Reviewerly/exHarmony huggingface dataset:
Camera-based omnidirectionally three-dimensional sensing for autonomous driving

For autonomous driving, we propose an omnidirectional three-dimensional sensing and viewing system employing monocular stereo camera which has both ranging and recognition function. In this system, four monocular stereo cameras, which are located at the corner of ego- vehicle, measure relatively short distance around each camera. Then, long-baseline stereo camera composed of adjacent two cameras among the four cameras measure relatively long distance. We will report the simulated and experimental results of ranging performance of the system.
Non-linear Root-signal Fusion based Single Hazy Image Enhancement

This paper presents a new technique for enhancing hazy images taken in indoor, outdoor, or underwater imaging environments. In the proposed technique, several root-signals having different bandwidths are derived from the given hazy image and its complement image. These root-signal images are enhanced through non-linear enhancement techniques using adaptive histogram equalization. The resulting images are fused to give the final dehazed image. The proposed technique is simulated using MATLAB software. The proposed methodology results are presented, and it is observed that the subjective and objective quality assessments of the dehazed images are comparable to or better than some of the existing state-of-the-art methods.
EO-PSI-CA: Efficient outsourced private set intersection cardinality

Private set intersection cardinality (PSI-CA) is a useful cryptographic primitive for many data analysis techniques, e.g. in genomic computations and data mining. In the last few years, several classical multi-party PSI-CA protocols have been designed where parties jointly compute the PSI-CA and at the end of the protocol none of them learns more than their private input sets and the output. The computation complexity of these multi-party protocols is quadratic in the size of the input sets and linear in the number of the parties involved in the protocol. In addition, the communication complexity scales quadratically as the number of parties increases. With the advent of cloud computing, it is now necessary to gain the benefits of the computation and storage capabilities of the cloud for outsourcing private input sets and PSI-CA computation. For the first time, in this paper, we design an efficient outsourced private set intersection cardinality named EO-PSI-CA in the multi-party setting. This protocol computes PSI-CA by employing the Bloom filter (BF) technique and the exponential ElGamal cryptosystem over encrypted Bloom filters. In our protocol, two or more parties outsource their private input sets to the cloud and finally one of the parties requests the EO-PSI-CA value. Due to the use of Bloom filter, the size of the parties' sets is independent of each other, and the computational and communication complexity of each party is independent of the total number of parties. We formally prove the security of our protocol in the semi-honest adversarial model and we claim that our scheme addresses the intersection size hiding. On a more positive note, our EO-PSI-CA is the first in its kind with linear complexity supporting outsourcing in a multi-party setting.
Under the Mode of “Internet Plus”, Construction and Practice of Regional Intelligent Education Cloud Platform—Take E City’s Smart Education Cloud Platform Construction as an Example

The educational cloud platform is one of the basic conditions to realize the modernization of regional education and promote the balance of regional educational resources. At the same time, its construction is also a difficult and practical problem. The construction and practice of the cloud platform of wisdom education in E city based on Internet thinking, the author summarizes the structure and function design of the cloud platform of regional wisdom education based on the mode of “Internet +”. For other regions to carry out the construction of educational cloud platform, promote educational information work has a certain reference role.
On the STEM Concept Projection on the Field of Astronomical Knowledge

Astronomy, as the result of activity and development of the technology of human cognition of his existence environment, should be considered as the basis for an effective educational approach. The STEM (Science, Technology, Engineering and Mathematics) approach has failed because of limitations caused by the focus on the needs of engineering education only. The STEM projection on the field of astronomical knowledge, technology of means, engineering of instrumentation and mathematical modeling as science and technology language, removes limitations and solves the task to form an educated person. This idea finds solid ground if from philosophy, as a tool for unification, we turn to psychology which studies systems organized around the phenomenon of memory with the goal to reflect and comprehend reality in order to create a new reality and environment for preservation of the viability of human being. This approach is present and developed in different aspects of The General Psychological Theory of Set of Dimitri Uznadze. Based on Uznadze, education is an organized process of accumulation in memory of information that we unconsciously, but adequately use in situations of reality recognizing them as already known. Consciousness serves the memory to create new sets of behavior in new previously unknown situations. Education seems to be ideal, if one step by step organizes situations-tasks of consciousness “switching on” to search for solutions in own memory, in external source or experimentally. If one uses the Psychology of Set as a model of the educational process, astronomy is the best information environment for it.
Innovation and Application of Computer Multimedia Aided Mode Method in College Online English

With the gradual realization of globalization in various fields, interlinked languages can quickly shorten the distance between people in different countries and lay a linguistic foundation for the development of individuals and countries. Since the formation of language is closely related to culture, it is necessary to understand the culture of the people using the language in order to eliminate conflicts caused by cultural differences. At present, bad teaching results have appeared in college English teaching. This paper studies educational communication theory, cognitive load theory, multimedia courseware interface design theory and other teaching theories, and SPSS analyzes teaching data.
Picture Hesitant Fuzzy Set

In this chapter, we present the concept of picture hesitant fuzzy set, and then, we deal with interval-valued picture hesitant fuzzy set. The last part of this chapter is devoted to presenting the concept of dual picture hesitant fuzzy set.
Multi-Relation Extraction via A Global-Local Graph Convolutional Network

Relation extraction (RE) extracts the semantic relations among entities in a sentence, which converts the unstructured text into structured and easy-to-understand information. Although RE has been studied over decades, it still faces two kinds of research challenges that are not well addressed thus far: 1) joint consideration of the global sentence structure and the local entity interaction, and 2) effective solution to the overlapping triplets within the same sentence. To tackle these issues, in this paper, we present global-local graph-based convolutional network towards multi-relation extraction, GAME for short. In particular, we devise two layers of graph convolutional network (GCN) with different structures to complete the feature extraction, which effectively improves the capability of relation extraction. Moreover, we implement the GCN layers via the pure GCN model and graph attention network respectively for further comparison. Besides, we adopt a classification strategy to extract relation among entity pairs, assisting in solving the more complicated problem of overlapping triplets in RE. Extensive experiments have been conducted on two widely-used benchmark datasets, demonstrating that our model significantly outperforms several state-of-the-art methods. As a side product, we have released our data, codes and parameter settings to facilitate other researchers.
A bipartite graph approach to retrieve similar 3D models with different resolution and types of cardiomyopathies

Three-dimensional (3D) model retrieval uses content-based image retrieval (CBIR) techniques to search for the most similar 3D objects in a dataset, usually considering their geometry and organization in a feature vector. Feature vectors from different objects were compared to establish their similarities. Although this type of comparison typically uses metric distances, such metrics present limitations when the vector lengths are different. Signal-based descriptors are a promising approach for extracting features from 3D objects, but they generate feature vectors with different lengths. Thus, new methods for measuring the similarity are required. This study proposes an approach to 3D model retrieval as a network flow problem using bipartite graphs. The approach was applied to support the diagnosis of cardiomyopathies, considering 3D objects reconstructed from cardiac images of the left ventricle. We achieved an AUC value of 0.93 under the best retrieval scenario. The results also indicate that modeling a 3D model retrieval technique as a network flow problem using graphs can provide a promising manner to compare 3D objects with different shapes and sizes. This strategy, coupled with personal patient data, achieves better results than methods using classical comparison approaches.
Information technology for time series forecasting by the method of the forecast scheme synthesis

The study is devoted to the development of information technology for forecasting based on time series. It has been found that it is important to develop new models and forecasting methods to improve the quality of the forecast. Information technology is based on the evolutionary method of synthesis of the forecast scheme grounded on basic forecast models. The selected method allows you to consider any number of predictive models that may belong to different classes. For a given time series, the weight coefficients with which the models are included in the resulting forecast scheme are calculated by finding the solution to the optimization problem. The method of constructing the objective function for the optimization problem in the form of a linear combination of forecasting results by basic forecasting models is shown. It is proposed to find the solution to the optimization problem using a genetic algorithm. The result of the method is the forecast scheme, which is a linear combination of basic forecast models. To assess the quality of the forecast, it is suggested to use forecasting errors or forecast volatility calculated as the standard deviation. Forecast quality criteria are selected depending on the context of the task. The use of forecast volatility as a quality criterion, with repeated use of technology, will reduce the deviation of forecast values from real data. The structural scheme of information technology is developed. Structurally, information technology consists of two blocks: data processing and interpretation of the obtained values. The result of the application of the developed information technology is the production rules for determining the predicted value of the studied quantity. Experimental verification of the obtained results was performed. The problem of forecasting the number of religious organizations in Ukraine based on statistical data from 1997 to 2000 has been solved. The autoregression method and the linear regression model were chosen as the basic forecast models. Based on the results of using the developed information technology, the weights of the basic models were calculated. It is demonstrated that the obtained forecast scheme allowed to improve the average absolute percentage error and forecast volatility in comparison with the selected models. Keywords: information technology; time series; forecasting; evolutionary technologies; forecast volatility; synthesis of the forecast scheme.
Emerson, Thoreau, Fuller, and Transcendentalism

Research Article| September 01 2021 Emerson, Thoreau, Fuller, and Transcendentalism Todd H. Richardson Todd H. Richardson University of Texas Permian Basin Search for other works by this author on: This Site Google American Literary Scholarship (2021) 2019 (1): 3–24. https://doi.org/10.1215/00659142-8928438 Cite Icon Cite Share Icon Share Twitter Permissions Search Site Citation Todd H. Richardson; Emerson, Thoreau, Fuller, and Transcendentalism. American Literary Scholarship 1 September 2021; 2019 (1): 3–24. doi: https://doi.org/10.1215/00659142-8928438 Download citation file: Zotero Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search Search Dropdown Menu toolbar search search input Search input auto suggest filter your search Books & JournalsAll JournalsAmerican Literary Scholarship Search Advanced Search The text of this article is only available as a PDF. Copyright © 2021 Duke University Press2021 Article PDF first page preview Close Modal Issue Section: Part I You do not currently have access to this content.
Defending Against Attacks Tailored to Transfer Learning Via Feature Distancing

Transfer learning is preferable for training a deep neural network with a small training dataset by leveraging a pre-trained teacher model. However, transfer learning opens a door for new attacks that generate adversarial examples using the pre-trained teacher model. In this paper, we propose a novel method called feature distancing to defend against adversarial attacks tailored to transfer learning. The method aims to train a student model with a distinct feature representation from the teacher model.We generate adversarial examples of the mimic attack with the teacher model, and the examples are used to train the student model. We use triplet loss to put the mimic attack examples close to their source images and far from their target images in the feature space of the student model. The proposed method is evaluated on three different transfer learning tasks with diverse attack configurations. It is the only method that achieves high "robust accuracy" and high "test accuracy" on every task we evaluate.
Aliens Attack Version 3

The lessons on designing with union types are used to advance the design of Aliens Attack. Emphasis is placed on operations being defined for a type and not for the representation of a type.
Woolery: Extending Frame Semantics to Structured Documents

This paper presents Woolery, a system for semantic annotation and mapping of structured documents (such as JSON key-value pairs) to FrameNet. Implemented as a graphical interface, Woolery provides an annotator with a guided means to map keys in a JSON document to FrameNet elements, without the need for extensive knowledge of FrameNet's semantic structures. Candidate frame elements are identified via a search across FrameNet's internal representations, or via mapping keys to their potential WordNet synsets. Final element selection is automated via a pretrained language model. Initial results are promising, with the model giving an overall accuracy of 77.8% when labeling frames across a diverse corpus of JSON document schemas.
The Mechanism of Consultant Enhanced Credibility in Lifecycle Supply Chain Management

In the future-oriented supply chain scenario, the mechanism of human-machine integration can empower each other to help small and medium-sized companies in supply chain break through the predicament. Blockchain technology can prevent data from being tampered with after being chained, but it can not guarantee the truth and validity of the data. We proposed a credit enhanced mechanism based on consultant nodes. The machine nodes of remote replicas and the human nodes of enterprise managers and consultants are placed on the same chain. All kinds of enterprises, especially those of small and medium size and with relatively low advantages, can prove their innocence and enhance additional credit, through human-machine integration and collaborative decision making. Various nodes accumulate tokens through usual credit behaviors. In emergencies, tokens will be used to vote for decision makings. Thus neither human nodes will be bypassed by strong computing power, nor machine perceptions will be ignored due to human subjectivity.
Collision Detection of NURBS Surface Split Technology

Collision detection is one of the inevitable problems in the field of robotics, animation simulation and virtual reality. “Virtual reality” is a realistic three-dimensional visual, auditory, tactile or olfactory world created by computer technology. Users can walk into this world, control the direction of browsing, and manipulate objects in the scene for human–computer interaction. In a virtual environment, due to user interaction and object movement, collisions may occur frequently between objects. In order to maintain the authenticity of the environment, it is necessary to determine whether there is a collision between two objects in time, and the basic task of collision detection is Determine whether two or more objects are touching each other or touching each other. Collision detection between objects is based on a simple observation in the real world, that is, two or more objects cannot occupy the same space area at the same time to destroy them.
A Robot Speed Boundary Control Strategy

For the ground mobile robot, the moving speed is a crucial concern when it comes to the applications like, vison-based object detection, map building. In this case, a controller that can strictly regulate the robot speed with the undesired trajectory is need. A mobile robot control strategy is proposed to achieve a satisfactory trajectory tracking task, and at the same time, achieve the speed regulation or limitation task. Compared to traditional methods, the proposed method no longer needed extra output calculation or saturation to the control output, which will avoid the unexpected oscillations and errors. Moreover, the proposed controller has the advantage of that, even if the provided reference signal is larger, or say, violates the desired boundary, the proposed controller can still be able to drive the robot speed within the desired boundary. In addition, the boundary regulation can be ensured, when the given reference signals are not ideal. The stated reference signal is not considered suitable in this work. Moreover, the stabilization and tracking speed regulation problem has been conducted, and the simulation results are also provided with the demonstration of its superiority over the traditional mobile robot control methods.
Pecha Kucha Presentations

This comparative research analyses some reflections regarding the teaching and learning approaches designed to foster communicative English language skills under the modality of online education with real-time interaction and multimodal communicative mediation. Because of the global pandemic COVID-19, the higher educational community of three different subjects on English for Specific Purposes (ESP) modified their programs to full online education with different digital tools and interactive methods. A survey was used to analyze students' preferences regarding this abrupt change. Consequently, the delivery of communicative skills through mediated multimodal communication or interaction in English were explored with students' online speaking presentations, which followed the Pecha Kucha model. It is suggested that the multimodal Pecha Kucha speeches allowed participants to produce, receive, interact, and mediate their interpersonal communication with interactive comments, expressed synchronously via MS Teams or posted asynchronously on the forum via written or audio messages.
Comparative Evaluation of the Condition of Academic Graduate School (Middle 2000s – Late 2010s)

The main task of the article was to identify the dynamics of changing social characteristics of graduate students from research institutes of Novosibirsk Academgorodok. For the comparative analysis we used the data of polls conducted in 2005 and 2018. We compared such variables as the reasons for admission to graduate school, assessments of the current state of the main elements of scientific activity, the expectations of graduate students about their future profession, primarily a scientific career, criteria and factors of its success. Based on these results we planned to identify the main trends inherent in graduate studies as the main method of training personnel for Russian science. It is concluded that at present the system of training highly qualified scientific personnel in the country is in an unstable state. As a result, there is an active discussion in the professional community about ways of further reforming graduate school.
Use of Dynamic Pose to Enhance Passive Visual Tracking

Passive visual tracking performance has drastically improved in recent years, thanks to advances in hardware and algorithms, but scenarios in which small mobile threats are indistinguishable from complex backgrounds remain challenging. There is an opportunity to explore whether the maneuverability of a multirotor can be leveraged in order to strategically influence perspective, an approach that can complement existing computer vision strategies. This paper describes an algorithm to determine candidate perspectives and plan host motion that will produce and maintain these perspectives, in order to improve threat detection. A baseline problem abstraction of tracking a mobile sphere is presented with appropriate assumptions, to validate the methodology.
An approach to increase the JPHIDE steganograms detection accuracy

The paper proposes a method for improving the accuracy of steganoanalytical systems that use an ensemble classifier. The method involves a weighted final vote of several highly sensitive models of characteristic vectors. Its effectiveness was evaluated for the task of detecting steganograms created by the Jphide program. The accuracy obtained by usage of one of the models: LIU, CC-PEV, CC-C300, DCTR, PHARM, GFR and with using a combination of several models according to the developed method was compared. The test results proved that the weighted final voting of several highly sensitive models does increase the accuracy of the detection of steganograms with a relatively small payload (short secret messages) without compromising the accuracy of the detection of steganograms with a high payload.
A Blockchain Framework to Increase the Security and Verifiability of Educational Certificates

Education not only means acquiring knowledge or skills, but it also includes acquiring morals, beliefs and values. Nowadays, most people think that gaining an educational certificate means that they are qualified, and because of that, some people make fake certificates to get the job. There is no easy way to validate these certificates, mainly when people belong to different countries. With the spread of coronavirus worldwide, travel restrictions were imposed between nations and within the nation itself. As a result, numerous educational activities, such as conferences, seminars etc., have been postponed. However, the organisers opted to hold these events over the Internet due to the pandemic's numerous limitations. Many of these activities offer certificates of participation, but it is not easy to verify the authenticity of these certificates and the coordinating institutes and attendees. Similarly, there are problems with attending several events at the same time. Many such challenges are explored thoroughly. Then a framework is proposed along with the algorithms that will explain in detail how these challenges can be solved using blockchain technology. As a result, a comparison of the proposed framework is made with the frameworks discussed in the literature and found that the proposed framework is much better in solving the discussed challenges. The article concludes with the future directions for implementing such a framework in the real world.