Reviewerly/exHarmony huggingface dataset:
Brute Force Attack on Distributed data Hiding in the Multi-Cloud Storage Environment More Diminutive than the Exponential Computations

Classical steganography is designed to hide data by cover media. Recent approaches fragmented the data and hide them in a distributed manner by embedding each fragmented data into a distinct cover media. This approach makes a secret message extremely difficult for an attacker to detect. However, cover media modification leaves fingerprints that could expose a secret channel to an attacker. To overcome the problem, a novel steganography concept designed by two technical contributions. I). cover media does not undergo any modification, i.e., the cover media act as a pointer to fragmented data. II). A secret message is stored in the multi-cloud storage environment. The approach claimed that it is computationally infeasible for an attacker to detect and extract the hidden message despite of having fully access to the accounts of the different clouds. In this paper, we analysed the security strength of the novel steganography concept and concluded that, attacker can get the secret value stored in multi-cloud storage environment using the brute force attacks more diminutive than exponential computations.
Marketing Strategies and Export Risks of Russian Higher Education in Conditions of Geopolitical Instability

The article describes the problem of export promotion of Russian higher education in the context of geopolitical instability. It is assumed that the reasonable use of marketing tools, the development and implementation of a marketing strategy, has a positive impact on the formation of the brand of an educational institution in the international market. The goals outlined in the study require theoretical substantiation and development of recommendations for competitiveness improvement of Russian higher education institutions. The authors analyzed the “client path” in the digital environment, the process of interaction in the Internet of a potential student at the points of contact with the university, as well as the factors affecting the public image of the university, the satisfaction of consumers of educational services in the field of higher professional education. The relevance of this approach is due not only to the digital transformation of the higher education system, but also to the internationalization of educational services. It was found that content marketing and a website are becoming a key success factor in positioning a university in the international market of educational services, starting with the Internet resources and ending with online interaction with potential students. The phenomenon of brand disloyalty is described; the “country effect” and the risks associated with the moral avoidance of Russian universities’ brands by foreign applicants are analyzed. The practical application of strategies for overcoming brand disloyalty is discussed - brand transformation, diversification, avoidance, brand strengthening and reputation restoration. Geographically promising segments for the promotion of higher education are suggested; options for digital marketing and relationship marketing to promote university education, along with the role of corporate culture and multicultural diversity are shown.
An Approximate Optimization Method for Solving Stiff Ordinary Differential Equations With Combinational Mutation Strategy of Differential Evolution Algorithm

This paper examines the implementation of simple combination mutation of differential evolution algorithm for solving stiff ordinary differential equations. We use the weighted residual method with a series expansion to approximate the solutions of stiff ordinary differential equations. We solve the problems from an ordinary stiff differential equation for linear and nonlinear problems. Then, we also implement our method for solving stiff systems of ordinary differential equations. We find that our algorithm can approximate the exact solution of a stiff ordinary differential equation with the smallest error for each length of series that we have chosen. Thus, this approximation method, by using the optimization method of simple combination differential evolution, can be a good tool for solving stiff ordinary differential equations.
Evaluate Database Management System Quality By Analytic Hierarchy Process (AHP) and Simple Additive Weighting (SAW) Methodolog

Any organization that intends to use component-based software development, like outsourcing software, must first evaluate existing components against system requirements to find the best fit among many alternatives. As a result, there should be a mechanism to help with decision-making. Our proposed methodology tries to select the best alternative among available components, using the best decision-making approach. As an integrated method for order preference, the methodology in this paper uses two well-known criterion decision-making procedures, namely Analytic Hierarchy Process (AHP) and Simple Additive Weighting (SAW). By analyzing and selecting the optimal solution among a variety of Out Sourcing (OS) modules, the new model design makes the decision-making process easier. We evaluated two software attributes and predicted which was more effective. In this case, the advantage of utilizing AHP is that it allows the developer to evaluate the structure of the OS selection problem and calculate weights for the chosen criteria. After that, the SAW technique is used to calculate the alternatives ratings for OS components. The integration strategy used in our model and the resulting preference indication, which is produced as an explicit numeric value.
Explanation and Speedup Comparison of Advanced Path-planning Algorithms Presented on Two-dimensional Grid

Path planning or network route planning problems are an important issue in AI, robotics, or computer games. Appropriate implementation and knowledge of advanced and classical path-planning algorithms can be important for both autonomous navigation systems and computer games. In this paper, we compare advanced path planning algorithms implemented on a two-dimensional grid. Advanced path planning algorithms, including pseudocode, are introduced. The experiments were performed in the Python environment, thus with a significant performance margin over C++ or Rust implementations. The main focus is on the speedup of the algorithms compared to a baseline method, which was chosen to be the well-known Dijkstra's algorithm. All experiments correspond to trajectories on a two-dimensional grid, with variously defined constraints. The motion from each node corresponds to a Moore neighborhood, i.e., it is possible in eight directions. In this paper, three well-known path planning algorithms are described and compared: the Dijkstra, A* and A* /w Bounding Box. And two advanced methods are included, namely Jump Point Search (JPS), incorporated with the Bounding Box variant (JPS+BB), and Simple Subgoal (SS). These advanced methods clearly show their advantage in the context of the speed up of solution time.
GrFrauder: A Novel Unsupervised Clustering Algorithm for Identification Group Spam Reviewers

As e-commerce has expanded, people's lives now include some aspect of online buying, because buyers frequently use online product reviews to make purchasing decisions.Merchants frequently collaborate with review spammers to write spam reviews that promote or demote selected items.Spammers who work in groups, in particular, are more dangerous than individual attacks.Previous studies provided various frequent item mining and graphbased techniques to detect such spammer groups.In this paper, we recommend a technique referred to as GrFrauder (Group Fraud detection) method to detect online spam reviewer groups with an unsupervised manner.Our technology identifies spammer candidate groups initially based on product -product review graph and collaboration among reviewers constructed with several behavioral patterns.It then embeds reviewers into an embedding space and calculates spam score for every group; with higher spam scores the model generates ranks for each group.Studies using four real-world datasets reveal that GrFrauder outperforms numerous state-of-the-art baselines in terms of precision and is able to identify more high-quality spammer groups.
Localization features of pyrite-polymetallic oresof the Tushkanikhinskoye deposit (Rudny Altai)

The Tushkanikhinskoye deposit is confined to the Devonian basalt-bearing rhyolite calcareous-siliceousterrigenous formation, which is represented by sedimentary, volcano-sedimentary, sedimentary-volcanogenic, pyroclastic, volcanic rocks of felsic and basic composition, as well as their subvolcanic equivalents. Felsic volcanogenic rocks show signs of ignimbrites. Primary pyrite-polymetallic ores with an uneven distribution of the main sulfi sphalerite, pyrite, galena, and chalcopyrite have been identified. The presence of collomorphic, framboidal and granoblastic pyrite in the ores, as well as the presence of sedimentary breccia ores with sulfi in clasts and matrix advocates for the hydrothermal-sedimentary origin of the ores. The ore bodies represent destroyed hydrothermal structures, so-called "ore hills".
CRITICAL DISCOURSE ANALYSIS OF POLITICAL SLOGANS OF MAJOR PAKISTANI POLITICAL PARTIES IN ELECTION

Political slogans are used as a conduit to disseminate one’s political ideology into masses’ conscious and unconscious and to deconstruct the narrative of the opposition. This research is focused on the slogans which were chanted during the election 2018 keeping in mind the narratives of the respective political parties. The rapport of language with narrative and ideologies is intricate and influences the political power structure substantially. Words contain and shape meanings and the exploitation and distortion of the essence of the meaning can only be understood through CDA, furthermore, the use of lexical choices effects the voting pattern as well. This research is qualitative in nature, where the three-dimensional discourse model of Fairclough and socio cognitive model of Van Dijk have been used as a theoretical framework to comprehend the intricate relationship of language, power and ideology. To linguistically analyze the slogans the Systemic Functional Linguistic (SFL) analysis which is developed by M.A.K Halliday, with specific focus on Lexicalization (Roger Fowler) has proved very instrumental. This research and analysis help the reader to comprehend the role of lexical choices, syntactic structures and metaphorization in constructing a narrative and its subsequent clout over the political power structure. Also, the significance of building one’s narrative and deconstructing opponents’ narrative through a slogan at the same time
Efficient Lattice based (H)IB-DRE

In CCS'04, Diament etc al. presented special kind of public key encryption called Dual Receiver Encryption (DRE).In DRE, sender encrypts the plaintext using public keys of two independent receivers.Both independent receivers can decrypt the ciphertext into the same plaintext using their own private keys.This new cryptography primitive has applications in construction of complete nonmalleability and plaintext-awareness public key encryption, for a secure management of data that is to be disseminated to distributed processors, for ubiquitous and mobile computing applications.Daode Zhang et.al. constructed lattice-based IB-DRE scheme which is secure against stronger security notion i.e. adaptive-ID.We present hierarchical identity based dual encryption (HIB-DRE) scheme under LWE assumption.To the best of our knowledge, this gives the first provably secure HIB-DRE scheme in the lattice based setting.Independent work by Naccache[1] and Chatterjee -Sarkar[2] presented a variant of Waters's identity based encryption scheme to reduce Public Parameters.They have considered an identity of l-bits as l chunks where size of each chunk is l/l .This reduces the Public Parameter (PP) size from l to l n × m matrices.This idea was named as blocking technique [3].We have used blocking technique to reduce the size of PP.Daode Zhang et.al.[4] presented adaptive secure IB-DRE scheme.This scheme[4] contains l + 1, n × m matrices as PPs, where l denotes the number of the bits in identity.Using blocking technique we have reduced the size of PP by around factor β .Because of this the size of prime number q in field Z q is increased by 2 β which results in increase in computation cost.We have shown that compared to Daode Zhang et.al.scheme the size of the PP can be decreased approximately by 80% and the time complexity is increased by only 1.40% for a suitably chosen β .
UNDERSTANDING OF ELECTRONIC EVIDENCE, ITS ACQUISITION AND STRENGTHENING IN CRIMINAL PROCEEDINGS

Criminal investigations now face a new reality at the outset of criminal investigations. It involves the gathering of evidence, which has become more different than in previous decades. In line with the information and technology age, criminal investigations are increasingly finding that a large proportion of criminal offenses and criminal offenses are based on electronic evidence. The taking and consolidation of electronic evidence must take place in such a way that it can also be subject to existing general principles of law.
Breast Tumor Detection using Machine Learning Boosting Classifiers

Breast cancer is the frequently found in women and the second greatest reason of death worldwide. As breast cancer is detected early, the ratio of survival rate increases because better therapy may be provided. ML algorithms are very vital in the early diagnosis of breast cancer. In this study, we purposed a Novel method that increases the accuracy and performance using these three different classifiers: Gradient Boost (GB), Ada Boost (ABC), and Extreme Gradient Boost (XGB). On the Public dataset WBC, we evaluated and compared the classifiers’ performance and accuracy. Because the chance of examples belonging to the majority of the class is relatively high, algorithms are far more likely to categorize new observations into the majority class in the classification phase. We address such a situation that True positive, false positive, precision, recall, F1 score, and accuracy are all used to evaluate the efficiency of each classifier. Experiments demonstrate that utilizing a boosting classifier improves the performance, with the Gradient Booster (GB) outperforming others in the WBC dataset.
Трагедия И.В. Гете «Фауст»: от образа к символу

The problem of the symbolic in the context of modern humanitarian knowledge occupies a special place in connection with the statement of the dialogue of cultures and eras and the need to determine the origins of interpretation. The article presents an analysis of the image of Faust and the theme of love from the position of the theory of the symbol. It is argued that, going beyond the boundaries of the part of the tragedy of J. W. Goethe, the image of Faust becomes something that in its meaning approaches the symbol. This phenomenon is accompanied by transformation into other specific incarnations and refraction of worldview constructs. The paper discusses the features of the theory of the symbol of Russian researchers of the twentieth century: A. F. Losev, Y. M. Lotman, S. S. Averintsev. The interpretation of the theme of love is based on the philosophical views of V. S. Solovyov. It is concluded that both a work of art, its episode, and an image can be fully covered only through the theory of symbol.
Discussion and Practice of Online and Offline Mixed Teaching of Track and Field Course Based on OBE Concept

The emergence of the “Internet plus education” program has provided an opportunity. In recent years, the government has issued relevant documents in succession, so as to create a new mode of training talents that is suitable for the times and share high-quality educational resources. Especially during the epidemic period of New Coronavirus pneumonia, the online and offline teaching mode plays a vital role in the teaching process of colleges and universities. However, the development of online and offline hybrid teaching is not perfect, which needs further research and continuous improvement by scholars. In response to the implementation of the national “Internet plus education” program, reforming the traditional physical education teaching mode, improving the learning efficiency of students and promoting the development of students’ personality, this paper, based on the OBE concept, takes the construction of online and offline blended teaching mode in track and field as the research object. Through the investigation and analysis of the current situation of traditional physical education teaching and the feasibility of online and offline mixed teaching mode of track and field course, this paper provides a basis for the construction and application strategy of online and offline mixed teaching mode of track and field course.
Power enterprises-oriented carbon footprint verification system using edge computing and blockchain

The purpose is to study the Carbon Footprint (CF) verification system of power enterprises, promote the Low-Carbon Economy (LCE) in the power industry, and improve resource utilization during Energy Conservation and Emission Reduction (ECER). The Carbon Dioxide Emission (CDE) of power enterprises is explored based on the CF. First, Edge Computing (EC) is adopted to calculate the direct Carbon Dioxide Emission (CDE) of the Chinese power industry from 2005 to 2020 based on energy input. The direct CDE and the changing trend are analyzed. On this basis, Blockchain Technology (BCT) is employed to quantify the indirect CDEs of power enterprises’ energy consumption. A comprehensive analysis is made of the changing trend and circulation of the total CF of power enterprises based on the direct and indirect CDEs. The data show that the proportion of direct and indirect CDEs in total CF gradually decreases and increases. The results show that the power industry should increase the proportion of clean power in the power industry, control the CDEs from the source, and improve energy utilization to optimize the CF verification.
Developing Mystery Box in Teaching Narrative Text for Speaking Class at Junior High School

This research aims to develop a Mystery Box for teaching speaking in narrative text for junior high school students. To improve speaking skills students often face several problems such as lack of confidence when speaking in a foreign language. The main purpose of this research is to help students improve students' speaking skills gradually during teaching and learning activities in the classroom. This study uses Research and Development (R&amp;D) model from Thiagarajan or commonly known as 4D (Four-D). The stage is Define, which is a definition that includes observation and analysis of student needs, then Design which includes product design formats and material selection, then Develop includes product design, validation by experts, revisions, and small-scale to large-scale experiments, the last is Disseminate, namely dissemination product form is a Guidebook. Observation data, interviews, and questionnaires for students used qualitative while the expert validator questionnaires and students' speaking scores used quantitative. There were two experts who tested this product and the participating students were class IX G, IX H, and IX I. The result of the analyzing all the data, according to the experts Mystery Box categorized was very good and most of the students felt enthusiastic in the class. It can be concluded that the Mystery Box is a learning media for helping students to improve students’ speaking skills.
Developing “Reverb English” Textbooks for Kindergarten Students: Is It Effective?

English is one of the foreign languages taught in Indonesia. It has separated curriculum from other subjects which are taught in primary, secondary, and high schools by using English textbooks. However, English textbooks are limited to be developed in Kindergarten area. Therefore, this research conducted and aimed to develop adequate English textbooks based on Kindergarten syllabus which are annual and semester programs by the school. The researcher took the group A and B learners of Kindergarten students at TK Negeri Pembina 1 Malang year 2021/2022. The researcher involved 70 students as the participants. Research and Development (R&amp;D) was conducted in this research with the ADDIE model. The instruments of the research were observation and interviews both teacher and students. The data analysis was obtained from the expert validation checklist also the transcription of the result from the interview with both teachers and students. Findings indicate that “Reverb English” textbooks are feasible and effective during the English teaching-learning process in the classroom for kindergarten students. It can help them to learn faster by visualizing the pictures and words in the book.
Research on news text classification based on RCNN

One of the popular directions of natural language processing is text processing, which is an effective method used to manage data, and it has developed rapidly after the rise of artificial intelligence. However, text classification based on traditional machine learning algorithms encountered bottlenecks in the development process, and after deep learning, a multi-level neural network, was introduced, it was soon widely used in natural language processing problems, making many branches of the field develop further, and now deep learning is the mainstream model in the field of text classification. In this paper, we first introduce the general process of text classification, point out the current problems of text classification based on traditional machine learning, and then describe the superiority of deep learning in this aspect of feature extraction. After that, three different deep learning models are experimented, and the differences between the trained models are compared and the relative optimal models are derived. Finally, the future trends and research directions of deep learning in this field are discussed.
Research on Interactive System of Movie Subtitle Speech Based on Machine Learning Technology

The composition elements of subtitles, from the early single text, have developed into the present text, graphics, colors, animation, special effects and other combinations. With the development of speech technology and natural language understanding, speech interaction system has become a hot research field. Different from the traditional data interaction between keyboard, mouse and display, using hearing to transmit data makes the interactive system of movie subtitles more anthropomorphic and intelligent. It is the most natural and convenient means for human beings to exchange information with intelligent systems by incorporating machines and equipment with voice information processing capabilities into human voice interactive objects and endowing movie subtitle interactive systems with biological language recognition functions. A machine learning-based movie subtitle voice interactive system is constructed, which can well expand the application of voice interactive system and improve the user experience. In this paper, a movie subtitle voice interactive system based on machine learning technology is proposed, so as to better and effectively realize human-computer voice interaction.