Reviewerly/exHarmony huggingface dataset:
An Optimal Lightweight RECTANGLE Block Cipher for Secure Image Transmission in Wireless Sensor Networks

The fast development of networking permits substantial documents, for example, multimedia images, to be effectively transmitted over the Wireless Sensor Networks (WSNs). An image encryption is generally used to guarantee the security as it may secure the images in the greater part. The process of securing the images in WSN against unauthorized users is a challenging one. For guaranteeing high security among Digital Images (DIs), Light Weight Cryptographic (LWC) algorithms are utilized which split the DI into a number of blocks; this will upgrade the level of security in WSN. Here, the proposed block cipher is RECTANGLE which separates the image in a bit-slice style; and improves the DI security level by encryption and decryption depending on the determination of optimal public key and private key individually. The key optimization was finished by the metaheuristic algorithm, for example, Opposition-based Grey Wolf Optimization (OGWO) which chosen optimal key on the basis of the most extreme PSNR value. The exhibited RECTANGLE–OGWO accomplished the least time to produce key which remained as an incentive to encrypt and decrypt the image. The result showed that the RECTANGLE–OGWO algorithm enhanced the accuracy of DI security for all the images (Lena, Barbara, Baboon, Airplane and House) when contrasted with existing algorithms.
Player Piano Roll

THE PLAYER PIANO ALSO known as the “Pianola” or the “Aeolian Pianola,” from the brand of the leading manufacturer in the early 1900s—is a mechanical instrument capable of automatically playing music scores converted into perforated paper rolls. It was the first technology for mechanical reproduction of music that was mass-produced and had widespread application and success. It fundamentally changed the way that we experience music; and the copyright battle that the technology generated was the beginning of a war over the control of music and content that is being fought to this day.
VCWE: Visual Character-Enhanced Word Embeddings

Chinese is a logographic writing system, and the shape of Chinese characters contain rich syntactic and semantic information. In this paper, we propose a model to learn Chinese word embeddings via three-level composition: (1) a convolutional neural network to extract the intra-character compositionality from the visual shape of a character; (2) a recurrent neural network with self-attention to compose character representation into word embeddings; (3) the Skip-Gram framework to capture non-compositionality directly from the contextual information. Evaluations demonstrate the superior performance of our model on four tasks: word similarity, sentiment analysis, named entity recognition and part-of-speech tagging.
Underwater Image Processing using Hybrid Techniques

Underwater imaging is an emerging area of research. The underwater image suffers degradation due to scattering and absorption. To overcome these issues, the acquired images are adjusted using color balance and then corrected using white balance. Common methods available for white balance are Retinex and Gray world. In this work, proposing Gray world technique for white balance. From the corrected image, weight maps-based feature extraction would be done followed by multi fusion and image enhancement. Due to the wide application of wavelet transform in image processing, here using two-dimensional Discrete Wavelet Transform as fusion operator. Also, make the synaptic network to the new level of application. The result demonstrates that the proposed enhancement algorithm can obtain a well visual result.
SBD'19

The International Workshop on Semantic Big Data (SBD) is already in the fourth year in conjunction with the ACM SIGMOD Conference. By focusing on topics related to Semantic Web and Big Data, it highlights these important research areas to all participants of the SBD workshop and the main conference. Hence, the workshop offers an ideal forum for open discussions and establishment of professional relationships between academic researchers and industrial members of the Semantic Web and database communities.
A Strange Approach to Information, Network, Sharing, and Platform Societies

Susan Strange's framework for international political economic analysis emphasises the importance of the interrelationships between what she saw as four interlinked structures and sources of power in the global economy: security, production, finance, and knowledge. As change occurs in one structure, it is important to systematically consider the implications of such changes in the other four structures. This chapter provides an overview of how the knowledge structure interacts with the other three structures of power. Second, it assesses the extent to which four major works related to transformations in the knowledge structure—Daniel Bell's The Coming of the Post-Industrial Society (1976), Manuel Castells' trilogy The Network Society (first published 1996–1998), Yochai Benkler's The Wealth of Networks (2006), and Nick Srnicek's Platform Capitalism (2017)—examine the interrelationships between Strange's four structures, and the consequences for their overall conclusions.
RANCANG BANGUN SISTEM PELAPORAN PELANGGARAN PARKIR BERBASIS ANDROID

The high level of ownership of private vehicles will require large parking lots in certain zones. Not all places are able to provide sufficient parking space, so that the road body around it is used for parking lots. This will cause traffic problems. Utilization of technology can be one solution to overcome these problems. The purpose of this research is to design and build an Android-based parking violation reporting system so that the community can take part in reporting violations in the form of photos that are directly sent to the DLLAJ server (Road Transport Traffic Service) and make it easier for officers in their handling. System modeling plans include the Use Case Diagram, Activity Diagram and database structure. The process of this application is to send a parking violation photo to the server, then extract the photo to get the metadata (latitude and longitude) that shows the location of the violation. Based on the results of testing the application with the Black Box Testing method, the overall functionality of the application has been declared successful. In addition, based on the results of the System Usability Scale (SUS) test, a score of 79.5 means that the value is above the average and the application can be accepted by the user.
Online Job and Candidate Recommendation System

To develop an enhanced web application, using web services for both online job and candidate recommendation system. By using Professional Social Recommender (PSR) and Text field filtering the recommendation of jobs and candidates will be classified. Three tier architecture designs have been implemented for efficient data retrieval and data transfer. They are Job seeker interface, Candidate recruitment interface and Recommendation database will be the architecture taken for developing this application. The primary architecture will be the job seeker interface, in followed with candidate recruitment interface and Recommendation database will be interconnected. The professional social recommender will works as a third party agent and the agent will retrieves all the recommended job and candidate profiles. A panel will be designed for displaying the recommended job and candidate details. All the displayed jobs will be more relevant to the user’s profile. The generated user and candidate profile will be encrypted in order to overcome the privacy breaches.
A Unifying Framework for Variance Reduction Algorithms for Finding Zeroes of Monotone Operators

It is common to encounter large-scale monotone inclusion problems where the objective has a finite sum structure. We develop a general framework for variance-reduced forward-backward splitting algorithms for this problem. This framework includes a number of existing deterministic and variance-reduced algorithms for function minimization as special cases, and it is also applicable to more general problems such as saddle-point problems and variational inequalities. With a carefully constructed Lyapunov function, we show that the algorithms covered by our framework enjoy a linear convergence rate in expectation under mild assumptions. We further consider Catalyst acceleration and asynchronous implementation to reduce the algorithmic complexity and computation time. We apply our proposed framework to a policy evaluation problem and a strongly monotone two-player game, both of which fall outside of function minimization.
QoS Preservation in Web Service Selection

In cloud computing domain, often service providers offer services with same functionalities, but with varying quality metrics. A suitable service selection method finds the most appropriate solution among the alternatives. The challenge is to deliver a solution satisfying the requirement (quality and other) of a consumer with minimum possible execution time. Many conflicting QoS objectives increase the complexity of the problem. In fact, the problem may be formulated as a multi-objective, NP-hard optimization problem. Most of the existing solutions either satisfies the QoS demands of consumer or only reduces execution time by considering a sub-set of required QoS metrics. Consumer’s feedback on the choice of required QoS metrics not only shall help increasing user satisfaction, but also may reduce the complexity effectively. However, this depends on the domain knowledge of a consumer. In this work, we have proposed a goodness measure that replaces all QoS metrics by a single one. The new technique using dimension reduction is proposed to offer significant improvement compared to the existing works in terms of execution time. Moreover, the solution satisfies all the QoS requirements of a consumer in most of the cases. The proposed data driven selection approach has been implemented and the experimental results substantiate the claims as mentioned.
Distance course as a form of self-dependent learning

The features of distance learning organization, the web resources which were required to provide distance English learning were considered in the article. There were mentioned the main necessary elements of distance learning implamentation, there was examined the most accessible and convenient information environment Moodle to form attainments and skills of independent learning, its main characteristics were given. The definition of the distance course was analyzed and generalized. There was systematized the step-by-step instruction of distance course developing in information environment Moodle. The basic elements for placing the educational information with giving examples of resources using in information environment Moodle were directly described: information course resources and interactive course elements. The special attention was given to measures for achieving an educational goal of distance course. There were considered the main characteristics of distance course forming, the structure and features of distance course development based on the electronic platform Moodle. The application of different scales and evaluation strategies in the information environment Moodle were explained. It was given the example of distance course development “English language courses for advanced training” in the information environment Moodle, done by authors, with clear indication of course format, a list of downloaded and used educational materials, the types of used course recourses and interactive course elements were mentioned, and also the system and the evaluation strategies of students’ results were appointed. It was made a conclusion that distance course was just one of the form of student’s self-dependent learning. The authors determined the place of distance course in the process of student’s self-dependent learning. The distinguish role of the teacher for student’s self-dependent learning according to the methodical recommendations for developed distance course was shown. It was proved the necessity of student’s self-dependent learning progress control by the tutor. Key words: self-dependent learning, distance learning, distance course, educational environment Moodle, information course resources, interactive course elements.
Polygonal Approximation Using a Multiresolution Method and a Context-free Grammar

An new method to obtain polygonal approximation for object contours is presented. The method consists of coding the contour with the Angle Freeman chain code (AF8), obtaining strings of eight symbols, and looking for patterns of substrings that represent slope changes along the contour. Our strategy for detecting dominant points is to look for the ends of discrete straight lines through patterns of AF8 symbols, which can be produced by a context-free grammar. With a multiresolution method, we present the polygonal approximation for noisy contours. A set of N dominant points is obtained, the integral square error (ISE) is calculated and, finally, based on lost pixels (LP) in decoding process a new error criterion, that we call lost ratio (LR), is proposed. We found that our method produces the lowest ISE, LP and LR regarding the state-of-the-art.
Constant-time BCH Error-Correcting Code.

Error-correcting codes can be useful in reducing decryption failure rate of several lattice-based and code-based public-key encryption schemes. Two schemes, namely LAC and HQC, in NIST's round 2 phase of its post-quantum cryptography standardisation project use the strong error-correcting BCH code. However, direct application of the BCH code in decryption algorithms of public-key schemes could open new avenues to the attacks. For example, a recent attack [1] exploited non-constant-time execution of BCH code to reduce the security of LAC. In this paper we analyse the BCH error-correcting code, identify computation steps that cause timing variations and design a constant-time BCH implementation. We implement our algorithm in software and evaluate its resistance against timing attacks by performing leakage detection tests. To study the computational overhead of the countermeasures, we integrated our constant-time BCH code in the reference and optimised implementations of the LAC scheme as a case study, and observed nearly 1.1 and 1.4 factor slowdown respectively for the CCA-secure primitives.
Reduced Cycle Spinning Method for the Undecimated Wavelet Transform

The Undecimated Wavelet Transform is commonly used for signal processing due to its advantages over other wavelet techniques, but it is limited for some applications because of its computational cost. One of the methods utilized for the implementation of the Undecimated Wavelet Transform is the one known as Cycle Spinning. This paper introduces an alternative Cycle Spinning implementation method that divides the computational cost by a factor close to 2. This work develops the mathematical background of the proposed method, shows the block diagrams for its implementation and validates the method by applying it to the denoising of ultrasonic signals. The evaluation of the denoising results shows that the new method produces similar denoising qualities than other Cycle Spinning implementations, with a reduced computational cost.
PENERAPAN DATA MINING MENGGUNAKAN METODE TEKNIK CLASSIFICATION UNTUK MELIHAT POTENSI KEPATUHAN WAJIB PAJAK BUMI DAN BANGUNAN

The goverment implements development in Indonesia, requires substantial funds. The entry of cash from the Land and Building Tax is the most important part for the development of a region, with the results that have been obtained by the regional government can increase regional development with various infrastructures that help the community to carry out various activities and make the area more advanced. One type of tax is the Land and Building Tax (PBB). With the increasing number of taxpayers and data paying contributions directly into the treasury of state finances, the UPT BPPD of SU II Subdistrict of Palembang city did not know how many obedient and non-compliant taxpayers. In this study using data mining techniques, namely classification by applying the Naive Bayes algorithm and getting from the number of taxpayers as many as 1,647 taxpayers with an accuracy of 99.33% which has the potential to not be on time in 16 ulu villages at 0,437 and sub-district households with data of 0.229.
NIESR: Nuisance Invariant End-to-end Speech Recognition

Deep neural network models for speech recognition have achieved great success recently, but they can learn incorrect associations between the target and nuisance factors of speech (e.g., speaker identities, background noise, etc.), which can lead to overfitting. While several methods have been proposed to tackle this problem, existing methods incorporate additional information about nuisance factors during training to develop invariant models. However, enumeration of all possible nuisance factors in speech data and the collection of their annotations is difficult and expensive. We present a robust training scheme for end-to-end speech recognition that adopts an unsupervised adversarial invariance induction framework to separate out essential factors for speech-recognition from nuisances without using any supplementary labels besides the transcriptions. Experiments show that the speech recognition model trained with the proposed training scheme achieves relative improvements of 5.48% on WSJ0, 6.16% on CHiME3, and 6.61% on TIMIT dataset over the base model. Additionally, the proposed method achieves a relative improvement of 14.44% on the combined WSJ0+CHiME3 dataset.
The Application of Immersion Model Approach to English Writing Teaching in High School

model is a teaching method to create the language context and use the target language teach directly and let students lost themselves in class. In order to explore whether the teaching approach of Immersion Model can facilitate high school learners' English writing. The author conducted an experiment study in two classes, an experimental class and a control class. The result showed that the achievement of experimental class have made progress compared with the control class. And the students in the experimental class had paid more attention to English writing process and were more motivate to learn. The experiment reveals that Immersion Model is feasible to develop learners’ ability of English writing in the high school.
Agile Exponential Software Organizations

In this Interactive Talk we present concept of exponential organizations and facilitate exponential thinking for agile practitioners. Exponential organizations (ExOs) are organizations whose impact (or output) is disproportionally large --- at least 10x larger --- compared to its peers because of use of new organizational techniques that leverage accelerating technologies. [2, p. 18] (e.g., Google, TED, Uber, Airbnb, Waze, and more, see http://top100.exponentialorgs.com/). ExOs are characterized by ten aspects that are derived from a massive transformative purpose (MTP), which is the higher, aspirational purpose of organization [2, p. 54] (e.g., TED's Ideas worth spreading, Google's Organize world's information). We demonstrate how agile organizations [1] and lean startups1 can use ExO thinking to promote both agility and exponential growth. Attendees gain knowledge on how to integrate 1) agility orientation with exponential thinking, and 2) agile development with ExO aspects. In practice, attendees gain experience with exponential thinking for their agile industrial use cases.
Can a Digitised Version Obtain Copyright Protection Within the EU?

This chapter examines the ability of a digitised version of a rare document recording public domain textual content to qualify for copyright protection within the EU legal framework. It provides a brief overview of the digitisation process, particularly focusing on the nature and extent of human involvement in the creation of a digitised version. It analyses the ability of a digitised version to fulfil the harmonised EU standard of originality (i.e., author’s own intellectual creation standard), as that standard has been interpreted and applied by the Court of Justice of the European Union (CJEU) and the national courts of the United Kingdom (UK), Germany, and France. It further explores the possibility for a digitised version to qualify for copyright protection under the traditional standards of originality that prevail(ed) in these jurisdictions prior to the introduction of the harmonised EU standard.
Natural Language Processing and Text Mining

Web search engines of any kind have to mainly deal with natural language text to carry out their tasks. Therefore, this chapter is dedicated to basic and advanced methods for state-of-the-art natural language processing and text mining. Here, the focus is set on graph-based methods approaches to determine characteristic terms or words in texts and to measure their semantic relatedness. Furthermore, algorithms for the clustering of words and texts are discussed.
Enhancing Medical Imaging Semantic Segmentation Using the Digital Annealer

Deep convolutional neural networks (DCNNs) are demonstrating their strong capability in solving computer vision problems. As for medical imaging semantic segmentation, DCNN models have become one of the most fundamental constituent. However, high-quality semantic segmentation requires pixel-wise prediction with high precision, which usually cannot be achieved only by DCNNs due to their lack of representation of pixel interactions. In this work, we propose a novel method based on conditional random fields (CRFs) and Ising model. It applies the Digital Annealer (DA) as a complement to traditional methods that only employ DCNNs. Our experiment results manifest that the use of DA can enhance the segmentation accuracy on BRATS2012 data set by over 8%. Our work potentially builds a new pathway in this realm.
Advanced security of two factor-authentication system using stego QR-Code

Many financial institutions are trying to protect their customers by offering improved and more secure technologies for authentication. One of the most common is two-factor authentication (2FA), which presents many vulnerabilities that allow attackers to retrieve confidential information such as mobile transaction authentication (mTAN). Thus, according to NIST (National Institute of Standards and Technology), 2FA based on SMS is deprecated and aims to find a secure communication channel other than SMS. Therefore in this paper, we propose a 2FA communication channel based on steganography in the QR-code. So, the mTAN can only be read by a specific scanner that implements the technique of extracting the hidden information while having the shared key and the public information in the QR-code readable by the standard scanners. Finally, we implement our proposed method and then do the test by simulating a line banking service.