Reviewerly/exHarmony huggingface dataset:
Properties of the Digital Image

The digital image has become an important carrier of information that supports diagnostics and therapeutics in medicine. Today there are a number of different imaging modalities that each reflects different tissue properties and are based on different technical principles. Together these techniques form a tremendous arsenal for patient diagnostics. Although the underlying physical and technical principles differ between modalities, there are some common principles in medical imaging. A basic understanding of the components of the digital image, how its information can be displayed and analysed, as well as its inherent limitations, is important for an adequate use. The ambition to use a common terminology and knowledge base to describe basic image properties is regarded important to maintaining a framework that enables translation of knowledge between the different specialties, of benefit for future development of the medical imaging field.
A Study on Human-to-Human Position Estimation using RSSI in a Real Environment

In recent years, the importance of visualizing the physical distance between people has increased with the epidemic of the new coronavirus. Furthermore, the technology to visualize the physical distance between people is expected to be applied to many fields in preventing traffic accidents caused by contact between people and in measuring social communication with maintaining a safe distance. In this paper, we propose a position estimation method using received signal strength indicator (RSSI), describe a technique that enables people to estimate each other's positions, and evaluate the effectiveness of the proposed method by simulations and actual experiments. The position estimation was performed by calculating the RSSI values of the surrounding environment, with a human as a radio transmitter and receiver in a 3D model built to imitate the real environment, and simulations and experiments were performed by changing the shape of the environment.
A Study on the Prevention of Sexual Abuse Against Preschool-Aged Children in a Community Area

Purpose: The purpose of this study was to investigate the degree of parental education for preschoolers’ sexual abuse (PSA) prevention and the appropriateness of the education topics for PSA prevention on parents in G city. Methods: Participants were 139 parents (64 fathers, 75 mothers) of preschoolers. Data were collected by a self-administered questionnaire conducted from April 22 to 24, 2013, and analyzed using prevalence rate, mean score, independent samples t-test, and one-way ANOVA with the SPSS 20.0 software. Results: The prevalence rate of parental education for PSA prevention was 62.6%. The prevailing parental education method was communication with children (87.0%). The mean score of parental education for PSA prevention was 2.60±1.05, while the appropriateness of the education topics for PSA prevention was 4.43±0.55. In addition, parental education for PSA prevention was significantly different from previous participation in parental education (t=3.07, p =.003). Conclusion: The results of this study suggest that more effective education for the prevention of child sexual abuse can be obtained by developing and offering programs that allow parents to educate themselves through the selection of educational subjects related to the prevention of sexual abuse of preschoolers.
Estimation of aggregate losses of secondary cancer cases using PH Panjer class (a,b,1) distributions,

This research in-cooperates phase type distributions of Panjer class $(a,b,1)$ in estimation of aggregate loss probabilities of secondary cancer. Matrices of the phase type distributions are derived using Chapman-Kolmogorov equation and transition probabilities estimated using modified Kaplan-Meir and consequently the transition intensities and transition probabilities. Stationary probabilities of the Markov chains represents $\vec{\gamma}$. Claim amount are modeled using OPPL, TPPL, Pareto, Generalized Pareto and Wei-bull distributions. PH ZT Poisson with Generalized Pareto distribution provided the best fit.
FEATURES OF DIGITALIZATION IN THE FIELD OF EDUCATION

The article considers the need to digitalize the sphere of education, the basis for the use of digital tools, its role and the advantages of using in the organization of the educational process in modern conditions of global digitalization. The necessity of mastering digital competencies by both teach-ers and trainees according to the corresponding training program is considered. The dynamics of the provision of e-learning facilities for students in higher education organizations, the dynamics of gradua-tion in the areas of training «Informatics and Computing», «Information Security» in 2017–2019 were analyzed.
IMPERFECT KNOWLEDGE BASE SELF-ORGANIZATION IN ROBOTIC INTELLIGENT COGNITIVE CONTROL: QUANTUM SUPREMACY ON BIG DATA ANALYSIS

The smart control design with secured achievement of information-thermodynamic trade-off interrelations is main goal for quantum self-organization algorithm of imperfect KB.Quantum genetic algorithm applied on line for the quantum correlation's type searching between unknown solutions in quantum superposition of imperfect knowledge bases of intelligent controllers designed on soft computing.Disturbance conditions of analytical information-thermodynamic trade-off interrelations between main control quality measures (as new design laws) discussed.Sophisticated synergetic quantum information effect in autonomous robot in unpredicted control situations) and swarm robots with imperfect KB exchanging between "master -slaves" introduced.A new robust smart controller on line designed from responses on unpredicted control situations of any imperfect KB applying quantum hidden information extracted from quantum correlation discussed.Within the toolkit of classical intelligent control, the achievement of the similar synergetic information effect is impossible.
College Management System using Salesforce

College Management system is Salesforce CRM based application which is the new technical way to manage all department related jobs. Collage management system is helpful for students as well as the colleges. In the existing system all the activities are done manually. It is very costly and time consuming. In our proposed system, students can view results using phones. The data will be stored in the Salesforce. The Admin, Faculty or the student should be a register user. The faculty can login into their college account through the application itself and update the academic result like internal exam marks obtained by the students. In this system students have easy access for viewing the marks; the application will check user authentications. Students are not permitted to manipulate any data. The proposed work has two modules: A. Student B. Teacher C. Admin. In the student’s module, students need to register their university registration number, college registration number, student name. Admin module maintains the student’s marks of internal college exams. Other than this the advanced features are: In case of natural calamities such as floods, etc. notification to students will be sent from admin office through application directly. Any new notice for a particular semester will be uploaded by professor through application notifying to respective semester students. The students can download different subject notes according to their departments. The faculty of particular department is responsible for updating the assignments, updating the attendance of every student, updating the notification related to department.
Formatting and Scanning Strings

In this chapter, I describe the standard library features for formatting and scanning strings. Formatting is the process of composing a new string from one or more data values, while scanning is the process of parsing values from a string. Table 17-1 puts formatting and scanning strings in context.
Finite Sample Forecast Properties and Window Length Under Breaks in Cointegrated Systems

The author shows that extending the estimation window prior to structural breaks in cointegrated systems can be beneficial for forecasting performance and highlights under which conditions. In doing so, the author generalizes the Pesaran and Timmermann (2005)’s forecast error decomposition and shows that it depends on four terms: (1) a period ahead risk; (2) a bias due to a conditional mean shift; (3) a bias due to a variance mismatch; (4) a gap term valid only conditionally. The author also derives new expressions for the estimators of the adjustment matrix and a constant, which are auxiliary to the decomposition. Finally, the author introduces new simulation-based estimators for the finite sample forecast properties which are based on the derived decomposition. The author’s finding points out that, in some cases, parameter instability can be neglected by extending the window backward and forecasters can be insured against higher forecast risk under this model class as well, generalizing Pesaran and Timmermann (2005)’s result. The author’s result gives renewed importance to break tests, in order to distinguish cases when break-neglection is (not) appropriate.
SPECIAL ASPECTS OF COGNITIVE FLEXIBILITY OF THE LABOUR MARKET MEMBERS OF NOVOSIBIRSK

The level of a person’s activity in the labour market mainly depends on the development of cognitive flexibility – mental ability characterizing the skill of an individual to transform cognitive attitudes adapting to new requirements of the present. The paper presents the results of measuring the cognitive flexibility of labour market members (on a sample of 380 professionally active residents of Novosibirsk). The authors measured cognitive flexibility using the Dennis &amp; Vander Wal Cognitive Flexibility Inventory (CFI) questionnaire adapted for the Kurginyan &amp; Osavolyuk Russian-speaking sample. The respondents were interviewed using the Google Forms anonymous survey tool. The paper aims at the study of special aspects of cognitive flexibility of Novosibirsk labour market participants. The authors studied the relations between the personal data of labour market participants (gender, age, education, marital status, financial situation, degree of activity in professional self-development) and cognitive flexibility (integral indicator and Alternatives and Control scales. The study identified that the respondents of the senior generation had a higher degree of activity in professional self-development and family people had the lower one. The Cognitive Flexibility integral indicator is most positively associated with the level of material well-being of the respondents, their involvement in the professional self-development. The authors mention gender dependence of the respondents’ cognitive flexibility indicators: the integral cognitive flexibility indicator and the Alternative scale indicator are higher in women, and the Control scale indicator is higher in men.
Mortality Prediction in the ICU: The Daunting Task of Predicting the Unpredictable

How to cite this article: Kumar AAK. Mortality Prediction in the ICU: The Daunting Task of Predicting the Unpredictable. Indian J Crit Care Med 2022;26(1):13-14.
A Coverage Flight Path Planning for Multiple Multicopter to Apply on Huge Area

We propose the development of a coverage flight planner that solves the domain coverage problem for the use of multicopters in wide-area surveys and other applications. In such multicopter application cases, collision-free and efficient coverage flight path planning is necessary. In this paper, two approaches to domain decomposition are separated and their optimality is discussed. In addition, a system is developed and demonstrated to set a flight path that is sub-optimal for each region. As a result, each of the two region partitions showed a good evenly divided region, and the flight paths designed on the two region partitions were also efficiently generated. In addition, flight tests of two multicopters were conducted using the generated flight paths.
Cross Domain Aspect Extraction Using Various Embedding Techniques and Language Models

In this age of ecommerce where most of the purchases are done by customers on the basis of online reviews of products and services, sentiment analysis is of prime importance for all businesses. Aspect Term Extraction (ATE) helps in the identification and association of sentiments with the different aspects of the products. Aspect Extraction has been tried out using various Deep Learning techniques. This includes running them for more epochs and various types of hyper parameter tunings. Though they all do well in the same-domain, they do not predict well in the unseen-domains. In this paper, we have implemented and tested Bidirectional Encoder Representation for transformers (BERT) with attention in aspect detection across domains. We see that BERT with attention gives good results in in-domain as well as unseen-domains aspect identification. Extensive experiments have been carried out using ten datasets using various algorithms and embeddings. In all the scenarios, it is noted that BERT with attention gives superior cross domain prediction results with minimal training as compared to all of the other algorithms using Deep Learning techniques.
Using the Go Tools

In this chapter, I describe the Go development tools, most of which were installed as part of the Go package in Chapter 1. I describe the basic structure of a Go project, explain how to compile and execute Go code, and show you how to install and use a debugger for Go applications. I also describe the Go linting and formatting tools.
Determinants of informal entrepreneurship in Africa

This study investigates the determinants of informal entrepreneurship in Africa. Using a cross-section of 21,954 firms from 47 African countries, the study estimates several multivariate models to examine the factors that are associated with the decision of firms to register at the start of their operation and the length of time to remain unregistered. The findings show that entrepreneurship in the informal sector is complex and context-bound as contextual factors unique to Africa, such as, corruption, political instability, crime rate, infrastructure (electricity and transportation), and access to land and finance, influence the entrepreneur's decision to register their firm at the start of its operation. The length of time firms remain unregistered is shown to be positively correlated to access to finance and infrastructural availability and negatively related to crime and political instability. These results vary based on the size of the business with larger businesses being impacted less by these variables.
Realization of Visualization of Character Relationship Based on Relationship Graph

Through big data analysis, a multi-level and multi-dimensional tag database of leading cadres has been constructed. Based on the statistics of the characteristics of data information, establish staff position tags, organization tags, and key event tags for common information to achieve rapid screening and analysis of data information. Finally, the four relationship dimensions of the personnel are displayed in the form of data visualization, namely, former colleagues, current colleagues, fellow villagers and alumni.
PIM2R: Packet interactive multi-media response for frugal, effective and scaled last mile connectivity

Till date, despite of having a very high mobile penetration, effective last mile connectivity is still a challenge. This disconnect is primarily with respect to assimilation and interpretation of online data. It leads to impaired economic progress of society. One of the reason is illiteracy or semi literacy. IVR's do significantly good job in providing the information to the user's despite of their literacy level. However, IVR is very capital intensive investment. To address this challenge, we developed PIM2R framework. It is an IVR like framework on mobile phone providing interface in native voice / text language. This framework is analogous to soft switch and offers internet scalable IVR capability. Significant efforts were put for doing the user study and applying design thinking principles to come up with standardized interface. Focus of design was on Basic Emergent Users. In last few years, we piloted few applications based on this framework in the field. We present two representative case studies. First case study is from telecom domain. We developed customer care application and piloted with a large mobile service provider. We also present an architecture integrating PIM2R framework in a typical mobile carrier infrastructure. It was used by several tens of thousands of customers and found it very useful. Second study is from agriculture domain. We developed, Mandi price, an application to provide real time trends data related to spot and future prices of agriculture commodities to illiterate farmers. First use case resulted in significant saving in customer interaction cost. In second use case, since there were many variables, it is really difficult to attribute saving by virtue of using this application, however farmers were confident about the rates and trend in soybean prices. They took informed decision when and how much to sell. At present, modified version of this framework is being used to service farmers in India.
Graph Convolutional Neural Network Using Wavelet Transform

Convolutional Neural Networks have brought great advancement in the field of deep learning. Graphs can be used to represent information in a natural way in many important areas of interest. CNN on graphs can be formulated either using a spatial or spectral approach. In this work, we propose a framework for designing a convolutional neural network on graphs where convolution is performed in the spectral domain. We are interested in defining the filters for convolutional layers using the wavelet transform. Wavelet transform has attracted much attention in recent years for the purpose of signal processing. The property that makes it desirable is that it can provide the time and frequency resolution of signals. The experiments have been conducted on the benchmark dataset, Cora, and the accuracies obtained with our proposed models are comparably high.
String Processing and Regular Expressions

In this chapter, I describe the standard library features for processing string values, which are needed by almost every project and which many languages provide as methods defined on the built-in types. But even though Go defines these features in the standard library, a complete set of functions is available, along with good support for working with regular expressions. Table 16-1 puts these features in context.
A Novel Path Planning Approach with Bidirectional A* Algorithm Based on Road Characteristics

The global path planning of a traditional A* algorithm is investigated to obtain the shortest path, which considers only the straight-line distance between grids without considering the effects of road slope and road resistance on the path distance and the energy consumption for ground vehicles. The heuristic function of shortest path based on road slope and the heuristic function of minimum energy consumption based on road resistance coefficient are respectively developed in this paper. Combining the two improvements, a novel comprehensive heuristic function is proposed in this paper. Through the distribution of weight coefficients between the shortest path and the minimum energy consumption, one more reasonable path can be obtained. In addition, a bidirectional A* search algorithm is also applied. The case studies validate that the improved A* search algorithm in this paper can generate a more reasonable path considering the distance and the energy consumption.
Effect of Fringe Patterns of Fizeau Interferometry According to Optical conditions

The optical method using a laser interferometry is used to measure a tiny displacement of less than 1 μm/fringe. The Fizeau interferometry has an important advantage of easy adjustment of the optical setup. Since the reference beam and the object beam have almost the same path, it is possible to construct a stable system in which the influences on the surrounding environment are compensated for each other. In this paper, Fizeau interferometer was constructed to measure the shape or out-of-plane displacement of an mirror-like surface of the object over the entire area. The fringe pattern formed under various optical conditions was evaluated using the optical mirror as a specimen. It is found from the result that making collimated beam illuminate on the optical flat at an inclined angle can obtain clearer interference fringes.
Researchers’ Perceptions of Research Data Management Activities

This study investigated researchers perceptions of RDM at the MGGL to recommend measures to enhance managing, sharing, and reusing data. The study was underpinned by the DCC Curation lifecycle model and the CCMF which enabled the investigator to employ a descriptive research design to purposively capture data from a broad cross-section of 330 researchers. The data was analysed using SPSS to generate descriptive and inferential statistics that enabled the Investigator to answer the problem.Study findings demonstrate no explicit policies to guide each stage of data curation and capabilities. There were also inadequacies in the knowledge and skills capability, technological infrastructure and collaborative partnerships. Overall, RDM faced challenges in all the examined capabilities. These challenges limited managing, sharing, and reusing data.The study recommends establishing a CMU within the MGGL to oversee the implementation of RDM activities by assembling all the needed capabilities to support data curation activities and enable efficient managing, sharing and reusing research data
Applying Cryptography in E-Banking Security

Electronic Banking that is furthermore define as E –Banking. It could be a supply of getting information concerning bank and its various administrations by means of web. E - Banking is at present the crucial substance of Banking administrations. Information innovation has purchased real changes inside the operational setting of the Banking sector. The creative strategies upheld by banks square measure inside the kind of programmed teller machine Machines – ATM's, on-line Banking, phone Banking, Mobile Banking and so on,. the wellbeing and protection of the learning is that the real concern on the whole web Banking techniques. Additionally the web keeping money industries inclined to assaults related with client validation. The objective of this paper is to discuss various encoding systems upheld science advancements and audit various methods for security in E-Banking
Integrating Policy Reuse with Learning from Demonstrations for Knowledge Transfer in Deep Reinforcement Learning

Transfer learning (TL) assisted deep reinforcement learning (DRL) has attracted much attention in recent years, which aims to enhance reinforcement learning performance by leveraging prior knowledge from past learned tasks. However, it still remains challenging to conduct positive knowledge transfer when the target tasks are dissimilar to the source tasks, e.g., the source and target tasks possess diverse environmental dynamics. Taking this cue, this paper presents an attempt to explore TL in DRL across tasks with heterogeneous dynamics towards enhanced reinforcement learning performance. In particular, we propose to combine policy reuse and learning from demonstrations for knowledge transfer in DRL. It allows multiple learned policies in separate source tasks to adaptively fuse to generate a teacher policy for the target task, which will be further used for knowledge transfer via learning from demonstrations to boost the learning process of the target DRL agent. To evaluate the performance of our proposed method, comprehensive empirical studies have been conducted on continuous control tasks, i.e., Reacher and HalfCheetah. The obtained results show that the proposed method is superior in contrast to recently proposed algorithms in terms of both accumulated reward and training computational cost.