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This article discusses PC reliability, one of the most pressing issues regarding computers. Nearly a quarter century after the introduction of the first IBM PC and the outset of the personal computer revolution, PCs have largely become commodities, with little differentiating one brand from another in terms of capability and performance. Most of today's software is similarly mature, having gone through many upgrades, with less opportunity for the introduction of groundbreaking capabilities. These days, what most differentiates one computer product from another is reliability--the hassle factor. The PC industry may be maturing, but computer products are still very much prone to glitches, bugs, security vulnerabilities, incompatibilities, premature failure and other problems.

One of the truisms about computers is that they're difficult. Despite the fact that the PC Revolution is now well into its third decade and the continuing improvements in the user friendliness of PCs and Macs, printers and scanners, and software and the Internet, using a personal computer can still be a hair-raising experience. This is particularly true with people older than 40 who weren't weaned on computers as kids are today. But it can be true with anybody who's not detail- or technically oriented, including people in work situations who need to use computers as part of their jobs. As many as two-thirds of managers/executives as well as clerical/support staff still feel hesitant about using technology in the office, according to research by Dr. Larry D. Rosen, psychology professor at California State University-Dominguez Hills, and Dr. Michelle M. Weil, president of the consulting company Human-Ware in Carlsbad, Calif.

This article provides an overview of the origins and early development of sports video games. The first generation of sports video games were developed by scientists in laboratories for academic purposes. Together with the rise of microcomputers and the widespread adoption of television (TV) sets, commercial video games began to emerge in the early 1970s. Like their laboratory predecessors, most of the first-generation commercial games were sports-themed and primarily designed as a platform for competition between players. In the second half of the 1970s, ball-and-paddle-based games began to be replaced by more sophisticated games adopting the rules and actions of real-life sports. By the late 1970s and early 1980s, intense competition between video game companies gave birth to many innovative titles, with various sports disciplines adapted into games. Most of the sports games created in this period were based on competitive sports including American football, basketball, baseball, soccer, and tennis, as well as recreational sports like bowling, pool, and darts, many of them long popular in Western Europe and North America, some with a huge fan base in Japan. They were clearly produced to cater to the needs of gamers and sports fans in the world's three major TV, personal computer, video game, and sports markets at the time. [ABSTRACT FROM AUTHOR]

Purpose: The Speech Accessibility Project (SAP) intends to facilitate research and development in automatic speech recognition (ASR) and other machine learning tasks for people with speech disabilities. The purpose of this article is to introduce this project as a resource for researchers, including baseline analysis of the first released data package. Method: The project aims to facilitate ASR research by collecting, curating, and distributing transcribed U.S. English speech from people with speech and/or language disabilities. Participants record speech from their place of residence by connecting their personal computer, cell phone, and assistive devices, if needed, to the SAP web portal. All samples are manually transcribed, and 30 per participant are annotated using differential diagnostic pattern dimensions. For purposes of ASR experiments, the participants have been randomly assigned to a training set, a development set for controlled testing of a trained ASR, and a test set to evaluate ASR error rate. Results: The SAP 2023-10-05 Data Package contains the speech of 211 people with dysarthria as a correlate of Parkinson's disease, and the associated test set contains 42 additional speakers. A baseline ASR, with a word error rate of 3.4% for typical speakers, transcribes test speech with a word error rate of 36.3%. Fine-tuning reduces the word error rate to 23.7%. Conclusions: Preliminary findings suggest that a large corpus of dysarthric and dysphonic speech has the potential to significantly improve speech technology for people with disabilities. By providing these data to researchers, the SAP intends to significantly accelerate research into accessible speech technology. [ABSTRACT FROM AUTHOR]

Several factors can impede the writing process of students with dyslexia. One recommended adjustment to help them overcome these writing challenges is the use of personal computers for writing. The research underscores the significance of effective keyboarding skills in optimizing the benefits of computer-based writing for these students, with touch-typing being the frequently recommended typing technique. Although research findings point to various reasons that indicate that students with dyslexia may face difficulties in developing fluent touch-typing skills, we found a lack of research in this area. In order to address this gap, in our study we examined and compared 12–13-year-old Slovenian students with dyslexia and their typically developing peers in terms of their existing, self-taught typing technique fluency, the fluency achieved in learning touch-typing and the fluency achieved in learning a simple finger-typing task. We found a significant difference between handwritten and self-taught typing fluency of students with dyslexia, with handwriting being a more fluent form of transcription. The results of students with dyslexia are significantly lower from their peers in handwriting fluency, self-taught typing fluency, touch-typing fluency and simple finger-typing task fluency. However, the learning trends for touch-typing and the simple finger-typing task do not differ between the groups of students. We comment on the differences found and make suggestions when considering typing as an additional or alternative transcription mode. [ABSTRACT FROM AUTHOR]

An (r , z , k) -mixed graph G has every vertex with undirected degree r , directed in- and out-degree z , and diameter k. In this paper, we study the case r = z = 1 , proposing some new constructions of (1 , 1 , k) -mixed graphs with a large number of vertices N. Our study is based on computer techniques for small values of k and the use of graphs on alphabets for general k. In the former case, the constructions are either Cayley or lift graphs. In the latter case, some infinite families of (1 , 1 , k) -mixed graphs are proposed with diameter of the order of 2 log 2 N. [ABSTRACT FROM AUTHOR]

In the domain of healthcare, wearable health monitoring devices have emerged as essential tools for the advancement of patient health tracking. These devices facilitate the provision of real-time medical data to clinicians, enabling early diagnosis, timely intervention, and enhanced management of individual health. This study introduces an innovative trimodal wearable health monitoring device in the form of a wristwatch. The device integrates a breath analyzer for the assessment of gaseous phase biomarkers, a sweat analyzer for the evaluation of aqueous-phase biomarkers, and an infrared sensor for the measurement of body temperature in the optical phase. Engineered on a compact 3 cm × 3 cm printed circuit board, the device has been optimized for wearability, power efficiency, and seamless integration with both wired and wireless charging and communication systems. Furthermore, custom software applications, designed for both Windows and Android platforms, have been developed to facilitate intuitive data visualization and storage on personal computers and smartphones. Empirical results from real-time chemical testing substantiate the device's efficacy and potential as an advanced solution for wearable health monitoring. [ABSTRACT FROM AUTHOR]

The community Noah with multi-parameterization options (Noah-MP) land surface model (LSM) that is widely used in studies from uncoupled land surface hydrometeorology and ecohydrology to coupled weather and climate predictions. In this study, we developed NMP-Hydro, a hydrological model written in CSharp(C#). NMP-Hydro was developed by faithfully translating the FORTRAN version Noah-MP from the uncoupled WRF-Hydro 3.0, and was coupled with a river routing model. NMP-Hydro exhibits the capacity of parallel execution on Windows systems, utilizing the multi-core CPUs commonly available in today's personal computers. The code of NMP-Hydro has been rigorously tested to ensure that it produces a high-degree of consistency with the simulation output of the original WRF-Hydro. High-resolution (6 km) simulations were conducted and assessed over a grid domain covering the entire Yellow River Basin and the most part of North China. The spatial maps and temporal variations of many state variables simulated by NMP-Hydro and WRF-Hydro/Noah-MP demonstrate consistent results, with occasionally minor discrepancies. The river discharge for the Yellow River under various scheme combinations of six Noah-MP parameterizations exhibits general close agreement with the natural river discharge at the Lanzhou station. NMP-Hydro can be regarded as a reliable replica of Noah-MP in WRF-Hydro 3.0, but it can leverage the modern, powerful, and user-friendly features brought by the C # language to significantly improve the efficiency of the model users and developers. [ABSTRACT FROM AUTHOR]

Achieving good performance in terms of a fast and accurate maximum torque per ampere (MTPA) control method depends on both accurate parameter estimation and a sophisticated control strategy. However, it often requires a complex and long computational process. This paper proposes an efficient control method using the relationship of torque and current angle for maximum torque per ampere control of the interior permanent magnet synchronous motor (IPMSM) for vehicle application. It was found that it is not necessary for the control method to determine the inductance in the d-q axes; the identification of the difference between each axis is enough. Furthermore, this paper presents a simple and effective procedure to estimate the difference in inductance online, where the linear iron loss calculation method is also designed to support the above process. The proposed control method was experimentally validated on a 5 kW prototype by a TMS320F28335 microcontroller and DSPACE synchronized with a personal computer. The results show that the control process has faster and more accurate performance than the conventional method. [ABSTRACT FROM AUTHOR]

A new system design tool for the simulation of a full hybrid rocket engine is developed in this article. This tool enables to simulate the behaviour of the engine at different conditions/configurations in several minutes from a desktop computer by keeping a balance between accuracy and computation time. This makes its use especially attractive for the pre-design phases of the engine. The main components of the hybrid rocket engine from our laboratory-characterized by a catalytic injection of the oxidizer-, are modelled and implemented in the tool: the feed/injection sub-system through 0-D models of a mass flow rate regulator and a catalyst; the combustion chamber, with a 1.5-D model; and the nozzle through a 1-D model. An iterative method is employed to reach the convergence of pressure in the combustion chamber between these sub-systems. The corresponding set of equations is solved by a Newton–Raphson technique. Seven experiments performed on our lab-scale engine were used to validate the system design tool. In five of the simulations, the relative differences of the main physical quantities with the experiment were below 30%, being the largest errors found in the fuel regression rate and mixture ratio. The best agreements with the experiments were retrieved for the cases with the largest oxidizer mass fluxes (above 230 kg/ m 2 /s) and mixture ratios closest to stoichiometry, defining thus, the range of applicability of the system design tool. The results presented in this article were issued of a Ph.D. thesis. • A 1.5-D combustion chamber model of a hybrid rocket engine was developed and validated. • 0-D/1-D mass flow regulator, catalyst and nozzle models were developed and validated. • A system design tool of a hybrid rocket engine implementing these models was developed. • The tool is adapted to pre-design phases, with a few minutes of computation time. • Errors between 8%–40% in fuel regression rate and below 10% in thrust and chamber pressure. [ABSTRACT FROM AUTHOR]

Increasingly advanced image analysis in computer vision, allowing computers to interpret, identify, and analyze pictures with accuracy comparable to humans. The availability of data sources in decimal, hexadecimal, or binary forms enables researchers to take the initiative in applying their study findings. Decimal formats are typically used on traditional computers like desktops and minicomputers, whereas hexadecimal and binary formats were utilized on single-chip controllers. Weightless Neural Network is a method that can be implemented in a single chip controller. The aim of this research is to develop a facial recognition system, for eye and mouth identification, that works in a single chip controller or also called a microcontroller. The suggested method is a Weightless Neural Network with Immediate Scan approach for processing and identifying eye and nose patterns. The data will be handled in many memory locations that are specifically designed to handle massive volumes of data. The data is made up of primary face data sheets and face input data. The data sets utilized are (x,y) pixels, and frame sizes range from 90x90 pixels to 110x110 pixels. Each face shot will be processed by selecting the region of the eyes and nose and saving it as an image file. The eye and nose will identify the face frame. Next, the photos will be converted to binary format. A magazine matrix will be used to transmit binary data from a minicomputer to a microcontroller via serial connection. Based on a known pattern, the resultant similarity accuracy is 83,08% for the eye and 84,09% for the sternum. In contrast, the similarity percentage for an eye ranges from 70% to 85% for an undefined pattern. [ABSTRACT FROM AUTHOR]

Purpose: Adverse Drug Reactions (ADR) classification is useful in modern medical diagnostics and related applications. ADR is an example of how medical information is frequently accessible on social media platforms for healthcare, where people can share their experiences with treatments on desktop computers and mobile devices. Many researchers are interested in gathering valuable medical data from social media for the ADR system training and classification process. Materials and Methods: This research explores the effects of three aspects on recognizing ADR mentions in social media for the medical field and proposes a deep neural network of Long Short-Term Memory (LSTM) neural networks to do so. The comments are collected from various social media platforms to implement the ADR system with proper training and testing processes. The texts from the dataset are initially preprocessed by using a data filtering and clustering process to remove the input data's redundant information to increase the training process's quality. Characteristic features, such as semantic features and text statistics, are extracted from the input text using the American Standard Code for Information Interchange (ASCII) array. Further, the features are converted and fed to LSTM networks for training and validation. Results and Conclusion: This work is evaluated using two datasets, CODEC, and ADR Corpus datasets are used to evaluate the performance of the proposed ADR technique via multiple angles. Via extensive experiments, this work achieved 99.79 accuracy, 98.37 sensitivity, 97.63 specificity, 99.72 precision, 98.39 recall, 97.62 F1-score for the CODEC dataset, 98.16 for accuracy, 99.19 for sensitivity, 98.49 for specificity, 99.49 for precision, 96.72 for recall, and 93.16 for F1-score for ADR corpus, respectively. [ABSTRACT FROM AUTHOR]

Copyright of Przegląd Elektrotechniczny is the property of Przeglad Elektrotechniczny and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Przegląd Elektrotechniczny is the property of Przeglad Elektrotechniczny and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This study presents an approach that integrates compressed sensing technology with two-dimensional hyperchaotic coupled Fourier oscillator systems (2D-HCFOS) to address the challenge of slow encryption speeds in agricultural unmanned aerial vehicles (UAVs). The primary challenge in enhancing encryption speed lies in the limited capacity inherent in traditional chaotic-based systems and the computational complexity of their processes. The 2D-HCFOS utilizes a complex two-dimensional hybrid chaotic system, which significantly enhances the security of agricultural UAV image data. Notably, the image encryption process is performed on a personal computer connected to the drone, ensuring efficient processing. By integrating advanced Fourier series and nonlinear coupled oscillators, the model surpasses existing chaotic-based methods, improving both the pseudo-randomness and robustness of encryption. Additionally, incorporating Bonouille functions into the discrete cosine transform (DCT) domain results in a sparser measurement matrix, which is essential for efficient encryption on personal computers. The effectiveness of 2D-HCFOS in securely encrypting agricultural drone images has been rigorously validated through simulations and analytical evaluations using sophisticated row, rotation, and matrix encryption techniques. The improved security performance is further verified by comparative analysis. Compared with other models, the Lyapunov index of 2D-HCFOS is 15.1039, and the sample entropy is 2.4987, indicating that it possesses superior chaotic performance and encryption reliability. [ABSTRACT FROM AUTHOR]

The industrial internet of things (IIoT) has undergone rapid growth in recent years, which has resulted in an increase in the number of threats targeting both IIoT devices and their connecting technologies. However, deploying tools to counter these threats involves tackling inherent limitations, such as limited processing power, memory, and network bandwidth. As a result, traditional solutions, such as the ones used for desktop computers or servers, cannot be applied directly in the IIoT, and the development of new technologies is essential to overcome this issue. One approach that has shown potential for this new paradigm is the implementation of intrusion detection system (IDS) that rely on machine learning (ML) techniques. These IDSs can be deployed in the industrial control system or even at the edge layer of the IIoT topology. However, one of their drawbacks is that, depending on the factory's specifications, it can be quite challenging to locate sufficient traffic data to train these models. In order to address this problem, this study introduces a novel IDS based on the TabPFN model, which can operate on small datasets of IIoT traffic and protocols, as not in general much traffic is generated in this environment. To assess its efficacy, it is compared against other ML algorithms, such as random forest, XGBoost, and LightGBM, by evaluating each method with different training set sizes and varying numbers of classes to classify. Overall, TabPFN produced the most promising outcomes, with a 10–20% differentiation in each metric. The best performance was observed when working with 1000 training set samples, obtaining an F1 score of 81% for 6-class classification and 72% for 10-class classification. [ABSTRACT FROM AUTHOR]

Background: The effectiveness of eLearning in enhancing healthcare professionals' capacity has received substantial attention globally. This review sought to synthesis evidence on the effectiveness of various types of eLearning programmes, and the facilitators and barriers to its use. Methods: The review was guided by Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Four main databases (PubMed, Web of Science, JSTOR, and Scopus) in July 2023 and 44 articles met the eligibility criteria and were included in the review. The JBI critical appraisal checklist was used to appraise the methodological quality of the studies. The data were examined using narrative review to determine the effectiveness of the intervention as well as the barriers and facilitators to its use. Results: This review found that asynchronous, synchronous, blended, and self-learning methodologies are effective eLearning approaches for continuous professional development. Previous positive experiences, user-friendly interfaces and relevance of the eLearning content to daily practice are critical elements that facilitate eLearning usage. Poor computer competence and literacy, lack of personal computers and high family duties were the main personal factors that hindered eLearning use. Some systemic barriers included; heavy workloads, shortage of specialised eLearning facilitators poor management involvement, and technical inadequacies within the ICT departments. Environmental issues such as poor infrastructure, including limited internet and frequent power outages acted as barriers. Conclusion: The review highlights the effectiveness of various eLearning approaches among health professionals and presents the disparities between developing and developed economies in relation to the facilitators and barriers. [ABSTRACT FROM AUTHOR]

NTT Access Network Service Systems Laboratories has long been developing technologies that contribute to more-efficient operations on personal computers and other information devices. We have implemented a collaborative business navigation platform as a new technology to continue this trend. Using this platform makes it possible to easily develop digital transformation (DX) tools suited to diverse work environments and operator roles. This article discusses the functions of the collaborative business navigation platform and the use cases of DX tools by using this platform. [ABSTRACT FROM AUTHOR]

This paper developed a scalable parallel computing method that can be used for platoon simulations and controller validations. A scalable adaptive platooning control law was firstly designed, which accommodates a variety of vehicle-to-vehicle communication topologies. A road vehicle dynamics model that considered the Magic Formula tyre model and suspension dynamics was then derived and validated. The parallel computing method adopted the Message Passing Interface technique to allow fast and scalable simulations. Platoon length changes do not require controller and algorithm changes. An 11-vehicle platoon on a real-world 10 km long road section was simulated. Different localisation sensor errors, communication delays, heterogenous vehicle masses and driving modes were considered. Results show that localisation errors have negligible influences on space errors. Aggressive driving and heterogeneous vehicle masses slightly increase space errors (increases less than 0.23 m). Communication delays are the greatest influencer for space errors. Increases for 15, 45 and 75 ms delays were 0.43, 1.41 and 2.41 m, respectively. It is further shown that parallel computing can improve the computing speed by three times on personal computers and seven to 12 times on workstations. [ABSTRACT FROM AUTHOR]

The use of mobile devices for web browsing has increased extraordinarily in recent years, becoming the main source of information. Unfortunately, developers cannot meet the needs of all users. As a result, users have been forced to adapt web content to their needs. Additionally, users face more costly interactions than on desktop computers due to the smaller screen size of cell phones. These interactions include URL typing, scrolling, taping, branching and tab-switching. If the number of web resources is large, the activity becomes unpleasant. Furthermore, should the quantity of interactions be extensive, the web experience also becomes unpleasant. Moreover, all these interactions lead to higher costs in terms of phone time and battery life, as well as more costly navigation. Web augmentation enhances the user web experience by adding content from different resources, modifying the original layout, or reducing interactions during web searches, among other benefits. To reduce user interactions and satisfy their information necessities, we propose MAWA, an extension for Firefox mobile that allows users to adapt any web page to their needs through web augmentation techniques. To validate our proposal, an evaluation of the tool has been carried out. The article presents the benefits introduced by MAWA as a response to the inconveniences experienced by users when performing their activities in the mobile browser. The results obtained show that MAWA is able to reduce the number of interactions significantly, as well as to reduce battery consumption and the time needed to obtain the desired information. In addition, users perceive that navigation is less cluttered. [ABSTRACT FROM AUTHOR]

Substance misuse is a criminogenic risk factor—however, substance-involved prison residents may have limited access to support and services that might be able to help them overcome their substance misuse. Research around the efficacy of the "Breaking Free" digital Cognitive Behavioural Therapy programme for substance-involved prison residents demonstrates that this digital technology may overcome barriers to support. Breaking Free is the first digital programme for substance misuse that has been implemented in prisons. In the United Kingdom (U.K.) the programme is delivered via secure desktop and laptop computers in staff-facilitated group sessions, and in the United States (U.S.) is delivered via individual secure tablets that prison residents can access independently, without staff support. This study compares U.K. and U.S. prison residents who have engaged with Breaking Free on a number of baseline measures (sociodemographic factors, types of problem substances reported, clinical complexity, and criminogenic risk factors). The delivery models employed in these two jurisdictions are compared in relation to their associations with prison residents' engagement with the programme and the clinical outcomes experienced. Differences between U.K. and U.S. prison residents in baseline clinical and psychosocial factors were identified, including greater clinical complexity in the U.K. group. U.K. prison residents, who were supported by staff when using Breaking Free, demonstrated higher levels of engagement with the programme than U.S. prison residents who were not supported by staff. The different delivery models employed in the United Kingdom and United States appeared to be associated with group differences in clinical outcomes. Guidance for the optimal implementation of Breaking Free, based on findings from this study, is provided. Further analyses will explore how the different approaches to the delivery of Breaking Free might interact with the differences in prison resident characteristics identified in this study (sociodemographic, clinical and criminogenic), in order to influence prison resident engagement with the programme and clinical outcomes. [ABSTRACT FROM AUTHOR]

This paper presents a precise two‐robot collaboration method for three‐dimensional (3D) self‐localization relying on a single rotating camera and onboard accelerometers used to measure the tilt of the robots. This method allows for localization in global positioning system‐denied environments and in the presence of magnetic interference or relatively (or totally) dark and unstructured unmarked locations. One robot moves forward on each step while the other remains stationary. The tilt angles of the robots obtained from the accelerometers and the rotational angle of the turret, associated with the video analysis, make it possible to continuously calculate the location of each robot. We describe a hardware setup used for experiments and provide a detailed description of the algorithm that fuses the data obtained by the accelerometers and cameras and runs in real‐time on onboard microcomputers. Finally, we present 2D and 3D experimental results, which show that the system achieves 2% accuracy for the total traveled distance (see Supporting Information S1: video). [ABSTRACT FROM AUTHOR]

Informed by theoretical perspectives on working memory demands and devices' potential to "prime" different types of cognitive processing, this paper investigates whether we tend to think "faster" and more intuitively, with less reflection when we use a smartphone instead of a personal computer (PC) or notebook. Three complementary experimental studies with a total of 823 participants reveal that the results of using such devices surface only when participants can select the smartphone as their preferred device. Controlling for potential confounding variables reveals no evidence of general differences between devices. Our findings caution against overemphasizing the importance of the type of device in thinking slow or fast and establish self-selection bias as an important factor in explaining such differences. This study contributes to clarifying the psychology of smartphone screens and how humans make choices when they are using these devices. [ABSTRACT FROM AUTHOR]

The present study aims to evaluate the relationship between smartphone addiction and depression in primary care. Three hundred fifty-two people who participated in our research, designed as a cross-sectional study, filled out the Short Version of the Smartphone Addiction scale and Beck's Depression Inventory. Among the participants, 28.9% were found to have smartphone addiction and 52.3% were found to have depressive symptoms. The mean score of participants in the Smartphone Addiction Scale was 24.32 ± 11.24 points (n = 352). The mean score in Beck's Depression Inventory was 10.80 ± 7.94 points. A positive significant relationship was found between depression frequency and social media usage duration (1-2 hours/day) and length of social media usage (≥5 hours/day). A weak but positive and significant correlation was found between Smartphone Addiction Scale and Beck's Depression Inventory (r = 0.147; p = .006). In the regression analysis, it was determined that having an income between 1000 and 1999 TL, having a computer at home, having other addictions other than smoking, and being addicted to a smartphone increase the risk of depression development. The relationship between smartphone addiction and depression should be given attention. The factors influencing smartphone addiction should be considered. Especially the social media and smartphone usage should be limited. [ABSTRACT FROM AUTHOR]

Purpose: The study aimed to determine the key factors influencing health-promoting behavior and the behavioral intentions of eHealth consumers based on the health promotion model and technology acceptance model. Methods: This research involved a longitudinal path analysis. The study was conducted with 360 eHealth consumers aged over 18 years, employed in the top five categories of the Korean standard classification of occupations, and living in the five largest cities in South Korea. The data were analyzed using SPSS 22.0 and AMOS 25.0. Results: Health-promoting behaviors were directly supported by prior health-related behavior and behavioral intention, and indirectly supported by perceived ease of use, perceived usefulness, perceived benefit, self-efficacy, and behavioral intention. These variables accounted for 36.3% of the variance in health-promoting behavior. Conclusion: The findings serve as a framework that can help health professionals and health information providers understand how to encourage consumers using eHealth to engage in health-promoting behaviors. [ABSTRACT FROM AUTHOR]

The integration of a blockchain-supported serverless computing framework enhances the performance of computational and analytical operations and the provision of services within internet-based data centers, rather than depending on independent desktop computers. Therefore, in the present research paper, a blockchain-assisted serverless framework for geospatial data visualizations is implemented. The proposed BS-GeoEduNet 1.0 framework leverages the capabilities of AWS Lambda for serverless computing, providing a reliable and efficient solution for data storage, analysis, and distribution. The proposed framework incorporates AES encryption, decryption layers, and queue implementation to achieve a scalable approach for handling larger files. It implements a queueing mechanism during the heavier input/output processes of file processing by using Apache KAFKA, enabling the system to handle large volumes of data efficiently. It concludes with the visualization of all geospatial-enabled NIT/IIT details on the proposed framework, which utilizes the data fetched from MongoDB. The experimental findings validate the reliability and efficiency of the proposed system, demonstrating its efficacy in geospatial data storage and processing. [ABSTRACT FROM AUTHOR]

Shape modeling is a dynamic area in computer graphics with significant applications in computer-aided design, animation, architecture, and entertainment. Virtual sculpting, a key paradigm in free-form modeling, has traditionally been performed on desktop computers where users manipulate meshes with controllers and view the models on two-dimensional displays. However, the advent of Extended Reality (XR) technology has ushered in immersive interactive experiences, expanding the possibilities for virtual sculpting across various environments. A real-time virtual sculpting system implemented in a Virtual Reality (VR) setting is introduced in this paper, utilizing quasi-uniform meshes as the foundational structure. In our innovative sculpting system, we design an integrated framework encompassing a surface selection algorithm, mesh optimization technique, mesh deformation strategy, and topology fusion methodology, which are all tailored to meet the needs of the sculpting process. The universal, user-friendly sculpting tools designed to support free-form topology are offered in this system, ensuring that the meshes remain watertight, manifold, and free from self-intersections throughout the sculpting process. The models produced are versatile and suitable for use in diverse fields such as gaming, art, and education. Experimental results confirm the system's real-time performance and universality, highlighting its user-centric design. [ABSTRACT FROM AUTHOR]

The point cloud provides viewers with intuitive geometric understanding but requires a huge amount of data. Moving Picture Experts Group (MPEG) has developed video‐based point‐cloud compression in the range of 300–700. As the compression rate increases, the complexity increases to the extent that it takes 101.36 s to compress one frame in an experimental environment using a personal computer. To realize real‐time point‐cloud compression processing, the direct patch projection (DPP) method proposed herein simplifies the complex patch segmentation process by classifying and projecting points according to their geometric positions. The DPP method decreases the complexity of the patch segmentation from 25.75 s to 0.10 s per frame, and the entire process becomes 8.76 times faster than the conventional one. Consequently, this proposed DPP method yields similar peak signal‐to‐noise ratio (PSNR) outcomes to those of the conventional method at reduced times (4.7–5.5 times) at the cost of bitrate overhead. The objective and subjective results show that the proposed DPP method can be considered when low‐complexity requirements are required in lightweight device environments. [ABSTRACT FROM AUTHOR]

Copyright of Tsinghua Journal of Education is the property of Tsinghua University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

[Background and Objective] In order to overcome the difficulty about laying electric wires in the field and realize unmanned filed irrigation, improving the intellectualization and precision of irrigation in rice planting area in Anhui Province and exploring the feasibility of intelligent control of irrigation sluice by using new generation electronic information technology would be carried out in the research. [Method] An intelligent irrigation control system based on AT89S52 single chip computer was designed in this paper, which included integrated lifting sluice, irrigation hardware subsystem and irrigation software subsystem. The gate of the sluice was adopted integrated design, which was integrated central processing unit module, sensor sensing module and solar power supply module based on AT89S52 MCU. Keil C developed the control software for the terminal of the gate, and the upper computer control software of the system was developed by C++. [Result] The application test showed that the automatic control response time of the motor was less than 1 s, the gate of the sluice opening control error was less than 1.5 mm, the water level control error was less than 8 mm, the maximum packet loss rate of data transmission was 0.11%, the calculation error of free discharge flow was less than 1%, and that of submerged outflow flow was less than 1.2%. [Conclusion] This system run safely and stably, and could meet the requirement of intelligent and precise water use in the complex environment of field irrigation of rice planting area. [ABSTRACT FROM AUTHOR]

Attentive User Interface (AUI), especially vision-based AUI systems, is a highly developed area of study. Cameras play a crucial role in modeling AUI inputs to monitor and understand user attention during interaction. This enables the optimization of interaction tasks between humans and machines. Typically, AUI systems are designed for desktop computers, employing various detection methods based on computer vision. This research introduces the exploration of AUI input through a low-cost Raspberry Pi 4 embedded system a smallsized system with limited voltage sources. This exploration serves as a reference for AUI design on embedded systems. The proposed AUI input design generating 8 AUI input categories. These include face detection, open or closed eye condition detection, and detection of forward, up, down, left, and right view directions. This study discusses three scenarios of AUI input modeling using various methods to identify the most effective design through Raspberry Pi 4. Based on experimental results and a series of tested tasks, Scenario 3, based on Mediapipe, yielded the best results with an average FPS value of 10 and 100% accuracy for facial landmark detection, detection of open eye conditions, detection of forward, up, down, right, and left gaze directions at various detection reading angles. [ABSTRACT FROM AUTHOR]

In the contemporary era, dizziness is a prevalent ailment among patients. It can be caused by either vestibular neuritis or a stroke. Given the lack of diagnostic utility of instrumental methods in acute isolated vertigo, the differentiation of vestibular neuritis and stroke is primarily clinical. As a part of the initial differential diagnosis, the physician focuses on the characteristics of nystagmus and the results of the video head impulse test (vHIT). Instruments for accurate vHIT are costly and are often utilized exclusively in healthcare settings. The objective of this paper is to review contemporary methodologies for accurately detecting the position of pupil centers in both eyes of a patient and for precisely extracting their coordinates. Additionally, the paper describes methods for accurately determining the head rotation angle under diverse imaging and lighting conditions. Furthermore, the suitability of these methods for vHIT is being evaluated. We assume the maximum allowable error is 0.005 radians per frame to detect pupils' coordinates or 0.3 degrees per frame while detecting the head position. We found that for such conditions, the most suitable approaches for head posture detection are deep learning (including LSTM networks), search by template matching, linear regression of EMG sensor data, and optical fiber sensor usage. The most relevant approaches for pupil localization for our medical tasks are deep learning, geometric transformations, decision trees, and RASNAC. This study might assist in the identification of a number of approaches that can be employed in the future to construct a high-accuracy system for vHIT based on a smartphone or a home computer, with subsequent signal processing and initial diagnosis. [ABSTRACT FROM AUTHOR]

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Objectives: The aim of this study is to examine the relationship between internet addiction and social safeness and pleasure level in nursing students. Methods: This study was design as a descriptive-cross-sectional and correlational study. The study was carried out in a state university nursing department between March 01, 2022, and June 10, 2022. The population of the study consists of nursing students (n=979). The sample consisted of 563 students. "Personal Information Form," "Young's Internet Addiction Test-Short Form (YIAT-SF)" and "Social Safety and Pleasure Scale" were used to collect the data. Results: In the present study, it was found that the students' YIAT-SF mean score was 27.47±8.99, and their Social Safeness and Pleasure Scale mean score was 30.17±8.43. Those who were 2nd-year students, had an average internet usage time of 5-9 h and more than 10 h, did not have a personal computer, and considered the time they spent on the internet more had higher internet addiction levels, and lower social safeness and pleasure levels; on the other hand, those who were younger than 20 years old, were staying in dormitories and houses with their friends, and evaluated their income status as moderate or low, had lower social safeness and pleasure levels; on the other hand, the level of internet addiction was higher for men and those living with their families. Conclusion: A negative significant correlation was found between internet addiction and social safeness and pleasure. As internet addiction increased, the level of social safeness and pleasure decreased. [ABSTRACT FROM AUTHOR]

Background: Ultra high molecular weight polyethylene composites are fiber based composites used in armor applications. While some characterization has been conducted experimentally, this study varies multiple parameters simultaneously to investigate material response under a wide range of conditions. Objective: This work focuses on characterizing the response of Dyneema® HB26 hard laminate composites under high-speed impacts to examine the influence of plate diameter, clamping pressure, and plate spacing on target performance. Additionally, micro Computer Tomography scans are used to nondestructively evaluate the damage evolution in the targets. Methods: These scan results are used in concert with more traditional armor performance metrics to evaluate the effect of various parameters using the method of orthogonal array analysis. This technique allows for multiple variables to be investigated in the same test series, saving time and budget while still providing quality results across a range of variables and variable values. Results: We conclude that of the parameters investigated, the plate spacing parameter has the largest effect on performance, followed by the plate diameter. Bolt torque was found to not have a significant impact on results, indicating that an edge clamping pressure is not critical to material response. Additionally, by examining the high resolution scans, we can quantify the damage with an effective damage angle and that this angle is a good predictor of performance. Conclusion: Finally a damage theory involving the effective bending strength of the plates is discussed as an explanation for all of the results observed in this test series. [ABSTRACT FROM AUTHOR]

Copyright of Baghdad Science Journal is the property of Republic of Iraq Ministry of Higher Education & Scientific Research (MOHESR) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Several unique challenges arise in the new field of integration between Model‐Based Systems Engineering (MBSE) models and game‐based digital twin visualizations. First, no known standardized interfaces between the MBSE model and game engine visualization are defined, which can lead to custom or stove‐piped solutions. Additionally, visualizing digital twin models in true to life scale is insufficient with typical desktop computers. The Bi‐Directional Interface Requirements Operational System Test (BIFROST) prototype, funded by the US Army Program Executive Office (PEO) Aviation, seeks to address these challenges. Progress of the BIFROST prototype is covered in the paper. The prototype aims to determine the feasibility and challenges of validating interfaces through visualizing changes to an MBSE model in a 3D game engine. Research was performed to visualize part of an uncrewed aircraft system ground control station in 3D using the Unity game engine. A Mission Control Architecture MBSE model, developed by PEO Aviation, is used to drive the digital twin of the ground control station through a set of virtual reality (VR) controls. Users can visualize, analyze, and test the human‐machine interaction of the 3D models in VR prior to real‐world system changes. This paper presents the recommended interfaces between the MBSE model and 3D engine, lessons learned, and future research areas. [ABSTRACT FROM AUTHOR]

Identification of different species of animals has become an important issue in biology and ecology. Ornithology has made alliances with other disciplines in order to establish a set of methods that play an important role in the birds' protection and the evaluation of the environmental quality of different ecosystems. In this case, the use of machine learning and deep learning techniques has produced big progress in birdsong identification. To make an approach from AI-IoT, we have used different approaches based on image feature comparison (through CNNs trained with Imagenet weights, such as EfficientNet or MobileNet) using the feature spectrogram for the birdsong, but also the use of the deep CNN (DCNN) has shown good performance for birdsong classification for reduction of the model size. A 5G IoT-based system for raw audio gathering has been developed, and different CNNs have been tested for bird identification from audio recordings. This comparison shows that Imagenet-weighted CNN shows a relatively high performance for most species, achieving 75% accuracy. However, this network contains a large number of parameters, leading to a less energy efficient inference. We have designed two DCNNs to reduce the amount of parameters, to keep the accuracy at a certain level, and to allow their integration into a small board computer (SBC) or a microcontroller unit (MCU). [ABSTRACT FROM AUTHOR]

Introduction:The ability to measure a patient's visual acuity at home (HVA) is by far the most desired remote telemedicine capability sought by ophthalmologists. Methods:A systematic literature review was done using Pubmed to search for publications from 2010 to 2022 in English reporting on 10 studies that compared a patient's HVA to the clinic visual acuity (CVA). Results:Approaches to measuring HVA included using a phone-based application, a physical chart, a computer, and a website. The most accurate of these was the use of personal computers (COMPlog, Macustat, Web based test) at home with a bias of 1 letter. The most accessible and reliable was the use of a printable visual acuity chart, available in the public domain, which had adifference between HVA and CVA of 1 to 3.5 letters. Phone apps (Verana Vision) and stand-alone websites (Farsight.com) both had a greater mean difference of about 6 letters, respectively,with a moderate correlation coefficient. Discussion:Overall, all three methodologies demonstrated a good negative predictive value demonstrating their potential use as an effective screening tool to flag drastic vision decline between clinic visits. [ABSTRACT FROM AUTHOR]

Modern technology was applied to the data recorded during the excavation of Santo António de Tanná in the 1970s. The original recording techniques and the subsequent attempts, in the 1980s, to extract further information from the data are described. With the advent of modern and extremely powerful desktop computers this information has now been reprocessed, enabling three-dimensional (3D) coordinates of control points on the site to be determined and a 3D rendered model of the site created. Using this model of the internal hull of the ship, measurements can be made to determine the shape and form of the ship. This paper examines the original methodologies used and compares the modern measurements with the manual measurements taken over 50 years earlier. An investigation to determine the accuracy of the two systems is described together with an analysis of the techniques involved. [ABSTRACT FROM AUTHOR]

In addition to providing critical knowledge of the accurate mass of ions, ion mobility‐mass spectrometry (IM‐MS) delivers complementary data relating to the conformation and size of ions in the form of an ion mobility spectrum and derived parameters, namely, the ion's mobility (K) and the IM‐derived collision cross section (CCS). However, the maximum amount of information obtained in IM‐MS measurements is not currently transferred into analytical databases including the full mobility spectra (CCS distributions) as well as capturing of additional ion species (e.g., adducts) into the same compound entry. We introduce CCSfind, a new tool for building comprehensive databases from experimental IM‐MS measurements of small molecules. CCSfind allows predicted ion species to be chosen for input chemical formulae, which are then targeted by CCSfind after parsing open source mzML input files to provide a unified set of results within a single data processing step. CCSfind can handle both chromatographically separated isomers and IM separation of isomeric ions (e.g., "protomers" or conformers of the same ion species) with simple user control over the output for new database entries in SQL format. Files of up to 1 GB can be processed in less than 2 min on a desktop computer with 32 GB RAM with computational time scaling linearly with the size of the input mzML file or the number of input molecular formulae. Results are manually reviewed, annotated with experimental settings, before committing the database where the full dataset can be retrieved. [ABSTRACT FROM AUTHOR]