

We investigated the mediating effect of burnout and depression on the relationship between adolescent academic stress and sleep quality. Participants comprised 757 adolescents aged 12 18 years, who completed self report questionnaires assessing academic stress, sleep quality, school burnout, and depression. Results showed that adolescent academic stress was negatively correlated with sleep quality, and that depression and school burnout were also negatively associated with sleep quality. Results of a multiple mediation model showed that adolescent academic stress was not only directly correlated with sleep quality, but was also indirectly associated with sleep quality through the mediating effect of school burnout and depression, as well as through the sequential mediating effect from school burnout to depression. Theoretical and practical implications are discussed.
Physical Layer Identification Based on Spatial Temporal Beam Features for Millimeter Wave Wireless Networks
Venue: IEEE Transactions on Information Forensics and Security
Year: 2020

With millimeter wave (mmWave) wireless communication envisioned to be the key enabler of next generation high data rate wireless networks, security is of paramount importance. While conventional security measures in wireless networks operate at a higher layer of the protocol stack, physical layer security utilizes unique device dependent hardware features to identify and authenticate legitimate devices. In this work, we identify that the manufacturing tolerances in the antenna arrays used in mmWave devices contribute to a beam pattern that is unique to each device, and to that end we propose a novel device fingerprinting scheme based on the unique beam pattern of different codebooks used by the mmWave devices. Specifically, we propose a fingerprinting scheme with multiple access points (APs) to take advantage of the rich spatial temporal information of the beam pattern. We perform comprehensive experiments with commercial off the shelf mmWave devices to validate the reliability performance of our proposed method under various scenarios. We also compare our beam pattern feature with a conventional physical layer feature namely power spectral density feature (PSD) To that end, we implement PSD feature based fingerprinting for mmWave devices. We show that the proposed multiple APs scheme is able to achieve over 99% identification accuracy for stationary LOS and NLOS scenarios and significantly outperform the PSD feature fingerprinting method. For mobility scenario, the overall identification accuracy is 99% In addition, we perform security analysis of our proposed beam pattern fingerprinting system and PSD fingerprinting system by studying the feasibility of performing impersonation attacks. We design and implement an impersonation attack mechanism for mmWave wireless networks using state of the art 60 GHz software defined radios. We discuss our findings and their implications on the security of the mmWave wireless networks.
The systemic inflammation based Glasgow Prognostic Score: a decade of experience in patients with cancer.
Venue: Cancer treatment reviews
Year: 2013

Since the initial work, a decade ago that the combination of C reactive protein and albumin, the Glasgow Prognostic Score (GPS) had independent prognostic value in patients with cancer, there have been more than 60 studies >30,000 patients) that have examined and validated the use of the GPS or the modified GPS (mGPS) in a variety of cancer scenarios. The present review provides a concise overview of these studies and comments on the current and future clinical utility of this simple objective systemic inflammation based score. The GPS/mGPS had independent prognostic value in (a) unselected cohorts (4 studies, >19,400 patients) (b) operable disease (28 studies, >8,000 patients) (c) chemo/radiotherapy (11 studies, >1500 patients) (d) inoperable disease (11 studies, >2,000 patients) Association studies (15 studies, >2,000 patients) pointed to an increased GPS/mGPS being associated with increased weight and muscle loss, poor performance status, increased comorbidity, increased pro inflammatory and angiogenic cytokines and complications on treatment. These studies have originated from 13 different countries, in particular the UK and Japan. A chronic systemic inflammatory response, as evidenced by the GPS/mGPS, is clearly implicated in the prognosis of patients with cancer in a variety of clinical scenarios. The GPS/mGPS is the most extensively validated of the systemic inflammation based prognostic scores and therefore may be used in the routine clinical assessment of patients with cancer. It not only identifies patients at risk but also provides a well defined therapeutic target for future clinical trials. It remains to be determined whether the GPS has prognostic value in other disease states.
Accelerating Oblivious Transfer with Batch Multi exponentiation
Venue: ACISP
Year: 2016

More and more people use smart end devices to retrieve digital items and purchase on the Internet. Oblivious transfer OT is a fundamental tool to protect user privacy in such applications. Most existing works devote to improving the communication performance of OT protocols; few work has been done to improve the computation efficiency. Modular exponentiation is the most frequent operation in OT protocols. It is known that the computation cost of any OT protocol must be linear with the database size; speeding up the exponentiations is critical for OT protocols to be deployed in practice. To this end, we investigate batch multi exponentiation algorithms and propose two new algorithms. Then we apply our batch multi exponentiation algorithms to acceleration of OT protocols. Our approach is especially useful for the k out n OT. We also exploit the algorithm to speed up simultaneous execution of 1 out n OT protocols which we called batch OT. We conduct a series of experiments and the experimental results show that our approach is effective and can significantly accelerate OT protocols.
UnMask: Adversarial Detection and Defense Through Robust Feature Alignment
Venue: 2020 IEEE International Conference on Big Data (Big Data)
Year: 2020

Recent research has demonstrated that deep learning architectures are vulnerable to adversarial attacks, high lighting the vital need for defensive techniques to detect and mitigate these attacks before they occur. We present UnMask, an adversarial detection and defense framework based on robust feature alignment. UnMask combats adversarial attacks by extracting robust features (e.g. beak, wings, eyes) from an image (e.g. "bird" and comparing them to the expected features of the classification. For example, if the extracted features for a "bird" image are wheel, saddle and frame, the model may be under attack. UnMask detects such attacks and defends the model by rectifying the misclassification, re classifying the image based on its robust features. Our extensive evaluation shows that UnMask detects up to 96.75% of attacks, and defends the model by correctly classifying up to 93% of adversarial images produced by the current strongest attack, Projected Gradient Descent, in the gray box setting. UnMask provides significantly better protection than adversarial training across 8 attack vectors, averaging 31.18% higher accuracy. We open source the code repository and data with this paper: https:/github.com/safreita1/nmask.
Therapeutic Opportunities in Inflammatory Bowel Disease: Mechanistic Dissection of Host Microbiome Relationships
Venue: Cell
Year: 2019

The current understanding of inflammatory bowel disease (IBD) pathogenesis implicates a complex interaction between host genetics, host immunity, microbiome, and environmental exposures. Mechanisms gleaned from genetics and molecular pathogenesis offer clues to the critical triggers of mucosal inflammation and guide the development of therapeutic interventions. A complex network of interactions between host genetic factors, microbes, and microbial metabolites governs intestinal homeostasis, making classification and mechanistic dissection of involved pathways challenging. In this Review, we discuss these challenges, areas of active translation, and opportunities for development of next generation therapies.
Trajectory design for aircraft taxi automation to benefit trajectory based operations
Venue: 2009 7th Asian Control Conference
Year: 2009

Trajectory based operations constitute a key mechanism considered by the Joint Planning and Development Office (JPDO) of the U.S. for managing traffic in high density or highly complex airspace in the Next Generation Air Transportation System (NextGen) With this concept applied to surface operations at major airports, current research has been exploring the use of surface 4 dimensional (4D) trajectories, which require the taxiing aircraft to meet required times of arrival (RTAs) at selected locations along the taxi route. Observing these RTAs as constraints along the taxi route, the flight still has many degrees of freedom in adjusting its state profiles (i.e. position, velocity, etc. as functions of time) to achieve the timing constraints. Previous research has applied the trajectory control freedom to assure passenger comfort by keeping the accelerations and decelerations within prespecified limits. This paper explores untapped flexibility in the trajectory design problem to achieve additional desirable behaviors, beginning with the consideration of fuel burn, emissions, and noise. A flight deck automation experimental prototype serves as the platform for evaluating the designs. The findings will benefit future designs of flight deck automation systems, as well as tower automation systems which rely on accurate understanding of the flight deck's operational behaviors to plan efficient and safe operations for the entire surface traffic.
Defective Localization With Impaired Tumor Cytotoxicity Contributes to the Immune Escape of NK Cells in Pancreatic Cancer Patients
Venue: Front. Immunol.
Year: 2019

Tumor infiltrating lymphocytes (TILs) found in patients with advanced pancreatic ductal adenocarcinoma (PDAC) are shown to correlate with overall survival (OS) rate. Although majority of TILs consist of CD8+/CD4+ T cells, the presence of NK cells and their role in the pathogenesis of PDAC remains elusive. We performed comprehensive analyses of TIL, PBMC, and autologous tumor cells from 80 enrolled resectable PDAC patients to comprehend the NK cell defects within PDAC. Extremely low frequencies of NK cells <0.5% were found within PDAC tumors, which was attributable not to the low expression of tumor chemokines, but to the lack of chemokine receptor, CXCR2. Forced expression of CXCR2 in patients' NK cells rendered them capable of trafficking into PDAC. Furthermore, NK cells exhibited impaired cell mediated killing of autologous PDAC cells, primarily due to insufficient ligation of NKG2D and DNAM 1, and failed to proliferate within the hypoxic tumor microenvironment. Importantly, these defects could be overcome by ex vivo stimulation of NK cells from such patients. Importantly, when the proliferative capacity of NK cells in vitro was used to stratify patients on the basis of cell expansion, patients whose NK cells proliferated <250 fold experienced significantly lower DFS and OS than those with =250 fold. Ex vivo activation of NK cells restored tumor trafficking and reactivity, hence provided a therapeutic modality while their fold expansion could be a potentially significant prognostic indicator of OS and DFS in such patients.
Soldering defect detection in automatic optical inspection
Venue: Adv. Eng. Informatics
Year: 2020

This paper proposes an integrated detection framework of solder joint defects in the context of Automatic Optical Inspection (AOI) of Printed Circuit Boards (PCBs) Both localization and classifications tasks were considered. For the localization part, in contrast to the existing methods that are highly specified for particular PCBs, we used a generic deep learning method which can be easily ported to different configurations of PCBs and soldering technologies and also gives real time speed and high accuracy. For the classification part, an active learning method was proposed to reduce the labeling workload when a large labeled training database is not easily available because it requires domain specified knowledge. The experiments show that the localization method is fast and accurate. In addition, high accuracy with only minimal user input was achieved in the classification framework on two different datasets. The results also demonstrated that our method outperforms three other active learning benchmarks.
Detection of Geologic Anomalies with Monte Carlo Clustering Assemblies
Year: 2019

Authors present new clustering based algorithms for detection of geologic anomalies and results of their testing on the data containing anomalies of two types: (a) high permeability anomaly with regular records containing smaller permeability values, and (b) gas filled sand anomaly with regular records containing data from brine filled sands. Results of algorithms testing, presented in the paper, demonstrate high stability of anomaly detection with false discovery rate below 20% and with the true discovery rate exceeding 73%
Long range speech acquirement and enhancement with dual point laser Doppler vibrometers
Venue: 2018 IEEE 23rd International Conference on Digital Signal Processing (DSP)
Year: 2018

This paper presents a long range speech acquirement and speech enhancement system by utilizing two laser Doppler vibrometers (LDV) to measure two separate points on only one vibration object or two different vibration objects. This proposed LDV system can provide dual channel synchronous signals, and thus the coherent to diffused ratio based and the multi channel linear prediction based algorithms can be introduced to reduce the reverberation and the noise of the acquired speech signals. The two algorithms are combined together to further improve the speech enhancement performance. Experimental results show that the proposed algorithm can significantly improve the PESQ scores.