Reviewerly/exHarmony huggingface dataset:
Classification Vowel-Consonant Letters with Deep Neural Networks in Turkish and Text-Voice Synchronization on a Basis Syllable Size

In the study, a syllable-scale synchronization study was carried out by considering the grammatical structure of Turkish to emphasize simultaneously the sound and the text. Therefore, it was aimed to classify the vowels and consonants in Turkish within the word. For this purpose, two different Artificial Neural Network (ANN) models were preferred for this classification, and also the Mel-Frequency Cepstrum Coefficients method was preferred for extracting features of voice data. It has been observed that ANNs give the best results with deep learning. Tests were made with different numbers of coefficients in feature extraction. In the first stage of this study, a certain number of recordings were taken from the vowels and consonants in Turkish. Then, their feature was extracted and prepared for the training of networks. The best network structure and parameters were selected as a result of training and test made with different parameters. In this training, networks were asked to distinguish vowels from consonants. Afterward, the vowel-consonant distinction was made among 10 predetermined vectors of words and phrases. Layer-recurrent Neural Network and Pattern Recognition Network achieved an average success of 97.43% and 98.04%, respectively, in deep learning training carried out through the Mathworks Matlab software. Because Pattern Recognition Network achieved 98.82% success in recognizing vowels and 97.27% in recognizing consonants, this network model was preferred in vowel-consonant classification. After the classification process, timing files were created by determining the transition times of the vowels in the word. In the last step, an interface was created on the C# .NET platform for the synchronization process, and a syllabic algorithm was developed in this interface to emphasize the syllable synchronization of the text. Thus, the desired high precision was achieved in the simultaneous highlighting of the words.
DECOHERENCE-FREE STORAGE INFORMATION SPACE

Quantum systems are of great interest in current realities. Quantum computers are not an alternative to the classic. Rather, they can be attributed to the class of devices specializing in a separate group of tasks. However, a key issue in the design of quantum computers is the issue of decoherence time. To combat that phenomenon, various methods of isolating a quantum system are being developed, including the use of extremely low temperatures and high vacuum. In addition, one of the ways to combat decoherence is to use dark states, due to the fact that a system of atoms in this state is not able to interact with light – absorb or emit photons. In this paper, various systems of three-level atoms are considered. Schemes of two types of atoms are represented graphically – λ-atoms, v-atoms. The concept of a dark quantum state and the concept of a family of a quantum state are introduced. An algorithm for finding the dimension and basis of the subspace of dark states is presented. According to the algorithm, the dimensions and bases of the subspaces of dark states in these systems are calculated.
Privacy Preserving Data Mining Using Random Decision Tree Over Partition Data: Survey

The development of data mining with data protection and data utility can manage distributed data efficiently. This paper revisits the concepts and techniques of privacy-preserving Random Decision Tree (RDT). In existing systems, cryptography-based techniques are effective at managing distributed information. Privacy-preserving RDT handles distributed information efficiently. Privacy-preserving RDT gives better precision data mining while preserving information and reducing the calculation time. This paper deals with this headway in privacy-preserving data mining technology utilizing emphasized approach of RDT. RDT gives preferable productivity and information privacy than cryptographic technique. Various data mining tasks utilize RDT, like classification, relapse, ranking, and different classifications. Privacy-preserving RDT utilizes both randomization and the cryptographic method, giving information privacy for some decision tree-based learning tasks; this is an effective technique for data mining with privacy-preserving distributed information. Thus, in horizontal partitioning of the dataset, parties gather information for various entities but have data for all attributes. On the other hand, various associations may gather different data about a similar set of people. Thus, in vertically partitioned data, all parties gather data for the same collection of items. In all of these cases, both horizontal and vertical partitioning of datasets is somewhat inaccurate.
Person Identification Based on Accelerations on Drawing Figures with a Smartphone

Several methods to estimate the user who is holding a smartphone by analyzing the acceleration obtained from the smartphone's accelerometer using deep learning have been proposed. However, these methods have some issues such as insufficient accuracy or the need for the user to hold a smartphone for a long time. In this paper, we discuss the estimation of the user based on acceleration measured in a shorter aperiod of time. We propose a method to identify a user by make a user draw a figure in the air. The proposed method is based on the assumption that a user is estimated from users given in advance. Acceleration data of all users is acquired in advance, and learning is performed by deep learning using these acceleration data to create a model for estimation. The acceleration data measured for identification are analyzed using this model, and the user who is holding the smartphone is idenfitied. We evaluated the proposed method using two networks, LSTM and DeepConvLSTM, and showed that the proposed method can identify the user with high accuracy. In particular, the accuracy of the method using DeepConvLSTM is high.
<i>Introductory Physics, A Model Approach by Robert Karplus (1969, revised and edited by Fernand Brunschwig, 2006) with a Teacher’s Guide</i>

First Page
Testing Deep Neural Networks for Classification Tasks Through Adversarial Perturbations on Test Datasets

Deep learning models often provide high accuracy on test datasets. However, sometimes, changes in the real-world distribution of the data in production may result in incorrect functioning. Such problems have motivated research in the safety and security-critical systems domains. In this research study, we test CNN models for the vehicle type classification from the AIT VISION Lab. The current vehicle type model is a GoogLeNet model trained on the task of classifying an input image as a car, van, bus, truck, or pickup truck. We used FGSM to adversarially perturb the GoogLeNet model to identify error cases. To make the mode testing approach more useful in a software development context, we developed a method to include adversarial testing of models in continuous integration (CI) framework. The method used a plugin for Jenkins open source CI framework to visualize results. With the plugin, we can visualize the build logs for standard and adversarially trained classifiers. This method can help the software engineering team to analyze the performance of the model. With this method, any kind of dataset can be used to generate adversarial examples, enabling us to detect model degradation and improve their expected error behavior under unexpected circumstances.
Formation of Professional and Personal Qualities of Future Elementary-school Teachers by Means of Pedagogical Metaphor

By compiling the fundamental psychological and pedagogical scientific works of famous researchers, an expert survey of the subjects of the educational process, a system of professional and personal qualities of an elementary-school teacher is highlighted, a brief description of them is provided, and the dominant professionally significant quality is determined – love for children. The essence, types, potential, properties of a pedagogical metaphor as an effective means of forming the professional and personal qualities of a future elementary-school teacher, its multifunctionality in the process of professional training are solved. The effectiveness of the method of using a pedagogical metaphor in the form of a piece of art (a philosophical tale, parable, story, poetic work, myth, popular expressions of famous people, maxims, paintings, etc.) is proved. Examples of the use of the pedagogical metaphor in the process of teaching pedagogical disciplines are given in order to form a tolerant, humanistic attitude towards a particular child, children's collective, parents and work colleagues among future elementary-school teachers.
On Social Experience, Prevention Consciousness and Network Fraud of College Students in Finance and Economics Based on Survey Data

With the development of the Internet, college students suffer from network fraud in many layers, which has aroused widespread concern in the society. Based on the questionnaire survey data of the current situation of college students suffering from online fraud in financial and economic colleges, this paper uses structural equation model to analyze the relationship between social experience, prevention awareness and college students suffering from online fraud. The study found that: (1) social experience not only has a significant direct effect on college students suffering from online fraud, but also has an indirect impact on college students suffering from online fraud through the pursuit of economic independence. (2) Prevention awareness has no significant direct effect on college students suffering from online fraud. Personal information protection plays a complete intermediary role between prevention awareness and college students suffering from online fraud. Based on the research results, it is proposed to strengthen the ideological and political education of college students, improve the awareness of risk prevention, build a long-term mechanism and link the comprehensive management of departments to prevent college students from suffering from online fraud and promote the healthy growth of college students.
Head and Gaze Orientation in Hemispheric Image Viewing

Head mounted displays provide a good platform for viewing of immersive 360° or hemispheric images. A person can observe an image all around, just by turning his/her head and looking at different directions. The device also provides a highly useful tool for studying the observer’s gaze directions and head turns. We aimed to explore the interplay between participant’s head and gaze directions and collected head and gaze orientation data while participants were asked to view and study hemispheric images. In this exploration paper we show combined visualizations of both the head and gaze orientations and present two preliminary models of the relation between the gaze and the head orientations. We also show results of an analysis of the gaze and head behavior in relation to the given task/question.
IMPLEMENTASI TEKNIK KRIPTOGRAFI VISUAL PADA CITRA KEABUAN DAN BERWARNA UNTUK OTENTIKASI PENGGUNA PADA TRANSAKSI ONLINE

Visual cryptography (VC) technique encodes an image into two or more shares that appear random in human eyes. In the decryption section, the pixels in the shared images are combined to obtain the information contained in the original image. This study applies visual cryptographic techniques to graysle and color images for user authentication in online transactions using the VC2,2 scheme. The server computer encodes the CAPTCHA image into two shared images that are sent to the user through different channels or applications. To authenticate himself, the user performs an XOR operation on both share images, identifies the information contained in the CAPTCHA and sends it to the server. In encryption test, histogram of the share image has a different pattern from the original image. The description test shows the decrypted image in this study visually has a better quality than the binary image has better quality than binary images.
National Standard Research in Universities

National Research Standards are the minimum criteria regarding the research system in universities that apply in all jurisdictions of the Unitary State of the Republic of Indonesia (NKRI) National Standards. This research also has several scopes and objectives that can be achieved by universities. In addition, a quality assurance system for higher education is needed, research-based learning and how to build a research culture in universities.
Apply Paraphrase Generation for Finding and Ranking Similar News Headlines in Punjabi Language

Paraphrase generation is an important task in Natural Language Processing (NLP) and is successfully applied in various applications such as question-answering, information retrieval & extraction, text summarization and augmentation of machine translation training data.A lot of research has been carried out on paraphrase generation but it is missing to apply it for finding similar news headlines.However, no approach is available for finding similar news headlines by using paraphrase generation in Punjabi Language.Hence, this paper presents an approach for finding similar news headlines by applying a paraphrase generation system to plug in the gap.Similar news is being detected by comparing the sentence vectors of news headlines.The input headline is compared with all available headlines using a combination of cosine and Jaccard similarity to find similar headlines.The detected news headlines are then ranked by comparing them with the given headline.To represent news headlines as sentence embeddings, RNN based Seq2Seq with different hyper-parameter settings and attention mechanisms is used.The direct method can restrict the process, so the proposed approach has applied a paraphrase generation system to rephrase the given headline for finding more relevant news headlines.To generate a paraphrase of the given headline, the current state-ofthe-art transformer with an augmented encoder is being used as transformers can learn long-term dependencies.The effect of Jaccard and cosine similarity has also been tested along with the combination of both metrics but the combination of Jaccard and cosine similarity performs better for finding similar headlines.The news headlines extracted from four newspapers have been used for evaluation in this article.Further, different evaluation metrics have been applied for in-depth comparisons, the BLEU score has been calculated between detected and input headlines.Another evaluation is done by comparing embeddings of the detected headlines and inputs along with human judgements.The generation of sentence vectors further enhanced the evaluation measure and showing that the proposed approach produced state-of-the-art results.
Rancang Bangun Aplikasi Pembelajaran Bahasa Arab Untuk Siswa Madrasah Ibtidaiyah Berbasis Android

With the increasingly open mindset of society today, especially Indonesia, it makes it easy for us to accept new things and implement them in our lives, these new things appear in many aspects such as one of which is education. In terms of education, it is better if it is carried out at an early age, especially in terms of learning a second foreign language or a foreign language substituting for English, this is what elementary school teachers have realized and has begun to be implemented recently, to do this elementary schools need tools to create methods. this learning becomes effective. Therefore the authors make an Arabic learning application that will make it easier for elementary school teachers to effectively introduce basic Arabic such as the recognition of the names of the day for elementary school children, which is equipped with sounds and images that can attract children's interests. This application can be run on an Android smartphone with a minimum Android OS 5.0 (Lollipop) and a maximum Android OS is 8.1 (Oreo).
Optimized scheduling of scientific workflows based on iterated local search

&lt;span&gt;Recent years have witnessed a great interest in scientific applications with large data and processing-intensive, so cloud computing is used which provides the resources needed to implement and run these applications. One of the challenges in the management of scientific workflow applications is scheduling them to solve many combinatorial optimization problems, including reducing execution time, cost, resource utilization, and energy &lt;span&gt;consumption. Due to the fact that the iterated local search algorithm (ILS) has been successfully applied to solve many combinatorial optimization problems, this paper investigates the performance of ILS in solving the scientific workflow scheduling problem which is a highly constrained problem. The main components that are different from one problem to others are the ILS parameters, local search, and perturbation, which must be&lt;/span&gt; &lt;span&gt;carefully designed. The performance of the standard ILS has been examined and compared with the latest technology. The experimental results show that the proposed algorithm (ILS) obtained good results compared to the best-known results in the literature. This is due to the ILS being an adaptable metaheuristic, which can be simply adapted to diﬀerent search situations and instances.&lt;/span&gt;&lt;/span&gt;
Peningkatan Kemampuan Kognitif Mengklasifikasi Benda Melalui Aktivitas Bermain Dengan Media Alam Di Rumah Pada Masa Pandemi Covid 19 Pada Peserta Didik Kelompok A Tk Marsudi Ilmi Cabak Kecamatan Tlogowungu Kabupaten Pati

This research is a study on increasing cognitive ability to classify objects through playing activities with natural media at home during the Covid 19 pandemic. The background of this research is that students' ability to classify objects is still low. It is evident from the 15 children, only 4 students or 26.67% are included in the BSB and BSH categories. The purpose of this study is to prove that the use of playing activities with natural media at home can improve cognitive ability to classify objects during the Covid 19 Pandemic Period in Group A Students of Marsudi Ilmi Cabak Kindergarten, Tlogowungu District, Pati Regency. This research belongs to the type of Classroom Action Research. The action plan consists of two cycles, namely: cycle I, and cycle II with each cycle having two meetings, with each cycle consisting of four stages, namely: planning, implementing actions, observing and reflecting. The subjects studied were 15 children in group A of Marsudi Ilmi Tlogowungu Pati Kindergarten, consisting of 7 boys and 8 girls. Data collection techniques include observation, interviews and documentation. While the data analysis techniques include: qualitative analysis and comparative analysis by calculating the percentage of children's cognitive abilities which are then compared to the percentage of completeness pre-cycle, cycle I, and cycle II. The results of the study prove that the use of playing activities with natural media at home can improve cognitive ability to classify objects during the Covid 19 pandemic in group A students of Marsudi Ilmi Cabak Kindergarten, Tlogowungu District, Pati Regency, for the 2020/2021 Academic Year. It is evident from the cognitive ability to classify students' objects in the pre-cycle which are included in the category of Very Good Developing (BSB) and Developing According to Expectations (BSH) only 26.67%. Then it increased in the first cycle of meeting 1 to 46.67% and meeting 2 to 60.00%. Then it increased again in the second cycle of meeting 1 to 63.33% and meeting 2 to 93.33%. Thus, it is known that there is an increase of 66.66%.
Le immagini di Sebastiano Vassalli dal profondo del tempo

En): In the extensive literary production of Sebastiano Vassalli (1941-2015), we can witness an evolution of his poetics from his initial formation within the avant-garde Gruppo 63 towards a more traditional prose.In this change of perspective, Vassalli's tendency to include in his narratives a documented attention to real historical events, within which his characters move, each following his own original destiny, played a fundamental role.The literary references, in Italy and abroad, from which Vassalli could draw are numerous and well known (Manzoni, Leopardi, Pirandello, Sciascia, Queneau, García Marquez...).On the strength of this methodology, Vassalli has been able to tell stories where the fulcrum of the plots always revolves around his interest in the various human types who have remained unchanged beyond historical periods and who face adverse events in a heroic way.
Scientific specialty «Library science, bibliography science and bibliology» and specialized dissertation research (1999–2020)

In the modern world, global changes are taking place in all spheres of society, including economy, science, education and culture. In this regard, a detailed analysis and comprehension of ongoing processes become relevant to develop a specific strategy. In 2021, the Ministry of Science and Higher Education adopted the Order «On the approval of the nomenclature of scientific specialties for which scientific degrees are awarded &lt;….&gt;”; the nomenclature of scientific specialties was published, where specialty 05.25.03 «Library Science, Bibliography science and Bibliology» was not reflected (among pedagogical, historical, philological, technical sciences). This document came next to a draft nomenclature of scientific specialties (2020), which was widely discussed by the scientific community. The library community and representatives of university science carried out a number of activities aimed at changing the situation. The authors recreate the picture of forming and growing the profile scientific specialty, including its presentation in the nomenclature of scientific specialties for which scientific degrees are awarded since 1957; analyze statistic materials on post-graduate training of highly qualified scientific personnel and activity to defense dissertations in 1999–2020; generalize and assess the data, consider the problems and vectors of this specialty development to justify the inclusion of the specialty «Library Science, Bibliography Science and Bibliology» in the new nomenclature of scientific specialties to continue the training of highly qualified scientific personnel in graduate school, and to carry out specialized research. The article argues that the consequences of the ongoing reforms in science have led to transformations, slowing down the rotation of scientific personnel, extinguishing the activities of dissertation councils and scientific schools in library science, bibliography and bibliology in the regions and complicating the development of library and information science in general.