Reviewerly/exHarmony huggingface dataset:
Multi-sensor Image Registration for Precisely Locating Time-sensitive Objects

Finding time-sensitive objects in time and precisely locating them in real time is the basis of successful operations. This paper analyzes the characteristics of images from space-based platforms such as satellites, and images from aerial platforms such as UAVs, and then presents a method for precisely locating time-sensitive targets. The idea behind this method is that, because the satellite images from intelligence image database have accurate geodetic coordinates associated with every pixel, aerial images can obtain the geographical coordinates of high accuracy by registration with the satellite images. The key of this method consists in alignment of the two kinds of images. To do so, this paper presents a two-stage image registration algorithm. The first stage performs image stitching for aerial images so that the resulting images can include more structural information of the scene. In the second stage, the resulting images are aligned with the geo-referenced images from the image intelligence database. Experimental results show that the proposed algorithm is effective and robust in case of scene variations.
Multipartite Entanglement Generation in a Structured Environment

In this paper, we investigate the entanglement generation of n-qubit states in a model consisting of n independent qubits, each coupled to a harmonic oscillator which is in turn coupled to a bath of N additional harmonic oscillators with nearest-neighbor coupling. With analysis, we can find that the steady multipartite entanglement with different values can be generated after a long-time evolution for different sizes of the quantum system. Under weak coupling between the system and the harmonic oscillator, multipartite entanglement can monotonically increase from zero to a stable value. Under strong coupling, multipartite entanglement generation shows a speed-up increase accompanied by some oscillations as non-Markovian behavior. Our results imply that the strong coupling between the harmonic oscillator and the N additional harmonic oscillators, and the large size of the additional oscillators will enhance non-Markovian dynamics and make it take a very long time for the entanglement to reach a stable value. Meanwhile, the couplings between the additional harmonic oscillators and the decay rate of additional harmonic oscillators have almost no effect on the multipartite entanglement generation. Finally, the entanglement generation of the additional harmonic oscillators is also discussed.
Disk-Based High Dimensional Index Structure

This paper aims to solve the problem of retrieval efficiency of video clips based on query samples under large-scale data. The paper will process a disk-based high dimensional index structure that extends the traditional LSH index structure to disk, in order to support the retrieval of larger video date.
The Question Answering System of Indonesia's History Using Dynamic Memory Networks (DMN) Model

The history of Indonesia which is quite long causes difficulty for our people in obtaining information about the history of Indonesia. In order to obtain information, people still need to seek from many books or documents on the history of Indonesia. Such a way is considered less efficient, thus a question answering system is considered necessary so that the information can be obtained quickly and efficiently. Questions on the topic of history have a tendency on the factoid question type so the type of question in this research is factoid. This research uses the Dynamic Memory Networks (DMN) model to obtain answers to the given questions. The parameter of the tested DMN model is learning rate, iteration, and episodes. This study uses 0.0005; 0.005; 0.05 as the value of learning rate, 1563; 3125; 6250 as the value of the number of iteration, and 3, 4, 5 as the value of the number of episodes. The dataset used in this research is 500 questions with a context in the form of single sentences and 500 questions with a context in the form of compound sentences which are taken from Wikipedia. The highest accuracy results are obtained by using the learning rate value of 0.005, iteration of 6250, and episodes of 5 on the dataset with the context in the form of single sentences amounted to 56% whereas the dataset with the context in the form of compound sentences amounted to 38.6%.
Research on a calculation method of the driving trajectory of mobile robot based on halcon

For the magnetic stripe, ribbon, two-dimensional code and other navigation methods, it is necessary to paste the identification mark on the ground. The paper uses machine vision technology to detect the ground features and obtain the driving trajectory of the mobile robot, lays the foundation for related research on mobile robots based on ground feature navigation. A method based on Forstner algorithm and RANSAC algorithm combined with calculation functions of pixel points' position informations is proposed. The image acquisition system is calibrated, the feature points in the images are extracted, the feature points in the adjacent images are matched, and the relative position informations of the two images are calculated by using the calculation functions of position informations based on the pixel points, thereby forming the driving trajectory of the mobile robot. The experimental results show that the appropriate threshold can be selected to calculate the center coordinates and deflection angles of the images, and the center coordinates and deflection angles can constitute the driving trajectory of the mobile robot. The feasibility of the method is verified.
Salient Object Detection via Quaternionic Local Ranking Binary Pattern and High-Level Priors

We proposed a novel salient object detection based on quaternionic local ranking binary pattern and high-level priors. Firstly, we employed a edge-preserving smoothing algorithm to smooth the minor variations within textures. Secondly, we adopted a local descriptor called quaternionic local ranking binary pattern (QLRBP) for smooth image, and got three feature maps. Futhermore, we presented a saliency measurement method based on Shannon entropy and L <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</inf> norm for the feature maps. Finally, we combined the two level priors with feature maps to generate three initial salieny maps, and we obtained final saliency map by the saliency measure method. The experimental results demonstrate that our method is effective and efficient.
The Innovation of the Mobile Intelligence Terminal in Foreign Language Teaching Under the Background of the Internet

The “Internet+” element has not only developed rapidly and popularized in various fields, but is also developing towards a pluralistic direction. From a thick paper dictionary to a portable electronic dictionary to an online dictionary that can be queried by mobile phones anytime and anywhere, the evolution of a multilingual online dictionary has always silently inspired foreign language teachers to explore new organization forms, teaching skills, teaching methods, teaching management models and guiding students to carry out the innovative and independent learning. The integration of the “Internet+” and education is no longer an unfamiliar concept. It will once again take wings for the development of the modern foreign language education and teaching.
Evaluation of school achievements of students with special educational needs – a preliminary study

In the first part of the article, the authors present new regulations in Kazakhstan that oblige teachers to monitor students’ academic achievements; they also draw attention to problems relating to the evaluation system for students with special educational needs in inclusive education. This gave grounds for undertaking research with the aim to analyze foreign experiences (in selected countries) and reflect in detail on the student evaluation system in Kazakhstan. In the next part of the article, the authors briefly outline Australian solutions and then provide a more detailed description of Polish and Russian solutions. A special focus is given to the analysis of the Kazakh system monitoring academic achievements in students with special educational needs, and both positive changes and the need to develop new systemic solutions are pointed out. The authors have found that I. Altynsarin National Academy of Education developed psychological and pedagogical approaches (student-centered, activity-based, and health-saving), pedagogical conditions, tasks, and functions of criterial evaluation of educational achievements, and requirements for a system of criterial evaluation of educational achievements of young students with special educational needs in an inclusive environment. At the same time, the questions concerning the procedure for evaluating individual achievements, the selection of methods, forms, means, and conditions of assessment as well as the consideration of personal indicators and the teacher’s professional and psychological readiness to participate in the assessment of students’ achievements have not been answered. That is why it is necessary to continue research on the process monitoring academic achievements in students with SEN that would result in creating a system to evaluate the performance of students with SEN, taking into consideration the Kazakh solutions and best practices as well as other countries’ experiences.
Two-Dimensional Path Planning on Improved A* Algorithm

The main computational complexity of A* algorithm lies in the state detection of nodes and the selection of nodes with the lowest cost. When the scenario of path planning is large, A* algorithm often occupies too much memory because of searching too many nodes, which seriously affects the efficiency of path finding. To solve the above problems, a new evaluation function is used to find the most suitable point on the adjacent edge as the search neighbor. Domain, which can not only find the destination node faster but also plan a shorter path. The simulation results show that the improved A* algorithm can plan a reasonable path in a shorter time on the raster map in a variety of environments.
Impact on Security Using Fusion of Algorithms

Cryptography is a technique used in transferring information in a protective and secured manner. Cryptography is usually about building and analysing the set of protocols that prevent the public and the third parties from reading private messages. The importance of cryptography in Network Security has gained a lot of importance and has become a research area for many researchers. Cryptography transforms data into a manner that is unreadable to a person who does not have authorization. This makes the data secured and privacy is maintained between the sender and receiver and the information is limited to themselves. This paper presents the study and examination of two individual encryption-decryption algorithms (T-RSA and Playfair) which are used in cryptography. It also shows how it improves security when combining than the individual ones.
Teaching Strategies of Literature Courses in the New Media Technology Environment

The development of new media technology in the new era has a great impact on education. Literature, as an indispensable part of university education, should make full use of the new media technology to innovate course teaching, realize the modernization of teaching and enhance students’ interest in learning literary knowledge, so as to make literature courses develop in a higher level. Based on the analysis of the current situation of literature course teaching, this paper elaborates the opportunities and challenges brought by the development of new media technology for teaching, and puts forward relevant course teaching development strategies, so as to realize the research purpose of literature course developing in a more professional direction under the new media technology environment.
U.S. Air Force Target Knowledge Graph Construction Based on Multi-source Intelligence Analysis

With the multi-source intelligence data grow exponentially, traditional methods can barely satisfy the requirement, which means to organize and understand the tremendous military knowledge. So, this research project aims to develop unified, highly connected military knowledge graph to integrate information. Using front-end interaction technology, supporting learning function based on inference, error-correcting and marking, this graph can continuously modify the logic model and improve the intelligence of itself, so the knowledge will be solid in our department. By doing this, we can reduce our dependence on the experience of special experts, and moreover, provide platform for developing data-driven general battle system in recent years.
Blind Multipurpose Image Watermarking Based on Secret Sharing

In this paper, in order to accomplish two goals of multimedia authentication and copyright protection, we present a multipurpose watermarking method based on a commonly used cryptographic primitive called verifiable secret sharing scheme. Utilizing this primitive, our scheme achieves blindness meaning that it needs neither the original host image nor the embedded watermark. Our scheme also does not need two distinct watermarks to authenticate the images and at the same time protect their copyright. Experimental results show that the features of the shares, obtained by the used primitive from watermark, enables our method to reconstruct extracted tampered watermarks after various attacks such as JPEG compression, cropping, salt and pepper noise, median filtering, some combined attacks, etc. Comparisons are provided with other multipurpose watermarking methods which primarily aim at protecting copyright of media and authenticating it simultaneously. We also show the superiority of our proposed method to three watermarking methods attaining the goals of copyright protection and authentication.
Towards Guided Summarization of Scientific Articles: Selection of Important Update Sentences

Guided summarization is aimed to distinguish the information from the prior and later documents for a given domain that are read by readers. Update summary is a second-crucial component to be generated from this task, after the initial summary. The existing techniques of guided summarization for news article cannot be directly adapted to the scientific article due to the different location structure of important information between these domains. In this research, we try to conduct the selection of important update sentences which is part of steps in guided summarization for the domain of scientific articles. We employ and compare some selection algorithms, such as Maximum Marginal Relevance (MMR) and TextRank. Because there is an initial summary that will become a reference to generate non- redundant information for update summary, so we modified their algorithms to minimize the similarity between the initial summary and candidates sentences for update summary. The result shows that the feature of `TextRank+ROUGE-SU4' fully gives the best ROUGE-2 recall performance that is 15.21% and the modified MMR and TextRank equation is better than baseline.
Optimization of Fermentation Medium of Camphor Lucidum Based on Artificial Neural Network and Genetic Algorithm

The complex fermentation process of medicinal filamentous fungus Cinnamomum camphora was modeled by optimization model, and the optimal fermentation medium composition was obtained. The morphological changes in the fermentation process of Anoderma camphora were observed. Artificial neural network (ANN) and response surface methodology (RSM) were used to model the fermentation process of Anoderma camphora, and genetic algorithm (GA) was used to optimize the composition of fermentation medium. The results showed that the ANN model had better fitting ability and predictive ability than RSM model, and the theoretical maximum value of biomass of Cinnamomum camphora was 6.2 g/L by GA algorithm. The optimization method based on ANN-GA can be used to optimize the complex fermentation process of other filamentous fungi to obtain biomass or active metabolites.
문장의 잉여 성분과 제시어

This paper proposes that the concept of the modified ‘theme’ can include all of the syntactic surplus constituents and established theme. These two classes of expressions share the grammatical status of independent constituent and pragmatic relation of topic-comment. Furthermore, these can be categorized into the modified theme. The defining feature that a theme must be a bare NP is no longer important in the concept of the modified theme. Thereby the differences between syntactic surplus constituent and the established theme function as the criteria that subclass the modified theme. Eventually, my new proposal dispenses with the confusion of syntax with pragmatics that occurs in the concept of the syntactic topic.
An ASIC for Discriminating Single Photon Detector Signal of High-Speed Quantum Key Distribution System

An ASIC is presented in this paper for discriminating signal from single photon detector (SPD) of high-speed quantum key distribution (QKD) system. The circuit is designed in 130 nm CMOS process. It receives and discriminates a small voltage pulse from a SPD, coinciding with a trigger signal and outputs the effective signal to next stage of QKD system. The pulse width of the voltage signal from SPD is less than 400 ps. The circuit mainly consists of bandgap reference, high speed comparator, delay chain and current mode logic (CML) driver. It should operate at a speed of 1.25 GHz. This work integrate all the front-end electronics for SPD into a chip. The area, stray capacitance and power consumption of the whole circuit are reduced. And then the whole receiver of QKD system can be integrated into a chip to improve performance.
Toward Improving Similar Item Recommendation for a C2C Marketplace

This study stems from actual challenges that we face in building a recommender system at Bukalapak. Our existing recommendation system, which is an item-to-item collaborative filtering based on co-view method has helped users during their shopping journey by offering them similar items recommendation in the product detail page. However, our baseline system has not utilized the information on how the user perceives the recommendation offered in our recommendation widget. This paper discusses how we improve our recommendation system with point-wise Learning-to-Rank (LTR) method. We also present specific features that support the LTR performance. Finally, we evaluate the LTR model by offline evaluation metrics and online A/B test, where we compare our baseline by using the model to rerank the candidates item before presenting them as recommendation sets. By calculating the Click Through Rate (CTR), it shows that the LTR method can outperform the baseline by 1.63%.
Two-layer resist process for printing thick patterns by exploiting a maskless projection exposure system using a liquid-crystal-display panel

To utilize maskless lithography using a liquid-crystal-display (LCD) panel for printing thick resist patterns, a novel two-layer resist process was developed. In the past research, simple and low-cost maskless exposure system was developed using an LCD panel in place of a reticle. However, commercial LCDs were fabricated not to irradiate short-wavelength light rays for protecting human eyes. Therefore, only thin g-line resists have been applicable for printing patterns. Nevertheless, patterning in 10–100 μm thick resist is frequently required for fabricating fluidic devices, lens arrays, and others. For this reason, a conventional g-line resist was coated on a thick UV resist, and patterns of g-line resist formed using the LCD maskless lithography was used as exposure masks of the bottom layer UV resist. As a result, various test patterns with widths of down to 40 μm and almost vertical side walls were successfully printed in the 70 μm thick UV resist.
Design of P2P English Teaching Platform Based on Network Technology and Streaming Media

At present, the network technology and streaming media technology with the continuous updating and development, promote the school English network teaching mode update and reform platform to create a diversified educational resource for English teaching. The teaching of English people network needs gradually expanding the scope, not only with browsing and downloading knowledge between teaching and learning the need for more teachers and students interact, because the bandwidth streaming media technology has been affected, can not effectively achieve information transmission, so the user, in order to solve this problem, using P2P network docking technology, design and develop a P2P based architecture. Firstly, the detailed analysis of English network teaching auxiliary system business requirements, describe the operation process of each system, then abstract the functional requirements of the system, and the use of UML modeling language to draw each function module use case diagram. This paper uses the SSH framework to achieve P2P network English teaching mode, access system based on browser, realize whenever and wherever possible learning and download a variety of teaching materials.
Mergemaps: Treemaps for Scientific Data

Topology driven methods for analysis of scalar fields often begin with an exploration of an abstract topological structure such as the merge tree. Such abstractions are hard to interpret and time-consuming, particularly for feature-rich data. Current visualization schemes often place less emphasis on enriching user experience, human perception, or interaction. In this work, we aim to bridge that gap by utilizing treemaps towards effective topological analysis. We present mergemaps, a treemap based interactive design, to better understand merge trees. To aid the perceptual understanding of large merge trees, we provide fusing and diffusing operations to reduce its hierarchical size while preserving topological features. We show multiple examples where our design leads to easy interpretations.
End-to-end Optical Chinese Character Recognition Based on Deep Learning

With the development of deep learning, the detection and recognition of text in natural images become much significant not only in academic field, but in daily life application. This technology, consists of end-to-end optical Chinese character recognition, can be easily employed in the transition from images to text. There are two main sections involved in this technology -- the detection and the recognition. For the detection, the state-of-the-art method is Region-CNN (R-CNN) and Region Proposal Network (RPN); and for the recognition, the state-of-the-art method is CNN. In this article, we employ Connectionist Text Proposal Network (CPTN) to detect sequential text lines in natural images, and incorporate Connectionist Temporal Classification (CTC) into DenseNet to recognize the text and transit it to Chinese characters.
Finding Circles with Deep Learning

Finding circles is a classification problem. Given a bunch of geometric shapes, we want the deep learning system to classify a shape as either a circle or something else. This is much simpler than classifying faces or digits. It is a good way to determine how well your classification system works. We will apply a convolutional network to the problem as it is the most appropriate for classifying image data.