Collaborating Authors

Networks Utilization Improvements for Service Discovery Performance Artificial Intelligence

Service discovery requests' messages have a vital role in sharing and locating resources in many of service discovery protocols. Sending more messages than a link can handle may cause congestion and loss of messages which dramatically influences the performance of these protocols. Re-send the lost messages result in latency and inefficiency in performing the tasks which user(s) require from the connected nodes. This issue become a serious problem in two cases: first, when the number of clients which performs a service discovery request is increasing, as this result in increasing in the number of sent discovery messages; second, when the network resources such as bandwidth capacity are consumed by other applications. These two cases lead to network congestion and loss of messages. This paper propose an algorithm to improve the services discovery protocols performance by separating each consecutive burst of messages with a specific period of time which calculated regarding the available network resources. It was tested when the routers were connected in two configurations; decentralised and centralised .In addition, this paper explains the impact of increasing the number of clients and the consumed network resources on the proposed algorithm.

Maritime port operators see great promise in artificial intelligence – DC Velocity


AI could improve operational consistencies and enhance equipment utilization, Navis survey shows. Global container terminals are expected to embrace automated decision making powered by artificial intelligence (AI) as they pursue ways to improve operational consistencies and enhance equipment utilization, a new survey shows. The findings indicate that container terminals, regardless of their AI maturity, are increasingly aware of the possibilities of automated decision-making, according to supply chain technology provider Navis LLC. The Oakland, California-based firm said its TechValidate customer survey included responses from nearly 60 Navis customers, representing a cross-section of container terminals around the world using various degrees of automation. In addition to the 86% who cited operational consistency and equipment utilization as the most important benefits of automated decision-making, port operators also named other goals.

CORE Pathways - Certilytics


CORE Pathways provides unprecedented insight into individual patient diagnostics and utilization to enable clinical and financial analysts to identify, report, and benchmark cost trends, treatment patterns, condition severity, and health outcomes. CORE Pathways is built on top of our proprietary DL&M Pipeline and organizes disparate claim-line data into individualized events, or COREs, allowing analysts and actuaries to review program performance, explain risk, and report on costs and utilization across billions of records.

Interesting AI/ML Articles You Should Read This Week (July 4)


This week I came across several articles that challenge the development and utilization of AI-based system across several domains. This week I came across several articles that challenge the development and utilization of AI-based system across several domains. I've never had to genuinely reflect on the philosophical and legal aspects of my contributions as a machine learning practitioner, but this has changed after reading some interesting articles that present the consequences of AI advancement that are happening now, and those that are yet to happen. Our lives today could look entirely different tomorrow. Would you let a machine learning model that has a failure rate of 98% and a false positive rate of 81% into production?

Fed: Industrial Production decreased 0.4% in August


This graph shows Capacity Utilization. This series is up 8.8 percentage points from the record low set in June 2009 (the series starts in 1967). Capacity utilization at 75.5% is 4.5% below the average from 1972 to 2015 and below the pre-recession level of 80.8% in December 2007. Note: y-axis doesn't start at zero to better show the change. The second graph shows industrial production since 1967.