Reviewerly/exHarmony huggingface dataset:
Research and Design of Knowledge System Construction System Based on Natural Language Processing

The digital processing of content resources has subverted the traditional paper content processing model and has also spread widely. The digital resources processed by text structure need to be structured and processed by professional knowledge, which can be saved as a professional digital content resource of knowledge base and provide basic metadata for intelligent knowledge service platform. The professional domain-based knowledge system construction system platform explored in this study is designed based on natural language processing. Natural language processing is an important branch of artificial intelligence, which is the application of artificial intelligence technology in linguistics. The system first extracts the professional thesaurus and domain ontology in the digital resources and then uses the new word discovery algorithm based on the label weight designed by artificial intelligence technology to intelligently extract and clean the new words of the basic thesaurus. At the same time, the relationship system between knowledge points and elements is established to realize the association extraction of targeted knowledge points, and finally the output content is enriched from knowledge points into related knowledge systems. In order to improve the scalability and universality of the system, the extended architecture of the thesaurus, algorithms, computational capabilities, tags, and exception thesaurus was taken into account when designing. At the same time, the implementation of “artificial intelligence [Formula: see text] manual assistance” was adopted. On the basis of improving the system availability, the experimental basis of the optimization algorithm is provided. The results of this research will bring an artificial intelligence innovation after the digitization to the publishing industry and will transform the content service into an intelligent service based on the knowledge system.
Improved generic construction of chameleon hash to group elements

Chameleon hash functions are trapdoor one-way functions with many applications as, for example, off-line/on-line signatures and chameleon signatures. Chameleon signatures are useful to protect privacy of signatures in some business systems where signatures are not allowed to be verified universally, and off-line/on-line signatures are particularly suitable for systems with limited computing resources on-line, but enough computation power off-line, such as in smart card applications. Previous research focused on concrete constructions based on different assumptions, as well as schemes without the key-exposure problem. The main contribution of this paper is a generic construction method of structure-preserving chameleon hash from quasi-adaptive noninteractive zero-knowledge (QANIZK) and two concrete constructions from adaptive sound and simulation sound QANIZK for witness sampleable (WS) distributions proposed by Kiltz and Wee in Eurocrypt 2015, with/without key-exposure respectively. Compared with the constructions from linearly homomorphic structure-preserving signature (LHSPS), our constructions improve the efficiency, the assumptions, as well as the security guarantees.
Research on Teaching Effectiveness Index System in Mixed Teaching Mode

This paper, taking the online teaching of "university computer" as an example of Jianghan University, puts forward a mixed teaching effect index system based on data analysis in large class teaching environment. Through the analysis of the actual effect of individualized and mixed teaching, the evaluation indexes are discussed in detail from the aspects of students' learning, teachers' teaching, curriculum construction and teaching management. At the same time, the purpose and significance of the quantitative index system are discussed.
RE: A Methodological Issue in Prediction of Cancer Masking in Screening Mammography Using Density and Textural Features - Authors’ Response

We thank the authors of the letter entitled “A methodological issue in Prediction of Cancer Masking in Screening Mammography Using Density and Textural Features” for their interest in our research. We agree that care must be taken when building models with limited data to avoid over-fitting. In our analysis, model building was guided through use of the Akaike Information Criterion (AIC), which penalizes model complexity. This leads to models with fewer parameters and thus restricts over-fitting. Others have shown that modeling with cross-validation and AIC is asymptotically equivalent when maximum likelihood is used ( 1 Stone M. An asymptotic equivalence of choice of model by cross-validation and Akaike's criterion. J Royal Stats Soc. 1977; : 44-47 Google Scholar ). Although the AIC may under-penalize highly complex models ( 2 Hastie T. Tibshirani R. Friedman J. The elements of statistical learning: Data mining, inference, and prediction. Springer, New York, NY2009: 228-233 Google Scholar ), our best model contained only three linear parameters, which suggests a low likelihood of overfitting. Nevertheless, it is always desirable to have more data. We noted in our discussion that we were limited to a small, specific cohort of women and that we are currently gathering data on a larger and distinct population of women to investigate and validate the robustness of the model.
The influence of parafoveal preview, character transposition, and word frequency on saccadic targeting in Chinese reading.

This article reports the results of an eye-movement experiment which manipulated the frequency and parafoveal preview (i.e., nonword, transposed-character, or identical) of 2-character Chinese target words using a gaze-contingent boundary paradigm (Rayner, 1975). The key findings were that progressive saccades were longer into high- than low-frequency target words, and that this word-frequency effect was more pronounced for identical than transposed previews. These findings suggest that Chinese readers adjust their saccade lengths in response to variables that influence the rate of parafoveal lexical processing. To examine the feasibility of this hypothesis, 2 computer simulations were completed that pitted this dynamic-adjustment account (Liu, Huang, Gao, & Reichle, 2017) against an account in which readers simply move their eyes to a small number of default saccade targets (e.g., the beginning or center of the upcoming word; Yan, Kliegl, Richter, Nuthmann, & Shu, 2010). The simulation results show that the dynamic-adjustment hypothesis more accurately describes our experimental findings using fewer parameters. The theoretical implications of the dynamic-adjustment account of saccadic targeting are discussed relevant to both models of eye-movement control in reading and modes of Chinese word identification. (PsycINFO Database Record (c) 2019 APA, all rights reserved).
Measuring Shapes with Desired Convex Polygons

In this paper we have developed a family of shape measures. All the measures from the family evaluate the degree to which a shape looks like a predefined convex polygon. A quite new approach in designing object shape based measures has been applied. In most cases such measures were defined by exploiting some shape properties. Such properties are optimized (e.g., maximized or minimized) by certain shapes and based on this, the new shape measures were defined. An illustrative example might be the shape circularity measure derived by exploiting the well-known result that the circle has the largest area among all the shapes with the same perimeter. Of course, there are many more such examples (e.g., ellipticity, linearity, elongation, and squareness measures are some of them). There are different approaches as well. In the approach applied here, no desired property is needed and no optimizing shape has to be found. We start from a desired convex polygon, and develop the related shape measure. The method also allows a tuning parameter. Thus, there is a new 2-fold family of shape measures, dependent on a predefined convex polygon, and a tuning parameter, that controls the measure's behavior. The measures obtained range over the interval (0,1] and pick the maximal possible value, equal to 1, if and only if the measured shape coincides with the selected convex polygon that was used to develop the particular measure. All the measures are invariant with respect to translations, rotations, and scaling transformations. An extension of the method leads to a family of new shape convexity measures.
Performance Comparison of Perturbation Signals for Time-Varying Water Temperature Modeling Using NARX-Based BPSO

There is an increasing concern on the perturbation signal analysis on nonlinear modeling for nonlinear systems. Several studies have shown the importance of suitable perturbation signal for the real nonlinear system applications. This study systematically reviews the performance comparison for nonlinear modeling using two perturbation signals, namely as Pseudo Random Binary Signal (PRBS) and Multi-level Pseudo Random Sequence (MPRS) for a time-varying water temperature of Steam Distillation Pilot Plant (SDPP). A Binary Particle Swarm Optimization (BPSO) algorithm was utilized in the model structure selection for polynomial Nonlinear Auto-Regressive with eXogenous (NARX) input. Three model’s selection criteria were examined; Akaike Information Criterion (AIC), Model Descriptor Length (MDL), and Final Prediction Error (FPE) for performance analysis that included model validation. The results presented lesser number of input and output lags, also fewer output model parameters for MPRS perturbation signal. Further analysis of the nonlinear model has demonstrated high R-squared and low MSE for model validation for both models using PRBS and MPRS perturbation signals.
Higher-order theorem proving and its applications

Abstract Automated theorem proving systems validate or refute whether a conjecture is a logical consequence of a given set of assumptions. Higher-order provers have been successfully applied in academic and industrial applications, such as planning, software and hardware verification, or knowledge-based systems. Recent studies moreover suggest that automation of higher-order logic, in particular, yields effective means for reasoning within expressive non-classical logics, enabling a whole new range of applications, including computer-assisted formal analysis of arguments in metaphysics. My work focuses on the theoretical foundations, effective implementation and practical application of higher-order theorem proving systems. This article briefly introduces higher-order reasoning in general and presents an overview of the design and implementation of the higher-order theorem prover Leo-III. In the second part, some example applications of Leo-III are discussed.
An Intelligent and Decentralized Content Diffusion System in Smart-Router Networks

Smart-routers develop greatly in recent years as one of the representative products of IoT and Smart home. Different from traditional routers, they have storage and processing capacity. Actually, smart-routers in the same location or ISP have better link conditions and can provide high quality service to each other. Therefore, for the content required services, how to construct the overlay network and efficiently deploy replications of popular content in smart-routers' network are critical. The performance of existing centralized models is limited by the bottleneck of the single point's performance. In order to improve the stability and scalability of the system through the capability of smart-router, we propose a novel intelligent and decentralized content diffusion system in smart-router network. In the system, the content will be quickly and autonomously diffused in the network which follows the specific requirement of coverage rate in neighbors. Furthermore, we design a heuristic node selection algorithm (MIG) and a replacement algorithm (MCL) to assist the diffusion of content. Specifically, system based MIG will select neighbor with the maximum value of information gain to cache the replication. The replication with the least loss of the coverage rate gain will be replaced in the system based on MCL. Through the simulation experiments, at the same requirement of coverage rate, MIG can reduce the number of replications by at least 20.2% compared with other algorithms. Compared with other replacement algorithms, MCL achieves the best successful service rate which means how much ratio of the service can be provided by neighbors. The system based on the MIG and MCL can provide stable service with the lowest bandwidth and storage cost.
A Survey On The Different Implemented Captchas

CAPTCHA is almost a standard security technology, and has found widespread application in commercial websites.There are two types: labeling and image based CAPTCHAs.To date, almost all CAPTCHA designs are labeling based.Labeling based CAPTCHAs refer to those that make judgment based on whether the question "what is it?"has been correctly answered.Essentially in Artificial Intelligence (AI), this means judgment depends on whether the new label provided by the user side matches the label already known to the server.Labeling based CAPTCHA designs have some common weaknesses that can be taken advantage of attackers.First, the label set, i.e., the number of classes, is small and fixed.Due to deformation and noise in CAPTCHAs, the classes have to be further reduced to avoid confusion.Second, clean segmentation in current design, in particular character labeling based CAPTCHAs, is feasible.The state of the art of CAPTCHA design suggests that the robustness of character labeling schemes should rely on the difficulty of finding where the character is (segmentation), rather than which character it is (recognition).However, the shapes of alphabet letters and numbers have very limited geometry characteristics that can be used by humans to tell them yet are also easy to be indistinct.Image recognition CAPTCHAs faces many potential problems which have not been fully studied.It is difficult for a small site to acquire a large dictionary of images which an attacker does not have access to and without a means of automatically acquiring new labeled images, an image based challenge does not usually meet the definition of a CAPTCHA.They are either unusable or prone to attacks.In this paper, we present the different types of CAPTCHAs trying to defeat advanced computer programs or bots, discussing the limitations and drawbacks of each.
Privacy-Preserving WSDM

The goals of learning from user data and preserving user privacy are often considered to be in conflict. This presentation will demonstrate that there are contexts when provable privacy guarantees can be an enabler for better web search and data mining (WSDM), and can empower researchers hoping to change the world by mining sensitive user data. The presentation starts by motivating the rigorous statistical data privacy definition that is particularly suitable for today's world of big data, differential privacy. It will then demonstrate how to achieve differential privacy for WSDM tasks when the data collector is trusted by the users. Using Chrome's deployment of RAPPOR as a case study, it will be shown that achieving differential privacy while preserving utility is feasible even when the data collector is not trusted. The presentation concludes with open problems and challenges for the WSDM community.
Time Efficient Inspection of Ground Vehicles by a UAV Team Using a Markov Inequality Based Rule

We present a control design for N unmanned aerial vehicles (UAVs) tasked with a time efficient inspection of M ground moving vehicles. The navigation and intent of each ground vehicle are unknown, therefore, the uncertainty of its navigation has to be anticipated in the navigation of each UAV. We use the minimum time stochastic optimal control to navigate each UAV towards the inspection of ground vehicles. Based on this control, we formulate assignments of ground vehicles to be inspected by UAVs as an optimization problem to inspect all ground vehicles in the minimum expected time. Accounting for ground vehicle uncertain trajectories, we update the optimal assignment by a Markov inequality rule. The rule prevents the possibility of indefinite updating of assignments without finishing the inspection of all vehicles. On the other hand, it updates an assignment if it leads to a statistically significant improvement of the expected time of inspection. The presented approach is illustrated by a numerical example.
A STUDY ON IMPROVEMENT METHOD LEAVING HOLLOW PART WITH STEEL &amp; COMPOSITE PILES IN CONSIDERING WORKABILITY

The objective of this study is to examine the improvement method with hollow part of SC pile in order to improve the deformation performance of SC pile. In the pile foundation structure, the improvement of design is prompted assuming large earthquake. However, study on the deformation performance of precast concrete pile is not sufficiently advanced. Therefore, the test data accumulation is not enough to discuss the deformation performance of pile. In the previous study, we confirmed that filling the hollow part of the SC pile with reinforcement was effective for improving the deformation performance. However, there were some issues on the terms of construction when it use the SC piles filled with reinforcement for the hollow parts. Therefore, we studied an improvement method that left the hollow part for preparing flexibility in terms of construction. We examined two improvement methods. Two improvement methods were 1) to increase the thickness of the pile body concrete, 2) to install an inside steel pipe in the hollow part of SC pile. We confirmed the effectiveness of the improvement method by simple beam bending test and cantilever beam bending shear test. We analyzed the relations between the displacement of vertical and the angle of member, relations between the load and the displacement, and relations between the bending moment and the curvature. Furthermore, we proposed an analytical method to evaluate the deformation performance of piles and compared the analytical values with the experimental values. The knowledge obtained from this study are shown below. 1) By increasing the thickness of the pile body concrete, it is difficult to suppress the large decrease in bending strength and axial displacement after confirming the maximum proof stress. However, the effect of improving deformation performance can be expected. 2) The effect of improving the deformation performance by increasing the thickness of the pile body concrete is inferior to reinforcement using concrete for filling material. However, it is same to reinforcement using soil cement for filling material. 3) By making the pile a double steel pipe, axial displacement due to repeated bending stress can be suppressed, and improvement effect on bending deformation performance can be expected. 4) The effect of improving the deformation performance by making the pile a double steel pipe is same to reinforcement using soil cement for filling material. 5) We proposed an analytical method considering the influence of the outer outside steel pipe and the pile hollow part. The relationship between the bending moment of the pile and the curvature can be evaluated by the proposed analysis method. However, the result of the proposed analysis method is underestimated when the hollow part is improved with multiple materials (inside steel pipe and mortar).
Two impartial games on finite <i>p</i>-groups

This paper is about two impartial combinatorial games, namely achievement and avoidance games. These games can be played on groups by two persons. If G is a finite group, then both players chose elements of G alternately. The player who builds a generating set for G is called the loser in avoidance game whereas the builder of generating set is called the winner in achievement game. Dana and Sieben have been provided concept of nim-numbers by plotting their structure diagrams for both games. Since, the nim-numbers provide a more easier analysis of impartial combinatorial games and provide final outcome of these impartial games. But it is hard to calculate the nim-numbers of an impartial game. In this paper, the nim-numbers for achievement and avoidance games on some non-abelian groups have been calculated. In particular, the simplified structure diagrams and nim-values of these two games for finite non-abelian p-groups, dicyclic type groups, and groups of the form ℂ3 × ℂp has been determined.
Fast Confidence Detection

Deep Neural Networks (DNNs) have shown phenomenal success in a wide range of real-world applications. However, a concerning weakness of DNNs is that they are vulnerable to adversarial attacks. Although there exist methods to detect adversarial attacks, they often suffer constraints on specific attack types and provide limited information to downstream systems. We specifically note that existing adversarial detectors are often binary classifiers, which differentiate clean or adversarial examples. However, detection of adversarial examples is much more complicated than such a scenario. Our key insight is that the confidence probability of detecting an input sample as an adversarial example will be more useful for the system to properly take action to resist potential attacks. In this work, we propose an innovative method for fast confidence detection of adversarial attacks based on integrity of sensor pattern noise embedded in input examples. Experimental results show that our proposed method is capable of providing a confidence distribution model of most of popular adversarial attacks. Furthermore, our presented method can provide early attack warning with even the attack types based on different properties of the confidence distribution models. Since fast confidence detection is a computationally heavy task, we propose an FPGA-Based hardware architecture based on a series of optimization techniques, such as incremental multi-level quantization and etc. We realize our proposed method on an FPGA platform and achieve a high efficiency of 29.740 IPS/W with a power consumption of only 0.7626W.
Accurate Extraction of Coronary Vascular Structures in 2D X-ray Angiogram Using Vascular Topology Information in 3D Computed Tomography Angiography

Since the 2D X-ray angiogram enables the detection of vascular stenosis in real-time, it is essential for percutaneous coronary intervention (PCI). However, the accurate vascular structure is very difficult to determine due to background clutter and loss of depth information of 2D projection. To cope with these difficulties, we propose a fast and accurate extraction method of a vascular structure in 2D X-ray angiogram (XA) based on the vascular topology information of 3D computed tomography angiography (CTA) of the same patient. First, an initial vascular structure is robustly extracted based on vessel enhancement filtering. Then, 2D XA and 3D CTA are spatially aligned by 2D–3D registration. Finally, the 2D vascular structure is accurately reconstructed based on 3D vascular topology information by measuring the similarity of 2D and 3D vascular segments. Experimental results showed the fast and accurate extraction of a vascular structure using 10 images each of the left coronary artery (LCA) and right coronary artery (RCA). Our method can be used as a computer-aided technology for PCI. Our method can be applied to the study of other various types of vessels.
Photonic-Assisted Modulation Classification for RF signals Using Probabilistic Neural Network

A photonic-assisted modulation classification for RF signals using PNN is proposed and experimentally demonstrated. The approach achieves >97% classification accuracy at −1∼15 SNR with 160 training samples for each SNR value and modulation format.