A Seven-Dimensional Building Information Model for the Improvement of Construction Efficiency by Zhimin Wang, Jin Liu

“…The performance of this model has been demonstrated through a case study of a complex project launched in China. The study shows that the implementation of the 7D BIM has achieved significant cost and time saving as well as project quality and work efficiency improvement.…”
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Parameter Adaptive LCD Screen Defect Detection Framework by LIU Wang, SHAO Huili, HE Yongjun, XIE Yining, CHEN Deyun

“…It is necessary to detect defects in the production process of LCD screens for quality improvements Manual detection brings a heavy workload and low accuracy Therefore, an efficient and accurate automatic detection method is urgently needed To this end, this paper proposes a new defect detection framework, which mainly includes screen area extraction, preprocessing, threshold segmentation and defect selection By adaptive adjustment of parameters, the detection method can adapt to various complex situations In order to eliminate the influence of illumination changes, the defect region is segmented by automatic parameter adjustment in the threshold segmentation First, the maximum grayscale value of the image is calculated, and then the fixed parameters and the coefficient of the defect image are determined according to the nodefect image, and finally the maximum value which was selected as the minimum threshold of the threshold segmentation from the fixed parameters and the product of the maximum grayscale value and the coefficient In addition, in order to solve the problem that the brightness difference of the images captured by lowresolution cameras is too small to detect defects in the saturation condition, selfadaptive adjustment of exposure parameters was used to collect images to process different parts of images with large difference in light and shade Experiments show that the method can achieve high performance and efficiency in detecting defects such as points, lines, Mura, saturation…”
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Leveraging transformer models to predict cognitive impairment: accuracy, efficiency, and interpretability by Kai Ma, Junzhi Zhang, Xinhang Huang, Mengyang Wang

“…Conclusion The enhanced Transformer model offers superior accuracy and efficiency in predicting cognitive decline compared to traditional models. …”
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A framework for complex signal processing via synthetic biological operational amplifiers by Wenjun Cao, Lili Liu, Qingxu Sun, Yang Shan, Ye Chen

“…Abstract Engineering genetic circuits to process complex biological signals remains a significant challenge due to non-orthogonal signal responses that limit precise control. …”
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Improving Computational Efficiency in Monte Carlo Simulation for Radiation Portal Monitor by Sim Hayoung, Seo Hee

“…In the present study, the applicability of the various techniques to improve calculation efficiency was evaluated. For example, as a simple but highly effective way, a simple box was used to surround the complex geometry of the RPM, resulting in 1.75 times of improvement in the calculation efficiency. …”
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DANNET: deep attention neural network for efficient ear identification in biometrics by Deepthy Mary Alex, Kalpana Chowdary M., Hanan Abdullah Mengash, Venkata Dasu M., Natalia Kryvinska, Chinna Babu J., Ajmeera Kiran

“…Despite numerous proposed convolutional neural network (CNN) based deep learning techniques for ear detection, achieving the expected efficiency and accuracy remains a challenge. …”
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Efficient Onboard Multitask AI Architecture Based on Self-Supervised Learning by Gabriele Inzerillo, Diego Valsesia, Enrico Magli

“…Experiments on three sample tasks of cloud segmentation, flood detection, and marine debris classification on a 7-W embedded system show competitive results with inference quality close to high-complexity state-of-the-art models and high throughput in excess of 8 Megapixel/s.…”
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Spectral Efficient Asymmetrically Clipped Hybrid FBMC for Visible Light Communication by Sanjeev Kumar, Preeti Singh

“…The analytical performance of the proposed technique is compared using parameters, namely, bit error rate (BER), spectral efficiency, computational complexity, and peak to average power ratio (PAPR). …”
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Novel Intermode Prediction Algorithm for High Efficiency Video Coding Encoder by Chan-seob Park, Gwang-Soo Hong, Byung-Gyu Kim

“…Moreover, in order to speed up the encoding time, the efficient merge SKIP detection method is developed additionally based on the contextual mode information of neighboring CUs. …”
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Spatial heterogeneity and peptide availability determine CTL killing efficiency in vivo. by Thea Hogan, Ulrich Kadolsky, Sim Tung, Benedict Seddon, Andrew Yates

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YOLO-MFD: Object Detection for Multi-Scenario Fires by Fuchuan Mo, Shen Liu, Sitong Wu, Ruiyuan Chen, Tiecheng Song

“…Fire refers to a disaster caused by combustion that is uncontrolled in the temporal and spatial dimensions, occurring in diverse complex scenarios where timely and effective detection is crucial. …”
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Improved YOLO for long range detection of small drones by Sicheng Zhou, Lei Yang, Huiting Liu, Chongqin Zhou, Jiacheng Liu, Yang Wang, Shuai Zhao, Keyi Wang

“…The model demonstrates strong cross-dataset generalization, balancing accuracy and efficiency. These findings contribute to advancements in small drone target detection.…”
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A comprehensive review of direct, indirect, and AI-based detection methods for milk powder by Xiaodong Song, Song Shen, Guanjun Dong, Haohan Ding, Haohan Ding, Zhenqi Xie, Long Wang, Wenxu Cheng

“…The indirect detection methods of milk powder mainly use microscopic imaging, spectral analysis, electronic nose system, environmental parameter monitoring and other technologies to establish complex mathematical models and provide a fast and non-destructive alternative. …”
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Machine learning algorithm for intelligent detection of WebShell by Hua DAI, Jing LI, Xin-dai LU, Xin SUN

“…WebShell is a common tool for network intrusions,which has the characteristics of great harm and good concealment.The current detection method is relatively simple,and easy to be bypassed,so it is difficult to deal with complex and flexible WebShell.To solve these problems,a supervised machine learning algorithm was put forward to detect WebShell intelligently.By learning the features of existing WebShell and non-existing WebShell pages,the algorithm can make prediction of the unknown pages,and the flexibility and adaptability were both very good.Compared with the traditional WebShell detection methods,the experiment proves that the algorithm has higher detection efficiency and accuracy,and at the same time there is a certain probability to detect new types of WebShell.…”
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Deep Learning-Based Algorithm for Road Defect Detection by Shaoxiang Li, Dexiang Zhang

“…However, challenges remain, such as insufficient detection precision for detection precision for road defect recognition and issues of missed or false detections in complex backgrounds. …”
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Efficient CNN architecture with image sensing and algorithmic channeling for dataset harmonization by Khadija Kanwal, Khawaja Tehseen Ahmad, Aiza Shabir, Li Jing, Helena Garay, Luis Eduardo Prado Gonzalez, Hanen Karamti, Imran Ashraf

“…The goal targets compact efficient image feature vectors that process data in parallel regardless of input color or grayscale consistency and work across different datasets and semantic categories. …”
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Interpretable Deep Learning for Efficient Code Smell Prioritization in Software Development by Maaeda M. Rashid, Mohd Hafeez Osman, Khaironi Yatim Sharif, Hazura Zulzalil

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An Improved YOLOv9s Algorithm for Underwater Object Detection by Shize Zhou, Long Wang, Zhuoqun Chen, Hao Zheng, Zhihui Lin, Li He

“…However, the complex marine environment, poor resolution, color distortion in underwater optical imaging, and limited computational resources all affect the accuracy and efficiency of underwater object detection. …”
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Vibration-Based Damage Detection With Structural Modal Characteristics by Yonggang Wang, Yulong Pei, Yangdon Zhao

“…To address this issue, a novel technique, referred to as damage estimator with modal parameters of structure before and after damage, is applied to detect the location and estimate the severity of existing damage of complex structures. …”
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An Approach for Detecting Tomato Under a Complicated Environment by Chen-Feng Long, Yu-Juan Yang, Hong-Mei Liu, Feng Su, Yang-Jun Deng

“…The results indicate that the improved Graph-CenterNet method significantly enhances the accuracy and robustness of tomato detection in complex environments.…”
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