Juno is a neutrino detector under construction 750m below Jiangmen in China. A collaboration between 17 countries, 730 scientists from 74 universities and national laboratories have worked on it. At …

The post Peering into the life of neutrinos appeared first on Electronics Weekly .

Bourns has created an AEC-Q200 compliant 1:1 signal isolation transformer for automotive battery management systems. SM91872AL is surface-mount and will fit into a 17.4 x 10.6 x 8.1 envelope – …

The post AEC-Q200 transformer isolates battery management signals appeared first on Electronics Weekly .

The 2024 Millennium Technology Prize has been awarded to Professor Jayant Baliga of North Carolina State University for his part in the invention and development of the IGBT. “Two thirds …

The post 2024 Millennium Technology Prize for IGBT pioneer appeared first on Electronics Weekly .

Scotland is welcoming its biggest ever space industry event next week: the inaugural Space-Comm Expo Scotland, at SEC Glasgow over 11-12 September. The organisers are expecting 3,000 delegates and 70 …

The post Glasgow next week: Space-Comm Expo Scotland appeared first on Electronics Weekly .

Today, Amazon Redshift launches session reuse feature in Data API that enables you to access data efficiently from Amazon Redshift data warehouses by eliminating the need to manage database drivers, connections, network configurations, data buffering, and more. Data API session reuse allows you to retain the context of a session from one query execution to another, which reduces connection setup latency on repeated queries to the same data warehouse.

With session reuse, you can utilize session context on objects like variables or temporary tables, which you create once and use multiple times for various queries. This reduces the overall execution time for your queries. To reuse sessions, you must specify in seconds how long a session should be kept for after a query finishes and any subsequent queries can reference this session until the time expires, or it’s extended.

Amazon Connect now provides a weekly view of agent schedules, making it easier for contact center managers to get an at-a-glance view of staffing for an entire week. With this launch, you can now ensure there is required coverage each day via daily aggregated metrics including service level, occupancy, and forecasted versus scheduled hours. For example, from the weekly view you can easily identify if there is overstaffing on Wednesday and understaffing on Friday. You can then move agent shifts from Wednesday to Friday within the weekly view. Weekly view also makes it easy to verify that agents receive the appropriate shifts each day (e.g. each agent has an 8-hour shift) and that they are not working too many days in a row (e.g. each agent gets at least 2 days off every week). Weekly view improves manager productivity by reducing time spent on day to day management of agent shifts and makes it easier to review staffing for multiple days in a single view.

This feature is available in all AWS Regions where Amazon Connect agent scheduling is available. To get started with Amazon Connect agent scheduling, click here .
 

Today AWS Network Load Balancer (NLB) is launching a new capability that allows you to align the TCP idle timeout value of NLB with clients and target applications. Using this capability you can now reduce TCP connection retries and latency in applications that use long-lived flows, such as telemetry reporting devices, databases, streaming services and ERP systems, when using NLB.

Prior to this launch, TCP idle timeout was a fixed value of 350 seconds, which could cause TCP connection handshake retries for the long-lived traffic flows of some applications and add latency. With this launch, you now have the flexibility to configure NLB’s TCP idle timeout to be a value between 60 seconds and 6000 seconds, with the default remaining at 350 seconds for backward compatibility. This configuration can help reduce latency for long-lived traffic flows by maintaining target stickiness for the optimal duration based on the needs of your application. You can configure the TCP idle timeout value using the ‘tcp.idle_timeout.seconds’ listener attribute on your existing and newly created NLBs.

This capability is available in all AWS commercial and AWS GovCloud (US) regions.

For more information on how to use this feature, see this AWS blog post and product documentation .
 

Amazon Connect forecasting, capacity planning, and agent scheduling now includes machine learning (ML) powered intraday forecast capabilities, available within the Amazon Connect Contact Lens dashboards. With intraday forecasts, you receive updates every 15 minutes with predictions for rest-of-day contact volumes, average queue answer time, and average handle time. These forecasts allow you to take proactive actions to improve customer wait time and service level. For example, if contact volume drops below expected levels, contact center managers can use the intraday forecast to predict how long that drop will continue, determine the required staffing levels, and shift the remaining agents into back office work or other higher volume queues.

This feature is available in all AWS Regions where Amazon Connect forecasting, capacity planning, and agent scheduling is available. To learn more see the Amazon Connect Administrator Guide .

AWS has expanded the AI recommendations for descriptions capability in Amazon DataZone to four new regions: South America (Sao Paulo), Europe (London), Asia Pacific (Sydney), and Canada (Central). This expansion helps improve data discovery, understanding, and usage by enriching the business data catalog. With a single click, data producers can generate comprehensive business data descriptions and context, highlight impactful columns, and include recommendations on analytical use cases.

With AI recommendations for descriptions in Amazon DataZone, data consumers can identify data tables and columns enhancing, which enhances data discoverability and cuts down on back-and-forth communications with data producers. Data consumers (such as data analysts, data engineers, and data scientists) have more contextualized data at their fingertips to inform their analysis. The auto-generated descriptions enable a richer search experience, as search results are now also based on detailed descriptions, possible use cases, and key columns. Data producers can also use APIs to programmatically generate descriptions for assets.

Amazon DataZone AI recommendations for descriptions is generally available in Amazon DataZone domains provisioned in the following AWS Regions : US East (N. Virginia), US West (Oregon), Europe (Frankfurt), Asia Pacific (Tokyo), South America (Sao Paulo), Europe (London), Asia Pacific (Sydney), and Canada (Central).

To learn more, see the Amazon DataZone Automate Data Discovery webpage, and User Guide . For pricing information, see the pricing page .
 

Amazon Connect Contact Lens can now generate transcriptions in 10 new languages that include Catalan (Spain), Danish (Denmark), Dutch (Netherlands), Finnish (Finland), Indonesian (Indonesia), Malay (Malaysia), Norwegian Bokmål (Norway), Polish (Poland), Swedish (Sweden), and Tagalog/Filipino (Philippines). With this launch, Contact Lens conversational analytics now provides transcription support for 33 languages.

Amazon Connect Contact Lens helps you to monitor, measure, and continuously improve contact quality and agent performance for a better overall customer experience. With Contact Lens conversational analytics, you can transcribe customer calls, analyze customer sentiment, discover top contact drivers, help redact sensitive data, and more, all natively within Amazon Connect.

Transcription support for these 10 new languages is available for post-call scenarios and across all regions where Contact Lens conversational analytics is available. To learn more, please visit our documentation and our webpage . This feature is included with Contact Lens conversational analytics at no additional charge. For information about Contact Lens pricing, please visit our pricing page .