#ZHENYU LUO

[aestum]

(by ZHENYU LUO)

[dangermousie]

Do I know what this drama is about? No.

Do I care what this drama is about? With a cast this pretty, also no.

[whispersoffateleo]

Introducing the Whispers of Fate cast

Heroes rise.

An epic showdown begins in Shenzhou!

Tv series: WHISPERS OF FATE

Whispers of Fate & Leo™

All music and image are copyrighted and belong to the respective owners, included the official film crew WHISPERSOFFATE.

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Disclaimer:

This video contains Chinese idioms and philosophical references which are adapted for audience understanding. The translation is not professional and there may be errors.

[lyselkatzfandomluvs]

Shûi Lóng Yín 水龍吟

Characters promo clip

[diaryofanauthor]

All images from Unsplash (Alexandru Acea, Mathias Reding, Dana Ward, Ahmad Matar, Sombre, Zhenyu Luo)

[iamanother]

Will you?

Will you keep holding my hand after you finally learn about me? I am anxious, I am scared, and I feel alarmed when my heart starts beating faster, as it takes me back to that feeling from the past. Will you still look into my eyes after you find out that I'm a monster? My heart feels heavy whenever I am thinking about your point of view. Can we just stop the time and enjoy these good memories with you? I hope you are the angel from my sinful soul; save me from hell as you lift me up from the sadness inside me. I hope that you are willing to listen to me and believe in what I am saying. I hope that you are not like them; I hope that you are the kindest person that I met. 

written by: iamanother.

Photo by: ZHENYU LUO

[forever-aimika]

AiMika Ship Aesthetic Collage 1

Photo Credits: Pixlr E Stock Images (From left to right) Alexandre Boucey, Leonard von Bibra, Phoebe Strafford, Zhenyu Luo, Wisconsinpictures, and Rae Wallis

[hphlseungyeonlee]

outfits inspired by hogwarts legacy: part 2 (click tag to see more)

bg: ZHENYU LUO

[drmikewatts]

IEEE Transactions on Artificial Intelligence, Volume 5, Issue 9, September 2024

1) Editorial: From Explainable Artificial Intelligence (xAI) to Understandable Artificial Intelligence (uAI)

Author(s): Hussein Abbass, Keeley Crockett, Jonathan Garibaldi, Alexander Gegov, Uzay Kaymak, Joao Miguel C. Sousa

Pages: 4310 - 4314

2) Incomplete Graph Learning via Partial Graph Convolutional Network

Author(s): Ziyan Zhang, Bo Jiang, Jin Tang, Jinhui Tang, Bin Luo

Pages: 4315 - 4321

3) Adversarial Machine Learning for Social Good: Reframing the Adversary as an Ally

Author(s): Shawqi Al-Maliki, Adnan Qayyum, Hassan Ali, Mohamed Abdallah, Junaid Qadir, Dinh Thai Hoang, Dusit Niyato, Ala Al-Fuqaha

Pages: 4322 - 4343

4) A Distributed Conditional Wasserstein Deep Convolutional Relativistic Loss Generative Adversarial Network With Improved Convergence

Author(s): Arunava Roy, Dipankar Dasgupta

Pages: 4344 - 4353

5) A Similarity-Based Positional Attention-Aided Deep Learning Model for Copy–Move Forgery Detection

Author(s): Ayush Roy, Sk Mohiuddin, Ram Sarkar

Pages: 4354 - 4363

6) Enhancing Reinforcement Learning via Transformer-Based State Predictive Representations

Author(s): Minsong Liu, Yuanheng Zhu, Yaran Chen, Dongbin Zhao

Pages: 4364 - 4375

7) Bilateral-Head Region-Based Convolutional Neural Networks: A Unified Approach for Incremental Few-Shot Object Detection

Author(s): Yiting Li, Haiyue Zhu, Sichao Tian, Jun Ma, Cheng Xiang, Prahlad Vadakkepat

Pages: 4376 - 4390

8) Regional Ensemble for Improving Unsupervised Outlier Detectors

Author(s): Jiawei Yang, Sylwan Rahardja, Susanto Rahardja

Pages: 4391 - 4402

9) Progressively Select and Reject Pseudolabeled Samples for Open-Set Domain Adaptation

Author(s): Qian Wang, Fanlin Meng, Toby P. Breckon

Pages: 4403 - 4414

10) A Lightweight Multidendritic Pyramidal Neuron Model With Neural Plasticity on Image Recognition

Author(s): Yu Zhang, Pengxing Cai, Yanan Sun, Zhiming Zhang, Zhenyu Lei, Shangce Gao

Pages: 4415 - 4427

11) A Multimodal Multiobjective Evolutionary Algorithm for Filter Feature Selection in Multilabel Classification

Author(s): Emrah Hancer, Bing Xue, Mengjie Zhang

Pages: 4428 - 4442

12) A Nonparametric Split and Kernel-Merge Clustering Algorithm

Author(s): Khurram Khan, Atiq ur Rehman, Adnan Khan, Syed Rameez Naqvi, Samir Brahim Belhaouari, Amine Bermak

Pages: 4443 - 4457

13) Universal Transfer Framework for Urban Spatiotemporal Knowledge Based on Radial Basis Function

Author(s): Sheng-Min Chiu, Yow-Shin Liou, Yi-Chung Chen, Chiang Lee, Rong-Kang Shang, Tzu-Yin Chang, Roger Zimmermann

Pages: 4458 - 4469

14) Building a Robust and Efficient Defensive System Using Hybrid Adversarial Attack

Author(s): Rachel Selva Dhanaraj, M. Sridevi

Pages: 4470 - 4478

15) Retain and Adapt: Online Sequential EEG Classification With Subject Shift

Author(s): Tiehang Duan, Zhenyi Wang, Li Shen, Gianfranco Doretto, Donald A. Adjeroh, Fang Li, Cui Tao

Pages: 4479 - 4492

16) Prefetching-based Multiproposal Markov Chain Monte Carlo Algorithm

Author(s): Guifeng Ye, Shaowen Lu

Pages: 4493 - 4505

17) Shuffled Grouping Cross-Channel Attention-Based Bilateral-Filter-Interpolation Deformable ConvNet With Applications to Benthonic Organism Detection

Author(s): Tingkai Chen, Ning Wang

Pages: 4506 - 4518

18) An Intelligent Fingerprinting Technique for Low-Power Embedded IoT Devices

Author(s): Varun Kohli, Muhammad Naveed Aman, Biplab Sikdar

Pages: 4519 - 4534

19) A Novel Applicable Shadow Resistant Neural Network Model for High-Efficiency Grid-Level Pavement Crack Detection

Author(s): Handuo Yang, Ju Huyan, Tao Ma, Yitao Song, Chengjia Han

Pages: 4535 - 4549

20) Prioritized Local Matching Network for Cross-Category Few-Shot Anomaly Detection

Author(s): Huilin Deng, Hongchen Luo, Wei Zhai, Yanming Guo, Yang Cao, Yu Kang

Pages: 4550 - 4561

21) IOTM: Iterative Optimization Trigger Method—A Runtime Data-Free Backdoor Attacks on Deep Neural Networks

Author(s): Iram Arshad, Saeed Hamood Alsamhi, Yuansong Qiao, Brian Lee, Yuhang Ye

Pages: 4562 - 4573

22) An Unbiased Fuzzy Weighted Relative Error Support Vector Machine for Reverse Prediction of Concrete Components

Author(s): Zongwen Fan, Jin Gou, Shaoyuan Weng

Pages: 4574 - 4584

23) Stabilizing Diffusion Model for Robotic Control With Dynamic Programming and Transition Feasibility

Author(s): Haoran Li, Yaocheng Zhang, Haowei Wen, Yuanheng Zhu, Dongbin Zhao

Pages: 4585 - 4594

24) A Unified Conditional Diffusion Framework for Dual Protein Targets-Based Bioactive Molecule Generation

Author(s): Lei Huang, Zheng Yuan, Huihui Yan, Rong Sheng, Linjing Liu, Fuzhou Wang, Weidun Xie, Nanjun Chen, Fei Huang, Songfang Huang, Ka-Chun Wong, Yaoyun Zhang

Pages: 4595 - 4606

25) Learning Counterfactual Explanation of Graph Neural Networks via Generative Flow Network

Author(s): Kangjia He, Li Liu, Youmin Zhang, Ye Wang, Qun Liu, Guoyin Wang

Pages: 4607 - 4619

26) Linear Regression-Based Autonomous Intelligent Optimization for Constrained Multiobjective Problems

Author(s): Yan Wang, Xiaoyan Sun, Yong Zhang, Dunwei Gong, Hejuan Hu, Mingcheng Zuo

Pages: 4620 - 4634

27) Strategic Gradient Transmission With Targeted Privacy-Awareness in Model Training: A Stackelberg Game Analysis

Author(s): Hezhe Sun, Yufei Wang, Huiwen Yang, Kaixuan Huo, Yuzhe Li

Pages: 4635 - 4648

28) An Explainable Intellectual Property Protection Method for Deep Neural Networks Based on Intrinsic Features

Author(s): Mingfu Xue, Xin Wang, Yinghao Wu, Shifeng Ni, Leo Yu Zhang, Yushu Zhang, Weiqiang Liu

Pages: 4649 - 4659

29) Unsupervised Representation Learning for 3-D Magnetic Resonance Imaging Superresolution With Degradation Adaptation

Author(s): Jianan Liu, Hao Li, Tao Huang, Euijoon Ahn, Kang Han, Adeel Razi, Wei Xiang, Jinman Kim, David Dagan Feng

Pages: 4660 - 4674

30) A Causality-Informed Graph Intervention Model for Pancreatic Cancer Early Diagnosis

Author(s): Xinyue Li, Rui Guo, Hongzhang Zhu, Tao Chen, Xiaohua Qian

Pages: 4675 - 4685

31) Remaining Useful Life Prediction via Frequency Emphasizing Mix-Up and Masked Reconstruction

Author(s): Haoren Guo, Haiyue Zhu, Jiahui Wang, Vadakkepat Prahlad, Weng Khuen Ho, Clarence W. de Silva, Tong Heng Lee

Pages: 4686 - 4695

32) UPR-BP: Unsupervised Photoplethysmography Representation Learning for Noninvasive Blood Pressure Estimation

Author(s): Chenbin Ma, Peng Zhang, Fan Song, Zeyu Liu, Youdan Feng, Yufang He, Guanglei Zhang

Pages: 4696 - 4707

33) SBP-GCA: Social Behavior Prediction via Graph Contrastive Learning With Attention

Author(s): Yufei Liu, Jia Wu, Jie Cao

Pages: 4708 - 4722

34) Quadratic Neuron-Empowered Heterogeneous Autoencoder for Unsupervised Anomaly Detection

Author(s): Jing-Xiao Liao, Bo-Jian Hou, Hang-Cheng Dong, Hao Zhang, Xiaoge Zhang, Jinwei Sun, Shiping Zhang, Feng-Lei Fan

Pages: 4723 - 4737

35) Automatic Plane Pose Estimation for Cardiac Left Ventricle Coverage Estimation via Deep Adversarial Regression Network

Author(s): Le Zhang, Kevin Bronik, Stefan K. Piechnik, Joao A. C. Lima, Stefan Neubauer, Steffen E. Petersen, Alejandro F. Frangi

Pages: 4738 - 4752

36) Variable Curvature Gabor Convolution and Multibranch Structures for Finger Vein Recognition

Author(s): Jun Li, Huabin Wang, Shicheng Wei, Jian Zhou, Yuankang Shen, Liang Tao

Pages: 4753 - 4764

37) ClassLIE: Structure- and Illumination-Adaptive Classification for Low-Light Image Enhancement

Author(s): Zixiang Wei, Yiting Wang, Lichao Sun, Athanasios V. Vasilakos, Lin Wang

Pages: 4765 - 4775

38) Improving Code Summarization With Tree Transformer Enhanced by Position-Related Syntax Complement

Author(s): Jie Song, Zexin Zhang, Zirui Tang, Shi Feng, Yu Gu

Pages: 4776 - 4786

39) Automated Detection of Harmful Insects in Agriculture: A Smart Framework Leveraging IoT, Machine Learning, and Blockchain

Author(s): Wahidur Rahman, Muhammad Minoar Hossain, Md. Mahedi Hasan, Md. Sadiq Iqbal, Mohammad Motiur Rahman, Khondokar Fida Hasan, Mohammad Ali Moni

Pages: 4787 - 4798

40) MTPret: Improving X-Ray Image Analytics With Multitask Pretraining

Author(s): Weibin Liao, Qingzhong Wang, Xuhong Li, Yi Liu, Zeyu Chen, Siyu Huang, Dejing Dou, Yanwu Xu, Haoyi Xiong

Pages: 4799 - 4812

41) Reinforced Reweighting for Self-Supervised Partial Domain Adaptation

Author(s): Keyu Wu, Shengkai Chen, Min Wu, Shili Xiang, Ruibing Jin, Yuecong Xu, Xiaoli Li, Zhenghua Chen

Pages: 4813 - 4822

42) Cross-Modality Calibration in Multi-Input Network for Axillary Lymph Node Metastasis Evaluation

Author(s): Michela Gravina, Domiziana Santucci, Ermanno Cordelli, Paolo Soda, Carlo Sansone

Pages: 4823 - 4836

43) A Novel Grades Prediction Method for Undergraduate Students by Learning Explicit Conditional Distribution

Author(s): Na Zhang, Ming Liu, Lin Wang, Shuangrong Liu, Runyuan Sun, Bo Yang, Shenghui Zhu, Chengdong Li, Cheng Yang, Yuhu Cheng

Pages: 4837 - 4848

[jcmarchi]

10 Ways to Make the Most of AI For Your Business - Technology Org

New Post has been published on https://thedigitalinsider.com/10-ways-to-make-the-most-of-ai-for-your-business-technology-org/

10 Ways to Make the Most of AI For Your Business - Technology Org

In today’s fast-paced business world, artificial intelligence (AI) is more than just a buzzword; it’s a transformative technology reshaping how companies operate. AI offers powerful tools for enhancing efficiency, understanding customer needs, and driving innovation. This article explores ten practical ways businesses can harness the power of AI, from improving customer service to personalizing marketing efforts.

An industrial robot – artistic rendering. Image credit: Zhenyu Luo via Unsplash, free license

One of the most immediate impacts of AI in business is seen in customer service. AI-powered chatbots and virtual assistants have revolutionized how companies interact with their customers. These tools can handle routine inquiries, freeing up human agents to tackle more complex issues. Additionally, AI systems can analyze customer feedback, identifying common issues and trends that can inform business strategy.

For example, chatbots like those used by e-commerce giants can handle thousands of queries simultaneously, providing instant responses that improve customer satisfaction. Moreover, these AI tools are becoming increasingly sophisticated, capable of understanding and responding to a wide range of customer emotions and queries.

Data is the lifeblood of modern business, but its sheer volume can be overwhelming. AI excels at processing large datasets, uncovering patterns and insights that might elude human analysts. These insights can inform everything from marketing strategies to product development. AI tools like machine learning algorithms can predict customer behavior, identify market trends, and even suggest areas for business expansion. For instance, a retail company might use AI to analyze purchase data, identifying which products are popular among different demographics and at different times of the year. This kind of analysis can help businesses tailor their offerings and stock levels more effectively.

For organizations looking to learn more about AI and leverage AI solutions, visiting https://www.sap.com/products/artificial-intelligence/what-is-artificial-intelligence.html will prove helpful.

AI also plays a crucial role in optimizing spply chain management. By analyzing data from various points in the supply chain, AI can help businesses predict demand, manage inventory levels, and identify potential bottlenecks before they cause problems. This results in more efficient operations and reduced costs. For example, an AI system might analyze weather patterns, historical sales data, and current inventory levels to recommend the optimal amount of stock to keep on hand. It helps prevent both overstocking and stockouts, ensuring that businesses can meet customer demand without tying up too much capital in unsold inventory.

Marketing is another area where AI is making a significant impact. By analyzing customer data, AI can help businesses create highly targeted marketing campaigns that resonate with individual consumers, which include personalized product recommendations, tailored email marketing, and dynamic website content. For instance, streaming services like Netflix use AI to recommend movies and TV shows based on a user’s viewing history, increasing engagement and customer satisfaction. Similarly, e-commerce sites use AI to show shoppers items they’re more likely to buy based on their browsing and purchase history.

AI is transforming human resource management by automating routine tasks and providing insights into employee performance and potential. AI-powered recruitment tools can scan through thousands of resumes, identifying candidates who best match the job requirements. It not only speeds up the hiring process but also helps eliminate unconscious bias. Additionally, AI systems can track employee performance and offer data-driven suggestions for training and development. For example, an AI system might analyze an employee’s work patterns and suggest specific courses or projects that could help them develop their skills and advance their career. This personalized approach to employee development can lead to a more engaged and efficient workforce.

Artificial Intelligence is revolutionizing the sales sector by predicting market trends and customer preferences. This predictive capability allows businesses to anticipate market demands, adjust their strategies accordingly, and identify new sales opportunities. AI-powered tools analyze past sales data, market conditions, and customer feedback to forecast future sales trends. It helps businesses stock the right products and target the right customers at the right time. For instance, a car dealership might use AI to predict which car models will be in demand in the coming months, allowing them to adjust their inventory and marketing strategies in advance.

Managing finances is a complex and critical task for any business. AI simplifies this by automating tasks such as budgeting, forecasting, and fraud detection. AI algorithms can analyze financial trends, track spending, and provide accurate financial forecasts, enabling businesses to make informed decisions about their financial strategies. In fraud detection, AI systems monitor transactions in real time, identifying and flagging suspicious activities that could indicate fraud. This proactive approach not only saves money but also protects the company’s reputation. For example, banks use AI to monitor credit card transactions, quickly detecting and responding to unusual spending patterns that could indicate fraud.

In an era where cyber threats are increasingly sophisticated, AI plays a pivotal role in enhancing a company’s security measures. AI systems monitor network traffic, detect anomalies, and immediately respond to potential threats. This continuous and automated monitoring means that AI can identify and neutralize threats much faster than human-operated systems. For example, AI in cybersecurity can detect patterns in data that might suggest a cyberattack, such as unusual login attempts or unexpected changes in network traffic. By responding swiftly to these threats, AI helps protect sensitive company data and maintain business continuity.

AI is not just about automating existing processes; it’s also a powerful driver of innovation and product development. By analyzing market trends, customer feedback, and current product performance, AI can identify opportunities for new products or improvements to existing ones. In industries like pharmaceuticals and automotive, AI accelerates the research and development process, reducing the time and cost of bringing new products to market. For instance, AI algorithms can simulate and analyze the performance of a new drug or car model in various scenarios, providing valuable insights that can guide the development process and improve the end product.

As AI becomes more integrated into business operations, the need for skilled professionals who can work with AI tools increases. Businesses can use AI itself to help train their workforce, offering personalized learning paths and identifying skill gaps. Online platforms and AI-based training programs can tailor learning content to each employee’s needs, making training more effective and efficient. For example, an AI training platform might analyze an employee’s performance and suggest specific courses or tutorials to improve their skills in areas like data analysis, AI maintenance, or AI ethics.

Conclusion

In conclusion, the integration of AI into various aspects of business operations is not just a trend; it’s a necessary evolution to stay competitive in today’s market. From enhancing customer service to innovating product development, AI offers a range of tools that can transform how businesses operate. By embracing AI, companies can improve efficiency, reduce costs, and provide better products and services. As AI continues to evolve, the possibilities for its application in business are only limited by our imagination.

[gothbutterfly]

ZHENYU LUO

[aestum]

(by ZHENYU LUO)

[chai-n-ivy]

Dark Academia aesthetic 🍷

📷: Unsplash

left to right: Alexandre Brondino, Javier Grixo, Joanna Kosinska, Annie Theby, Zhenyu Luo, Andrew Neel, Thomas Kelley, and Emre Gencer

[whispersoffateleo]

Luo Yunxi leads a star-studded cast in Shui Long Yin / The Dragon Chant. Who are you most excited for?

This tv series boasts an exciting lineup, led by Luo Yunxi, with a cast featuring Xiao Shunyao, Ao Ziyi, Fang Yilun, Lin Yun, Chen Yao, Bao Shang’en, Xu Zhengxi, Yang Shize, Chang Huasen, Xia Zhiguang, Jiang Zhenyu, Xiu Qing, Wang Yilun, Xie Binbin, Bai Shu, Li Fei, Zhang Zhixi, Qiu Xinzhi, Zhang Junning, Liu Yuhan, Wang Zirui, Li Jiahao, Chen Bohao, Deng Xiaoci, and more.

Who are you most excited for?

Tv drama: The Dragon Chant / Shui Long Yin Shui Long Yin & Leo All music and image are copyrighted and belong to the respective owners, included the official film crew SHUILONGYIN.

[virtuallyinsane]

Photo by ZHENYU LUO

[twirld]

ZHENYU LUO