Reviewerly/exHarmony huggingface dataset:
The Tool Bag

The techniques in this book are heavily reliant on external tools. This book does not teach you how to develop those tools but attempts to enlighten you on how you can make use of these tools to both build and test your apps. That’s why I have dramatically decided to call this chapter “The Tool Bag.” I will also spend a little time telling you about my setup that I use when reverse engineering and debugging Android apps. Your mileage will considerably vary, and perhaps you do not want to or are unable to set up your environment this way. This is fine. You can still get the job done, so don’t fret too much. In this chapter, I will talk about tools that I use to build, test, and break Android apps. The list will be a combination of free and commercial tools that I use personally in my daily routines depending on whether I am wearing a builder hat or breaker hat. I skew toward breaker by nature and by the career that I have had. This may be apparent in the dearth of the builder tools covered here, but it will cover the basics of what you need so that you can build your apps and then ensure that they are secure.
Review of Physical Layer Security Technology in Battlefield Network

Abstract Global openness of battlefield network makes it face many security threats, the physical security technology can provide an important support to traditional security system and strong protection to messages transmission, studying its application in battlefield network is of great significance. In view of the current and future network development trend, this paper studies the physical layer security problem from the perspective of battlefield network under modern warfare conditions, summarizes and analyzes the basic model of physical layer security, sorts out and introduces the physical layer security technology of wireless communication, and finally summarizes the risks and challenges still faced by the physical layer of the current battlefield network.
Bypassing SSL Pinning

With so much discussion around the topic of securing data in transit, I wanted to take a bit of time to dive into the actual process of SSL/TLS encryption and how Android and apps written for Android handle this. The best way to go about it is to get down and do the work, so in this chapter, we will see how to generate an SSL certificate, write a back-end API in Golang, and write an Android client to talk to that back end, and finally we will see how to intercept SSL traffic.
Upshot of Blockchain Technology: A Study

The blockchain technology is at a stage where its threshold capabilities have not yet been recognized. Various technologies emerge as the technological era progresses but one technology that is at its core roots and has the potential to disrupt many industries is blockchain. This technology has the potential to create an unimaginable difference in our lives. The blockchain technology is the answer and various questions can be framed across it. It has the potential to change the way the centralized systems work and can lead to an unimaginable futuristic technological advancement.
Data Management for Early Career Scientists &amp;#8211; How to Tame the Elephant

&amp;lt;p&amp;gt;Data Management can be overwhelming, especially for Early Career Scientists. In order to give them a kick-start, the World Data System (WDS) organised a 3-day EGU-sponsored workshop on current achievements and future challenges in November 2019 in Paris. The purpose of the workshop was to provide Early Career Scientists with practical skills in data curation and management through a combination of practical sessions, group discussions and lectures. Participants were introduced to what are research data andcommon vocabulary to be used during the workshop. Later, a World Caf&amp;amp;#233; session provided an opportunity to discuss individual challenges on data management and expectations of the workshop in small groups of peers. Lectures and discussions evolved around Open Science, Data Management Plans (DMP), data exchange, copyright and plagiarism, the use of Big Data, ontologies and cloud platforms in Science. Finally, the roles and responsibilities of the WDS as well as its WDS Early Career Researcher Network were discussed. Wrapping-up the workshop, attendees were walked through what is a data repository and how do they obtain their certifications.This PICO presentation given by two attendees of the workshop will showcase the main topics of discussion on data management and curation, provide key examples with special emphasis on the importance of creating a DMP at an early stage of your research project and share practical tools and advise on how to make data management more accessible.&amp;lt;/p&amp;gt;
A Deep Learning Approach to Detection of Warping Forgery in Images

In recent years, image forensics has received full attention from researchers. A large number of algorithms for image smoothing, JPEG compression, copy-move, and shear tampering were published. However, there are still many image tampering algorithms that are not involved. In this paper, we publish a dataset of image warping, which contains more than 10000 images, and propose a novel convolutional neural network called DWF-CNN to identify warped images. In experiments, we compared the performance with 4 alternative networks. The proposed network with the preprocessing layer of the SRM layer and Bayar convolutional layer got the best result, which reached to the accuracy of 99.36%. The experiments also showed that the network with the regular convolutional layer performed even worse than a random guess. It illustrates the importance of the well-designed preprocessing layer in this research area again.
Low-Rank Binary Matrix Approximation in Column-Sum Norm.

We consider 𝓁₁-Rank-r Approximation over {GF}(2), where for a binary m× n matrix 𝐀 and a positive integer constant r, one seeks a binary matrix 𝐁 of rank at most r, minimizing the column-sum norm ‖ 𝐀 -𝐁‖₁. We show that for every e ∈ (0, 1), there is a {randomized} (1+e)-approximation algorithm for 𝓁₁-Rank-r Approximation over {GF}(2) of running time m^{O(1)}n^{O(2^{4r}⋅ e^{-4})}. This is the first polynomial time approximation scheme (PTAS) for this problem.
PFHTS-IDSS: A Hybrid HTS-based Framework for Indonesian Speech Synthesis via Phoneme and Full-context Lab

In recent years, globalization has highlighted the importance of having machines that can truly provide customized communication for different languages. Majority of the research in the field focus on developing technologies for widely used languages such as English. In this study, we apply HMM-based speech synthesis (HTS) technology for Indonesian language. The proposed hybrid HTS-based framework, PFHTS-IDSS, uses phoneme and full-context lab to synthesize Indonesian with higher accuracy. First, we identify a list of Indonesian phonemes according to the initial-final structure of Chinese language. Based on this, we add zero-initials that match the Indonesian acoustic performance and HTS, which can make the synthesized speech natural and smooth. Second, we consider Indonesian phonemes as synthetic units to synthesize speech through the triphone and full-context lab. In addition, we design context properties of the full-context lab and the corresponding question set to train the acoustic model, which can eliminate machine sounds. Experimental results suggest that the accuracy of phoneme segmentation (PSA) and the naturalness of speech synthesis (SSN) are significantly improved via PFHTS-IDSS. Especially, the PSA of selecting phonemes as synthetic units reaches 88.3% and the corresponding SSN based on full-context lab is 4.1. The results demonstrated by PFHTS-IDSS presented in this paper may be used in multilingual free interactive system to promote better communication in terms of voice navigation, intelligent speaker and question-answering system.
Recovery of Lost Information from Unclear Images Using MRF-Based Inpainting

The work given in this paper explains the process of inpainting the images under global optimization technique. Initially, patch selection has been taken from an image by the clustering method to determine the portion of the unavailable information in an image. This takes place by the selection of the patch of lost portion in an image by grouping of the pixels in a region that gives a high quality of the image which has been followed by the refining of patches. The patch refinement takes place using high order singular value decomposition (HOSVD) that gets the cluster of patches and remove the unwanted pixels that are not needed for the inpainting. This collects the pattern from the patches that are clustered initially. At last, the weight value is obtained from the patches that has refined and the objective function has been included to get the clear image which gives a clear resemblance of the original image using Markov random field (MRF).
Tooltips and Popovers

Tooltips and popovers are great tools to embed extra, secondary useful information to the content of your page. This chapter teaches you both Twitter Bootstrap tooltips and popovers.
Point-to-Point Offline Authentication Consensus Algorithm in the Internet of Things

In the era of Internet of Things, identity and information authentication have drawn more and more attention. Existing identification mechanisms for identity information generally require networks, biometrics, etc., which exist security vulnerabilities such as security holes, privacy leaks, and vulnerability to attacks. A non-interactive concise offline authentication scheme based on block-chain technology is proposed which no need for complex services such as networking, and hardware implementation is simple. We research anonymity based on block-chain, workload proof and privacy protection technologies, design system models. Integrate device information, data, and confidentiality. The cloud platform function such as key management completes the hardware verification of the offline token authentication algorithm. The experiment results show that the scheme has the characteristics of extremely low recognition rate with a certain difficulty, high performance, high security, low cost, etc. Compared with the existing authentication methods, ours has more advantages.
Research on Chain of Evidence Based on Knowledge Graph

Evidence plays an extremely important role in legal proceedings, historical research, and diplomatic disputes. In recent years, more and more evidence data has been presented in the form of electronic data. Therefore, the extraction, organization, and validation of knowledge in electronic evidence also seem more and more important. In order to effectively organize the evidence data and construct the Chain of Evidence that can meet the practical needs, this paper uses Knowledge Graph based method to conduct relevance of evidence research. Firstly, through Knowledge Extraction, Knowledge Fusion, Knowledge Reasoning, the evidence data Knowledge Graph is constructed. After that, the Chain of Evidence will be built through evidence correlation and evidence influence evaluation, and finally different forms of knowledge presentation are carried out for different users. In this paper, the work and process of evidence chain association based on knowledge map are introduced, and the possible research direction in the future is prospected.
A Theoretical Review on Deliberation and Social Studies Education

현대 민주주의에 대한 성찰로 숙의민주주의가 주목받고 있다. 이러한 경향은 사회과교육에서도 확인되는데, 최근 토의·토론수업으로 구체화되고 있다. 그러나 숙의지향의 수업은 때때로 그 의도와 결과가 다르게 나타기도 한다. 이는 실천에 우선하는 이론에 대한 제한된 이해와 엷은 고민에 기인하는 측면이 있다. 이에 본고는 숙의민주주의의 이론적 전제를 사회과교육과 연관 지어 검토하였다. 우선 숙의민주주의와 사회과교육의 친밀성을 교과 내외의 측면에서 규명하였다. 이어서 숙의에 전제된 가치인 자율성과 상호존중 간의 긴장으로 인해 나타나는 실천의 어려움을 확인하였다. 또한 이러한 난점은 숙의가 구성하려던 정당화 규범까지도 훼손하며, 동일한 맥락에서 숙의를 지향하는 사회과교육이나 토론수업을 제한하게 된다는 점을 지적하였다. 논의의 말미에는 확인된 어려움을 극복하기 위한 방안으로 숙의지향의 사회과 수업에서 발화와 합의 양식의 다양화를 제안하였다. 덧붙여 교사의 역할을 통해 숙의의 방향을 가늠하고 적절히 조정하는 효과를 강조하였다.Nowadays a deliberative democratic approach has taken lead in reflecting modern democracy. Such a trend is being found easily in discussions and deliberations in social studies classrooms. But sometimes deliberative classroom discussions have an unintended or wrong consequence because of limited understanding of and thin consideration to theoretical premises of deliberative democracy. Accordingly, the study was to review the premise of deliberative democratic theory associating with social studies education. For this, first, an affinity between deliberative democracy and social studies education was discussed in contexts both inside and outside the subject. Second, It was pointed out that values such as autonomy and mutual-respect are embedded in deliberative processes and a tension existing between the two values makes deliberative practices difficult. Third, It was suggested that the difficulty might damage even the justification norms that are supposed to govern deliberative practices and restrict deliberative classroom discussion in social studies. Finally, I demonstrated the diversity in modes of discourse and consensus, and teachers’ role as coordinator of deliberative practices with mediation.
Analysis of Fluctuation and Correlation Tendency among Precipitation, Wind, and Solar from Various Spatio-temporal Perspectives: a Case Study in China

&amp;lt;p&amp;gt;Analysis of correlation among precipitation, wind, and solar resources could explore their complementary features, enhance the utilization efficiency of renewable energy and further alleviate the carbon emission issues caused by fossil energy. In this study, we discuss the correlation between precipitation and wind, wind and solar, precipitation and solar from various Spatio-temporal perspectives (from east to west in China, in terms of plain, plateau, hill, and mountain, from daily to ten days and monthly) with observed data. With investigation of daily time series of precipitation, wind speed and solar radiation ranging from 1961-1-1 to 2016-12-31 of 726 meteorological stations located in various landform and distributed dispersedly in China, the results show that 1) the fluctuation value, quantified by Mei-Wang Fluctuation index, denotes the descending tendency when the time resolution increases, and this tendency is stronger in the southern and eastern China; 2) the correlation coefficient, characterized by Kendall&amp;amp;#8217;s rank correlation coefficient, changes from east to west in China, and the strength of this correlation displays certain connection to the local topography (e.g., in Qinghai province which is located in the plateau region the complementarity between precipitation and wind speed is stronger than that between precipitation and solar, the mid-stream basin of Yangtze River where the topography is scattered and complex has the weaker complementarity compared to other areas in China). According to the results of this research, it is helpful from the temporal perspective to understand the requirement of complementarity in the utilization of wind, and solar resources which are intermittent, and from the spatial perspective to know the solution of mitigating fluctuation via integration of multi-renewable energy situated in different locations.&amp;lt;/p&amp;gt;
A study on the reconnaissance efficiency of the radar countermeasure equipment based on the DHGF algorithm

In the modern information warfare, the evaluation of the reconnaissance efficiency of the radar countermeasure equipment is fundamental to response timely and master the development of equipment. In this paper, according to the basic tasks of the radar countermeasures reconnaissance, the evaluation model of the reconnaissance efficiency is constructed based on the DHGF algorithm. Firstly, Delphi algorithm is adopted to construct the multi-index evaluation system. Secondly, the weight of each index is calculated by AHP algorithm. Afterwards, the grade of the reconnaissance efficiency is evaluated by grey correlation analysis and the fuzzy evaluation. Finally, the grade of evaluation object is analyzed and verified by an example. Thus, the validity of the DHGF algorithm is verified, which provides the basis for equipment efficiency evaluation.
Smart Technologies for the Environmental Design of Smaller Urban Centres

The present study focuses on welfare measures and specifically on healthcare. The challenge we would like to accept is to provide efficient healthcare to residents in an isolated area without health services, maintaining the same level of healthcare ensured by hospitals. The innovative design, that we want to experience, is closely linked to the use of ICT, information and communication technologies, because these technologies would be able to perform autonomously multiple functions, using remote control. Telemedicine or “virtual health” is a particular branch of ICT that can improve future quality of living in a marginal urban center as a tool to ensure prompt access to expert advice, as well as patient monitoring, wherever patients and medical centers may currently be located. Mobile technology applied to healthcare could stimulate advances in telemedicine: handheld and mobile phones, equipped with specific software with advanced diagnostic instruments, being small and user friendly, could enhance medical services if integrated in houses and if the users might have a direct access to them. The research consists, in a first step, the analysis of the main technologies for active and healthy ageing and then re-designed an healthcare system structure in a case study (a small town near Palermo), in terms of usability and accessibility for health authorities and, most of all, patients. We chose as a case study a little mountain town, which because of its location, is forced to wallow in a condition of marginality, far from fundamental services for citizens.
Research on feedback Cognitive Method of Insulator Self-blast State Based on Multi-scale Convolutional Network

In view of the lack of the existing insulator self-blast state detection method and the scale defects of deep neural network structure, imitated the human cognitive model, and learn from the closed-loop control theory, this paper explores a feedback recognition method of insulator self-blast state with multi-scale convolutional neural network. Firstly, for the pre-processed insulator images, based on ResNet-18, branches with different network structure are added to improve the network ability to adapt to different resolutions. At the same time, the multi-scale information fusion module is added at the end of the network. Secondly, the multi-scale feature vector is sent to stochastic configuration networks (SCN) with universal approximation ability to establish the classification criterion of the self-blast state of insulator images with strong generalization ability. Finally, an imitation of human thinking patterns is employed that exhibits repeated deliberation and comparison. Consequently, based on generalized error and entropy theories, the performance index is defined to evaluate the uncertain results of the insulator self-blast states in real time. Then, the regulation mechanism is given to realize the self-optimizing of fixed feature space and the reconstruction of classification criteria, which renders the insulator self-blast states is re-recognized with feedback mechanism. Experimental results show that, compared with other open-loop and closed-loop algorithms, the proposed method enhances the generalization ability and improves the recognition accuracy of the model.
Research on Machine Vision Image Mosaic Algorithm for Multi-workpiece Cutting Platform

The cutter head parts of the tunnel boring machine (TBM) are of different sizes, and the cutting platform is of large size. The panoramic view of the cutting platform that meets the accuracy requirements through image stitching is a prerequisite for realizing the visual guidance of autonomous cutting. An image stitching algorithm is studied to reduce the complexity of the algorithm on the basis of ensuring the stitching precision. The ORB algorithm is selected to implement feature detection, and a series of strategies are adopted on this basis. The ROI region is extracted, and only the images in the region of interest are matched. Then, the feature detection, description and matching are performed by the ORB feature detection algorithm and Hamming distance. The feature points are purified by the RANSAC algorithm, and the transformation matrix H is calculated. Finally, the image fusion is carried out. The experimental results show that the ROI-based ORB image stitching algorithm satisfies the accuracy requirements of subsequent visual guidance.
Laboratory works in courses of algebraic disciplines of higher educational institutions.

At the same time, in the system of mathematical preparation of a university student, the formation of his research competence is not sufficiently described in the pedagogical literature developed by us. In particular, there is a gap in the implementation of laboratory work on mathematics (as one of the most powerful means for forming the student’s research competence) in the educational process. We believe that laboratory work must integrate theoretical knowledge, practical skills and abilities of students into a single process of teaching and research activity, that is - in laboratory work.
Semantic Segmentation Using ENet Architecture

Interests in augmented reality wearable’s, automated devices used in home, self-driving vehicles are in high demand, which uses semantic segmentation. The methodology includes the consideration of each and every pixel, i.e., every pixel may belong to any one category and can be operated in real-time applications on less-power mobile devices. Although, huge availability of data sets and many machine learning algorithms outstrip the performances of this kind of application but as a penalty in floating-point operators which increases the running time. In order to classify the spatial images along with the meaningful segmented regions, numerous Neural Networks are proposed includes Signet or Fully CNN for multiple class classification. In this work, we used the newly introduced model ENet also called Efficient Neural Network, which is specially designed for tasks requiring low latency operations. This model is 18× times faster, using less number flops, i.e., 75× less, and uses less number of parameter, i.e., 79× less. The proposed method uses Cityscapes database for the experiments and the results are compared with other conventional techniques.
Study on the Extraction of Target Contours of Underwater Images

Image is an important medium for human to obtain information, and the study of underwater image information plays an important role in marine scientific research. This paper studies the target contour extraction in the complex underwater environment. In this paper, we focus on the external contour calibration, and the study aims to segment the contours of many images with prominent texture, chromatic aberration, and shape differences. We also improve underwater image denoise and enhancement technology, restore target area features as much as possible, and process color channel selection with K-means algorithm. At the same time, the external contour extraction and the filling of the target area are partially optimized. Multi-scale watershed algorithm is used to improve the performance of the algorithm. Finally, the Canny and Grabcut algorithms are selected to detect the edges of the image. The experimental results verify that our method is feasible to extract the contours of fish in complex environments.