Reviewerly/exHarmony huggingface dataset:
Exploring the Convergence of Design, Security, and Human Dynamics in Social Networks in India

This Exploration dives into the complex exchange between social networks, zeroing in on their design, security measures, and the impact of human factors. As social networks keep on molding present day correspondence and connection, understanding their elements turns out to be progressively pivotal. The examination investigates the architecture and user-focused design rules that improve user experiences, encourage community associations, and empower self-expression. All the while, the review tends to the squeezing security challenges presented by these platforms, dissecting risks like identity theft and misinformation dispersal, and proposing techniques for powerful encryption and data protection. Moreover, the review digs into the domain of human behavior and brain research, clarifying how individual inspirations, cognitive biases, and social standards add to content creation, sharing, and commitment inside social networks. The bits of knowledge acquired give a complete perspective on what user activities mean for network elements and the development of online networks. By exploring these aspects, the review expects to illuminate platform developers and policymakers, offering important direction on upgrading design, carrying out powerful security measures, and figuring out user behavior. Eventually, this examination adds to an all-encompassing comprehension of social networks, introducing a diverse investigation of design, security, and human factors. The discoveries guide the advancement of more user-centric, secure, and socially significant social organization platforms that line up with user inclinations and contribute decidedly to the digital landscape.
Exploring the Psychological Dimensions of Mobile-Assisted Language Learning (MALL) in English Language Education

This research investigates the psychological aspects influencing student engagement with Mobile-Assisted Language Learning (MALL) in English language education. The study contributes to a deeper understanding of the role that students' attitudes, personalities, expectations, and motivations play in shaping their learning experiences. The research employs a narrative inquiry approach coupled with semi-structured focus group interviews. A purposive sampling method based on individual factors such as gender, age, and culture was used to select participants from Universitas Borneo Tarakan. The qualitative analysis identified key themes and patterns from the students' narratives about their MALL experiences. The findings reveal that positive attitudes towards MALL, genuine interest in language learning, and high expectations significantly enhance student motivation and active participation in MALL activities. Furthermore, robust institutional support emerged as crucial for the successful implementation of MALL programs. These insights suggest that by understanding these psychological dimensions and ensuring adequate institutional support, educators can improve students' experiences with MALL. It has implications for fostering enhanced engagement and success in language learning.
3D vibration modes estimation of complex-shaped structure by Phase-based motion magnification and DIC method

Knowing the 3D mode shapes of a structure is important in solving unwanted vibration and noise problems in mechanical systems. Accordingly, various analysis methods for estimating the vibration modes of complex-shaped structures have been proposed. However, it is difficult to attach accelerometers to a complex-shaped structure, and to cover a large area, many accelerometers must be attached. So experimental verification of the mode shapes of an actual structure is insufficient. Therefore, the purpose of this study is to experimentally estimate the 3D vibration modes of a complex structure using two cameras by Phase-based image magnification and DIC method. In addition, by using non-contact sensor such as a camera, it is possible to estimate the modes without affecting the mass or stiffness of the structure.
Investigations on relationship between vibration characteristics and shapes of effect cymbals with finite element method

Cymbals are musical instruments consisting of round brass plates in slightly concave shape that are struck against another or struck with a stick to make sounds. Their vibration characteristics depend on the shape of cymbals, therefore, some cymbals have been specially shaped for desired characteristics, as called effect cymbals. Usually, it takes the craftsman numerous retrials in prototyping the effect cymbals to realize the desired characteristics. This leads to a large cost of prototyping effect cymbals. On the other hand, the cost can be significantly reduced if the optimal shape for the desired sound can be estimated in advance. However, to estimate the shape, it is necessary to clarify the relationship between the shape of a certain cymbal and its vibration characteristics. In this paper, we focus on the effect cymbals with holes. Aiming to estimate the optimal hole shape for desired sound, we investigate the relationship between the hole shape of hole effect cymbals and their vibration characteristics based on frequency response analysis by finite element method. We analyzed multiple models with different hole sizes for each cymbal, the analysis results show that the vibration tends to be simpler as the hole size is larger.
Contrast Enhancement of Alzheimer’s MRI using Histogram Analysis

Contrast enhancement of MRI images frequently needs considerable pre-processing to provide accurate data for disease diagnosis and proper treatment. Enhancing the appearance of medical images becomes a difficult task owing to the uncertainty of the obtained image quality. In this study, Alzheimer’s MRI images are subjected to a contrast enhancement algorithm for easy diagnosis. A noise reduction and contrast enhancement technique for MRI images is discussed in this research. Histogram-based algorithms are used to solve the problems of de-noising and enhancing the contrast of images for identification of the infected region. The proposed method is based on contrast-limited adaptive histogram equalization (CLAHE) and the comparison with Histogram Equalization (HE). The suggested enhancement technique's performance can be evaluated using several metrics, including Structure Similarity Index Measure (SSIM), and Peak Signal-to-Noise Ratio (PSNR). Observational studies revealed that the suggested approach is significantly more efficient than the basic enhancement techniques such as HE.
UNDAMENTALS OF INFORMATION AND COMPUTATION IN THE REALM OF THE QUANTA

Information is a physical. Physical systems register and process information. These facts generated enormus interest in the development of novel quantum tecnologies, especially because the construction of smaller electronic devices ultimately leads to a consideration of quantum mechanical effects in electronic and computer desingns. The notion of the classical bit of information theory was formally pushed into the realm of the quanta with the introduction of the quantum bit or qubit, in the seminal works of Deutsch (Deutsch, 1985) and Shor (Shor, 1994). They demostrated that, indeed, controlled multipartite qubit interference effects could provide the means for a radical new way of computing, allowing the computation of many intractable computational problems, such as the factoring of large number or exact simulation of large quantum systems. The field of experimental and theoretical research in quantum information and computation has emerged as very important player in the understanding of quantum phenomena the both the basic and technological levels. This has attracted the attention of numerous researchers with backgrounds ranging from computer science, mathematics and engineerin, to the physical sciences, and we now have an interdisciplinary field where great efforts are being made in order to build devices that allow the progressing of information at a quantum level.&#x0D; A concise introduction to the field of quantum information and quantum computation is presented. This stars with the bassic definitions of bits, quantum registers, through to the universal gate-set for building the universal quantum computer, from a quantum network model of computation. The work shows how two-qubit gates suffice for quantum computation, emphasing the power of the quantum circuit representation for entagling and disentagling quantum states. This leads to the “no-cloning theorem”, which leads us to many interesting applications, such as quantum cryptography. Two alternative approaches or performing quantum computation are also described i) the one-way or measurement based quantum computer method, and ii) holonomic or geometric quantum computation. Following this, quantum entaglement quantification is highlighted, particulary its usefulness as a communication resource, in order to describe some of its most celebrated practical applications to date: quantum teleportation, cryptography, dens coding, and data compression. Deutsch’s concept of quantum parallelism is enphasized in order to gain insight into the potential for efficiently solving certain classically intratable algorithms. A subject central to the field of QIP- quantum decoherence- is then introduced.. Possible ways to overcome it, in particular quantum error correction, are discussed. A descriptios of some of the currently available hardware of the practical implementation of quantum computation is provided with a discussion of the main physical quantum bits that are currently employed (or proposed) for a such a purpose.
Prediction-segmentation tasks for self-supervision of anomaly detection networks under noisy conditions

For detecting anomalies from sounds generated by electronic devices, self-supervised learning of deep neural networks (DNNs) has been popularly employed. In self-supervised learning, a DNN model is trained over normal data to solve some pretext tasks, and test data giving reduced task performance are regarded as anomalies. Popular choices for the pretext task are the reconstruction and the classification tasks, where a model is trained to predict masked parts of the spectrogram and to classify the internal classes of normal data, respectively. However, the reconstruction task is hard to distinguish anomalies from noises in noisy conditions, and the classification task often fails to learn meaningful features when the diversity across internal classes is too small or too evident. We propose a combination of prediction and segmentation tasks to overcome these limitations. For the proposed tasks, two different machine sounds are mixed with a constant ratio, and a model is trained to predict both the mixed spectrogram of future time and mixing ratio based on the present and past sound mixture. We train a WaveNet-based model using dual tasks simultaneously, which shows remarkable performance improvements over the conventional models and achieves state-of-the-art performance on the DCASE 2020 Task 2 dataset.
Optimizing the shapes of concert halls through parametric design

Building acoustic simulation tools have often been used to ensure a room's acoustic performance, but they are rarely used in the early design stage. In this study, an acoustic simulation plug-in of Grasshopper for Rhino, Pachyderm, was combined with parametric design and a multi-objective optimization process to study the acoustic performance of a shoe-box-shaped concert hall in the early design stage. Three different factors of the sound field, sound pressure level A-weighting (SPL(A)), reverberation time (RT), and clarity 80 (C80), were discussed. One of the most famous shoe-box-shaped concert halls, Großer Musikvereinssaal, was selected as the comparison model. Two thousand results were generated through a multi-objective process in 36 hours. Compared with Großer Musikvereinssaal, the Pareto front of the 2000 results showed better performance in various factors of the sound field according to what it optimized.
Singular spectral analysis-based interpolation for missing segments of speech signals extracted from videos captured by dual rolling-shutter cameras

Recent studies have been proposed to extract speech signals from captured videos of objects vibrating by sound waves. Among them, a method for extracting speech signals from videos captured by a rolling-shutter camera, which is widely used, has been attracting attention. A rolling-shutter camera records image data in one row of pixels at a time, thereby capturing the vibration of objects caused by sound waves. However, there are time intervals between frames of the videos, resulting in missing segments in the extracted speech signals. The conventional method uses an autoregressive model to interpolate these missing segments. However, the conventional method ignores the noise in the extracted speech signals, and therefore the noise remains. In this paper, we propose a method to interpolate missing segments based on singular spectrum analysis, which considers the noise to further improve speech quality, by dual rolling-shutter cameras. By using the singular spectral analysis, the missing segments can be determined using only the speech components in the signals, which are related to large singular value, thereby reducing the noise. Experimental results show that the proposed method outperforms the conventional methods in terms of quality and intelligibility of the extracted speech signals.
An experimental investigation of ground board mounted microphones for outdoor noise measurement

This paper reports an experimental investigation on the use of ground board mounted microphones for making outdoor noise measurements. The experiments utilized a 400 mm diameter thin metal ground board into which a probe microphone was flush mounted at a number of different radii. The ground board was placed on the floor of an anechoic chamber and the noise level from a source at a fixed height was measured for a large number of different ground board orientations. These measurements were used to assess the variation in the sound pressure level over the ground board.
Comparative Analysis of Quantum Key Distribution Protocols: Security, Efficiency, and Practicality

Conventional cryptography commonly relies on the complexity of mathematical algorithms and the impractical amount of time required to crack the method, which ensures the strength of security in key distribution. However, if the process for distributing secret keys is inaccurate, it will be unsuccessful. As a recent solution to the key distribution problem, Quantum Key Distribution (QKD) has recently attracted a lot of research interest. QKD is a method for securely distributing encryption keys using the properties of quantum mechanics. There are several different protocols for QKD, each with its own advantages and limitations. In this comparative analysis, the most commonly used QKD protocols, including BB84, B92, E91, and SARG04 are examined and compared. Also, their proposed work, generation rates, and experimental feasibility are analyzed. The future directions and challenges for each of these protocols are discussed in this paper. The goal of this study is to provide a comprehensive understanding of the various QKD protocols and their strengths and weaknesses.
Intelligent Farming based on Uncertainty Expert System with Butterfly Optimization Algorithm for Crop Recommendation

Meeting the current population's food demands has become challenging, given the rising population, frequent climate fluctuations, and limited resources. Smart farming, also known as precision agriculture, has emerged as an advanced approach to tackle modern challenges in crop production. At the heart of this cutting-edge technology is machine learning, serving as the driving force behind its implementation. Though, there are many algorithms are available in crop prediction process, the problem of predicting vague information is still a challenging issue. Unfortunately, existing algorithms mostly avoids the complicated instances in crop recommendation dataset by not handling them effectively, due to imbalance class distribution. Hence in this research work to conduct an intelligent farming, two different uncertain theories are adopted to handle the issue of vagueness in appropriate recommendation of crop by considering soil fertility and climatic condition. The proposed is developed based on uncertainty expert system with both neutrosophicalparaconsistent inference model. The neutrosophic inference model is integrated with the paraconsistent logic to overcome the problem of uncertainty in prediction of appropriate crop by representing the factors in terms of certainty degree and contradiction degree. The rule generated by paraconsistent model is validated to improve the accuracy of crop prediction by fusing the knowledge of butterfly optimization algorithm. The nectar searching behavior of the butterflies are used for searching potential rules as a validation process. With the pruned rules generated by uncertainty expert model, the suitable crop is predicted more accurately compared to the other existing prediction models.
Comparison of conventional and digital lectures and examinations with respect to the conditions after COVID-19 period – an example for a bachelor lecture on textile finishing

Due to the appearance of COVID-19, many lectures and examinations at universities are forced to digital formats. In the first post-pandemic semester again, the change from digital to conventional lectures was demanded. By this background the question arises, what is the better format for lecture and exam – digital or conventional? This question is discussed on the example of a bachelor lecture on textile finishing for the time period from 2019 to 2023. The combination of digital lecture and digital exam leads to strong participation numbers and by this to more successfully passing students. If the exam is done as conventional written text, the influence if the lecture is digital or conventional is weak. Also, the numbers of passing students or the finally achieved mark are mainly not dependent on the type of lecture format. Finally, it can be state that a digital lecture is more successful if there are also digital parts in the examination. Also, the return to conventional lectures and exams after the pandemic period is possible without influencing the student performance compared to pre-pandemic situation.
Социально ориентированные стартапы как перспективное направление студенческого инновационного предпринимательства

The purpose of the article is to offer recommendations for the development of socially oriented student startups in Russian universities based on the results of the author’s original sociological study. The theoretical object of the study is socially oriented startups as a social phenomenon, the empirical object of the study is students of one of the leading economic universities in Russia — the Financial University under the Government of the Russian Federation. The results of in-depth interviews and quantitative research were interpreted. The results of the study showed that students see the commonalities and differences between such key concepts as “entrepreneurship”, “socially oriented entrepreneurship” and “socially responsible business”. A socially-oriented startup, in the students’ opinion, is an enterprise that is created with the goal of solving social problems and improving the well-being of society. Students are interested in creating socially oriented startups, although most of them, by their own self-assessment, do not have a sufficient level of knowledge in the field of socially oriented entrepreneurship. Students are aware of the risks that may arise when creating socially oriented startups. At the same time, students do not have a clear understanding of what the sources of funding for such projects may be, the criteria for assessing their effectiveness, how they differ from socially oriented non-profit organizations (hereinafter referred to as SO NPOs), etc. Respondents are quite pragmatic in their assessment of the opportunities that open up for student startups in the process of interaction with SO NPOs.
On the institutionalization of the education system in modern society. Comparative analysis experience

The article analyzes the problems of functioning and development of the education system, the effectiveness of education in the conditions of increasing demands of society and the state, the tasks of designing a modern system of higher education. Educational organizations are an example of an institutionalized form of education that is embedded in solid socio-economic realities, determining the scope and directions of the proposed transformations and reform visions. The cultural factors characteristic of the societies of individual countries also influence, certain non-pedagogical criteria are determined that determine the prospects for the development of education on a national and international scale. The importance of civil society in the formation of priorities and directions for the development of reforms in the education system is stated, attention is focused on the continuity and evolution of education and upbringing. The necessity of research on the experience of non-state corporate universities and pedagogical theories relevant to the tasks of improving the education system is substantiated.
150 Anniversary of the Opening of Real School in Chișinău: Following an Educational Tour in Iași

The dialogue with Alla Ceastina, who’s the doctor in the study of arts, senior scientific researcher, focuses on an interesting document discovered in the National Archives Agency of the Republic of Moldova, which provides information about the trip of a group consisting of 25 students and 4 teachers from the Real School for the boys travelling from Chișinău to the Romanian city of Iași, which took place at 4 and 5 October 1909. Today it is particularly interesting to follow in the footsteps of this excursion, surprisingly rich in historical facts, to visit architectural monuments such as: the Church of the Three Holy Hierarchs, the Metropolitan Cathedral, the Saint Nicholas Church, the university, the theater, etc. Such a trip to Iași city remains relevant and can present the basis of a modern exciting tourist route for any guide. It’s known that the Real School for the boys of Chișinău opened on December 6, 1873, and its purpose was the development of practical and technical skills with the completion of general education. So, this year we celebrate 150 years since its establishment, it’s an additional reason to remember this institution.