Reviewerly/exHarmony huggingface dataset:
Leukemia Detection with Overlapping Blood Cells Using Watershed Algorithm and Convolutional Neural Networks

Various techniques in image processing are generally utilized in the field of medicine, considering the factor of health, therefore it must be contrived in a circumspect manner. The study was developed to analyze and identify if the Watershed Algorithm will affect the accuracy in classifying blood smear images as a candidate for Leukemia or not. The proponents constructed a system using a Convolutional Neural Network to classify the input blood images. The system will process both batches of raw input blood images and with separation of overlapping blood cells, through image processing techniques and Watershed Algorithm, before proceeding to the image classification algorithm. The system was trained and tested three times in both cases to ensure the reliability of the Convolutional Neural Network classification model with and without the Watershed Algorithm applied. The system without the Watershed Algorithm applied yielded an accuracy of 90%, 88%, and 90%, respectively with an average of 89.33% while the system with Watershed Algorithm applied yielded an accuracy of 96%, 94%, and 94%, respectively with an average of 94.67%.
Developing an Emotion Recognition Tool for Tweets

This research in the domain of sentiment analysis aims to maintain high effectivity and applicability by not just understanding how the user feels, but by accurately quantifying their emotions. With the desired end product being a web application, the visualization that is received as an output aids the user in comparing the intensity of their emotions of anger, fear, joy and sadness demonstrated in the input tweets. This web application was built with the use of a dataset from the SEMEVAL-2018 competition. Training and testing of the dataset using 6 machine learning algorithms and their evaluation using performance metrics including R2, MAE, MSE and RMSE led us to arrive at the result that 'Support Vector Regressor' was the best performing algorithm for anger, sadness and fear while the Gradient Boosting algorithm performed best for joy. To that end, the web application uses the following algorithm for evaluating the respective emotions. In addition to developing a prediction model, the research also involved extensive data visualization an analysis that conveyed the most used words and hashtags when the user experiences each of the aforementioned emotions. To highlight the research's accomplishment- the author has been able to create a fairly accurate and relatively quick sentiment analysis model for public opinion.
ChatterBox- A Real Time Chat Application

&lt;p&gt;The chat application is something that allows users to get in touch directly. People can interact using this online application. People can interact using this online application effectively even far apart. To be utilized by many people, this web-based application is supposed to be real-time and multiplatform. Chatterbox is a real-time chat application developed using MERN stack development thus it is easily extendible and developed with recent technologies. Also, it has features like voice calls, video calls, screen sharing, chatting, and much more for users in one application. Particularly the application is more secure and comes with the option of screenshare which other applications mostly don’t have making it handy and easily reliable as well. Also, with further system demands for running higher ends of the project, multiple features can be added to the application due to the extensible code and the application can be extended.&lt;/p&gt;
Applications of Advanced Mathematics in The Field of Economics

Abstract The application of mathematics permeates different fields, especially in the field of economics. The connection between economics and mathematics is indispensable. It can also be said that the problems and research in the economic field are inseparable from the support of mathematics. This paper explores the connection between advanced mathematics and economics and its application in economics through the literature review method. Through example studies, the paper finds that only by choosing appropriate mathematical methods for different economic problems can economic problems be solved effectively.
Peer Review Statement

All papers published in this volume have been reviewed through processes administered by the Editors. Reviews were conducted by expert referees to the professional and scientific standards expected of a proceedings journal published by IOP Publishing Publishing. • Type of peer review: Single Anonymous • Conference submission management system: Morressier • Number of submissions received: 130 • Number of submissions sent for review: 112 • Number of submissions accepted: 94 • Acceptance Rate (Submissions Accepted / Submissions Received × 100): 72.3 • Average number of reviews per paper: 9 • Total number of reviewers involved: 16 • Contact person for queries: Name: Professor I Wayan Sutapa Email: wayan.sutapa@untad.ac.id Affiliation: Universitas Tadulako
Design and Research of Automatic Error Correction Algorithm for Electric Energy Metering Device

Abstract Aiming at the problems of long error correction time and poor correction effect of electric energy metering device, an automatic correction algorithm design of electric energy metering error is proposed. First, the stationary characteristics of the electric energy metering device when errors occur are extracted, and the regular interval of error correction is found. Second, in the regular interval, the average power of the quantization error of the metering device is determined, and the location of the error is found. Finally, the stability is corrected according to the error. According to the interval and error position, an automatic error correction model is constructed, which shortens the error correction time, enhances the automatic error correction of the power calculation device, and realizes the accurate correction of the power calculation error. The comparative experimental results show that the error correction time of the algorithm is short, and it has the ability of real-time error correction, which can be applied in real life.
A Systematic Literature Review on Mathematics Mobile Applications in Education

&lt;p class="Default"&gt;&lt;span&gt;The usage of mobile applications in today’s teaching and learning system is an active area of research. This study was a Systematic Literature Review (SLR) using the PRISMA model by identifying various appropriate and relevant kinds of literature to identify the usability of mobile applications in education. Data search was carried out using criteria determined by researches from various search engines such as Google Scholar, ERIC, Scopus, Research gate and others as SLR was performed on papers obtained from these databases. In total 77 articles were retrieved; out of which 30 were similar to the purpose of this paper. Out of 30, only 15 articles were relevant to this study. Furthermore, the data were analysed using a qualitative approach to describing the research findings. The results showed that three main research themes have been found, namely the purpose of the study, targeted population and research design. Outline, the analysis results of these articles stated that the implementation of mathematics mobile applications in education is still under consideration in Malaysia. These findings are expected to serve as a foundation for teachers, education observers, and education policymakers at all levels of government, including local, state, and federal governments, as well as the Ministry of Education, to develop policies that support the development of mathematics mobile applications in education. The findings of SLR provided insight into the field's primary contributions, gaps, and chances, which created a conversation about essential research areas in future.&lt;/span&gt;&lt;/p&gt;
A Comprehensive Comparison of Pre-training Language Models

&lt;p&gt;Recently, the development of pre-trained language models has brought natural language processing (NLP) tasks to the new state-of-the-art. In this paper we explore the efficiency of various pre-trained language models. We pre-train a list of transformer-based models with the same amount of text and the same training steps. The experimental results shows that the most improvement upon the origin BERT is adding the RNN-layer to capture more contextual information for short text understanding. But the conclusion is: There are no remarkable improvement for short text understanding for similar BERT structures.&lt;/p&gt;
BLOCKCHAIN AS A TOOL FOR THE INCLUSION OF EDUCATIONAL ORGANIZATIONS IN THE CIVILIZATIONAL CONTEXT

1 Blockchain as a tool for the inclusion of educational organizations in the civilizational contextEducation is a fundamental public good, a foundation for peace and a prerequisite for sustainable development, and therefore education is a priority for UNESCO.Already UNESCO's first report, "Learning to Be: The World of Education Today and Tomorrow" (1972) warned of the threat of growing inequalities, deprivation and suffering, and it also stressed the need for continuous development of education and lifelong learning systems.
NEW EDUCATIONAL METHODS OF SHAPING HUMAN CAPITAL FOR THE CONDITIONS OF DIGITAL TRANSFORMATIONS AND POSTWAR RECOVERY

1 New educational methods of shaping human capital for the conditions of digital transformations and postwar recoveryModern socio-economic development of society and its transition to Industries 3.0 and 4.0 and postwar recovery requires using new innovative methods and technologies for teaching and learning.In particular, in-depth learning for students of economic specialties allows future specialists to be more competitive on the labor market.The concept of "innovative teaching methods" is multicomponent because it combines new practical approaches to successful educational processes (acquisition, transmission, and production of knowledge) [405].It contributes to the intensification and modernization of learning and develops creative approaches and the personal potential of graduates.Innovations in education can be divided into psychological and pedagogicalinnovations in the educational, educational, and management process; scientific and productioncomputer and multimedia technologies; socio-economiclegal and economic innovations [406].Innovative technology in the higher education system is based on organizational and methodological innovations.The most popular innovative teaching methods are contextual learning, simulation, problem learning, modular complex knowledge acquisition, and distance learning.Table 1 shows the comparative characteristics of innovative teaching methods.
Design and Application of DHP Controller Based on Online Leaky Echo State Network

In wastewater treatment process (WWTP), which has nonlinear and dynamic characteristics, it is difficult to realize the tracking control of dissolved oxygen (DO). To solve this problem, the online double heuristic programming (DHP) controller based on leaky echo state network (LESN) is proposed, the controller is named as DHP-LESN for short. Firstly, three Leaky ESNs are used in DHP to produce the control strategy, the system state and the derivatives of evaluation function, respectively. Then, the online gradient algorithm is used to update the output weights of three LESNs. Finally, the performance of the proposed DHP-LESN controller is tested and evaluated on Benchmark Simulation Model 1 (BSM1). The simulation results show that the proposed DHP-LESN controller can achieve better control nerformance than PID controller.
The archive of Professor Georgi Zlatarski – knowledge source of the foundation of geology and paleontology in Bulgaria

This paper presents a part of the documents, which are stored in the personal archive of Professor Georgi Zlatarski at the Department of University Archive of Sofia University (Bulgaria). This valuable treasure embodies not only the development of geology in Bulgaria, but also the path of a brilliant scientist towards the realization of the plans he shared in 1880 in a letter to Prof. Konstantin Irechek: “to divide Bulgaria in separate parts and to study each one in detail”; to “make a precise geological map”, and to “arrange and systematize the collection of Bulgarian fossils”. At the end of his not very long life, it can be seen that Prof. Zlatarski succeeded in realizing his plans. In 2022, a joint project between the Faculty of Geology and Geography and the Department of University Archive, which aimed to promote the archival heritage of this eminent scientist, was carried out. With the help of geologists and paleontologists, some of the document annotations were revised to define more accurately certain documents or scientific studies. After the revision, the archive is at a higher scientific level, as it includes precise terms in geology and paleontology, making it more understandable and accessible to specialists in these fields. The chronological limits of some of the undated documents were also specified. A permanent exposition of documents on the websites of the University Archive and the Faculty of Geology and Geography, as well as a presentation on the scientific career of Prof. Zlatarski, which will be used in teaching, will soon be available.
3D Objective Detection for Autonomous Driving based on Two-stage Approach

As one of the hottest areas in the current technology industry, the field of autonomous driving has attracted the attention of many technology workers. How to use point cloud data for accurate multi-objective prediction is a key issue, which includes 3D object detection and multi-object tracking. CenterPoint proposes a novel anchor-free, two-stage 3D object detection method. The first stage uses a CenterNet approach, that is, using the center point to represent the object, using the feature map after feature extraction as input, and outputting a heatmap of the probability of the location of the center of the object for each category to predict the location of the target object, and obtaining other properties from the feature regression of the point location. The second stage is to extract features from the center point of the bounding box of the prediction target to refine the prediction results. However, the 3D backbone network of the CenterPoint has the disadvantages of low feature extraction accuracy and low second stage refinement accuracy. In order to solve these problems, this paper proposes to use VoxelResBackBone8x based on deep residual network Resnet as the 3D backbone network, simplify the 2D backbone network to improve feature extraction accuracy, and use the Set Abstraction Module to make the model use both the processed advanced features and the original point cloud features to further improve the accuracy.
MOHALLA (OR COMMUNITY/ NEIGHBORHOOD) CLINICS TO REINFORCE PRIMARY HEALTHCARE IN DELHI, INDIA: A SYSTEMATIC REVIEW BASED ON PRISMA 2020 GUIDELINES

“Mohalla” in Hindi language means community or neighborhood. In July 2015, government of Delhi started establishing Mohalla (or community/neighbourhood) clinics (MCs) for strengthening primary healthcare services in Delhi, India. Primary objectives these clinics include making primary care accessible and affordable, reducing burden on tertiary care facilities etc. This article contains a review of past publications concerned with MCs to assess their performance. A systematic review based on PRISMA 2020 guidelines was carried out and database search was completed on 8 Feb, 2022. A total of 24 studies were finally selected for review. The review revealed that MCs have the potential to make primary care services accessible and can help in achieving universal health coverage. These clinics provide cost-effective primary care services and avoid overcrowding in big hospitals. MCs circumvent self-medication practices and are highly effective in low-income settings. To improve efficiency of MCs, it is suggested to strengthen health workforce and expansion of MCs beyond primary care. Additionally, there is a need of functional referral system along with launching telemedicine services at MCs
The Scope of Application of Letter Frequency Analysis in Substitution Cipher

Abstract Since its inception, substitution ciphers have been a popular type of cipher, and over time, academics have studied them in an effort to discover patterns that will allow them to be broken. They created it because substitution ciphers are a reasonably simple type of cipher. Through a survey of the literature, this paper investigates the encryption and decryption of three sub-types of monoalphabetic ciphers: shift cipher, affine cipher, and random substitution cipher. Letter frequency analysis is the foundation of the primary decryption technique. After that, two sub-kinds of monoalphabetic ciphers, Hill cipher and Playfair cipher, which are resistant to this decryption method because the letters encrypted hardly keep the original frequency, will be introduced. The paper shows that statistical analysis of letter frequency is only useful for deciphering single-table substitution ciphers.
Design and implementation of ECC combined with OPT encryption algorithm

Abstract 【Objective】 Combining ECC and OPT, a novel elliptic curve algorithm was proposed, which can effectively resist the reverse calculation of quantum computer and ensure the security of private key. 【Method】 On the basis of elliptic curve encryption algorithm, OPT algorithm was introduced to protect the private key. 【Result】 The signature and verification of messages can be successfully completed by the repeated algorithm on Python platform. Finally, the algorithm is proved to be safe under Shor algorithm and quantum computer attack through algorithm theory. 【Conclusion】 ECC combined with OPT encryption algorithm can effectively resist reversible computation of functional quantum devices, prevent eavesdroppers from forging signatures, and ensure the security of modern public key cryptosystems.
Analysis of Some Major Types of Coin Sorting Devices

Abstract This paper summarizes and compares several main types of coin sorting devices. Through different processes and principles, the coins of 1 jiao, 5 jiao, and 1 yuan are classified and collected separately. Because of the structural characteristics of coins, they have the advantages of multiple circulation, wear resistance, easy recovery, and so on. Coins play an important role in small denomination currency. These coin sorting devices can realize the rapid and effective classification of a large number of coins, reduce the manual burden, and replace manual sorting, so as to effectively improve the efficiency of coin separation and collection.
Experimental assessment of the informativity of signs in the analysis of 2d images of bone objects in forensic examination.

This article describes the software implementation of the system for extracting and evaluating information features from 2D images of bone fractures and bone objects for classifying fractures and identifying the alleged instrument that caused the injury. As parameters, the textural characteristics of Haralick, local binary patterns of pixels for 2D images, Gabor filters, Laws energy texture characteristics for 2D images are considered. The analysis carried out on basis of information content estimation to select the features that are most suitable for solving the problem of bone fractures classification. The results will be used for development of methods for complex forensic examination of complex polygonal surfaces of solid objects for automated system for analyzing digital images.
Methods and Technical Means for Ensuring Uniformity of Nanoparticle Size Measurements

The paper proposes a set of technical tools for solving the problem of ensuring the uniformity of measurements of micro- and nanoparticles. To do this, it is necessary to ensure the traceabilityof particle size measurements to a unit of length – a meter, as well as equivalent diameters used in measurements in various dispersed media (aerosols and suspensions). To ensure traceability of particle diameter measurements to the meter, it is proposed to use a nanomeasuring machine with an atomic force microscope as a probing system. The paper presents a diagram of the measuring system, describes the principle of operation of the machine and the method for measuring particle sizes. The main alleged sources of errors in particle measurement by this method are also identified. To ensure the traceability of measurements of the hydrodynamic diameter of nanoparticles, which characterizes particles in a liquid (suspension), it is proposed to use a nanoparticle size analyzer that implements the method of dynamic light scattering. The scheme of the analyzer with a description of the principle of measuring the size of nanoparticles by the method of dynamic light scattering is presented in the paper. The scheme of the column of the analyzer of the differential electrical mobility of particles is presented to ensure the traceability of measurements of their diameter, which is equivalent in electrical mobility. Diameter is usually used to characterize particles in the aerosol state. A diagram of an analyzer for the differential electric mobility of particles is given with a description of the operating principle, a formula for calculating the particle diameter is derived.
Continual Repeated Annealed Flow Transport Monte Carlo

We propose Continual Repeated Annealed Flow Transport Monte Carlo (CRAFT), a method that combines a sequential Monte Carlo (SMC) sampler (itself a generalization of Annealed Importance Sampling) with variational inference using normalizing flows. The normalizing flows are directly trained to transport between annealing temperatures using a KL divergence for each transition. This optimization objective is itself estimated using the normalizing flow/SMC approximation. We show conceptually and using multiple empirical examples that CRAFT improves on Annealed Flow Transport Monte Carlo (Arbel et al., 2021), on which it builds and also on Markov chain Monte Carlo (MCMC) based Stochastic Normalizing Flows (Wu et al., 2020). By incorporating CRAFT within particle MCMC, we show that such learnt samplers can achieve impressively accurate results on a challenging lattice field theory example.
A general approach for of schema matching problem: case of databases

Abstract The problem of schema matching is one of the main tasks in several processes dealing with databases, data transformation and data integration. Schema matching involves the generation and linking of heterogeneous schemas. This heterogeneity makes the implementation of a solution difficult and the sources of heterogeneity are multiple. The need for a methodology that can adapt to the largest number of points of variation is necessary. In this paper, we propose a flexible, global and generic approach to meet this need where the main idea is to exploit as much information available in the schemas and this through the implementation of federated interoperability that allows the interpretation of information on the fly. To this end, the approach uses graph theory, more specifically hypergraphs and optimization models for the modelling of schemas and the automation of the solution of the schema matching problem by converting it into a graph matching problem. Our contributions include the proposal of an optimization model to add specific constraints to the schema matching problem, as well as the propagation algorithms to propagate the matching relationships between the source and target schemas. The approach is finally evaluated on two use cases, one academic and one industrial.