Search Results (66)

This study examines the use of digitalized educational solutions among students in higher education institutions (HEIs). Drawing upon theories of technology, digitalization, and education, we analyze the suitability of different digitalization solutions for students in HEIs. Educational organizations that apply different digitalized technologies provide customizable platforms for authoring and disseminating multimedia-rich e-education and smart education. However, pedagogical practices indicate several gaps between the level of HEI digitalization achieved and its suitability for HEI participants. Thus, we analyze the state of various digitalized technologies in HEIs and their suitability for meeting students’ expectations. The results of our research show that students most highly rate modern educational methods such as practical learning supported by access to digitized materials via websites, social networks, and smartphones while assigning a lower rating to the use of classic education, supported by digital textbooks and traditional technologies such as Skype, Zoom, podcasts, and online videos. This study has several theoretical implications, among which is the need to further develop highly digitized materials and purpose-designed digitized solutions for individual areas and specific educational purposes. The practical implications indicate the need to expand the use of website networks, smartphones, and smart table solutions in modern educational practices in HEIs. Full article

Single-image super-resolution imaging methods are increasingly being employed owing to their immense applicability in numerous domains, such as medical imaging, display manufacturing, and digital zooming. Despite their widespread usability, the existing learning-based super-resolution (SR) methods are computationally expensive and inefficient for resource-constrained IoT devices. In this study, we propose a lightweight model based on a multi-agent reinforcement-learning approach that employs multiple agents at the pixel level to construct super-resolution images by following the asynchronous actor–critic policy. The agents iteratively select a predefined set of actions to be executed within five time steps based on the new image state, followed by the action that maximizes the cumulative reward. We thoroughly evaluate and compare our proposed method with existing super-resolution methods. Experimental results illustrate that the proposed method can outperform the existing models in both qualitative and quantitative scores despite having significantly less computational complexity. The practicability of the proposed method is confirmed further by evaluating it on numerous IoT platforms, including edge devices. Full article

Emergency remote teaching was first introduced in the educational system of the Republic of Serbia during the COVID-19 pandemic, not as a planned change but as an imposed solution aimed at suppressing this infectious disease. This raises the question of the sustainability of remote teaching after the pandemic and the effects and experiences with emergency form of this method of teaching in the form it was used during the pandemic. Therefore, this paper is aimed at examining whether and in what manner technical factors such as digital competence, device equipment, Internet connection, and Zoom fatigue could contribute to students’ attitudes and satisfaction with this form of teaching, as well as how all these factors might contribute to the perception of satisfaction, efficiency, and sustainability of RT among the students of the teacher education faculties. The research involved 138 female university students from the faculties of education in Serbia. The results point to the unpreparedness of the educational system for the quick transition to emergency remote teaching and to inadequate logistic support for the implementation of this form of learning: from insufficient computer literacy, problems with the good-quality Internet in the territory of the whole country, having no adequate devices for following classes (most frequently mobile phones), students’ dissatisfaction with the effectiveness, to the phenomenon of Zoom fatigue as a consequence. The main finding is that students perceive remote teaching as a “necessary evil”, something that should be applied only when it is absolutely impossible to have the usual form of classes, only in emergency situations. This is also corroborated by the fact that after the pandemic, the school system returned to classes under traditional conditions. This leads to a conclusion about the unsustainability of the remote teaching model in Serbia, at least in the form that was applied, most probably because it was university students’ first and only experience in relation to it gained with emergency remote teaching, in the conditions of the COVID-19 crisis with its health, psychosocial, and economic pressures and with emergency form of this method of teaching. Full article

There are over 300 million smart homes worldwide and 60.4 million smart homes in the US, using devices like smart thermostats, smart plugs, smart door locks, etc. Yet in this age of smart and connected devices, we still use paper-based sticky notes on doors to display messages such as “Busy, do not disturb”, “In a Zoom meeting”, etc. In this project, a novel IoT-connected digital sticky note system was developed where the user can wirelessly send messages from a smartphone to a sticky note display. The sticky note displays can be hung on the doors of offices, hotels, homes, etc. The display could be updated with the user’s message sent from anywhere in the world. The key design challenge was to develop the display unit to consume as little power as possible to increase battery life. A prototype of the proposed system was developed comprising ultra-low-power sticky note display units consuming only 404 µA average current and having a battery life of more than six months, with a Wi-Fi-connected hub unit, an MQTT server, and a smartphone app for composing the message. Full article

As web maps are now extensively used by billions of users, the energy consumption of these maps is not marginal anymore. Green cartography seeks to reduce the energy consumption of maps to promote more sustainable digital tools. To reduce energy consumption, we first need to better understand the different sources of energy consumption for web maps. Among these sources, this paper focuses on the tiles that are stored on servers and then constantly transferred each time a user explores the map. This paper presents several experiments carried out with current web maps to assess this energy consumption. We first try to assess the number of map tiles that are loaded through the web when users explore web maps, and we determine which types of interaction are used with the maps, and a similar amount of tiles is loaded. Then, we try to assess which zoom levels are the most loaded by users; it appears that the medium–large scales are the most used (between zoom levels 11 and 17). Then, we explore the size of the map tiles and try to assess which ones are larger and thus require more energy to load over the web; we can find clear differences between zoom levels. Finally, we discuss how map generalization could be used to reduce energy consumption by creating lighter tiles. These experiments show that the current web maps are suboptimal regarding energy consumption, with many tiles loaded at zoom levels where the tiles are larger than necessary. Full article

To address the challenges of low accuracy and the difficulty in balancing a large field of view and long distance when tracking high-speed moving targets with a single sensor, an ROI adaptive digital zoom tracking method is proposed. In this paper, we discuss the impact of ROI on image processing and describe the design of the ROI adaptive digital zoom tracking system. Additionally, we construct an adaptive ROI update model based on normalized target information. To capture target changes effectively, we introduce the multi-scale regional measure and propose an improved particle filter algorithm, referred to as the improved multi-scale regional measure resampling particle filter (IMR-PF). This method enables high temporal resolution processing efficiency within a high-resolution large field of view, which is particularly beneficial for high-resolution videos. The IMR-PF can maintain high temporal resolution within a wide field of view with high resolution. Simulation results demonstrate that the improved target tracking method effectively improves tracking robustness to target motion changes and reduces the tracking center error by 20%, as compared to other state-of-the-art methods. The IMR-PF still maintains good performance even when confronted with various interference factors and in real-world scenario applications. Full article

Australia is an ethnically diverse nation with large numbers of migrants and refugees entering the country yearly. Despite research demonstrating that individuals from culturally and linguistically diverse (CaLD) communities experience an elevated risk of developing a mental illness, mental health services uptake is consistently low. To improve the mental health outcomes of these CaLD individuals in Australia, there is an urgent need to understand barriers to treatment, such as stigma. Research has noted that gender may play a role in mental health stigma and help-seeking. Using a qualitative approach as part of the Embrace Multicultural Mental Health Project, the aim of this study was to explore gender perspectives in mental health stigma and help-seeking among Arabic-speaking and Swahili-speaking individuals in Sydney. A total of five focus group discussions and 18 interviews were undertaken online using Zoom, digitally recorded, transcribed, and thematically analysed. Three major themes were identified. The first theme related to stigma and the fears regarding mental illness being discovered by others. The second theme related to the different approaches to confronting stigma. The last theme related to the various issues considered when identifying sources of help. Our findings suggest that a nuanced approach using the ‘what matters most’ framework can explain how men and women within each community may experience stigma and emphasise different aspects of help-seeking. These findings can help to guide clinical practitioners in delivering gender-specific and culturally sensitive and effective treatment sessions with these CaLD individuals, in addition to offering directions for stigma-reduction initiatives. Full article

Background/Objectives: We examined the feasibility, acceptability, and potential mental health impact of a digital peer support intervention involving videoconferencing and text-based support for parents of school-aged children living with T1D and analyzed posts exchanged by parents on a texting platform. Methods: Eighteen parents were recruited for Huddle4Parents, a 4-month digital intervention that involved four synchronous group-based Zoom sessions coupled with an asynchronous 24/7 peer support texting room. Primary outcomes were feasibility (i.e., ability to recruit n = 20 parents and retain at least 75%) and acceptability (i.e., satisfaction ratings of “good” to “very good”). Baseline and 4-month assessments also measured diabetes distress, quality of life, and perceived support. A content analysis of text exchanges was also performed. Results: All 15 parents who completed the intervention attended at least one Huddle and posted at least one message on the 24/7 peer support room. The retention rate was 83%, with 100% indicating that they would “definitely” or “probably yes” recommend both platforms to other parents. They also rated the topics, facilitator, and overall Huddles as “good” to “excellent.” No changes were observed for psychosocial endpoints. Of the 1084 texts posted, core support themes included the following: (1) dealing with technology and devices; (2) seeking and providing emotional support; (3) managing T1D in the school setting; and (4) exchanging tips and strategies. Conclusions: Huddle4Parents, a digital T1D caregiver intervention offering synchronous and asynchronous support, is feasible based on recruitment, participation, and attrition rates and acceptable as demonstrated by engagement and satisfaction ratings for the Huddles and 24/7 peer support room. Full article

The problem of academic fraud has recently grown and includes plagiarism, the use of cellphones, copying from others, and writing by use of artificial intelligence (AI). The objective of this study was to examine the connection between academic dishonesty, class attendance, self-efficacy, and the use of digital tools. The study focused on higher-education students in Israel and included 121 participants. It was a mixed qualitative and quantitative study based on a structured questionnaire and on the previous literature. Studies showed that academic dishonesty increases when students fail to attend classes, have low self-efficacy, and attend classes remotely via communication platforms such as Zoom. In the current study, 50% of the participants reported that academic dishonesty was perceived as legitimate among their peer students. Preventive measures such as strengthening the students’ self-efficacy during tests and other stressful situations and emphasizing the importance of acquiring professional knowledge and skills may more effectively eliminate fraud than the common method of disciplining wrongdoers. Full article

This paper presents a low-power, energy-efficient, 12-bit incremental zoom analog-to-digital converter (ADC) for multi-channel bio-signal acquisitions. The ADC consists of a 7-stage ring voltage-controlled oscillator (VCO)-based incremental ΔΣ modulator (I-ΔΣM) and an 8-bit successive approximation register (SAR) ADC. The proposed VCO-based I-ΔΣM can provide fast phase-alignment of the ring-VCO to reduce the interval settling time; thereby, the I-ΔΣM can accommodate time-division-multiplexed input signals without phase leakage between consecutive measurements. The SAR ADC also adopts splitting unit capacitors that can support V_CM-free tri-level switching and prevent invalid states from the phase frequency detector with minimal logic gates and switches. The proposed ADC has been fabricated in a standard 180 nm standard 1P6M CMOS process, exhibiting a 67-dB peak signal-to-noise ratio, a 74-dB dynamic range, and a Walden figure of merit of 19.12 fJ/c-s, while consuming a power of 3.51 μW with a sampling rate of 100 kS/s. Full article

This paper presents the development of a comprehensive, on-site industrial Optical Character Recognition (OCR) system tailored for reading text on iron plates. Initially, the system utilizes a text region detection network to identify the text area, enabling camera adjustments along the x and y axes and zoom enhancements for clearer text imagery. Subsequently, the detected text region undergoes line-by-line division through a text segmentation network. Each line is then transformed into rectangular patches for character recognition by the text recognition network, comprising a vision-based text recognition model and a language network. The vision network performs preliminary recognition, followed by refinement through the language model. The OCR results are then converted into digital characters and recorded in the iron plate registration system. This paper’s contributions are threefold: (1) the design of a comprehensive, on-site industrial OCR system for autonomous registration of iron plates; (2) the development of a realistic synthetic image generation strategy and a robust data augmentation strategy to address data scarcity; and (3) demonstrated impressive experimental results, indicating potential for on-site industrial applications. The designed autonomous system enhances iron plate registration efficiency and significantly reduces factory time and labor costs. Full article

Spatial image transformation is a commonly used component in many image processing pipelines. It enables the correction of optical distortions, image registration onto a common reference plane, electronic image stabilisation, digital zoom, video mosaicking, etc. With the growing tendency to embed image processing in low-power devices, attaining an efficient transformation solution becomes increasingly decisive. Furthermore, interpolation is the key operation in achieving the high quality of the transformed data from the original data. Fortunately, different implementations have already seen several efficiency improvements in recent years. However, interpolation relies on sampling a set of neighbouring points from memory, which has yet to be addressed efficiently for smaller computational platforms with limited memory resources. In this work, we derive a generic mathematical model and circuit design principles for the spatial transformation accelerator design for N-dimensional data. Furthermore, we present an efficient simultaneous access scheme for high-quality signal reconstruction. Finally, the introduced ideas are verified in field programmable gate arrays using one-dimensional and two-dimensional data transformation use cases. The presented solution is able to transform images with sizes ranging from 256 × 256 to 8192 × 8192 and achieves a transfer rate of 275 frames per second with 512 × 512 images. Full article

Passive location based on TDOA (time difference of arrival) and FDOA (frequency difference of arrival) is the mainstream method for target localization. This paper proposes a fast time–frequency difference positioning method to address issues such as low accuracy, large computational resource utilization, and limited suitability for real-time signal processing in the conventional CAF (cross-ambiguity function)-based approach, aiming to complete the processing of the target radiation source to obtain the target parameters within a short timeframe. In the mixing product operation step of the CAF, a frequency-domain approach replaces the time-domain convolution operation in PW-ZFFT (pre-weighted Zoom-FFT) to reduce the computational load of the CAF. Additionally, a quadratic surface fitting method is used to enhance the accuracy of TDOA and FDOA. The localization solution is obtained using Newton’s method, which can provide more accurate results compared to analytical methods. Next, a signal processing platform is designed with FPGA (field-programmable gate array) and multi-core DSP (digital signal processor), and works by dividing and mapping the algorithm functional modules according to the hardware’s characteristics. We analyze the architectural advantages of multi-core DSP and design methods to improve program performance, such as EDMA transfer optimization, inline function optimization, and cache optimization. Finally, this paper constructs simulation tests in typical positioning scenarios and compares them to hardware measurement results, thus confirming the correctness and real-time capability of the program. Full article

In the past, plant layouts were regarded as highly static structures. With increasing internal and external factors causing turbulence in operations, it has become more necessary for companies to adapt to new conditions in order to maintain optimal performance. One possible way for such an adaptation is the adjustment of the plant layout by rearranging the individual facilities within the plant. Since the information about the plant layout is considered as master data and changes have a considerable impact on interconnected processes in production, it is essential that this data remains accurate and up-to-date. This paper presents a novel approach to create a digital shadow of the plant layout, which allows the actual state of the physical layout to be continuously represented in virtual space. To capture the spatial positions and orientations of the individual facilities, a pan-tilt-zoom camera in combination with fiducial markers is used. With the help of a prototypically implemented system, the real plant layout was captured and converted into different data formats for further use in exemplary external software systems. This enabled the automatic updating of the plant layout for simulation, analysis and routing tasks in a case study and showed the benefits of using the proposed system for layout capturing in terms of accuracy and effort reduction. Full article

Since their inception with Bitcoin in the late 2000s, cryptocurrencies have grown exponentially, reshaping traditional financial paradigms. This transformative journey, while innovative, brings forth pressing concerns about their energy consumption and carbon footprint. While many studies tend to zoom in on Bitcoin, this paper broadens the perspective by evaluating energy consumption across various cryptocurrencies. We analyze nine cryptocurrency projects, chosen for their market value, technology, and data availability. These span a spectrum from pioneering to emerging digital coins, offering a holistic view of the crypto realm. To contextualize, we juxtapose the energy usage of these digital currencies with traditional payment means like Visa and Mastercard. Our analysis shows vast differences in energy use among cryptocurrencies, largely tied to their consensus algorithms. Notably, while Bitcoin stands out as highly energy-intensive, several newer digital currencies have energy footprints mirroring those of conventional payment methods. Additionally, CO₂ emissions estimation presents challenges due to variances in miner locations and regional energy sources, with potential higher emissions if concentrated in carbon-intensive regions like China. Nonetheless, the silver lining emerges as many cryptocurrencies, especially those beyond Bitcoin, register considerably lower CO₂ emissions. By moving the lens beyond Bitcoin, this paper paints a more nuanced picture of the environmental ramifications of the crypto world. Full article