Reviewerly/exHarmony huggingface dataset:
Social Network Search Guided by Spherical Evolution

Socia1 network search (SNS) is one of the up-to-date nature-inspired algorithms that modulates optimization behavior by simulating the behavioral and emotional changes of social network users. SNS has proven to be relatively good at handling different types of optimization problems. Spherical search has been one of the more successful search strategies in recent years because it uses a spherical search approach to search a larger solution space and has a good embedding in various algorithms. We propose an improved algorithm SESNS based on these properties, mapping out a better approach and strategy for the hybrid algorithm. To verify the success of this improved algorithm, we choose CEC2017 as the test set and several other metaheuristic algorithms as competitors to demonstrate the effectiveness of our improved method.
Seminar as a Practice of Creating a Philosophical Community: Philosophy of Culture Seminar at the Philosophy Department of Samara University

The article reviews the Philosophy of Culture Seminar (lead by V.A. Konev) as a cultural and philosophical phenomenon. The article discusses the seminar’s research program, its basic scientific principles, as well as the content of books published as a result of the seminar. The Philosophy of Culture Seminar became the basis for the formation of a philosophical community in Samara. Thanks to the constant work of the theoretical seminar, Samara philosophers found themselves in a situation of compulsion to fundamental philosophical practices – reading and discussing philosophical texts, polemics, debates. Reading and discussing the fundamental works of contemporary philosophy has become a good school for many Samara philosophers, allowing them to clarify or redevelop their methodological position. The Philosophy of Culture Seminar in Samara gives us an example of how the existence and development of philosophy is possible not only in Russia but in the whole culture, of how a very rich environment of philosophical communication and living philosophical thought are vital for philosophy.
CNN-based Algorithm for Joint Channel and Phase Noise Estimation in OFDM Relay Systems

In this paper, it is proposed a convolutional neural network (CNN)-based algorithm for joint estimation of the channel and phase noise in orthogonal frequency-division multiplexing (OFDM) relay systems. Due to the time-varying nature of the oscillator phase noise in higher frequency bands, this impairment can no longer be treated as additive white gaussian noise leading to the deterioration in the overall performance of wireless communication systems. Thus, jointly with the channel frequency response, the proposed algorithm infers the intercarrier interference in the received baseband signal introduced by the phase noise of the transmitter and receiver oscillators. The impact of the number of cascaded channels between the source and the destination of the relay system is also studied. The proposed CNN-based approach has the potential to deal with the challenging phase noise problem, which is still an open issue for the cascaded channels. The obtained results show that due to the relevant intercarrier interference mitigation, the CNN-based approach outperforms the least square practical estimation and presents a considerable improvement in the bit error rate (BER). To the best of author’s knowledge, this is the first work that unifies the relay cascaded channel and phase noise estimation in the frequency domain using a CNN-based algorithm.
A Hybrid Feature Selection Method Based on Binary Differential Evolution and Feature Subset Correlation for Microarray Data

Obtaining essential genes from microarray data that can diagnose diseases can be very useful for researchers to understand diseases and develop drugs. However, the high computational cost due to the “curse of dimensionality” and the high redundancy among features limit the application of evolutionary algorithms to the feature selection problem for high-dimensional data. This paper proposes a two-stage hybrid feature selection method to address this problem. In the first stage, a simple and efficient filtering me thod is used to initially filter redundant features, reduce the feature dimensionality, and reduce the search space of the evolutionary algorithm in the second stage. In the second stage, we propose an improved differential evolution algorithm. We redesign the binary quantization of the differential evolution algorithm for the characteristics of microarray data and improve the algorithm’s variation process to balance the algorithm’s search efficiency and accuracy. In addition, we define the redundancy of feature subsets and add it to the fitness function to reduce the redundancy of the final feature subsets. The proposed method is compared with classical feature selection methods and advanced hybrid feature selection methods on eight publicly available microarray data, and the effectiveness and advancement of the proposed method are demonstrated.
Image Feature Enhancement Using Hybrid Superpixel Reconstruction

Feature enhancement is a most fundamental and challenging issue in machine vision. In this article, a feature enhancement method is presented using hybrid superpixel reconstruction. (1) A superpixel concept, called hybrid superpixel, is proposed for over-segmentation. Second, fast feature enhancement (FFE) is developed based on hybrid superpixel, fuzzy optimization and data reconstruction. Extensive experiments are performed, showing that FFE advances the state-of-the-art comparison systems significantly.
Semi-global depth prediction network based on post-processing module

The 3D reconstruction can be used for model making, robot navigation, virtual reality and autonomous pilot. Data sets and algorithms, Stereo matching method based on convolutional network has been widely concerned and achieved great success. Based on the GA-NET, this paper verifies the influence of SGM improved SGA and LGA on stereo matching based on deep learning algorithm. At present, most of the mainstream stereo matching networks use the residual of the output disparity of the simple convolutional network to tune. But, as a matter of fact, ordinary convolution kernel can not reduce various mode errors effectively. Simple convolutional networks sometimes smooth the whole result excessively in order to reduce the mean error. Based on the variable convolutional network and traditional stereo matching algorithm, this paper proposes and adds the Post-Processing Module(PPM), which is used to find effective neighborhood points to update the disparity value, so as to reduce the mismatching rate of stereo matching.
Research on Evaluation and Influencing Factors of Innovation Ability of Undergraduate Students Majoring in Economics

This template explains and demonstrates how to prepare your camera-ready paper for Trans Tech Publications. The best is to read these instructions and follow the outline of this text. Please make the page settings of your word processor to A4 format (21 x 29,7 cm or 8 x 11 inches); with the margins: bottom 1.5 cm (0.59 in) and top 3 cm (1.18 in), right/left margins must be 2 cm (0.78 in). This template explains and demonstrates how to prepare your camera-ready paper for Trans Tech Publications. The best is to read these instructions and follow the outline of this text. Please make the page settings of your word processor to A4 format (21 x 29,7 cm or 8 x 11 inches); with the margins: bottom 1.5 cm (0.59 in) and top 3 cm (1.18 in), right/left margins must be 2 cm (0.78 in). Based on 290 questionnaire survey data, this paper constructs an evaluation index system of innovation capability from three dimensions: innovative practical ability, innovative thinking ability and innovative learning ability, and adopts factor analysis and regression analysis to study the innovation capability and its influencing factors of undergraduate students majoring in economics. This paper finds that: (1) Innovative practical ability is the core element of innovation capability. The number of scientific research projects, the number of academic papers published and the proportion of innovation ability to individual ability are important factors that affect innovative practical ability. In the innovative thinking ability, logical thinking ability is the key factor that affects the innovative ability, while innovative learning ability has little influence on the innovative ability of undergraduates,but it is still an indispensable element in the innovative ability of students. (2) Among the influencing factors of innovation ability, students' comprehensive quality and grade have a significant positive impact on students' innovation ability. (3) Finally, the paper puts forward some policy suggestions to improve the innovation ability of undergraduates from the aspects of strengthening the teaching staff, optimizing the curriculum system and building a platform for practical activities.
Funtional Singature for Large Scale IoT-based Applications

IoT devices are widely used in supply chain management applications to increase production efficiency and data management accuracy. Due to resource scarcity in IoT devices, they delegate tasks to the device's owner that reduce the network's efficiency and security. Due to the large network with multiple communication, devices cannot be allowed unauthorized access and shared data should not be manipulated. We have proposed the functional signature efficiently in the IoT-based supply chain management applications that provide fine-grained access control of data, authentication of devices and integrity of shared data. The function generates every task accordingly requested by users, which includes the required conditions for owners and IoTs. Moreover, the function delegates authorization and verification of data flow. We provide the formal security proof where the scheme is unforgeable against the adaptive chosen message attack using the RoR model. We have implemented and compared the scheme with existing schemes based on computing the communication cost, demonstrating the scheme's efficiency and securing IoT-based supply chain management applications.
From conflict of discourses to military conflict: multimodality of identity construction in Russo-Ukrainian war discourse

This study is an attempt to grasp the discursive nature of Russo-Ukrainian war. The critical discourse analysis of the conflicting ways Russian and Ukrainian identities are constructed in discourse and by discourse can shed light onto the covert reasons of the unprovoked military aggression Russia has been executing against Ukraine. Our assumptions are based on the idea that identity is a manifold of stances taken by individual as well as collective speakers in various situations of communication. Having epistemic and affective dimensions, stances are inherently interactive, and, thus, have a collective or social nature. Generally speaking, conflictual stances, built in war discourse, express national, political, or sociological worldviews of the stance-takers, reflecting their ideologies, values, and beliefs. The way people see the conflict differs according to what "frames" they choose to see it through. In this study, the frames circumscribing Ukrainian and Russian conflictual identities, as they are built in Ukrainian and Russian media discourse, including social media, have been deconstructed and analyzed. As there are diverse semiotic systems that are used to create, transmit and understand meanings (e.g., verbal and non-verbal, written and oral, visual and audial) various modalities employed in the process of discursive construction of these identities were taken into consideration.
Automatically Fixing Breaking Changes of Data Science Libraries

Data science libraries are updated frequently, and new version releases commonly include breaking changes. These are updates that cause existing code to not compile or run. Developers often use older versions of libraries because it is challenging to update the source code of large projects. We propose CombyInferPy, a new tool to automatically analyze and fix breaking changes in library APIs. CombyInferPy infers rules from the history of library source code in the form of Comby templates, a structural code search and replace tool that can automatically transform code. Preliminary results indicate CombyInferPy can update the pandas library Python code. Using the Comby rules inferred by CombyInferPy, we can automatically fix several failing tests and warnings. This shows this approach is promising to help developers update libraries.
A Unified Specification Mining Framework for Smart Contracts

Smart contracts are self-governed computer programs that run on blockchain to facilitate asset transfer between users within a trustless environment. The absence of contract specifications hinders routine tasks, such as program understanding, debugging, testing, and verification of smart contracts. In this work, we propose a unified specification mining framework to infer specification models from past transaction histories. These include access control models describing high-level authorization rules, program invariants capturing low-level program semantics, and behavior models characterizing interaction patterns allowed by contract implementations. The extracted specification models can be used to perform conformance checking on smart contracts, with the goal of eliminating unforeseen contract quality issues.
Inference for Bayesian Nonparametric Models with Binary Response Data via Permutation Counting

Since the beginning of Bayesian nonparametrics in the early 1970s, there has been a wide interest in constructing models for binary response data. Such data arise naturally in problems dealing with bioassay, current status data and sensitivity testing, and are equivalent to left and right censored observations if the inputs are one-dimensional. For models based on the Dirichlet process, inference is possible via Markov chain Monte Carlo (MCMC) simulations. However, there exist multiple processes based on different principles, for which such MCMC-based methods fail. Examples include logistic Gaussian processes and quantile pyramids. These require MCMC for posterior inference given exact observations, and thus become intractable when the data comprise both left and right censored observations. Here we present a new importance sampling algorithm for nonparametric models given exchangeable binary response data. It can be applied to any model from which samples can be generated, or even only approximately generated. The main idea behind the algorithm is to exploit the symmetries introduced by exchangeability. Calculating the importance weights turns out to be equivalent to evaluating the permanent of a certain class of (0,1)-matrix, which we prove can be done in polynomial time by deriving an explicit algorithm.
Cloud Computing in Distance Learning

The advancement in information & communication technologies has led to various new initiatives in the market.Cloud computing is such a new concept that has evolved with the concept of the Internet later which gave birth to cloud computing.Cloud computing is just like hired infrastructure, services and platforms where the user's data, information, files, and applications are stored on remote servers rather storing on local devices or hard drives.It gives relaxation from the tension of storing, caring and backup of the data.So, it makes free the librarians and other staff to have tension about the storing and backup of data and e-resources etc.This paper tells about the distance education and distance learning and possible use of cloud computing in providing distance education.
Proposal for a test plan oriented to Internet of Things projects

This study introduces a test plan oriented to projects based on the Internet of Things (IoT) to support the implementation of quality tests. The above is motivated to verify further and validate technological solutions in this area. This proposed method aims to support the implementation of rigorous quality assurance processes by developing a specific test plan for IoT projects. A mixed methodology based on the waterfall model and Scrum activities was selected to deal between rigorous requirements, quality assurance processes, and agility in new deliverables development through iterations. Besides, activities associated with the perception, network, and application layers of the used architecture for IoT projects were identified. The expert judgment technique was used to validate the relevance of the proposed tests according to the three-layer architecture established for projects based on the Internet of Things. As the main contribution, this work presented a test plan based on the architectural layers needs and the mixed methodology selected for developing projects based on IoT. Two criteria were identified that influence decision-making about recommended tests, considering architecture layers of projects based on the Internet of Things framework.
Conclusion

The demand for data ownership guarantees has been ever-increasing, and keeping data always encrypted in transit, at rest, and in use has become one of the widely agreed principles to safeguard private data in a worry-free manner. Searchable encryption, as a specific line of research along the direction of securing data in use, has made tremendous progress since its first construction was proposed in the early 2000s.
Virtual Object Placement in MR Space Using a 3D Miniature Model of a Room

In this research, we propose a World in Miniature (WIM) -based technique for object placement in MR space. We considered that this would make it possible to freely place objects in 3D space, and to immediately check the position of objects that have been rearranged. In our prototype, we used the mesh of the room provided to represent the occlusion relationship by the MR device to generate a 3D miniature model of the room. We also made it possible to manipulate the virtual objects in the room by manipulating the miniature objects in the miniature model. In order to obtain a guideline for future system design, we conducted an experiment to investigate the characteristics of the manipulation of miniature objects in MR. The results showed that the manipulation of miniature objects in MR is effective in object searching, moving, and reducing physical workload, but that scaling manipulation is difficult. The results also suggest that these effects are affected by the viewing angle and the accuracy of hand tracking of the MR device, and provide guidelines for future system design.
Transformation of authorship in the transition from traditional media to digital

The article deals with the transformation of authorship in the context of changing media epochs, starting from the philosophical concept of Roland Barthes we investigate authorship through the prism of information culture. The author shows that in the late 20th and early 21st centuries there was a radical change in the very understanding of authorship. Its transformation from an elitist activity to the activities of everyday life and even everyday life is evident. The paper analyzes how in the era of total authorship the line between the author as a philosopher and creator, and the author in the linguistic sense, who wrote just a chain of words, is erased.
impact of digitalization on the financial sector

Present-day consumer society increasingly satisfies its needs through digital channels, and financial products and services are no exceptions. The 4th industrial revolution is not only about the penetration of technology, but also the paradigm shift of business processes. The traditional members of the financial sector must adapt to the digitalized world to keep their positions in the market. The penetration of BigTech and FinTech companies influenced the expectations of consumers: customer experience became the main criteria of their decisions. In order to simplify and accelerate processes, banks use the methods of digitalization, and automatize the system to increase client satisfaction. In this article, we will introduce the threebank types based primarily on the usage of innovative technology, the extension and depth of the cooperation with FinTech companies, and the status of a bank’s internal digital transformation. Also, we will introduce the current status of the banking sector evidenced by our SWOT-analysis and mention some of the existing payment solutions.JEL Classification: G21, G23
Language Learning Plateau in the Context of Business English: Emerging Causes and Suggested Solutions by means of Online Tools and Technologies

The paper investigates the problem of the language learning plateau, its impact on the learners of foreign languages, especially Business English (English for Special Purposes) as well as suggested methods to overcome this problem through mutual efforts of learners and educators. Research and works carried out by prominent scientists and educators have been studied and presented in the paper. The paper targets to meet the needs of students studying Business English, who feel that they face the language learning plateau through applying modern and online technologies to envision the efficiency of technology-embedded learning in eliminating the language learning plateau. Evident is the fact that some students face stagnation in their studies, whereas others continue their way toward language proficiency. Our research resulted in the development of the Motivation Matrix and PINE model to address the problem and solve it according to the needs.
Information and communication technologies in teaching professionally-oriented speaking to technical students in non-linguistic higher education institutions

The article discusses the use of information and communication technologies (ICT) in teaching a foreign language to students of technical sciences at non-linguistic universities. Currently, this is the main mechanism aimed at improving the effectiveness of training and aimed at developing motivational potential and an individual approach. ICT significantly intensifies the independent work of students. The paper describes the benefits of using ICT. The authors present the basic types of ICT for the training of highly qualified specialists in the field of political science. The work emphasizes the role of the teacher, who in this situation acts as an active assistant, and his main function is to organize and promote the learning process. The authors also give practical recommendations for improving the effectiveness of teaching a foreign language using ICT. As the advantages of computer programs, the possibility of their flexible use, depending on the features and structure of texts, is emphasized.