CFR-YOLO: A Novel Cow Face Detection Network Based on YOLOv7 Improvement by Guohong Gao, Yuxin Ma, Jianping Wang, Zhiyu Li, Yan Wang, Haofan Bai

“…With the rapid development of machine learning and deep learning technology, cow face detection technology has achieved remarkable results. …”
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Object detection with afordable robustness for UAV aerial imagery: model and providing method by Viacheslav Moskalenko, Artem Korobov, Yuriy Moskalenko

“…The detector training method was developed for the first time, combined the RetinaNet loss function with the gate unit loss function and applied meta-learning to the results of adaptation to various types of synthetic disturbances. …”
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Unsupervised Global Difference Modeling for Image Change Detection by Wenhua Zhang, Qihao Weng, Jia Liu, Zeng Qu, Yong Li, Jinjin Chai, Liang Xiao

“…Then, a new loss function is derived to alternately train the feature learning network and generalization network. …”
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A ranking hashing algorithm based on listwise supervision by Anbang YANG, Jiangbo QIAN, Yihong DONG, Huahui CHEN

“…Recently,learning to hash technology has been used for the similarity search of large-scale data.It can simultaneous increase the search speed and reduce the storage cost through transforming the data into binary codes.At present,most ranking hashing algorithms compare the consistency of data in the Euclidean space and the Hamming space to construct the loss function.However,because the Hamming distance is a discrete integer value,there may be many data points sharing the same Hamming distance result in the exact ranking cannot be performed.To address this challenging issue,the encoded data was divided into several subspaces with the same length.Each subspace was set with different weights.The Hamming distance was calculated according to different subspace weights.The experimental results show that this algorithm can effectively sort the data in the Hamming space and improve the accuracy of the query compared with other learning to hash algorithms.…”
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Association of radiographic structure deformity phenotypes of knee OA to clinical symptoms and risk for progression: Proposing a modification of Kellgren-Lawrence grade - Data from... by Sunho Ko, Yunhee Choi, Hyuk-Soo Han, Seong Hwan Kim, Du Hyun Ro

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Negotiating Cultures in Cyberspace: Participation Patterns and Problematics by Kenneth Reeder, Leah P. Macfadyen, Joerg Roche, Mackie Chase

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Predictive validity of consensus-based MRI definition of osteoarthritis plus radiographic osteoarthritis for the progression of knee osteoarthritis: A longitudinal cohort study by Xing Xing, Yining Wang, Jianan Zhu, Ziyuan Shen, Flavia Cicuttini, Graeme Jones, Dawn Aitken, Guoqi Cai

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DNN-based Sub-6 GHz assisted millimeter wave network power allocation algorithm by Changyin SUN, Liyan LIU, Fan JIANG, Jing JIANG

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Lightweight malicious domain name detection model based on separable convolution by Luhui YANG, Huiwen BAI, Guangjie LIU, Yuewei DAI

“…The application of artificial intelligence in the detection of malicious domain names needs to consider both accuracy and calculation speed,which can make it closer to the actual application.Based on the above considerations,a lightweight malicious domain name detection model based on separable convolution was proposed.The model uses a separable convolution structure.It first applies depthwise convolution on every input channel,and then performs pointwise convolution on all output channels.This can effectively reduce the parameters of convolution process without impacting the effectiveness of convolution feature extraction,and realize faster convolution process while keeping high accuracy.To improve the detection accuracy considering the imbalance of the number and difficulty of positive and negative samples,a focal loss function was introduced in the training process of the model.The proposed algorithm was compared with three typical deep-learning-based detection models on a public data set.Experimental results denote that the proposed algorithm achieves detection accuracy close to the state-of-the-art model,and can significantly improve model inference speed on CPU.…”
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Exploring Variational Methods in Hydro- and Hemodynamics Through Incompressible Velocity Distribution Sampling by Ivan Stebakov, Alexei Kornaev, Elena Kornaeva, Sergey Majorov

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Boosting Verbal Memory Capacity in Elementary School Students : A Face to Face Intervention Study by Faza Izzuddin Nuha, Puji Lestari Suharso

“…The intervention focused on enhancing D's phonological loop function through face-to-face, non-digital working memory training exercises, such as the odd one out and listening recall tasks. …”
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Research on Automotive Radar Mutual Interference Mitigation Method based on V2X Communication Assistance by Yangshui Gao, Liping Kui, Qinbiao Yang, Lei Xiong, Rong Zhang, Zhenting Chen

“…To solve mixed integer nonlinear programming optimization problems, Q-learning algorithm is introduced. In our Q-learning algorithm, based on the action state space established by transmission power and channel resources, the optimization problem is transformed into solving using a reward function. …”
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Educating Student Teachers to Become High Quality Professionals – A Finnish Case by Hannele Niemi

“…Finnish pre-service teacher education seems to function very well and to be effective in providing the skills teachers need to work as independent professionals. …”
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Target Detection and Image Enhancement for Underwater Environment: Research on Improving YOLOv7 by Yang Luo, Wen Feng

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Combining single-cell ATAC and RNA sequencing for supervised cell annotation by Jaidip Gill, Abhijit Dasgupta, Brychan Manry, Natasha Markuzon

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AdaPDTW: An Efficient Abstract-Adaptive Piecewise Dynamic Time Warping for Time Series Classification by Qinglin Cai, Leiying Chen, Jian Shao, Ling Chen

“…We formulate a joint objective function that combines global classification loss with local clustering loss, and introduce an efficient optimization method based on closed-form solutions. …”
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Vygotskij, Tolstoj e la costruzione del senso by Grazia Basile

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Intelligent multi-modeling reveals biological relationships and adaptive phenotypes for dairy cow adaptation to climate change by Robson Mateus Freitas Silveira, Angela Maria de Vasconcelos, Concepta McManus, Luiz Paulo Fávero, Iran José Oliveira da Silva

“…Biological analysis formed seven distinct mechanisms, each associated with specific biological functions and climate-driven effects on physiological and productive traits. 1) Blood traits were related to all milk components; 2) Lipid and energy metabolism, as well as kidney function, are related to the regulation of body temperature and milk composition; 3) Immunity and thyroid hormones are related to radiant thermal load; and 4) Homeostasis is the organic balance maintained between thermoregulatory, hormonal, hematological, productive, and biochemical functions, which are influenced by environmental variables. …”
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Educating Student Teachers to Become High Quality Professionals – A Finnish Case by Hannele Niemi

“…Finnish pre-service teacher education seems to function very well and to be effective in providing the skills teachers need to work as independent professionals. …”
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Loan classification using logistic regression by U. I. Behunkou, M. Y. Kovalyov

“…At the same time, machine learning is one of the tools for making such decisions. …”
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