Current Issue : January - March Volume : 2021 Issue Number : 1 Articles : 5 Articles
This paper proposes a real-time thermal monitoring method using embedded integrated\nsensor interfaces dedicated to industrial integrated system applications. Industrial sensor interfaces\nare complex systems that involve analog and mixed signals, where several parameters can influence\ntheir performance. These include the presence of heat sources near sensitive integrated circuits, and\nvarious heat transfer phenomena need to be considered. This creates a need for real-time thermal\nmonitoring and management. Indeed, the control of transient temperature gradients or temperature\ndifferential variations as well as the prediction of possible induced thermal shocks and stress at early\ndesign phases of advanced integrated circuits and systems are essential. This paper addresses the\ngrowing requirements of microelectronics applications in several areas that experience fast variations\nin high-power density and thermal gradient differences caused by the implementation of different\nsystems on the same chip, such as the new-generation 5G circuits....
Diabetic retinopathy is one of the leading causes of vision loss in the United States and\nother countries around the world. People who have diabetic retinopathy may not have symptoms\nuntil the condition becomes severe, which may eventually lead to vision loss. Thus, the medically\nunderserved populations are at an increased risk of diabetic retinopathy-related blindness. In this\npaper, we present development efforts on an embedded vision algorithm that can classify healthy\nversus diabetic retinopathic images. Convolution neural network and a k-fold cross-validation\nprocess were used. We used 88,000 labeled high-resolution retina images obtained from the publicly\navailable Kaggle/EyePacs database. The trained algorithm was able to detect diabetic retinopathy\nwith up to 76% accuracy. Although the accuracy needs to be further improved, the presented results\nrepresent a significant step forward in the direction of detecting diabetic retinopathy using embedded\ncomputer vision. This technology has the potential of being able to detect diabetic retinopathy\nwithout having to see an eye specialist in remote and medically underserved locations, which can\nhave significant implications in reducing diabetes-related vision losses....
A topological index is an important tool in predicting physicochemical properties of a chemical compound. Topological indices\nhelp us to assign a single number to a chemical compound. Drugs and other chemical compounds are frequently demonstrated as\ndifferent polygonal shapes, trees, graphs, etc.............................
Recently, knowledge graph embedding methods have attracted numerous researchersâ?? interest due to their outstanding effectiveness\nand robustness in knowledge representation. However, there are still some limitations in the existing methods.On the one\nhand, translation-based representation models focus on conceiving translation principles to represent knowledge from a global\nperspective, while they fail to learn various types of relational facts discriminatively. It is prone to make the entity congestion of\ncomplex relational facts in the embedding space reducing the precision of representation vectors associating with entities. On the\nother hand, parallel subgraphs extracted from the original graph are used to learn local relational facts discriminatively. However,\nit probably causes the relational fact damage of the original knowledge graph to some degree during the subgraph extraction. Thus,\nprevious methods are unable to learn local and global knowledge representation uniformly. To that end, we propose a multiview\ntranslation learning model, named MvTransE, which learns relational facts from global-view and local-view perspectives, respectively.\nSpecifically, we first construct multiple parallel subgraphs from an original knowledge graph by considering entity\nsemantic and structural features simultaneously. Then, we embed the original graph and construct subgraphs into the corresponding\nglobal and local feature spaces. Finally, we propose a multiview fusion strategy to integrate multiview representations of\nrelational facts. Extensive experiments on four public datasets demonstrate the superiority of our model in knowledge graph\nrepresentation tasks compared to state-of-the-art methods....
As a substitute for the IEEE 754-2008 floating-point standard, Posit, a new kind of number\nsystem for floating-point numbers, was put forward recently. Hitherto, some studies have proven\nthat Posit is a better floating-point style than IEEE 754-2008 in some fields. However, most of these\nstudies presented the advantages of Posit from the arithmetical aspect, but none of them suggested\nit had a better hardware implementation than that of IEEE 754-2008. In this paper, we propose\nseveral hardware implementations that contain the Posit adder/subtractor, multiplier, divider, and\nsquare root. Our goal is to achieve an arbitrary Posit format and exploit the minimum circuit\narea, which is required in embedded devices. To implement the minimum circuit area for the\ndivider and square root, the alternating addition and subtraction method is used rather than the\nNewtonâ??Raphson method. Compared with other works, the area of our divider is about 0.2Ã?â??0.7Ã?\n(FPGA). Furthermore, this paper provides the synthesis results for each critical module with the\nXilinx Virtex-7 FPGA VC709 platform....
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