RDMA has been widely used in modern data centers because it can provide low-latency and high-bandwidth network communication for distributed applications. However, how to build an efficient RDMA-based RPC framework is...
RDMA has been widely used in modern data centers because it can provide low-latency and high-bandwidth network communication for distributed applications. However, how to build an efficient RDMA-based RPC framework is still challenging. We observe that existing work may have the following problems: First, the lack of a serialization module makes the RPC framework difficult to use, and cannot further be optimized by overlapping serialization and network communication. Second, CPU resources are ignored to scale out instead of focusing on QP and memory resources, which may result in the RPC framework not being scalable. In this paper, we propose LightRPC, which provides users with easy-to-use and portable interfaces via a new resource abstraction and achieves efficient performance through co-design of serialization and communication, usage of pre-registered memory, and adaptive polling mode. Compared to bRPC’s IPoIB and RDMA modes, LightRPC improves throughput by about 2.5x and 1.5x, respectively, and has lower median and tail latency.
Aiming at the problems of machining redundancy and rough process intersection caused by the existing single-process machining CNC programming method, a CNC programming technology based on process fusion is proposed af...
Aiming at the problems of machining redundancy and rough process intersection caused by the existing single-process machining CNC programming method, a CNC programming technology based on process fusion is proposed after analyzing the polygon clipping algorithm for machining path optimization. Firstly, the geometric characteristics of the process are analyzed, and the actual machining problem is transformed into a polygon clipping problem, thus establishing a mathematical model to solve it. Secondly, a new data structure and polygon clipping algorithm are designed to speed up problem solving. Finally, the process sequence is fused to generate a more efficient and reliable process execution flow. through simulation experiments, the CNC programming technology based on process fusion is compared withthe traditional CNC programming technology, and has significant advantages in improving machining efficiency and quality.
Fear of stigmatization has been a barrier for thai undergraduate students to actively reach out to health practitioners for support when they experience a mental health problem. Commercially available mental health sy...
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ISBN:
(纸本)9783031148323;9783031148316
Fear of stigmatization has been a barrier for thai undergraduate students to actively reach out to health practitioners for support when they experience a mental health problem. Commercially available mental health systems struggle to find a balance between effective clinical diagnostic capability and engaging user experience. In natural ambience, it is proven that users could better articulate their thoughts, which results in a higher efficacy of prescreening results in mental health assessment. Natural language processing (NLP) techniques are promising to enable this by developing a human-like digital assistant for mental health. the usability and user interface design of such mental health assessment tool should support the frictionless interaction while being compatible withthe thai context (e.g., language). To fill these gaps, in this study, we developed anNLP-based digital healthcare assistant as a pre-screening tool that can be used to detect undergraduate students' anxiety levels and identify their needs for psychological support. We conducted a pilot usability evaluation of the system focusing on the system's usability effectiveness, efficiency, and reliability. the findings can be concluded that creating a natural and user-friendly experience for users, with flexibility that allowed for individual preferences through a chat-based NLP system, results in an engaging user experience and less friction towards the adoption of the tool. these findings can be used to support the future development of an effective and user-friendly pre-screening tool for this particular user group.
Cloud manufacturing adopts contemporary information cutting-edge technologies including advanced concepts such as cloud computing to support the manufacturing industry. Under a wide range of network resource manufactu...
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Transportation serves as a means of connecting and has a very significant role in the movement of goods and people. Road transportation as connectivity between regions in urban areas, has tunnel roads that serve car a...
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Electrical impedance myography (EIM) is a non-invasive measurement technique capable of determining physiological and morphological changes in skeletal muscle tissue. the method consists of applying an alternating cur...
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ISBN:
(纸本)9783031077043;9783031077036
Electrical impedance myography (EIM) is a non-invasive measurement technique capable of determining physiological and morphological changes in skeletal muscle tissue. the method consists of applying an alternating current on the skin through two electrodes to determine the bioimpedance of the medium. EIM has contributed to the study of degenerative diseases that changes the electrical properties of muscle tissue during its evolution of the disease. the objective of this work is to develop a portable and low-cost impedance measurement instrument to assist in activities related to the study and diagnosis of muscle diseases. We present a modular hardware architecture that allows the impedance measurement of multiple muscles at the same time, but in the present work we test the performance of the prototype with a single impedance measurement channel implemented. the tests were performed with known theoretical impedance calculated to evaluate the accuracy of the impedance meter, as well as other performance tests of the system.
the outbreak of the COVID-19 pandemic has brought online education under the spotlight. Universities have resorted to online education practices, including online instruction and learning, to achieve outcomes that are...
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ISBN:
(纸本)9781665419338
the outbreak of the COVID-19 pandemic has brought online education under the spotlight. Universities have resorted to online education practices, including online instruction and learning, to achieve outcomes that are essentially comparable with offline classroom teaching. In this paper, an analysis was conducted to identify the impact of parallel online education on instructors and students, and relevant aspects were discussed. this study was aimed at obtaining a deeper understanding of the nature of online education so as to facilitate its long-term growth. this paper suggests that instructors should consider the particularity of online education when completing their pre-class, in-class and after-class instructional design, with a special focus on enhancing the learning outcomes of students.
Rectifier bridges and inverter bridge systems in high-power power equipment are usually sources of conduction interference on sensitive equipment. In order to effectively estimate the interference signal from the cabl...
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Withthe continuous development of computer technology, software application development and database technology, there is an urgent need to establish a complete and unified management information system in the manage...
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Medical image segmentation is a plan that has a lot of potential. the achievement of automated picture segmentation makes it simple to gather biomedical and anatomical information. In terms of the subject, more study ...
Medical image segmentation is a plan that has a lot of potential. the achievement of automated picture segmentation makes it simple to gather biomedical and anatomical information. In terms of the subject, more study and work have increased efficacy. In the field of image processing, this work provides a type-2 fuzzy system-based image application. computeraided diagnosis and medical image analysis both heavily rely on segmentation. this study presents a fuzzy type 2 algorithm based automated threshold selection method for the division of therapeutic pictures. It has been established that fuzzy set theory may be an effective tool for recitation surroundings when the facts are unclear or inaccurate. the algorithms have been put into practice and evaluated using brain MRI (magnetic resonance imaging) images. the outcomes have been evaluated and documented. the comparison of the controller’s efficiency of CNN has 92%.
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