Reviewerly/exHarmony huggingface dataset:
Genetic Algorithm and Particle Swarm Optimization Techniques for Inverted Pendulum Stabilization

Inverted Pendulum is a popular non-linear, unstable control problem where implementation of stabilizing the pole angle deviation, along with cart positioning is done by using novel control strategies. Soft computing techniques are applied for getting optimal results. The evolutionary computation forms the key research area for adaptation and optimization. The approach of finding optimal or near optimal solutions to the problem is based on natural evolution in evolutionary computation. The genetic algorithm is a method based on biological evolution and natural selection for solving both constrained and unconstrained problems. Particle swarm optimization is a stochastic search method inspired by collective behavior of animals like flocking of birds, schooling of fishes, swarming of bees etc. that is suited to continuous variable problems. These methods are applied to the inverted pendulum problem and their performance studied.
Prognostic value of machine learning for acute heart failure

Abstract Funding Acknowledgements Type of funding sources: None. Background At onset of acute heart failure (AHF), various clinical fundamental parameters including vital sign, laboratory data, or initial treatment were investigated, and we can roughly estimate the prognosis. However, machine learning method for prediction of the prognosis was not studied. Purpose To elucidate prognostic value of machine learning for AHF comparing conventional statistical model. Methods We enrolled consecutive 300 patients with AHF (79.5 ± 12.1 years, 158 Males). Patients with acute coronary syndrome, mechanical circulatory support cases, and cardio-pulmonary arrest cases were excluded. The patients were randomly divided into 80% (240 cases) and 20% (60 cases), and the former was used as train data, and the latter as validation data. Objective variable was set as cardiac death in one year. First, logistic regression analysis with Akaike’s information criterion (AIC) was performed, and extracted predictive parameters. The predictive model for the cardiac prognosis was constructed by cut-off value of ROC curve analysis of propensity score was calculated. Next, machine learning (random forest method and deep learning) to build predictive model was performed with the predictors. Finally, accuracy of each predictive model was compared. Results Thirty cases showed cardiac death in one year. Logistic regression with AIC extracted 8 predictors, and the cut off-value of propensity score with the 6 parameters was 0.110. The accuracy was 0.714 and area under ROC (AUROC) was 0.836. Conversely, random forest method demonstrated the accuracy as 0.927, AUROC 0.860. On deep learning, the accuracy was 0.937 and AUROC 0.901. The top 4 high feature importance of random forest were Cl/red blood cell count/pH/Anion Gap. However, accuracy of those predictors was lower than that of machine learning. Conclusion Machine learning was a powerful tool to predict cardiac prognosis of AHF, comparing with conventional statistical model. Abstract Figure. Statistical model
In-Depth Analysis of Cryptographic Algorithms for Cloud-Database Security

Scientific computing in the present era has grown from a single fixed environment to a scattered or distributed environment. In this concern, the security of data becomes a major issue for every user. As per the present trend and scenario, Cloud Computing (CC) enables users to access enterprise applications from almost anywhere you have an Internet connection. Shifting to CC enterprises’ annual expenditure as well as maintenance are thought to be more effective, according to evidence. Fortunately, there seem to be a lot of challenges that arrive with the significant features of CC for data security. There are several techniques and algorithms to reach the goal of security concerns. In this paper, we have mentioned several security issues and made a comparative study on various cryptographic algorithms which is used in cryptography to overcome the security issues and archive information security goals.
Super-Resolution of 3D Magnetic Resonance Images of the Brain

Magnetic Resonance (MR) has a paramount dependence on the acquisition process, sometimes generating low-quality images useless for clinical diagnosis. One of the problems to be faced is the lack of enough resolution, which makes fine details of the brain inappreciable. Image Super-Resolution (SR) intends to solve an ill-posed problem to increase its resolution. The first approaches were based on the frequency and the spatial domain, extrapolating the high-frequency information from the low-resolution (LR) image, or regularization strategies, incorporating the prior knowledge of the unknown high-resolution (HR) image. Nowadays, deep learning (DL) has become the most competitive method to perform SR. Many models have been developed to enhance 2D slices only instead of using the 3D spatial information. This chapter begins with an introduction to the SR problem and goes over traditional and deep neural network models for 3D MR super-resolution. Finally, a compilation of the most recent methods is presented, compared quantitatively and qualitatively using the newest public datasets.
Mitigate the Side Channel Attack Using Random Generation with Reconfigurable Architecture

A side channel analysis is major threat in secure communication device. Here our object is very clear to protect the sensitive information by adding DNA cryptography with chaotic countermeasure method. To overcome the side channel issues. Due to the side-channel attack can retrieve easily sensitive information from crypto embedded devices. So that the reason we need to protect the sensitive information (encryption key) in crypto embedded devices by applying the random number generation method. Mostly the random number generation used in medical data transmission, information security, and all sensitive areas. So in the research work, we apply a random generation by using the chaotic circuit. And also the paper concentrate to realize the chaotic circuit in hardware using FPGA with partially reconfigurable. And also based on Lorenz’s chaotic circuit used to protect sensitive information. Simulation and Synthesis verification done by using the VIVADO tool. Security analysis is done by hierarchical UACI, NPCR, and correlation.
Pelatihan Penulisan Artikel Ilmiah Bagi Guru di SMAN 1 Tanjung Sakti PUMU Kabupaten Lahat

This training aims for teachers to be able to compose scientific papers, conduct citations and can increase teachers' awareness and understanding of the importance of writing scientific papers. The method of implementing activities in the form of training, workshops, mentoring, practicum and evaluation as well as follow-up. While the activities were carried out at SMA N 1 Tanjung Sakti Pumu, Lahat Regency. The target of this training is teachers at SMA N 1 Tanjung Sakti Pumu, Lahat Regency, which consists of 50 participants. The results of this training are increasing knowledge and being able to write scientific papers independently, increasing teacher awareness and understanding of the importance of writing scientific papers. Writing scientific papers appropriately and according to standards will certainly be able to improve teacher assessment and quality.
Motion Detection and Alert System

In the era of the internet and with an expanding number of individuals as its end users, countless trespassers are presented every day. In 2016, four Pakistani terrorists illegally entered into the Indian army base and carried out grenade attacks on the security forces. Thus, tracking the movement and the location of different trespassers and intervention of unknown or unauthorized persons with the assistance of Intruder Detection Systems is the proposed work in this paper. Intruder Detection System is a developing pattern in research in today's technological world. Existing investigations and with their use of technology show adequacy and poor approaching ability of AI in dealing with Intruder Detection Systems. In this research paper, we intend to clarify and improvise the identification pace of Intruder Detection System by utilizing OpenCV a built-in library in python.
Interactive Map Application For Real-Time Crime Reporting

Crime is very common in India and it happens in many different ways throughout the country. Along with violent crimes (like homicide, robbery, and assault), and property crimes (like burglary, theft, motor vehicle theft, and arson), there are also major problems with organized crime, illegal drug trade, illegal arms trafficking, corruption, and cybercrime as well. Surprisingly, location has a significant impact on crime in India, with Delhi at the top of the list with the highest crime rate among all Indian states. Crime prevention is critical to maintaining law and order in the country. Deterring criminals through the deployment of more police is one of the major strategies practiced [1]. Apart from an increase in crime rates, there has also been a sudden rise in unsolved cases and crimes, with culprits still at large. The major reason for this is a crime not being reported, minimal or no evidence against the offender, and corruption.In this paper, we address exactly that aspect of crime reporting which will minimize crime. The methodology proposed in this paper consists of two aspects: an android and a web application. These systems together can be used by police authorities to assist in curbing crime and to provide assistance to the victims or witnesses.
Proposed Enhanced Security on Face Recognition Technology for Mobile Devices

Although Face Recognition has many advantages over traditional technology (fingerprint, keystroke, Passwords, Pins, Patterns and voice) like feature used for protection and reduction risks of accessing other’s information without permission and provide fast and easy accessibility of the information stored in the device for authorized user. However, some of the systems can be fooled with a picture or video of a user’s face that can be unlocked by someone that looks similar to you (such as a twin), other point if the mobile phone user was kidnapped and be forced to unlock his /her device for Froude use. As mentioned above issues, they are still having a leakage about the security of information stored in the device according to their working algorithm. In this paper, we are proposing a way to enhance the security on face recognition for mobile devices by connecting the mobile device to the other wearable device in order to increase security on face recognition to the mentioned issues and ensure that the information is more secured.
The influence of labeling techniques in classifying human manipulation  movement of different speed

In this work, we investigate the influence of labeling methods on the classification of human movements on data recorded using a marker-based motion capture system. The dataset is labeled using two different approaches, one based on video data of the movements, the other based on the movement trajectories recorded using the motion capture system. The dataset is labeled using two different approaches, one based on video data of the movements, the other based on the movement trajectories recorded using the motion capture system. The data was recorded from one participant performing a stacking scenario comprising simple arm movements at three different speeds (slow, normal, fast). Machine learning algorithms that include k-Nearest Neighbor, Random Forest, Extreme Gradient Boosting classifier, Convolutional Neural networks (CNN), Long Short-Term Memory networks (LSTM), and a combination of CNN-LSTM networks are compared on their performance in recognition of these arm movements. The models were trained on actions performed on slow and normal speed movements segments and generalized on actions consisting of fast-paced human movement. It was observed that all the models trained on normal-paced data labeled using trajectories have almost 20% improvement in accuracy on test data in comparison to the models trained on data labeled using videos of the performed experiments.
An Innovative TRIZ Insight on the Pilot Test Run Issue in NPI Through Intelligent System

New Product Introduction (NPI) is one of the most crucial aspects in every company to survive in a competitive environment. NPI is a process where working prototypes are tested before launched into the market. Companies are expected to deliver new products with high quality just in time and with reasonable cost. In the NPI, companies often run pilot tests on new products to ensure their utmost quality before the products are approved for mass production. However, companies often face dilemma in conducting pilot tests because they requires investment of resources in terms of time and cost which could outweigh the benefits. Therefore, companies may run small sample size tests or skip the process due to tight budget and to meet the expected delivery date. Ideally, a pilot test should be run in adequately large sample size to expose and address potential quality problems before releasing the products to the customers. This study aims to suggest a solution to resolve the pilot test issue using Engineering Contradiction in inventive problem solving methodology (TRIZ). The inventive principle preliminary action suggests the possible solutions such as an intelligent system that can provide new insights on the pilot test run issue in the NPI.
Information System for Predicting Fisheries Outcomes Using Regression Algorithm Multiple Linear

Bireuen is one of the regencies in Aceh province which has quite a lot of potential for marine and fishery resources, both capture fisheries and aquaculture, because some areas in this district are coastal areas supported by several fish landing bases (PPI), namely PPI Kuala Jangka, Kuala Jeumpa, Peudada, Jeunip, Pandrah, and Bate Iliek which are supporting sectors of the regional economy. The importance of this research is so that the Department of Food Security, Maritime Affairs and Fisheries can estimate the catch of fish in the coming year so that it can be used in terms of policies to increase the fishery production sector. The method used in information systems research to predict fishery results Multiple Linear Regression Algorithm using two independent variables (X), namely, the number of motorized boats (X1), the number of rainy days (X2) and one dependent variable, namely the number of fish caught (Y). ). The steps taken in this research are data collection, calculation of each variable, completion of the elimination method, substitution to get constant values, coefficients and inserting constants and coefficients into the Multiple Linear Regression equation. Based on data obtained from 2016, 1017, 2018, 2019 and 2020 using the Multiple Linear Regression algorithm, the prediction results of the Tangka fishery in Bireuen Regency in 2021 are 12,813.88 tons.
ANALISIS PENGAMBILAN KEPUTUSAAN MENGGUNAKAN METODE ANALYTIC HIERARCHY PROCESS DALAM MENETAPKAN SISTEM OPERASI SMARTPHONE YANG TEPAT

The operating system has become a somewhat important part of the development of smartphones in the modern era. Several operating systems have also succeeded in helping several new smartphone brands participate in coloring the mobile gadgets business competition, which is developing in Indonesia. The interest of the Indonesian people to develop through the adaptation of the latest operating system technology is also very fast. However, this public interest tends to lead more to lifestyle than needs. This research was conducted to present an alternative smartphone operating system according to the needs and effectiveness of its use in the community using the Analytic Hierarchy Process model. The target community that tests in this study includes three groups, namely: lecturers, students, and employees. The final result shown by this model is in the form of an alternative decision of a smartphone operating system that supports the level of activity of using each group.
Secure and Efficient General Circuits Attribute-Based Access Control in Cloud Computing

The access structure of a general circuit can represent the access control policy flexibility and has broad applications in the field of dense data access control. All previous proposals are declared to support fined-grain access control for encrypted data and secure sharing in cloud. However, these schemes have their limitations, as the circuit nodes can only output layer by layer, and the circuit depth of the access structure implemented in the system is a fixed value. In addition, recent results show that these schemes have serious security defects, such as unresisting collusion attacks and vulnerability of the ciphertext stored in cloud. This article aims at solving the problems mentioned above and a scheme with improved efficiency and security is proposed. In the presented scheme, the circuit access structure with any depth less than or equal to the maximum depth is realized through equivalent conversion of circuit. By modifying the parameter form of shares, we solved the limitation that the previous scheme could only output layer by layer upward, and realized that each node could output to any node with a depth greater than its own across layers. This scheme greatly reduces the redundant computational overhead and improves the encryption and decryption efficiency.
Key-Region and Layout Learning for Contract Intelligent Identification

Multimodality has become the main means of multimedia information analysis and understanding. Researchers at home and abroad have achieved good results in the field of multimodal learning. In this study, we introduce a new multimodal data representation to deal with the unstructured visual rich document understanding task. By introducing the key area features detected by the target, combining the two dimensional position information, we splice it into text embedding and image embedding, and input it into the transformer. This method not only retains the layout information of the document, the alignment learning between image and text is enhanced. The experimental results show that our model has a good effect on the public datasets FUNSD and DocVQA.
Towards Internet Of Secure Elements

This poster introduces the Internet Of Secure Elements (IOSE) infrastructure. IOSE enables the deployment of personal Hardware Secure Module (HSM), based on secure element (SE) grid, providing secure storage and tamper resistant computing resources.
Sensing and Control of Autonomous Driverless Car on Road (SCAD)

Intelligent robot navigation has gained numerous attentions from the space, transportation, and industrial areas. It is a vital part in making the robot moves autonomously in various static and dynamic conditions. In robot navigation, a camera becomes the main sensor of the sensing of the environment. Any inputs that come across the camera (the eyes of the robot) will then be sent to the image processing system with an algorithm that can decide the navigation of the robot. The real-time image processing for this project is using OpenCV with C++. The controller for the navigation is using Arduino. This study is divided into two sections which are vision image processing and robot navigation control. In this paper, only the vision image processing section are discussed.
Development of the algorithm to ensure the protection of confidential data in cloud medical information system

The main purpose to ensure the security for confidential medical data is to develop and implement the architecture of a medical cloud system, for storage, systematization, and processing of survey results (for example EEG) jointly with an algorithm for ensuring the protection of confidential data based on a fully homomorphic cryptosystem. The most optimal algorithm based on the test results (analysis of the time of encryption, decryption, addition, multiplication, the ratio of the signal-to-noise of the ciphertext to the open text), has been selected between two potential applicants for using (BFV and CKKS schemes). As a result, the CKKS scheme demonstrates maximal effectiveness in the context of the criticality of the requirements for an important level of security.
Mathematical Foundations of Data Science Using R

In order best exploit the incredible quantities of data being generated in most diverse disciplines data sciences increasingly gain worldwide importance. The book gives the mathematical foundations to handle data properly. It introduces basics and functionalities of the R programming language which has become the indispensable tool for data sciences. Thus it delivers the reader the skills needed to build own tool kits of a modern data scientist.
I’m Trying to Love Rocks; by Bethany Barton

Reviewed by: I’m Trying to Love Rocks; by Bethany Barton Elizabeth Bush Barton, Bethany I’m Trying to Love Rocks; written and illus. by Bethany Barton. Viking, 2020 [40p] Trade ed. ISBN 9780451480958 $17.99 E-book ed. ISBN 9780451480965 $10.99 Reviewed from galleys R 5-7 yrs Barton (author of I’m Trying to Love Spiders, BCCB 10/15) returns to nudge skeptical kids to adopt—or at least consider—a new enthusiasm. Unlike spiders, which can be scary, the psychological obstacle rocks must overcome is, frankly, their strong reputation for being boring. “Hmmm,” says the narrator. “It turns out rocks don’t really do much. Maybe we should poke it? . . . It’s still not doing anything. Welp, that didn’t work. Maybe the next book will be better. THE END.” Not so fast, though. A dark-skinned, curly-coifed rock lover takes on the narrator with a fully engaged and engaging lecture on all the ways geology is amazing—volcanoes!, diamonds!, fossils!—and firmly tamps down any snarky narrator comment to the contrary. Correct scientific vocabulary and plenty of diagrams make this curriculum ready, while several opportunities for a little tactile (if make believe) interaction with the rocks will appeal to viewers taking this on in a smaller setting. Endpapers offer tacit congratulation to listeners who actually moved the needle on their human/rock relationship, with an assortment of specimens in front labeled “rock” and the same specimens labeled by specific name in the back. Copyright © 2020 The Board of Trustees of the University of Illinois
Crosstalk creates a more secure source of randomness based on quantum phenomena

Using a drawback of the quantum channel for randomness generation
DEVELOPMENT OF A PROTOTYPE SYSTEM FOR WRITING A SCIENTIFIC ARTICLE

This article offers the reader to get acquainted with the prototyping of an information system for the preparation and writing of a scientific article. The article also discusses the functionality of this system and its functionality.
Typology of Tasks for Establishing Numerical Patterns in Elementary School

The article discusses the expediency of forming in elementary school the intellectual ability to recognize patterns in the surrounding world. Based on the analysis of the available literature, the article reveals the concepts of "regularity", "task for establishing patterns", characterizes the features of the methodology for teaching younger schoolchildren to establish graphic and numerical patterns. The subject of the article is primarily numerical patterns, in connection with which cyclic, increasing, decreasing, as well as mixed numerical patterns that underlie tasks for their identification are described. For some types of tasks, examples of the use of numerical patterns are given: when systematizing, generalizing the program material of the initial mathematics course; checking the level of formation of the corresponding computational skills; preparation for the development of new computational techniques.