Research on real-time data visualization methods is necessary to achieve the most accurate and clear representation of information. Creating specific boards and modifying current platforms are two key tasks in perform...
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Digital microfluidic biochip provides an alternative platform to synthesize the biochemical protocols. Droplet routing in biochemical synthesis involves moving multiple droplets across the biochip simultaneously. It i...
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Due to the negligence of driver or to some exterior factors may cause many people lost their lives in road accidents. So, there is a vital requirement to develop an efficient and effective accident detection system wh...
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This paper introduces a guide aimed at aligning academic learning with industry standards in Agile methodology and Scrum framework usage. Targeting students, educators, and industry practitioners, it addresses the pre...
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In this paper, we consider the problem of multi-cell interference coordination by joint beamforming and power control. Recent efforts have explored the use of reinforcement learning (RL) methods to tackle this complex...
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In recent years, there has been a persistent focus on developing systems that can automatically identify the hate speech content circulating on diverse social media platforms. This paper describes the team "Trans...
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Over the past years, researchers across the globe have made significant efforts to develop systems capable of identifying the presence of hate speech in different languages. This paper describes the team Transformers&...
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The Internet of things (IoT) is widely used for communication between portable and intelligent heterogeneous devices, like laptops, smartphones, computers, etc. IoT networks are popular in the modern era because they ...
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In the field of machining, product quality must meet customer specifications. In general, surface roughness is an essential indicator of machining quality. Low surface roughness correlates with increased fatigue stren...
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In the field of machining, product quality must meet customer specifications. In general, surface roughness is an essential indicator of machining quality. Low surface roughness correlates with increased fatigue strength and corrosion resistance. However, the main factor that affects surface roughness is the selection of the machining parameters. When different parameters are combined, the resulting machining quality varies. Therefore, to achieve the desired machining quality, appropriate machining parameters must be selected. In this study, an ultrasonic-assisted machining system (UAMS) was designed to help users determine the machining parameters and machine SiC materials. To establish a prediction model for surface roughness, a novel network mapping fusion (NMF) convolutional neuro-fuzzy network (CNFN) model was used in the designed UAMS. The differential evolution algorithm was then used to search for optimized machining parameters. To explain the prediction model, which can help analyze the factors that have the greatest influence on surface roughness, a Shapley additive explanations method is proposed. The proposed NMF–CNFN model was more accurate than were the other deep learning models and exhibited a MAPE of 1.98%. When optimized machining parameters were selected, the desired surface roughness was obtained, thereby confirming the effectiveness and accuracy of the proposed UAMS. Moreover, the proposed model was implemented in a field-programmable gate array (FPGA) to reduce its power consumption and increase its computational performance. Experimental results indicated that the computational speed of the FPGA was 99.64%and 99.16%higher than those of the CPU and GPU, respectively. IEEE
Intention detection is a crucial aspect of natural language understanding (NLU), focusing on identifying the primary objective underlying user input. In this work, we present a transformer-based method that excels in ...
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