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"Failure Prediction for Large-scale Water Pipe Networks Using GNN and T" by Shuming Liang, Zhidong Li et al.

Pipe failure prediction in the water industry aims to prioritize the pipes that are at high risk of failure for proactive maintenance. However, existing statistical or machine learning models that rely on historical failures and asset attributes can hardly leverage the structure information of pipe networks. In this work, we develop a failure prediction framework for pipe networks by jointly considering the pipes' features, the network structure, the geographical neighboring effect, and the temporal failure series. We apply a multi-hop Graph Neural Network (GNN) to failure prediction. We propose a method of constructing a geographical graph structure depending on not only the physical connections but also geographical distances between pipes. To differentiate the pipes with diverse properties, we employ an attention mechanism in the neighborhood aggregation process of each GNN layer. Also, residual connections and layer-wise aggregation are used to avoid the over-smoothing issue i ....

Graph Neural Network , Failure Prediction , Infrastructure Networks , Point Process , Proactive Maintenance , Emporal Failure Pattern ,

How is ML fueling another age of application advancement?

From the time of introduction of the computers, the primary objective of the evolution has been taking into consideration automating the tasks that won’t take a lot of time. Artificial intelligence serves as a term that is talk of the town a lot lately when it comes to task automation. Various app development companies are aggressively using ML for web and app development. In this regard, machine learning in apps has made automation possible. The machine learning market is projected to cultivate from $1.03 Billion in 2016 to $8.81 Billion by the year 2022, at a CAGR of around 44.1% during the estimated time ....

Technostacks Infotech , Mrudul Shah , App Development , Graph Neural Network , Application Development , Convolutional Neural Network , Latest Development , Machine Learning , Use Cases , Alien Isolation , Natural Language Generation , Natural Language Processing , Natural Language Understanding , Artificial Intelligence , Automated Logical Reasoning , Time Translation , Mobile Application , Iot Product Engineering , Web Solutions ,

Finland's IPRally raises 2 million euros to fuel growth

The round was co-led by Join Capital and Spintop Ventures, with participation from previous investor Icebreaker.vc.
“I have filed over 20 patents myself, so I have first-hand experience of the inefficiencies in the patent system. The IPRally AI-based approach is the way to go, disrupting an industry that hasn’t changed much for the past 100 years,” said Sami Niemi, partner at Spintop Ventures.
IPRally says it enables Intellectual Property professionals as well as R&D engineers to intuitively build search queries in minutes allowing very precise searches of similar existing patents saving huge amounts of time, and helping to discover patents not possible to find through regular keyword searches. Moreover, IPRally’s unique Graph Neural Network technology allows for machine reasoning of the search results, shifting the paradigm from black-box AI solutions to explainable AI solutions. ....

Sakari Arvela , Sami Niemi , Graph Neural Networks , Graph Neural Network , Fresenius Medical Care , Join Capital , Spintop Ventures , Intellectual Property , Graph Neural , சாமி நீஎம்ி , வரைபடம் நரம்பியல் நெட்வொர்க்குகள் , வரைபடம் நரம்பியல் வலைப்பின்னல் , ப்ரேசெனிுச் மருத்துவ பராமரிப்பு , சேர மூலதனம் , அறிவுசார் ப்ராபர்டீ , வரைபடம் நரம்பியல் ,