-
1مؤتمر
المساهمون: Dilillo, Nicola, Ferrero, Renato, Gandino, Filippo, Rebaudengo, Maurizio
مصطلحات موضوعية: cold chain, Internet of Thing, RFID, Bluetooth, sensor, communications technology, computers and information processing
الوصف: Thermal monitoring is a key requirement for cold chain management. In this context, the Internet of Things (IoT) offers new opportunities for dense and/or large-scale deployment of sensors, which need to collect data to effectively control the cooling system. Various technologies are used for data transmission. Although Bluetooth is widely exploited for transmitting data in IoT applications, its use in the cold chain management is rare. In this paper, the architecture of an IoT temperature monitoring system is studied and the technological choices of its components are analyzed and compared. In particular, the paper focuses on IoT node boards with Bluetooth, in order to highlight the opportunities of a currently undervalued technology. A theoretical analysis highlights its benefits for the application context and evaluates its suitability for monitoring systems suitable for cold rooms. The theoretical results are supported by an experimental analysis based on the implementation of different systems.
وصف الملف: ELETTRONICO
العلاقة: info:eu-repo/semantics/altIdentifier/isbn/979-8-3503-2711-3; ispartofbook:2023 IEEE Conference on AgriFood Electronics (CAFE); AgriFood Electronics (CAFE), IEEE Conference on; firstpage:89; lastpage:93; numberofpages:5; https://hdl.handle.net/11583/2982667Test; info:eu-repo/semantics/altIdentifier/scopus/2-s2.0-85178638763; https://ieeexplore.ieee.org/document/10291686Test
الإتاحة: https://doi.org/10.1109/CAFE58535.2023.10291686Test
https://hdl.handle.net/11583/2982667Test
https://ieeexplore.ieee.org/document/10291686Test -
2دورية أكاديمية
المؤلفون: Durmus Ozdemir, Musa Selman Kunduraci
المصدر: IEEE Access, Vol 10, Pp 35675-35684 (2022)
مصطلحات موضوعية: Artificial intelligence, computers and information processing, insect classification, Electrical engineering. Electronics. Nuclear engineering, TK1-9971
الوصف: Insects are a class of the arthropod branch and the most crowded animal group in terms of species and taxonomy. Due to destruction and forest fires, some insect species could go extinct without being detected. Identifying new insects and having knowledge about insects in terms of biodiversity will contribute positively to the studies carried out, especially in entomology, agriculture, the pharmaceutical industry, medicine, robotics, and other branches. In this study, we produced a mobile-based decision support software with a deep learning model to classify and detect insects at the order level. We also presented the comparative analysis results of SSD MobileNET, YoloV4, and Faster R-CNN InceptionV3 deep learning methods and adapting processes for order-level insect classification. Our approach studies the suitability of existing models towards such an objective, and we conclude that Faster R-CNN InceptionV3 performs the best at classifying and detecting insects at the order level. In addition, we shared 25820 training and 1500 test data in the kaggle database in order to contribute studies to be carried out in this area. As a result, we believe that this research will be beneficial to entomologists, naturalists, and other researchers in related fields.
وصف الملف: electronic resource
-
3دورية أكاديمية
المؤلفون: Mehmet Rida Tur, Hidayet Ogras
المصدر: IEEE Access, Vol 9, Pp 27323-27332 (2021)
مصطلحات موضوعية: Chaotic encryption, computers and information processing, frequency control, smart grids, power system security, Electrical engineering. Electronics. Nuclear engineering, TK1-9971
الوصف: Data communication security between power systems, which has become a chronic problem in the classical network, is characterized by the application of information communication technology (ICT) in modern network models. Nowadays, the electricity network is spread over very large areas, and the load taking, and load shedding instructions are transmitted one-way and unsafe in the current structure. However, utilities in the smart grid are developing new methodologies to secure the communication infrastructure. This article presents a design that will make the current grid model more reliable and provide a secure data communication in accordance with the modern grid infrastructure. This design provides auxiliary communication codes such as chaotic codes embedded in the communication instructions between power systems, which are generation balance instructions sent to the power plants by the load dispatch center to achieve frequency balance. Used as a case study, one-day instructions are transmitted and encoded four times a day, which is the amount of capacity that only the receiver and transmitter can understand with two-sided encryption. The necessary reserve capacity, chaotic encryption and suitability for real-time applications were evaluated using experimentally obtained power system data for frequency control, which is very important in terms of sustainability in energy and economy against cyber-attacks, and very accurate results were obtained.
وصف الملف: electronic resource
-
4دورية أكاديمية
المؤلفون: Manuel Trinidad, Mercedes Ruiz, Alejandro Calderon
المصدر: IEEE Access, Vol 9, Pp 46505-46544 (2021)
مصطلحات موضوعية: Bibliometrics, computers and information processing, gamification, science mapping, scientometrics, Electrical engineering. Electronics. Nuclear engineering, TK1-9971
الوصف: Gamification has rapidly emerged as one of the favorite persuasive technologies widely used with the aim of promoting a positive change in the user’s behavior by means of including game-like elements in non-game contexts. As a research discipline, gamification is growing fast, maturing from basic and fundamental questions such as what and why gamify to more mature ones such as how to gamify, when and when not, and still facing empirical and theoretical challenges to prove the effects of its practice and consolidate the principles that guide meaningful gamification designs. The purpose of this paper is to conduct a bibliometric study to describe how gamification as a scientific discipline is structured and how it has evolved over time. To do this, we make use of bibliometric performance analysis and science mapping methods to display and analyze the intellectual, conceptual and social network structures of gamification research, as well as the evolution and dynamical aspects of the discipline. The results reveal the research fronts and intellectual structures of the field, the internal relationships among articles, authors and keywords, the existing networks of collaboration, the emerging trends, the hot topics, and the most influential authors, publications and sources. Together, they picture the intellectual landscape of gamification as a scientific field that will be useful for junior and senior researchers, practitioners, funding agencies and policymakers.
وصف الملف: electronic resource
-
5دورية أكاديمية
المؤلفون: Angela Locoro, William P. Fisher, Luca Mari
المصدر: IEEE Access, Vol 9, Pp 71053-71071 (2021)
مصطلحات موضوعية: Computers and information processing, information and communication technology, information management, visual communication, visualization, Electrical engineering. Electronics. Nuclear engineering, TK1-9971
الوصف: A major problem in education and visual information design is that, while tools to measure people’s reading and writing ability with texts and numbers are ripe, the ability to properly process information from data graphics – an ability that can be called Visual Information Literacy – is still off the radar, and even less interest is apparently devoted to its evaluation. The purpose of this research is that of presenting an exploration of methods and tools towards the measurement of data graphics effectiveness and efficiency, and of proposing a definition of ‘Visual Information Literacy’, together with the design of a model characterizing it as a developmental skills progression that covers the cognitive abilities activated when dealing with data graphics. A final goal of this paper is to report a first round of results assessing the validity of the model designed, by bringing statistical evidence that data graphics comprehension depends on the matching of users’ ability and data graphics difficulty. The contribution of this paper is twofold: comparing the current research on Visual Information Literacy and advancing it by designing a model for its characterization to allow the design of a Visual Information Literacy measurement scale standard.
وصف الملف: electronic resource
-
6دورية أكاديمية
المؤلفون: Conrad J. Haupt, Ekow J. Otoo, Ling Cheng
المصدر: IEEE Access, Vol 9, Pp 80415-80433 (2021)
مصطلحات موضوعية: Data compression, computers and information processing, digital elevation models, radio astronomy, space-filling curves, multidimensional data, Electrical engineering. Electronics. Nuclear engineering, TK1-9971
الوصف: For multidimensional data, Space-Filling Curves (SFCs) have been used to improve the execution time of spatial data queries. However, their effect on compression, when used to reorder the uncompressed values, is known to a lesser extent. We investigate the impact of three SFCs on Shuttle Radar Topographic Mission (SRTM) elevation data and Square-Kilometre Array telescope (SKA) radio-astronomy data: two types of datasets to which SFCs have not been extensively applied, within a compression context. This work contributes to the understanding of how such reorderings impact compression performance and affect different compression schemes and preprocessing techniques through their use. We show empirical results from combining eight common compression schemes, the Z-Order, Gray-Code, and Hilbert space-filling curves, and the bitwise preprocessing technique BitShuffle. The Hilbert Curve consistently outperforms the other orderings for the SRTM dataset though the mapping implementation incurs a significant speed penalty. However, the Z-Order and Gray-Code Curves are best for the SKA dataset. Through an analysis of the dataset autocorrelations, file-entropies, and block-entropies; we show that the SKA dataset’s dimensional bias is not exploited as much by the Hilbert Curve compared to the Z-Order and Gray-Code Curves. However, the Hilbert Curve is the most appropriate for the SRTM dataset as it can be modelled as isotropic and has a significantly higher level of local autocorrelation. BitShuffle is necessary to practically compress the SKA data, but does contribute to the compression performance of the SRTM dataset. These curves and BitShuffle are advantageous in reducing block-entropy values for such datasets.
وصف الملف: electronic resource
-
7دورية أكاديمية
المؤلفون: Billy Peralta, Alejandro Figueroa, Orietta Nicolis, Alvaro Trewhela
المصدر: IEEE Access, Vol 9, Pp 156701-156716 (2021)
مصطلحات موضوعية: Community question answering, image processing, social computing, user demographic analysis, computers and information processing, data systems, Electrical engineering. Electronics. Nuclear engineering, TK1-9971
الوصف: There are several reasons why gender recognition is vital for online social networks such as community Question Answering (cQA) platforms. One of them is progressing towards gender parity across topics as a means of keeping communities vibrant. More specifically, this demographic variable has shown to play a crucial role in devising better user engagement strategies. For instance, by kindling the interest of their members for topics dominated by the opposite gender. However, in most cQA websites, the gender field is neither mandatory nor verified when submitting and processing enrollment forms. And as might be expected, it is left blank most of the time, forcing cQA services to infer this demographic information from the activity of their users on their platforms such as prompted questions, answers, self-descriptions and profile images. There is only a handful of studies dissecting automatic gender recognition across cQA fellows, and as far as we know, this work is the first effort to delve into the contribution of their profile pictures to this task. Since these images are an unconstrained environment, their multifariousness poses a particularly difficult and interesting challenge. With this mind, we assessed the performance of three state-of-art image processing techniques, namely pre-trained neural network models. In a nutshell, our best configuration finished with an accuracy of 81.68% (Inception-ResNet-50), and its corresponding Grad-Cam maps unveil that one of its principal focus of attention is determining silhouettes edges. All in all, we envisage that our findings are going to play a fundamental part in the design of efficient multi-modal strategies.
وصف الملف: electronic resource
-
8دورية أكاديمية
المؤلفون: Özdemir, Durmuş, Kunduracı, Musa Selman
المساهمون: Özdemir, Durmuş
مصطلحات موضوعية: Artificial Intelligence, Computers And Information Processing, Insect Classification
الوصف: Insects are a class of the arthropod branch and the most crowded animal group in terms of species and taxonomy. Due to destruction and forest fires, some insect species could go extinct without being detected. Identifying new insects and having knowledge about insects in terms of biodiversity will contribute positively to the studies carried out, especially in entomology, agriculture, the pharmaceutical industry, medicine, robotics, and other branches. In this study, we produced a mobile-based decision support software with a deep learning model to classify and detect insects at the order level. We also presented the comparative analysis results of SSD MobileNET, YoloV4, and Faster R-CNN InceptionV3 deep learning methods and adapting processes for order-level insect classification. Our approach studies the suitability of existing models towards such an objective, and we conclude that Faster R-CNN InceptionV3 performs the best at classifying and detecting insects at the order level. In addition, we shared 25820 training and 1500 test data in the kaggle database in order to contribute studies to be carried out in this area. As a result, we believe that this research will be beneficial to entomologists, naturalists, and other researchers in related fields. © 2013 IEEE.
وصف الملف: application/pdf
العلاقة: IEEE Access; Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı; WoS - Science Citation Index Expanded; https://hdl.handle.net/20.500.12438/9425Test
-
9دورية أكاديمية
المؤلفون: Rodriguez, Pau, Cucurull, Guillem, Gonzàlez, Jordi, M. Gonfaus, Josep, Nasrollahi, Kamal, Moeslund, Thomas B., Xavier Roca, F.
المصدر: Rodriguez , P , Cucurull , G , Gonzàlez , J , M. Gonfaus , J , Nasrollahi , K , Moeslund , T B & Xavier Roca , F 2022 , ' Deep Pain : Exploiting Long Short-Term Memory Networks for Facial Expression Classification ' , I E E E Transactions on Cybernetics , vol. 52 , no. 5 , 7849133 , pp. 3314-3324 . https://doi.org/10.1109/TCYB.2017.2662199Test
مصطلحات موضوعية: deep learning, pain recognition, Affective computing, cybercare industry applications, human factors engineering in medicine and biology, computer applications, medical services, monitoring, patient monitoring computers and information processing, pattern recognition
الوصف: Pain is an unpleasant feeling that has been shown to be an important factor for the recovery of patients. Since this is costly in human resources and difficult to do objectively, there is the need for automatic systems to measure it. In this paper, con- trary to current state-of-the-art techniques in pain assessment, which are based on facial features only, we suggest that the performance can be enhanced by feeding the raw frames to deep learning models, outperforming the latest state-of-the-art results while also directly facing the problem of imbalanced data. As a baseline, our approach first uses convolutional neural networks (CNN) to learned facial features from VGG Faces, which are then linked to a Long Short-Term Memory (LSTM) to exploit the temporal relation between video frames. We further compare the performances of using the so popular schema based on the canonically normalized appearance versus taking into account the whole image: As a result, we outperform current state- of-the-art AUC performance in the UNBC-McMaster Shoulder Pain Expression Archive Database. In addition, to evaluate the generalization properties of our proposed methodology on facial motion recognition, we also report competitive results in the Cohn Kanade+ facial expression database.
وصف الملف: application/pdf
الإتاحة: https://doi.org/10.1109/TCYB.2017.2662199Test
https://vbn.aau.dk/da/publications/56823ffc-8ae0-420f-b235-f64833bd72cfTest
https://vbn.aau.dk/ws/files/293129334/Deep_Pain_Exploiting_Long_Short_Term_Memory_Networks_for_Facial_Expression_Classification.pdfTest -
10دورية أكاديمية
المؤلفون: Jiseon Kang, Jeongjin Lee, Yeong-Gil Shin, Bohyoung Kim
المصدر: IEEE Access, Vol 8, Pp 93335-93345 (2020)
مصطلحات موضوعية: Computer graphics, computers and information processing, image generation, imaging, depth of field effect, direct volume rendering, Electrical engineering. Electronics. Nuclear engineering, TK1-9971
الوصف: Direct volume rendering is a widely used technique for extracting information from three-dimensional scalar fields acquired by measurement or numerical simulation. However, the translucency of direct volume rendering to express the internal structure of the volume often makes it difficult to recognize the depth of complex structures. In this paper, we propose a new method for applying depth-of-field effects to volume ray-casting to improve the depth perception. A thin lens camera model is used to simulate rays passing through different parts of lens. The proposed method is implemented in the GPU pipeline with no preprocessing, so any acceleration techniques of volume ray-casting can be applied without restrictions. We also propose a multi-pass rendering framework using progressive lens sampling. This new technique uses a different number of lens samples per pixel, depending on the size of the circle of confusion at the point where each ray intersects the volume data. In the experiments with various data, we demonstrated that higher quality images with better depth perception were generated up to 9x faster than the existing depth-of-field method in direct volume rendering.
وصف الملف: electronic resource
النص الكامل