Reviewerly/exHarmony huggingface dataset:
Clustering-based medical image segmentation: a survey

Image segmentation is a popular phenomenon to dividing a digital image into various meaningful and disjoint segments based on certain criteria. It is used to represent the original representation of the image into a more meaningful representation which can be easily analysed. The segmentation of medical images is one of the key steps for analysis of the medical images. It has been gaining much attention due to its application in clinical diagnosis. Computer-aided image segmentation not only reduces the effort of medical practitioners but also reduces the chances of error due to the human intervention. Proper segmentation of medical images leads to accurate diagnosis of the disease which may lead to appropriate treatment. A lot of algorithms have been suggested to segment an image into its most informative form but image segmentation still remains quite a challenging problem. Out of all these segmentation algorithms the clustering-based segmentation algorithms are quite popular to segment both low- and high-dimensional medical images. These algorithms segregate the input image into a finite number of clusters each having a group of pixels based on certain criteria. In this chapter, the different clustering-based algorithms proposed for medical image segmentation have been reviewed. Concise overview of different clustering algorithms proposed for segmentation of medical images is presented along with their key benefits and limitations.
Qiwi: A Beginner Friendly Quantum Language

Acknowledging the inter-disciplinary aspect of quantum computing, there is a need to make quantum programming more accessible for its fast-growing community. With the advent of quantum computers with hundreds of qubits designing circuits manually is infeasible. Most current languages are low-level or involve a steep learning curve or lack control. Thus we propose a quantum programming language (QPL) that allows for high-level abstractions with intuitive syntax while still allowing users to directly construct circuits.
Formally Verified Resource Bounds through Implicit Computational Complexity

Automatic complexity analysis has not reached mainstream adoption due to outstanding challenges, such as scalability and usability, and no formally verified analyzer exists. However, the need to evaluate resource usage is crucial: even a guaranteed correct program, whose memory usage exceeds available resources, is unreliable. The field of Implicit Computational Complexity (ICC) offers a potential avenue to resolving some of these outstanding challenges by introducing unique, machine-independent, and flexible approaches to program analysis. But since ICC techniques are mostly theoretical, it is unclear how strongly these assumptions hold in practice. This project defines a 3-directional plan---focused on practical analysis, compiler-integration, and formal verification---to assess the suitability of ICC to address outstanding challenges in automatic complexity analysis.
ADDITIONAL EDUCATION AS ONE OF THE IMPORTANT COMPONENTS IN TEACHING AND EDUCATION OF STUDENTS

In this article the questions connected with the problems of qualitative education of students in general education schools inьKyrgyz Republic on the background of further vocational training. The creative beginning, which is present in every pupil, should be to form, starting from the early years. The development of human capital is based on quality education, which implies Creation of an environment where a student can create and successfully develop individuality in conditions of active life position, based on humanistic principles of education. The search for of the most effective teaching methods is carried out at all stages of education, from preschool to higher education. education, the ultimate goal of which is to form such the end goal is to form a personality that is ready for independent life the end goal is to form a personality that is prepared to live independently.
THE PROBLEM OF DISTANCE LEARNING AS A FORM OF SOCIALIZATION OF STUDENTS

The article deals with the problem of the influence of distance learning on the socialization of students. The relevance of scientific work lies in the fact the distance learning can negatively affect quality educational process of students, motivation for learning activities, assimilation social norms, values and skills of students. Socialization is considered from the standpoint of structural-functional sociology and humanistic psychology. The following issues are considered: theoretical analysis of the phenomenon of socialization, description of distance learning, its relevance in the educational process, issues, disadvantages and advantages of distance learning that affect quality of education of students and their socialization.
Revealing the Future of Graphology-Based Students (Handwriting Analysis) and E-Bookcreator-Based Learning in State MA Salatiga

The aim of this research is how to know earlier their personality, intelligent, etc. through hand writing analysis or graphology method. And then the using of e-smart application, namely e-book creator, the population in this research is the students of grade XI, which amounts 165 students, the method of this research is use the ADDIE development model (Analysis, design, development, implementation, evaluation) which aims to lead or achieve effective learning, as the basics of stages in a coherent manner (nuszewski &amp; Molenda, 2008). There is progress the participation rate of the process of smart learning via Pra using e-book creator under 15% and Pasca using e-book creator more than 88%.
CodeSpider: Automatic Code Querying with Multi-modal Conjunctive Query Synthesis

Querying code conveniently is an appealing goal to the software engineering community. This work advances this goal by presenting a multi-modal query synthesis technique. Given a natural language description and code examples, we synthesize a conjunctive query extracting positive examples and ignoring negative ones, which is further used to query desired constructs in a program. To prune the huge search space, we generate well-typed query sketches for refinement by analyzing code examples and API signatures. We also introduce two quantitative metrics to measure the quality of candidate queries and select the best one. We have implemented our approach as a tool named CodeSpider and evaluated it upon sixteen code querying tasks. Our experimental results demonstrate its effectiveness and efficiency.
PERBANDINGAN DAN KOMBINASI KINERJA ALGORITMA LEAST SIGNIFICANT BIT DENGAN PIXEL VALUE DIFFERENCING PADA STEGANOGRAFI CITRA WARNA

One of the most common problems in this digitalization era is data security issues, such as being compromised by digital data. Actually, there are many ways to protect digital data, one of which is by using steganography techniques. Where the steganography technique is a technique for inserting a secret message into an image media. In this study, we will discuss how the performance of two teganographic methods, namely Least Significant Bit (LSB) and Pixel Value Differencing (PVD) and how the results if the two methods are combined in implementing color image steganography. To determine the quality of the method studied, MSE, PSNR, and SSIM were used as testing methods. As a result, the PVD algorithm on the red tifanny layer image obtained an MSE value of 0.051, PSNR 60,974, and SSIM 0.998. For the LSB algorithm, the flax image in the green layer obtained MSE values of 0.0039, PSNR 72.218, and SSIM 1.000. Finally, the combination algorithm between PVD and LSB on tifanny's image in the red layer obtained an MSE value of 0.054, PSNR 60,734, and SSIM 0.998.
KLASIFIKASI BUAH SEGAR DAN BUSUK MENGGUNAKAN ALGORITMA CONVOLUTIONAL NEURAL NETWORK DENGAN TFLITE SEBAGAI MEDIA PENERAPAN MODEL MACHINE LEARNING

CNN (Convolutional Neural Network) is one of the type of Deep Learning algorithm that can accept input in the form of images, or objects such as fruit, animals, office equipment, and so on. This CNN works is inspired by the neuron system in humans based on visual perception. The CNN model can be implemented into the Android system using TFLite. TFLite is a Machine Learning library specially designed for Android devices to create Machine Learning models in small binary and low latency. This can make it easier for Machine Learning researchers to use smartphones to develop the research system. Current technological advances make the fruit industry no longer use the manual fruit sorting process carried out by humans. The process of sorting fruit that is fit for consumption (fresh) and unfit for consumption (rotten) can reach hundreds and thousands, so it needs the help of machines to increase work speed. This fruit sorting process can be circumvented by creating a Machine Learning model that can classify fresh and rotten fruit which will then be processed by the system based on the desired output requirements. If the model can perform the classification well, then the fruit industry can take steps to make an automatic sorter by implementing the model into its system. This study aims to create a model with the CNN (Convolutional Neural Network) Algorithm and design a prototype system that can classify fresh and rotten fruit (red apples, bananas, and mandarin oranges) and apply the resulting model using TFLite on an Android Smartphone. The results indicated that the resulting prototype model can be used by users in the Android system. The results of the training model obtained an accuracy value of 98.20%. Meanwhile, the results of testing showed that the model can classify images from the same or different sources by 91.65% from 1090 images. These results indicate that the model is included in the excellent classification category.
Team Harmony before, during, and after COVID-19

Teamwork is integral to any computer science curriculum because it provides students with experiences that mirror the industry. Some students are resistant to working in teams because of the perceived inequities. Assessing individual participation and team dynamics can provide faculty with valuable information to design and deploy interventions to improve students’ teamwork skills and help dysfunctional teams.
Effect of Sports Rhythm Training on the STROOP Cognitive Function and Brain Function Quotient in Elementary School Students

The purpose of this study was to examine the effects of sports rhythm training program on the STROOP cognitive function and brain function quotient of elementary school students, and to suggest the effectiveness of cognitive function and brain health through physical activities of child and adolescents. The subjects of this study were 30 male elementary school students, and 15 exercise group and 15 control group participated in sports rhythm training regularly for 12 weeks and 3 days a week. The sports rhythm training program consisted of preparation exercise, main exercise, and arrangement exercise. The cognitive function of the items was measured by the STROOP word test, STROOP color test, and STROOP color-word test. The brain function index was measured and evaluated by the basic rhythm quotient, self-regulation quotient, attention quotient, activation quotient, emotional quotient, anti-stress resistance quotient, left, right brain correlation quotient, and brain quotient. The results of this study showed that the main effect (p.001) and interaction effect (p.001) were shown in the STROOP word examination, STROOP color test, and STROOP color-word test after participating in the sports rhythm training program for 12 weeks. In brain function quotient, main effect(p.001) and interaction effect(p.001) were shown in basic rhythm quotient, self-regulation quotient, attention quotient, activation index, emotion quotient, anti-stress resistance quotient, left and right brain correlation quotient, brain quotient. In conclusion, elementary school students who participated in the sports rhythm training program applied to this study showed significant effects on STROOP cognitive function and brain function. Therefore, it is expected that the sports rhythm training program will contribute to the improvement of the quality of life of adolescents when applied to the growth development program of child and elementary school students.
Evaluasi Pengelolaan Keuangan Sekolah Berdasarkan PSAK 45

Evaluation is the process of describing, obtaining, and presenting useful information to formulate an alternative decision. Evaluation is part of the management system, namely planning, organization, implementation, monitoring and evaluation. Financial management is planning, controlling, organizing, controlling resources related to funds so that the goals of an organization can be achieved. Financial management is very important because without financial management, finances cannot run properly and smoothly. Statement of Financial Accounting Standards (PSAK) No. 45 on Financial Reporting of Non-Profit Organizations. Non-profit organizations are usually engaged in services by providing services to the community. The forms of service also vary from education, health to religion.&#x0D; The objectives of this discussion are: (1) knowing financial management at Kosgoro High School, (2) knowing the financial reports at Kosgoro High School, Bogor City, (3) knowing whether the financial reports at Kosgoro High School Bogor City are in accordance with PSAK 45.&#x0D; The results of this discussion indicate that the financial management at SMA Kosgoro is in accordance with PSAK 45 but has not been fully realized according to the recommendations of PSAK 45.&#x0D; &#x0D; Keywords: Evaluation, financial management, PSAK 45
Workshop Review: Virtual workshop on AI and machine learning in geophysics draws global audience

A recent SEG workshop enabled discussion among participants from around the world on the application of machine learning and artificial intelligence (AI) to a number of geophysical methods, applications, and to geophysical data at various scales. Applications of Machine Learning and AI in Geophysics was organized by SEG's Eurasia Regional Advisory Committee and took place virtually from 10 to 13 May 2022.
Simple Extensible Programming through Precisely-Typed Open Recursion

In this abstract, we show that a small extension to the MLscript programming language gives a simple solution to the Expression Problem through precisely typed open recursion.
MAJALAH DINDING ELEKTRONIK DENGAN AUDIO AMPLIFIER MENGGUNAKAN IC LM386 UNTUK PENYANDANG TUNANETRA

Limitations in the sense of sight do not prevent the blind from getting the latest information even in the COVID-19 condition. An alternative solution is needed so that blind people can still get information without physical contact, such as in Braille. From this problem the researchers designed a wall magazine that makes it easier for blind people to get information by not touching common objects and avoiding direct contact with wall magazines in the form of sound that can be controlled by doing hand movements without touching braille but using sensors. By analyzing the regulation voltage at the source, input and output voltages on the amplifier, and the power amplifier using the LM386 IC on the device to work according to the component datasheet so that it can work properly according to its specifications. Audio amplification analysis on electronic wall magazine content with amplifier is also needed so that the visually impaired can get good information. From the research results, the gain works optimally at a gain value of 20 dB with a hearing distance of 7 meters, this is in accordance with the characteristics of the LM386 IC datasheet. The curves have the same issues, so the FFT analysis is the same which has an average range of 60 dB. With this research, it can help blind people to receivethe contents of electronic mail without difficulty.
Saratov’s plot in Yu. N. Chumakov’s letters

The article discusses the place of Saratov-based plot in Yu. N. Chumakov’s letters addressed to the author of the article. The subject of discussion in the correspondence is the defense of Yu. N. Chumakov’s dissertation at Saratov University in 1970 and its role in his scientific biography. The defense of the dissertation with Yu. M. Lotman as the first opponent became the key event of the Saratov plot and its climax. Having singled out fragments from the correspondence related to the plot of Saratov, the author seeks to explain the direction of the ensuing epistolary dialogue, why the defense of the dissertation was perceived by Yu. N. Chumakov as a more than significant event for him, especially in the context of his dramatic biography. The author proves that the defense was an explosion of the linear sequence of the text of life, which dramatically changed the fate of the scientist. The desire to talk in detail about the defense, to find out what impression it made, and to look at what was happening on that memorable day for him through the eyes of the addressee of the letter, betrayed the desire to read and interpret his fate again and again. Particular attention is paid in the correspondence to the personalities of such outstanding philologists, professors of Saratov University as A. P. Skaftymov and E. I. Pokusaev. Yu. N. Chumakov was not A. P. Skaftymov’s student and was not familiar with him, but specifically noted the acquisition and subsequent development of the principles of a scientific approach to the work, set out in his theoretical article in 1923. About the personality of E. I. Pokusaev, his supervisor, and the history of the relationship with him, Yu. N. Chumakov wrote in great detail. Having told about the role of E. I. Pokusaev, who supported the dissertation at the defense, and having outlined his complex, large and humanly attractive personality, Yu.N. Chumakov completes the plot of Saratov, which was very meaningful for him, primarily for self-understanding of his scientific path.
Blockchain in banking and financial services

Across the globe, many organisations from various industries are focusing on and moving towards adopting blockchain technology. The banking and financial sector is a leading example in which blockchain can serve as a game-changer to solve the existing challenges that the industry faces. To explore and outline the potential of blockchain technology in banking and financial services, this study aims to provide an overview of the advantages and applications of blockchain technology in banking and financial services. A critical analysis of extant literature on blockchain technology in banking and financial services revealed the superiority of this innovation in terms of lowering cost, increased transparency, disintermediation, improved data privacy and security, and reduced error solving and reconciliation. The technology can assist the financial services industry through various applications, including know your customer (KYC), trade finance, digital currency, taxing, capital markets, insurance, cross-border payments, etc. After understanding the enormous potential of blockchain technology in banking and financial services, the study highlights the various risks and challenges which should be considered while blockchain adoption. The study also illustrates the global scenario of multiple banks and financial institutions adopting blockchain technology.
Senior Responsibilities: Obligations That You Now Have As a Senior Engineer

As with every other job, when you add “senior” in front of your title, not only does the money go up but so do your responsibilities. I do have to preface this chapter with the fact that you have the option to not do anything that I tell you to do. If you do not want to mentor a junior or mid-level engineer at your job, do not do that! However, successful senior software engineers that will eventually be promoted to staff and principal engineers follow the same formula, and a lot of that is centered around human interactions and great technical understanding.
Of pandemics and progress

The COVID-19 pandemic has ushered in an unprecedented age of technological innovation. Many herald this as a mark of civilization and progress. But modern technologies are a double-edged sword for new health interventions: they offer both tremendous potential and significant risks, particularly as human bodies become reliant on the internet via devices and processes that affect safety and health, from body/GPS tracking technology to diagnostic monitoring. This chapter discusses five inquiries that warrant consideration for health tech intervention proposals in the era of the Internet of Bodies: definitions of progress and the types of claims they make, the implications of new technologies on human dignity, the ethics of revenue models, sustainability, and threat models of technology implementation.
Unscented Kalman filter with stable embedding for simple, accurate, and computationally efficient state estimation of systems on manifolds in Euclidean space

Abstract This article proposes a simple, accurate, and computationally efficient method to apply the ordinary unscented Kalman filter (UKF) developed in Euclidean space to systems whose dynamics evolve on manifolds. We use the mathematical theory called stable embedding to make a variant of UKF that keeps state estimates in close proximity to the manifold while exhibiting excellent estimation performance. We confirm the performance of our devised filter by applying it to the satellite system model and comparing the performance with other UKFs devised specifically for systems on manifolds. Our devised filter has a low estimation error, keeps the state estimates in close proximity to the manifold as expected, and consumes a minor amount of computation time. Also our devised filter is simple and easy to use because our filter directly employs the off‐the‐shelf standard UKF devised in Euclidean space without any particular manifold‐structure‐preserving discretization method or coordinate transformation.
Human behavior recognition based on residual generative adversarial networks

In order to improve the accuracy of human action recognition, a Residual Generative Adversarial Network (Res-GAN) method is proposed by combining the characteristics of Generative Adversarial Networks and Residual Networks. The generator uses an improved residual block extraction feature to obtain deep texture information and enhance the regularization of the model; residual blocks construct the discriminator. On the one hand, the accuracy of image feature extraction is improved, and the convergence speed of the network is accelerated. On the other hand, the discriminator performs the classification pre-training of human behavior recognition while distinguishing true and false samples. In order to avoid the influence of residual generative adversarial network generator on the recognition accuracy due to the instability of the reconstructed samples, the trained residual generative adversarial network discriminator was constructed as a classifier for human behavior recognition. Experiments on the KTH dataset demonstrate the effectiveness of the proposed method.