Reviewerly/exHarmony huggingface dataset:
Methodological Aspect of the Interconnection between Science and Research

The present research features the relationship between science and scientific research as internal elements of scientific knowledge. The subject is the methodological aspect in the study, namely, the theoretical self-consciousness of science in a specific historical period, the analysis of the evolution of socio-cultural forms of life of science – monodisciplinary, interdisciplinary, transdisciplinary, supra-disciplinary. Each of these forms once had historically formed methodological potential-techniques, methods, principles, ideals, and norms of knowledge. At each stage, new ways of understanding are formed, and new meanings that revolutionize science, practice, and culture are created. The increase in methodological equipment of science expands cognitive horizons. The changes in socio-cultural forms of science and the nature of scientific research are not synchronized, but they are internally determined. Approach as a methodological tool acts as a connecting link. The choice of methodological approach is determined by the methodological culture of the researcher and, as a rule, reflects the dynamics of scientific knowledge. The authors use the following methodological tools: dialectics of the historical and the logical, dialectics of content and form. They highlight the immanent connection of scientific research and science as the most important components of a specific form of cognition, i. e. science; show the interrelation between the socio-cultural form of science and its epistemological content; demonstrate the dynamics of the complexity of methodological tools in the history of science – from techniques and methods of research to such a methodological phenomenon as the approach, which, in turn, has yet to be investigated.
Conceal secret letter using 2D wavelet packet

This system uses three stages to hide the secret letter. The first stage uses the summation of two images and applies a 2D wavelet packet at level one (L1), level two (L2), and level three (L3). In the second stage, Haar filters are applied at L1, L2, and L3, and the third stage conceals the binary secret letter using AS CII to convert each symbol in the secret letter to a binary number to hide it in the 2D image wavelet packet. It can hide each bit in one location using the least significant bit (LSB). The secret key is used to select the location, which depends on the equation 2n2 + 1 to find the position of the hidden bits of the secret letter in the 2D wavelet packet. The outcome of the algorithm is efficient, robust, transparent, and highly secure. The system hides the secret letter well in the stego image without being sensed by attackers.
Hand Gesture Recognition Using PCA, KNN and SVM

To interact with world using expressions or body movements is comparatively effective than just speaking. Gesture recognition can be a better way to convey meaningful information. Communication through gestures has been widely used by humans to express their thoughts and feelings. Gestures can be performed with any body part like head, face, hands and arms but most predominantly hand is use to perform gestures, Hand Gesture Recognition have been widely accepted for numerous applications such as human computer interactions, robotics, sign language recognition, etc. This paper focuses on bare hand gesture recognition system by proposing a scheme using a database-driven hand gesture recognition based upon skin color model approach and thresholding approach along with an effective template matching with can be effectively used for human robotics applications and similar other applications .Initially, hand region is segmented by applying skin color model in YCbCr color space. Y represents the luminance and Cb and Cr represents chrominance. In the next stage Otsu thresholding is applied to separate foreground and background. Finally, template based matching technique is developed using Principal Component Analysis (PCA), k-nearest neighbour (KNN) and Support Vector Machine (SVM) for recognition. KNN is used for statistical estimation and pattern recognition. SVM can be used for classification or regression problems.
An Anonymous off Block Chain Scheme for I-Voting Using Bit Coin in the Real World

Democratic voting is a crucial and serious event in a country. The most common way in a country votes through a paper based system, but is it not time to bring voting into the 21st century of modern technology Digital voting system uses electronic devices such as voting machines or an internet browser to cast votes. These are sometimes referred to as e-voting where voting use a machine in a polling station and i-voting when using a web browser. Security of digital voting is always the biggest concern to implement a digital voting system. One way the security issues can be potentially solved through the technology of block chain. Block chain technology originates from the architectural design of the cryptocurrency bitcoin. With the use of block chains a secure and robust system for 4 digital voting can be devised. The report outlines our idea of how block chain technology could be used to implement a secure digital voting system.
Air Gap Penetration

The issue of data security is very paramount for any organization now a day So through this project we will show how an attacker can steal data from the air �gapped channels and also provide some measures in order to protect data from such type of attacks. Now a day attackers can leak data from isolated, air-gapped computers to nearby smart phones via covert magnetic signals. Attacks have been demonstrated on eavesdropping computer displays by utilizing these emissions as a side-channel vector. The accuracy of producing a screen pic depends on the emission sampling rate and bandwidth of the attackers signal hardware. The cost of radio frequency hardware increased with supported frequency range and bandwidth. A number of affordable software defined radio equipment solutions are currently available satisfying a number of radio-focused attacks at a proper price point. This work investigates that the accuracy influencing factors, other than the sample rate and bandwidth, which are noise removal, image blending, and image quality adjustments, that affect the perfection of monitor image reconstruction through electromagnetic side-channel attacks.
On the observation of the dynamical Lamb effect using a superconducting circuit

Get PDF Email Share Share with Facebook Tweet This Post on reddit Share with LinkedIn Add to CiteULike Add to Mendeley Add to BibSonomy Get Citation Copy Citation Text M. Amico, O. L. Berman, and R. Y. Kezerashvili, "On the observation of the dynamical Lamb effect using a superconducting circuit," in Quantum Information and Measurement (QIM) V: Quantum Technologies, OSA Technical Digest (Optica Publishing Group, 2019), paper F5A.71. Export Citation BibTex Endnote (RIS) HTML Plain Text Citation alert Save article
DNS: A multi-scale deconvolution semantic segmentation network for joint detection and segmentation

Real-time semantic segmentation has become crucial in many applications such as medical image analysis and autonomous driving. In this paper, we introduce a single semantic segmentation network, called DNS, for joint object detection and segmentation task. We take advantage of multi-scale deconvolution mechanism to perform real time computations. To this goal, down-scale and up-scale streams are utilized to combine the multi-scale features for the final detection and segmentation task. By using the proposed DNS, not only the tradeoff between accuracy and cost but also the balance of detection and segmentation performance are settled. Experimental results for PASCAL VOC datasets show competitive performance for joint object detection and segmentation task.
NEAR: Normalized Network Embedding with Autoencoder for Top-K Item Recommendation

The recommendation system is an important tool both for business and individual users, aiming to generate a personalized recommended list for each user. Many studies have been devoted to improving the accuracy of recommendation, while have ignored the diversity of the results. We find that the key to addressing this problem is to fully exploit the hidden features of the heterogeneous user-item network, and consider the impact of hot items. Accordingly, we propose a personalized top-k item recommendation method that jointly considers accuracy and diversity, which is called Normalized Network Embedding with Autoencoder for Personalized Top-K Item Recommendation, namely NEAR. Our model fully exploits the hidden features of the heterogeneous user-item network data and generates more general low dimension embedding, resulting in more accurate and diverse recommendation sequences. We compare NEAR with some state-of-the-art algorithms on the DBLP and MovieLens1M datasets, and the experimental results show that our method is able to balance the accuracy and diversity scores.
Photon-Subtracted Continuous-Variable Graph States

Mode-selective photon subtraction is a viable method to introduce non-Gaussian features in continuous-variable graph states. Non-Gaussian properties are shown to spread up to next-to-nearest neighbours of the graphs vertex in which the photon was subtracted.
Clustering of inaccurate data using information on its precision

In this paper, an approach to clustering inaccurate data with taking into account information on their imprecision is proposed. The presented procedure allows to reasonably determining the maximum number of clusters, coordinated it with data accuracy: the low accuracy of the measurement results will not give grounds for separating some of the object states from others. Also taking into account the uncertainty of the initial data allows to simplify the clustering procedure by matching the complexity of the methods used in its implementation to the accuracy of the initial data. The proposed procedure allows not to create or specify clusters during the classification of inaccurate data beyond what is necessary, the experimental results of the application of described approach are presented in this paper.
Free Speech on Australian Campuses: Hidden Barriers.

Speech at Australian universities is restricted in various ways. A few of them, such as student protests against visiting speakers, receive lots of attention. Others seldom do, such as defamation threats and cyber harassment. Self-censorship may be more significant than overt censorship. Those who want to raise awareness of hidden limitations on speech can learn from the methods used to raise the alarm about student protests.
Application of the Computer Aided Language Teaching Based on the Internet in the Business English Teaching

Because of its own uniqueness of the Business English teaching, the traditional Business English curriculums cannot meet the learners’ requirements. The development of the computer-aided language teaching mode provides the powerful technical support for the Business English teaching. With the rapid development of our society, the application of Business English has entered a new stage. However, throughout its teaching mode, it still stays in the traditional stage of “ear-to-mouth transmission”. Therefore, how to optimize the teaching mode and change the mechanical and outdated teaching appearance has become a subject under the new situation.
A Novel Hybrid Sequential Model for Review-Based Rating Prediction

Nowadays, the online interactions between users and items become diverse, and may include textual reviews as well as numerical ratings. Reviews often express various opinions and sentiments, which can alleviate the sparsity problem of recommendations to some extent. In this paper, we address the personalized review-based rating prediction problem, namely, leveraging users' historical reviews and corresponding ratings to predict their future ratings for items they have not interacted with before. While much effort has been devoted to this challenging problem mainly to investigate how to jointly model natural text and user personalization, most of them ignored sequential characteristics hidden in users' review and rating sequences. To bridge this gap, we propose a novel Hybrid Review-based Sequential Model (HRSM) to capture future trajectories of users and items. This is achieved by feeding both users' and items' review sequences to a Long Short-Term Memory (LSTM) model that captures dynamics, in addition to incorporating a more traditional low-rank factorization that captures stationary states. The experimental results on real public datasets demonstrate that our model outperforms the state-of-the-art baselines.
A Representation of Rhythmic Motions

Skill is an action requiring intelligence. It has been debated whether motions require representations because they are thought to describe procedures. The dichotomy between thought and execution has puzzled us because we are unsure how thinking process intervenes with execution and how execution is understood by thinking process. We have in other words no logical theory of executions. We propose an intermediate level of representation between thought and execution. Hinted by an illustration by a professional musician, we propose to represent the skill knowledge as a phase space. The shape conveys necessary items of information to dance and play samba with different types of instruments thanks to the abstract representation of motions. We show that the shape is established by abstracting over physical particulars such as velocity, direction, position, etc. The abstract form of representation bridges the gap between thought and execution. It also allows masters to transfer his knowledge to pupils. We hypothesise that more layers would exist between thought and execution, enabling the agent to effectively plan and control his motions.
Dynamic Diversification for Interactive Complex Search

Many real-world searches are examples of complex information needs such as exploratory, comparative or survey oriented searches. In these search scenarios, users engage interactively with search systems to tackle their information needs. On one hand, user interactions can be leveraged to induce search intents and reformulate queries. On the other hand, the nature of these scenarios introduces constraints in the search process. For instance, systems are expected to satisfy the information needs earlier in the interaction. This research investigates a dynamic diversification approach that observes user interactions and dynamically changes its behaviour in response. In this research, we investigated how dynamic diversification methods should be evaluated. In that regard, we studied and analysed a wide range of offline metrics that model topical relevance novelty and user effort. In addition, this research investigates how to exploit user interactions to develop dynamic diversification methods. In particular, we study the impact of the different dimensions of user relevance feedback, the internal components of relevance feedback algorithms and diversification methods on the overall performance of dynamic diversification methods. Lastly, we intend to measure user satisfaction with these methods using a controlled user study.
Use of Mobile Apps and Creator-Audience Matchmaking

With a bird's-eye-view of the journey of exploring mobile use and its impacts in India, one of the biggest mobile markets in the world, the author of this chapter provides an analytical and insightful review of earlier studies on mobile communication development and utility-driven usage. Although country-specific, this chapter provides a very interesting, insightful, and invaluable model to the world, that is, the model of creator-audience matchmaker. As demonstrated by the two cases in this chapter, the creator-audience matchmaker model can be used as a heuristic tool for understanding mobile app development and success in India.
Wrongful Life in the Age of CRISPR-CAS: Developing a Legal Fiction for Wrongful Gamete Manipulation Cases

Virtually all wrongful life claims (those brought by children harmed prior to gestation), are denied. The basis for these holdings pivots around refusal to allow recompense for actions which result in the child’s being born, an offshoot of cases where parents are denied the right of abortion. We therefore are faced with a legal lacuna, where children suffering serious harms as a result of wrongful genetic manipulation (WGM) caused by the latest reproductive technologies are legal orphans. This article details avenues of potential harm generated by the latest technologies before proceeding to create a legal fiction, “the conceptual being” which would enable these children to bypass current restrictions and claim an expanded class of damages, including pain and suffering, emotional injury and unjust enrichment.
Ghost-removal image warping for optical flow estimation

Traditional image warping methods used in optical flow estimation usually adopt simple interpolation strategies to obtain the warped images. But without considering the characteristic of occluded regions, the traditional methods may result in undesirable ghosting artifacts. To tackle this problem, in this paper we propose a novel image warping method to effectively remove ghosting artifacts. To be Specific, when given a warped image, the ghost regions are firstly discriminated using the optical flow information. Then, we use a new image compensation technique to eliminate the ghosting artifacts. The proposed method can avoid serious distortion in the warped images, therefore can prevent error propagation in the coarse-to-fine optical flow estimation schemes. Meanwhile, our approach can be easily integrated into various optical flow estimation methods. Experimental results on some popular datasets such as Flying Chairs and MPI-Sintel demonstrate that the proposed method can improve the performance of current optical flow estimation methods.
Classification of student activities based on a sequence of images from a single camera

In an active learning environment, a student activities is crucial to his/her learning achievment. However, keeping track of the student activities by teaching staffs is almost impossible. Hence, using technology for such tedious but important job has become attractive or even necessary. Focusing on such environment, this paper proposes a method of classifying whether a student is writing or reading or working on other things such as doing experiments based on sequential image frames from a single camera. For each frame, an area including the student is cropped out using a background subtraction and thresholding. Then, using the skin detection technique, face and hands of the target students are detected. Such face and hand areas of n sequence of frames are combined as a Gait Energy Image (GEI), which is being used as feature images for the classification in which the Principal Component Analysis is applied. A sum score of the PCA in which each row as an observed sample is taken as a feature while another score of PCA in which a column is considered to be an observed sample is taken as another feature. Using the support vector machine, the two features are used to classify whether a student is “reading” or “not reading” first. Then, for a “not reading” sample, it is classified whether it is “writing” or “doing experiment”. Based-on a sequence of simulated activities, the proposed method can classfy between “reading” and “not reading” with 93% accuracy while the classifying between “writing” and “doing experiment” class achieved 90% accuracy.
When OR is conjunctive in child Mandarin

According to a recent proposal, children license a conjunctive inference for statements with disjunction even without a licensing expression that adults require, e.g., the deontic modal verb is allowed to (Singh, Wexler, Astle, Kamawar, & Fox, 2016; Tieu et al., 2017). However, the rates of children’s conjunctive inferences vary considerably across studies, which may be due to the different experimental tasks and materials. Using a Truth Value Judgment Task (Crain & Thornton, 1998), the present study systematically investigated children’s interpretation of disjunctive sentences with and without a deontic modal verb. It was found that children computed conjunctive inferences only in sentences with the deontic modal verb. We discuss the possible reasons for the varying findings of children’s interpretation of disjunction in previous studies.
Construction and Application of Intelligent Campus in Colleges and Universities Under the Background of Big Data

With the advent of the era of “Internet plus”, information technology in Colleges and universities is facing unprecedented new situations and new challenges. Intelligent campus is a new stage in the development of educational informatization. This paper analyses the connotation and characteristics of smart campus, puts forward the idea of building smart campus, and takes S University as an example to introduce the specific application of smart campus. Colleges and universities should take the construction of intelligent campus as an opportunity to continuously promote the realization of educational modernization.
CYBERDEMOCRACY: A NEW PHENOMENON IN SPANISH SOCIOLINGUISTICS

Te article analyses ciberdemocracy as a new phenomenon that emerged in the Spanish society in the 21st century. Te development of digital technologies and ICT’s (in particular, Internet), which is substantiated by the statistics for the last decade provided by the Spanish National Institute of Statistics and the comparative analysis of data for 2008 and 2016, created new political instruments and means of getting ideas benefcial to certain political groups across to the electorate. Not only do linguists research into this phenomenon but also the Spanish Government. Te article presents characteristic features of ciberdemocracy, gives its defnition on the basis of those provided by Spanish authors and suggests a fgure that illustrates a systemic functioning of ciberdemocracy. Te inﬂuence of the new phenomenon on the Spanish language is analysed from the point of view of social and cognitive linguistics: the emergence of NetSpeak, neologisms, the penetration of emotive lexis into messages due to the limited characters number for one message or post in social netwoks or web-sites, as well as new manipulative instruments of journalese discourse to exercise aﬀect on the audience. Te article contains ideas of possible further changes in the Spanish language due to ciberdemocracy.
Multi-level Security Approach on Weapon Systems

Scope of this paper is to show how is possible to implement Bell-LaPadula model using Linux Container on a single host machine; this innovative technology, which will be explained better in next chapters, allows to create segregated and isolated environment into same machine. The creation of multi-level security system inside a container environment can effectively guarantee the confidentiality of the application software and data, restrict illegal attacker, and prevent attackers from arbitrarily destructing system information; moreover, it can also be easy to configure and manage the system policy.