Reviewerly/exHarmony huggingface dataset:
THE REVOLUTIONARY ATTACK ON «FREEDOM OF EDUCATION», OR THE PROLETARIAN READING OF SOCIAL DISCIPLINES IN THE 1920s: FROM CONCEPTION TO IMPLEMENTATION

The article examines the problems of the Soviet education formation in one of the most troubled periods of the Soviet history – in the 1920s. The features of the policy of the Soviet government in this direction are studied. Through the study of a number of steps taken by the Soviet government in the field of university curricula transformation, a general picture of large-scale changes in the entire educational system is given. The work focuses on social disciplines that became key ones in creating the Soviet educational system. On the example of the activities performed by two universities in the Volga region (the largest at that time) – Saratov State University and Kazan State University -the main reasons and principles of introducing new social disciplines are studied. What it involves first is Marxist-Leninist social disciplines, which are actively implanted by the new government in the educational programs of the country’s universities in general and the universities of the Middle Volga Region in particular. The process of building social institutions designed to accumulate the study of Marxist-Leninist disciplines in universities is shown. On the basis of examining the archival documents reflecting the activities of these universities, particular moments of history associated with the beginning of the introduction and teaching Marxist-Leninist disciplines were reconstructed. The emphasis is placed on studying the reflection of the higher-education teaching personnel and their individual representatives on the ongoing changes. Individual statements of university teachers, their speeches, articles, and their direct social practices became one of the main sources that made it possible to reconstruct the attitude of the university intelligentsia to the flooding of the educational process with Marxist-Leninist disciplines and to the transformation of their professional space as a whole. The paper also traces the methods of the university intelligentsia’s influencing the ongoing changes. The interconnection between the socio-cultural practices of university professors and lecturers and the results of social disciplines transformations is revealed. It is noted that the initial plans of the authorities were largely adjusted, largely under the influence of the higher-education teaching personnel. In general, the article defines the significance of socio-cultural practices of the university intelligentsia for the emerging Soviet educational system.
Distributed Registration and Multi-target Tracking with Unknown Sensor Fields of View

This paper addresses the problem of distributed multi-target tracking (MTT) in a radar network wherein both the positions and fields of view (FoVs) of each radar are unknown to the network. The probability hypothesis density (PHD) filters are running locally in each radar for MTT. The Weighted Arithmetic Average (WAA) fusion rule is employed because of its robustness to multi-sensor tracking with different FoVs. Due to the unknown FoVs of radars may be different and time-varying, in our method, the local intensity densities are decomposed into a number of sub-densities by a clustering algorithm. Then the positions of sensors are estimated by minimizing the Cauchy-Schwartz divergence (CSD) between the sub-densities which belong to the same cluster. Further, the WAA fusion is also performed in parallel using the sub-densities in each cluster and the fused intensity is constructed as the sum of the fused sub-intensities. The efficacy of the proposed method is demonstrated in a challenging tracking scenario via simulations.
Discriminative Multi-view latent Space learning based on Marginal Fisher Analysis

In recent years, samples are usually represented with different views of features. Although the features from different views represent the same sample, they are heterogeneous and the information contained in one view feature is unlikely to comprehensively describe all samples. Therefore, in multi-view learning, how to effectively integrate multiple views feature for better depicting the samples is of vital importance. In this paper, we propose a novel supervised multi-view latent space learning algorithm based on Marginal Fisher Analysis, named Discriminative Multi-view latent Space Learning DMSL. In this approach, a latent representation of multi-view feature is obtained, which encodes the information from different views feature by exploiting their complementarities. Moreover, we utilize the graphs which characterize intraclass compactness and interclass separability to improve latent representation discriminability. Thus, DMSL can integrate the information from multiple views feature to construct a compact latent representation and encodes the discriminative information into it simultaneously. Our model can be optimized efficiently by using the Augmented Lagrangian Multiplier with Alternating Direction Minimization (ALM-ADM) framework. Plenty of experiments on diverse datasets demonstrate the effectiveness of the proposed method.
Enyo: A Multistage Partition and Transposition Based Cipher

The increase in demand for information security has made cryptography a basic need for protecting data from unauthorized access. In this paper, a computationally inexpensive Enyo block cipher has been presented. This multi-layered algorithm provides a promising solution to safeguard user’s information. The cipher works on the same line as the Feistel-based network with the symmetric structure and operates on 8-bit ASCII characters. Using 6-bit custom encoding, a secret key generates 6-bit encrypted text. This cipher modeled using undemanding operations utilizes partitioned key-based encryption with unique mapping followed by various bitwise swaps, a shifted modulo encryption, and using a transposition matrix. The proposed cipher is highly customizable as per user demands and necessities that make it more dependent on user inputs. Enyo cipher is faster in encryption and decryption than the Playfair cipher and shows comparable performance with XOR encryption. Enyo cipher demonstrates good resistance to a brute-force attack. It is well suited for small-scale applications where the computational power is a bottleneck. A comparison is also made that shows the impact of the proposed cipher to commonly available classical ciphers.
Quantum Algorithm for Machine Learning and Circuit Design Based on Optimization of Ternary - Input, Binary-Output Kronecker-Reed-Muller Forms

Paper introduces a new spectral expansion of ternary-input binary-output functions that generalizes the binary Kronecker-Reed-Muller forms. Two binary Davio Expansions are generalized to 27 Ternary-Input Davio Expansions. New KRM spectrum has 28 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">n</sup> expansions for n ternary variables. By creating an oracle for this problem we generalize the quantum Grover-based algorithms presented for the binary FPRM and KRM forms in the past. Because the method finds solutions also to incompletely specified functions, it can be used to both quantum circuit design and Machine Learning classifier design.
Proof of Authentication for Secure and Digitalization of Land Registry Using Blockchain Technology

The aim is to secure land records and eliminate the fraudster to create duplicate land records and sell to another party. By using blockchain technology, we can solve this problem, the current land registries are still it is paper-based, and performance of document verification process is slow and unreliable in terms of accuracy, security, and occasionally corrupt. In this paper, we propose an architecture to improve the performance of record management. Architecture is separated by application domain and core system so that it improves the performance. The consensus algorithms play an important role in the blockchain for creating new blocks and appending them to the blockchain. The proposed New Block generate algorithm for creating a new block provides an efficient way of storing data in blocks. Before placing the block in the blockchain network, the block is digitally signed by using cryptographic techniques. The second algorithm is proof of authentication consensus protocol; it is used for the block validation process.
Securing Three Dimensional Regions with Stereo Vision

Although there exist many different solutions for securing volumes of space with various kinds of security cameras such as conventional monocular or thermal cameras, using stereo vision has not been attempted as an alternative method. By combining motion detection via image subtraction and range-finding via stereoscopic vision, a single stereo camera can secure a large three-dimensional volume within its field of view. With this, many individual areas can be secured by a single stereo camera placed further away that would otherwise have to be secured by many conventional or thermal cameras placed near areas of interest. Our solution works well for depth-ranges of up to 20 feet. At ranges beyond 20 feet, the disparity map becomes too noisy. Within the 20 feet range, the depth detection is highly accurate with only 0.18% error.
The Application of Knowledge Map and the Construction of Enterprise Knowledge Map

With rapid development of the new generation of information technology, the exchanges and interactions between people, machines and machines, and people and machines become more and more frequent, and the information environment and data base of the development of artificial intelligence technology have undergone significant and profound changes. The rapid accumulation of massive data, the substantial improvement of computing power, the continuous optimization of algorithmic models and the rapid rise of industrial applications have comprehensively promoted the development of a new generation of artificial intelligence technology.
LEARNING A COMBINED MODEL OF TIME SERIES FORECASTING

The method of construction of the combined model of forecast ing of time series based on basic models of forecasting is developed in the work. The set of basic models is dynamic, ie new prediction models can be included in this set. Models also can be deleted depending on the properties of the time series. For the synthesis of a combined model of forecasting time series with a given forecast step, the optimal step of prehistory is determined at the beginning. Next the functional is constructed. The optimal prehistory step is determined using the autoregression method for a fixed forecast step. It determines the period of time at which the accuracy of models from the base set is analyzed. For each basic model during the process of the construction of the combined model is determined by the weighting factor with which it will be included in the combined model. The weights of the basic models are determined based on their forecasting accuracy for the time period determined by the prehistory step. The weights reflect the degree of influence of the base models on the accuracy of the combined model forecasting. After construction of the combined model, its training is carried out and those basic models which will be included in the final combined model of forecasting are defined. The rule of inclusion of basic models in the combined model is established. While including basic models in the combined forecasting model, their weights are taken into account, which depends on the same parameter. The optimal value of the parameter is determined by minimizing the given functional, which sets the standard deviation between the actual and predicted values ​​of the time series. Weights with optimal parameters are ranked in decreasing order and are used to include basic models in the combined model. As a result of this approach, as predicted values for the real time series show, it was possible to significantly improve the forecasting accuracy of the combined model in many cases. The developed method of training provides the flexibility of the combined model and its application to a wide class of time series. The results obtained in this work contribute to solving the problem of choosing the most effective basic models by synthesizing them into one combined model.
Software Security Framework using the Combination of Use-Misuse Diagrams and Test Driven Development

In recent years, Software Security has gained an important role in the research of information systems as the increasing popularity of hacking and attacking software systems. Therefore, the need for security measures grows and many researchers have put security measures into account from the early stages of software development starting from the requirement engineering phase. Traditional security methods introduced numerous approaches to this subject from the identification of security requirements representation using different processes and techniques such as misuse case diagrams and attack trees, etc. However, these approaches focus on identifying security requirements and ignoring their inclusion in the system. This study investigates the problem of embedding security requirements within the system to ensure and improve security. A framework has been proposed to overcome this problem. The framework has been applied to a case study, i.e., Car Rental System and FileZilla FTP Server as verification and evaluation of the concept. An experimental study has been conducted to ensure that the framework can be applied in real-world applications by several software engineers with different expertise and background. A discussion about the evaluation comparison has been taken place to demonstrate the results. The results have been encouraging and prove that the proposed solution is valid.
56‐3: <i>Student Paper:</i> An Amplifier with Higher Gain Using Corbino—TFTs

In this paper, an amplifier circuit using oxide TFTs for amplifying brain signal is proposed. The proposed circuit is largely composed of two TFTs. It consists of a driving transistor that receives an input and a load transistor that determines the voltage gain through interaction with the driving transistor. Based on depletion load inverting amplifier, we analyzed the small signal modeled circuit. By using a circular TFT called Corbino‐TFT, we were able to obtain a greater voltage gain. The measurement results were compared with the calculated voltage gain. In addition, to get a higher gain, method of connecting two amplifiers in series is presented and simulation results are also presented.
Research by Subject: Fair Use: Fair Use

This guide offers basic information on using images and media in research. Reasonable use of images and media in teaching, course papers, and graduate theses/dissertations are generally covered by fair use.
Exploration on the Practice of Reading Teaching for English Majors in the New Situation

The teaching of English reading plays an important role in the teaching process of English majors. From expanding vocabulary to improving reading speed, from improving logical thinking ability to understanding language and cultural background knowledge, students’ professional knowledge and ability are consolidated. However, at present, the teaching objectives of English major reading teaching are not clear, and the teaching mode is conservative and single. This hinders students from learning knowledge and improving their professional ability. In order to improve the quality of teaching and learning, and students’ sense of accomplishment, from the advantages of reading teaching for English majors under the new situation, this paper puts forward some suggestions for improvement.
Extent of integration of the Information Communication Technology in teaching at selected public elementary schools in the Division of Pasig City, District IV: Indices for an improved instructional delivery

This study determined the integration of ICT in teaching by the teachers in selected public elementary schools at District IV in the Division of Pasig City, assessed by the heads, and teachers themselves.The method used was descriptive to collect quantitative information by setting up a condition that allowed respondent to answer the survey questionnaire through a checklist about integration on instructional technologies and capabilities of their school.In this study, the heads and the teachers in selected public elementary schools at District IV of the Division of Pasig City-Ninoy Aquino Pilot Community Elementary School (NAES), and Manggahan Elementary School (MES), were tasked to answer the research questions.There were 27 heads and 134 teachers who partook in assessing the research problems.The majority of the respondents were mature and old enough to handle their students.It also shows that since they were mature, they were confident and more experienced than the beginner teachers.Furthermore, most head teachers and teachers were females; thus' they were all guided by their maternal instinct in teaching their students.Most of the teachers considered Graduate School as part of their profession.They are all continuing their education for them to gain more knowledge about teaching.There are 22 percent of the respondents who needs to be encourage in attending training/seminars regarding ICT.The extent of ICT integration required by the two groups of respondents classified as to entry, adaptation and appropriation rated as Agree.While in terms of adoption and invention, it ranked as Highly Agree.There is a significant difference between the assessments of the two groups of respondents on integrating ICT in teaching.There is a significant difference between the extent of teacher's integration when grouped according to the teacher's age, sex and number of training/seminars attended regarding ICT.However, when it comes to highest educational attainment, there is no significant difference.
Stateless Key Management Scheme for Proxy-Based Encrypted Databases

To preserve the confidentiality of important data stored in third-party managed platforms like public cloud databases is continuously raising security concerns.Mallaiah, Kurra Gandhi, Rishi Kumar Ramachandram, S. Such databases need to be shielded from malicious administrators or malicious software attacks, so as to increase the trust of the potential customers of such security. Therefore, it is very important that the data must be protected at rest, in transition and also while in operation to achieve full confidentiality for the data stored in databases. Shielding the confidentiality of data at rest and in transition is adequately addressed but shielding the confidentiality of data while in operation is still a big challenge. CryptDB provides confidentiality for relational databases by supporting the computations on encrypted data. The keys which are used in CryptDB are stored in the proxy. This paper proposes a stateless key management scheme, inversely the state-full key management scheme of CryptDB. The security proof is presented along with cryptographic security definitions and that the security of our key management under the random oracle model security assumption. The proposed key management scheme is the first of its kind that is a stateless key management. The scheme eliminates the storing of user cryptographic keys in the proxy and, hence, avoids possible attacks and analysis on keys in the proxy and also various other problems such as key backup, key loss, and key audit. Our proposed solution also satisfies regulatory compliance by not storing the cryptographic keys anywhere.
TempDiff: Temporal Difference-Based Feature Map-Level Sparsity Induction in CNNs with <4% Memory Overhead

The diffusion of vision sensor nodes in a wide range of applications has given rise to higher computational demand at the edge of the Internet of Things (IoT). Indeed, in-node video sense-making has become essential in the form of high-level tasks such as object detection for visual monitoring, mitigating data deluge from the wireless network to the cloud storage level. In such applications, deep neural networks are well known to be a prime choice, in view of their performance and flexibility. However, such properties come at the cost of high computational requirements at inference time, which directly hamper power efficiency, lifetime and cost of self-powered edge devices. In this paper, a computationally-efficient inference technique is introduced to perform the ubiquitously required task of bounding box-based object detection. The proposed method leverages the correlation among frames in the temporal dimension, uniquely requires minor memory overhead for intermediate feature map storage and architectural changes, and does not require any retraining for immediate deployment in existing vision frameworks. The proposed method achieves 18.3% (35.8%) computation reduction at 3.3% (3.2%) memory overhead, and 3.8% (6.8%) accuracy drop in YOLOv1(VGG16) SSD(VGG16) neural networks under the CAMEL dataset.
A Corpus-based Study on Semantic Prosody of English Synonyms Declare and Announce

Based on the data-based approach, a case study of a pair of synonyms, declare and announce, is conducted in this paper through searching COCA, aiming to reveal their different semantic prosodic features and witnesses the powerful vitality of corpus as a language research tool. Through retrieving significant collocates of these two synonyms and comparing their collocates in meaning and usage, this study found that declare generally collocates with words of negative prosody, whereas announce is normally accompanied by words which have the most distinctively strong neutral prosody. With results of this paper, it is hopeful to arouse EFL teachers' attention on semantic prosody and make full use of corpus-based language teaching.
Computing Algorithm of Robot Distributed 3D Graphic Simulation System

Abstract In view of the shortcomings of current multi-robot path planning strategies, such as high path coupling, long total path, and long waiting time for collision avoidance, as well as the resulting problems of low system robustness and low robot utilization, the paper proposes Multi-robot path planning particle swarm algorithm based on distributed three-dimensional space-time graphics and motion decomposition. We first generate a dynamic temporary obstacle in the time dimension according to the existing path set and the current robot position, and expand it together with the static obstacle into a three-dimensional search graphics space. Secondly, in the three-dimensional image space, the total path movement time is divided into three parameters: movement time, turning time and staying time in place, and using the conditional depth-first search strategy to calculate all the matching parameters from the starting node to the target node the required path collection. The experimental results show that the path of distributed 3D graphics planning by our proposed particle swarm algorithm has the advantages of total length, less running time, system collision-free, and high robustness, which solves the problem of multi-robot systems completing continuous random tasks.