Reviewerly/exHarmony huggingface dataset:
Remainder with Threshold Substitution Data Hiding Scheme: Counterexamples and Modification

A well-known data hiding scheme, Remainder with Threshold substitution (RT), is analyzed. RT uses a threshold value, T, and two moduli numbers, mu, and ml, ml<mu, to embed secret data into a cover image. RT does not impose any divisibility constraints on the selection of the parameters, T, mu, and ml, and its correctness (i.e., the data extracted are always the same as the data embedded) is not proved. By counterexamples constructing, we show that RT works for them incorrectly. Also, RT scheme uses pseudo-random number generator (PRNG) to define a pixel for embedding of the next secret bit portion. PRNG can produce repeated values leading to the repeated embedding into the same pixel, thus overwriting previously embedded secret and preventing its correct extraction. We modify RT scheme (by imposing divisibility constraints on the threshold, moduli values, and PRNG), and prove correctness of the modification. Note that in the reported experiments on RT, its parameters used, T=160, and (ml, mu) from (4, 8), (16, 32), exactly satisfy our constraints, and, thus, the scheme may be correct for such settings.
THE DIGITALIZATION PROCESS IN SUB-SAHARAN AFRICA: ISSUES AND WAYS OF DIGITAL ECONOMY DEVELOPMENT IN SUB-SAHARAN AFRICA

ІІ International Scientific Conference Modern Economic Science Development in the Context of Digitalisation : Conference Proceedings (September 22–23, 2023). Riga, Latvia : Baltija Publishing, 148 pages.
A Dataset and Post-Processing Method for Pointing Device Human-Machine Interface Evaluation

The evaluation of human-machine interfaces (HMI) requires quantitative metrics to define the ability of a person to effectively achieve their goals using the HMI. In particular, for pointing-device type HMIs such as the computer mouse, an experiment quantifying movement by performing repetitive target selections allows defining a useful metric known as throughput (TP) using the Fitts’ Law test. In this work, a dataset obtained from an automated protocol application is presented, which is made publicly available through an on-line platform. A post-processing method to obtain performance parameters from the dataset is also presented, and its output is used to validate the data against similar experiments in the literature.
Classification of COVID-19 Symptoms Using Multilayer Perceptron

The COVID-19 virus had easily affected people worldwide through direct contact. Individuals diagnosed with positive COVID-19 virus may be affected with many symptoms, such as fever, tiredness, dry cough, difficulty in breathing, sore throat, chest pain, nasal congestion, runny nose, and diarrhea. An individual can also be diagnosed with COVID-19 even when he does not have any symptoms or be in contact with an infected person. Data classification was required due to the size of COVID-19 data that will be analyzed for future countermeasures determination. Some problems in data classification occurred due to unorganized data, such as time consumption, human error in complexity of symptom features and the diagnosis process data needed expert knowledge. This study aimed to use the artificial neural network (ANN) approach, which was multilayer perceptron (MLP) to classify the COVID-19 data by using patient symptom data. The MLP process involved data collection, data normalization, MLP design, MLP training, testing, and MLP verification. From the experiments, the MLP method was able to obtain an accuracy rate of 77.10%. In conclusion, the MLP method could classify the COVID-19 data and achieve a high accuracy rate
Proposed Secure Hypertext Model in Web Engineering

Secure web application development is one of the prime challenges for the software industry. In the last decade, web applications have rapidly developed but web engineering methods have some limitations while designing web applications. The extensive literature survey explores various concepts like web engineering, hypertext modelling, web applications hypertext modelling methods, attacks on web applications, same origin policy (SOP) and cross origin resource sharing (CORS). The complexity of web pages is a major concern for security. The proposed secure hypertext model (SHM) provides hypertext modelling of web applications and helps in the identification of attacks on hypertext links. It provides security stereotypes and precisely specifies vulnerability defences in web application design. This standardized attack vector and defence mechanism will help developers to build more secure applications.
A Story of Four Documentation Designs for One Medical Device: User Experience Analysis and Recommendations

This paper critiques the design of four instruction manuals in diverse modalities developed for a COVID-19 home test kit. Drawing from usability and user experience research and critical document analysis tools, the paper systematically describes the visual design and content of the print instruction manuals. Employing accessible design theory embedded in video evaluation and web accessibility guidelines from WCAG 2.0, it also analyzes a mobile app and a video guide included in this COVID-19 home test kit. The paper raises a number of questions about designing pandemic era emergency instructions and communications for blind users. The authors emphasize that the context of use is central to designing accessible instructional media in medical devices for disabled populations. The paper further stresses the need to understand the overall ecosystems within which products and their documentations function for these users, which have been complicated by the mixing of print and digital interfaces.
Strategy To Build Public Awareness In Preventing Online Fraud Crimes In The Jurisdiction Of The Cimahi Police

This research is motivated by the negative impact of the development of information technology, especially the internet, which has caused an increase in cases of cyber crime. The number of victims in this type of crime is partly triggered by low public awareness. Therefore, this research is aimed at explaining appropriate strategies for building public awareness in preventing online fraud crimes in the Cimahi Police jurisdiction. The theories used in this research are criminology theory, rational choice theory, social control theory, planned behavior theory, communication theory, and social psychology theory. This research method was carried out through a qualitative approach, using data collection techniques through interviews, observation and data documentation. The research results show that cases of online fraud at the Cimahi Police are increasing along with technological developments and increasingly widespread internet connectivity. This crime has detrimental social and economic impacts on victims, including financial losses and psychological impacts. Therefore, appropriate steps are needed to increase public understanding of the risks and tactics of online fraud. A number of strategies that can be used to build public awareness in preventing online fraud crimes include: adopting a continuous education approach, strong public awareness campaigns need to be introduced through various media, collaboration with the private sector, especially e-commerce and banking platforms, developing complaint applications digital tools that enable people to report fraud easily and safely, adequate law enforcement training in digital investigations must be a priority, implementing victim protection programs, establishing partnerships with schools and integrating cyber security education in educational curricula, as well as conducting data analysis and prediction of online fraud trends the new one.
Vision Enhancement System for Foggy Weather in Opencast Mines

The presence of fog and smog in the environment hinders the visibility of heavy earth-moving machinery operators in opencast mines. The paper describes an intelligent driving assistance system to enhance the drivers’ visibility in opencast mines during harsh weather conditions. The system integrates different devices like proximity radar, infrared cameras, global navigation satellite systems (GNSS), wireless devices, anti-collision laser lights, and image processing algorithms (image dehazing, image stitching, and object detection using artificial intelligence technique) for assisting the drivers to navigate in dense foggy conditions. The system aids the operators in driving during dense fog environments, generates an audio-visual alarm while facing any obstruction, and mitigates colloidal vehicle accidents. The final processed output of cameras, GNSS-based navigation using 3D geo-tagged digital mine map, and proximity radar are displayed on the dashboard screen fitted in forward-facing of driver’s seat. The system incorporates artificial intelligence, image processing techniques, and advanced analytics for dehazing foggy video footage, proximity warning, object detection, and fleet management.
Science Behind Observations

Global climate change is one of main concern of modern society. To estimate this change usually one estimates the global mean temperature. Measuring and calculating the Earth's average temperature are multi-steps complex processes which combine data from various sources and use statistical techniques. Nowadays, the dataset containing the spatial-temporal data about Earth's temperature is readily to use. Although scientists claim that to be able to achieve an accuracy of a few tenths of a degree, the main question is not the accuracy but, does the global mean temperature make sense at all? It is shown that the existing methodology of determining the global mean temperature is quite inappropriate and in long term creating wrong science. A new methodology is introduced, concerning energy budget of heating and cooling of the Earth. The total influence of the atmosphere in global warming can be easily estimate by comparison with the Moon's temperature as a bare body. 'The potential temperature for cooling' is introduced as a right parameter to estimate global warming trend and climate change. Using the new methodology in temperature's averaging, many surprising results would be expected and would give right insight about the climate change. Key words: climate change, the average planet's temperature, greenhouse effect, modelling
Analysis for satellite-based high-dimensional extended B92 and high-dimensional BB84 quantum key distribution

A systematic analysis of the advantages and challenges associated with the satellite-based implementation of the high dimensional extended B92 (HD-Ext-B92) and high-dimensional BB84 (HD-BB84) protocol is analyzed. The method used earlier for obtaining the key rate for the HD-Ext-B92 is modified here and subsequently the variations of the key rate, probability distribution of key rate (PDR), and quantum bit error rate (QBER) with respect to dimension and noise parameter of a depolarizing channel is studied using the modified key rate equation. Further, the variations of average key rate (per pulse) with zenith angle and link length in different weather conditions in day and night considering extremely low noise for dimension d=32 are investigated using elliptic beam approximation. The effectiveness of the HD-(extended) protocols used here in creating satellite-based quantum key distribution links (both up-link and down-link) is established by appropriately modeling the atmosphere and analyzing the variation of average key rates with the probability distribution of the transmittance (PDT). The analysis performed here has revealed that in higher dimensions, HD-BB84 outperforms HD-Ext-B92 in terms of both key rate and noise tolerance. However, HD-BB84 experiences a more pronounced saturation of QBER in high dimensions.
Vital Media: Making, Design, and Expression for Human and Other MaterialsVital Media: Making, Design, and Expression for Human and Other Materials, by Michael NitscheCambridge, MA: The MIT Press, 2022, 222 pp. PB 9780262544580. US$35.00.

Click to increase image sizeClick to decrease image size Additional informationNotes on contributorsMaria Smith BohannonMaria Smith Bohannon is an Assistant Professor of Graphic Design at Oakland University. smithboh@oakland.edu
Application of Two-way Fixed Effects Regression on the Error Analysis of Seismic Magnitude Estimation: Hypotheses, Theory and Testing

Seismic magnitude has been an indistinct concept since modern seismology was established. The author discusses it thoroughly , provides an general expression of definition that is only relevant to the source characteristics and explains the magnitude conversion problem physically. Based on the essential understanding of magnitude estimation problems, the author introduces a method called two-way fixed effects regression, which has been applied in seismology since Keiiti Aki studied the properties of coda waves. A series of check tests are carefully designed to examine the hypotheses of this method and then the author applies it to the error analysis of the peak ground acceleration magnitude. The source, path and site errors are estimated by this approach and the robustness of separation is checked. The acquired knowledge about the errors in magnitude estimation may help us to improve the precision of magnitude estimation during earthquake early warning.
Advancements in Image-Guided Navigation for Surgical Procedures

Surgeons may now conduct complex surgeries with more precision, accuracy, and safety thanks to image-guided navigation. This article analyzes how image-guided navigation devices have changed surgical operations. Surgeons now approach procedures differently thanks to the integration of imaging modalities like Computed Tomography (CT), Magnetic Resonance Imaging (MRI), and ultrasound with surgical navigation systems. Surgeons can confidently navigate complex anatomical features and plan surgical paths using these technologies' real-time, three-dimensional anatomy visualization. Image-guided navigation has advanced with Augmented Reality (AR) and Virtual Reality (VR). Augmented Reality (AR) devices improve spatial awareness and reduce errors by superimposing patient-specific anatomical data onto the surgeon's field of view. VR allows surgeons to perform complex surgeries in a virtual environment, increasing their skills and aiding preoperative planning. Another innovation is machine learning and Artificial Intelligence (AI) algorithms in image-guided navigation systems. These algorithms evaluate massive volumes of patient data, including medical pictures, surgery plans, and results, to help surgeons make predictions and judgments. Data-driven algorithms in AI-driven navigation systems optimize surgical operations, accuracy, and patient outcomes. Miniaturized and wireless tracking systems provide less invasive image-guided navigation. Electromagnetic and optical monitoring devices allow surgeons to track surgical tools inside the patient's body, providing real-time feedback and instruction. Image-guided navigation is being used in laparoscopic, endoscopic, and robotic-assisted surgeries. Image-guided navigation still faces challenges. The incorporation of diverse imaging modalities, system accuracy, and smooth compatibility with surgical instruments are ongoing research and development. To promote widespread adoption of these technologies, cost-effectiveness, training, and regulations must be addressed. Image-guided navigation has improved surgical visualization, navigation, and decision-making. Augmented reality, virtual reality, machine learning, and tiny tracking have improved surgery and patient outcomes. Image-guided navigation could become common surgery with continued study and improvement in this sector.
Integrating magnetic tunnel junctions with femtosecond laser pulses

Spintronic MRAM is highly promising towards a next-generation “universal” memory paradigm. As its key building block, perpendicular magnetic tunnel junctions (p-MTJs) have been an active field of research, aiming at a high access speed with low power consumption. However, state-of-the-art p-MTJs are still fundamentally limited by the spin precession process, resulting in a sub-ns speed limitation. Recently, manipulating or even switching the magnetization of ferrimagnets in a highly non-equilibrium regime has been realized by a single femtosecond (fs) laser pulse, leading to a plethora of opportunities for device applications. In this presentation, we report our recent experimental progress on integrating p-MTJ with fs lasers. First, we introduce fs laser-assisted switching in a high-performance p-MTJ device using a direct electrical readout. Reconfigurable switching operations and a switching phase diagram are shown by the interplay of the laser and synchronized field. Second, we demonstrate fs laser-induced all-optical switching of a p-MTJ, by using a composite free layer structure employing interlayer RKKY coupling. All-optical switching speed within 10 ps is demonstrated, with a high energy efficiency and a decent TMR ratio. We believe our hybrid research approach might pave the way towards a new category of integrated photonic memory, as well as an alternating scheme for next-generation MRAM design.
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. • Type of peer review: Double Anonymous • Conference submission management system: Morressier • Number of submissions received: 243 • Number of submissions sent for review: 207 • Number of submissions accepted: 147 • Acceptance Rate (Submissions Accepted / Submissions Received × 100): 60.5 • Average number of reviews per paper: 3.08 • Total number of reviewers involved: 117 • Contact person for queries: Name: Serhiy O. Semerikov Email: semerikov@acnsci.org Affiliation: Academy of Cognitive and Natural Sciences
Influence of Teaching Strategies on Students’ Competences in Mathematics in Public Secondary Schools in Rwanda

The level of students’ competency in various subjects like mathematics depends on the effectiveness of teachers while teaching especially teaching strategies used in teaching process. The purpose of this study therefore, thought to examine influences of parent’s involvement in teaching strategies and students ‘competences in mathematics from selected Bugesera Public Secondary Schools. The target population was 454 people that provided the sample size of 146 respondents got using Yamane formula. Interview guide and questionnaire were used as data collection instruments. A descriptive survey design was also employed. The findings revealed that group work, too much tests and quizzes and homework were discovered to be the most commonly used teaching approaches used by teacher and head teachers also good for learners in the selected schools. But ICT was not a teaching strategy favored by both teacher and students. The results showed that teaching strategies have high positive correlation to students’ competences as shown by 0.529 of Pearson coefficient. Multiple linear regression analysis found that teaching strategies have significant influence on students ‘competences at 64.9% of R-Square. Further, there is a highly significant positive correlation between teaching methods and student competencies. Moreover, the study established that there is a highly significant positive correlation between teaching methods and student competencies. The study recommends that Teachers should increase their efforts in finding where mathematics is relevant and applying it to math’s problems when they connect with students in the class. Ministry of Education to supply sufficient teaching and learning materials such as textbooks, computers and internet. In addition, providing training to teachers on how to use effective teaching strategies that influence students’ competences such as ICT and among others is necessary. Keywords: Mathematic competences, Teaching strategies, Group work and assignments
APPLICATION OF DIFFERENT MODELS FOR RESEARCH TOPOLOGY ON FINITE SETS

The study of topological structure on a finite set includes solving problems of counting and enumerating topologies. For this purpose, topologies are modeled by graphs, matrices, Boolean functions, ordered sets of non-negative integers – topology vectors. The results of studies of topologies on a finite set are closely related to digital image processing based on finite sets of observations, that is, an attempt to understand the content of an image based on the concept of proximity of points. This paper provides a brief overview of methods for studying topologies on an n -element set. T0 -topologies play an exceptional role in solving the problems of enumerating and calculating the number of all topologies. It is convenient to say that when a topology has m open sets, it belongs to the m -class (or has weight m ). The use of topology vector made it possible to investigate all T0 -topologies with weight m 2n 1 (close to discrete topology), to describe all T0 -topologies on the n????-???? element set with weight 2n 1 2n m , which are compatible with topologies close to discrete topology on an n 1 -element set. Comparison of the obtained results with the results of the works Stanley R.P. 1971, Kolli M. 2007 2014 helped to list the classes of topologies in which all topologies are compatible with topologies close to discrete topology on an n 1 ????-???? element set, as well as to show that there are the classes of topologies with the weight m n n 5 2 4 ,13 2 5 , which are not exhausted by T0 -topologies compatible with topologies close to discrete topology on an n 1 -element set or dual to them. When modeling topologies using Boolean functions for each T0 -topology there is a single conjunctive normal form of a certain type (maximal 2-CNF). The use of 2-CNF of Boolean functions made it possible to develop a technique for recognizing mutually dual and self-dual T0 -topologies and counting the number of T0 -topologies with a given weight. This article studies T0 -topologies on the n -element set with weight 2n 1 2n m , which are not compatible with topologies close to discrete topology on an n 1 -element set. Topology vector as a model is used to study of these T0 -topologies.
CAML: Cryptographic-Based Cloud Security for Healthcare Data with Machine Learning Technique

Background: The Cloud model is one of the most realistic frameworks with a vast range of social networking interactions. In medical data, security is a major constraint as it incorporates information about the patients. The cloud environment subjected to mobility and openness is exposed to security issues and limits authorization levels for data transmission. Objective: This paper aims to propose a security model for attack prevention within the healthcare environment. Method: The proposed Cryptographic Attribute-based Machine Learning (CAML) scheme incorporates three stages. Initially, the homomorphic encryption escrow is performed for secure data transmission in the cloud. Secondly, the information of the users is evaluated based on the consideration of users' authorization. The authorization process for the users is carried out with the attribute-based ECC technique. Finally, the ML model with the classifier is applied for the detection and classification of attacks in the medical network. Results: The detected attack is computed and processed with the CNN model. Simulation analysis is performed for the proposed CAML with conventional ANN, CNN, and RNN models. The simulation analysis of proposed CAML achieves a higher accuracy of 0.96 while conventional SVM, RF, and DT achieve an accuracy of 0.82, 0.89 and 0.93, respectively. Conclusion: Conclusion: With the analysis, it is concluded that the proposed CAML model achieves higher classification accuracy for attack detection and prevention in the cloud computing environment.