Memorize S90-05A Cheatsheet questions before you go for test

Even if you go through all S90-05A course books, the situations asked in actual tests are totally different. Our S90-05A real questions contains every one of the interesting inquiries and answers that are not found in the course books. Practice with S90-05A VCE test system and you will be certain for the genuine S90-05A test.

Exam Code: S90-05A Practice exam 2022 by Killexams.com team
SOA Technology Lab
SOA Technology test prep
Killexams : SOA Technology test prep - BingNews https://killexams.com/pass4sure/exam-detail/S90-05A Search results Killexams : SOA Technology test prep - BingNews https://killexams.com/pass4sure/exam-detail/S90-05A https://killexams.com/exam_list/SOA Killexams : Are Test Prep Books Worth It?

Students sometimes put off taking the MCAT, GMAT, GRE, and LSAT in the hopes of getting a better score the first time around because they are balancing coursework, extracurricular activities, and other responsibilities. Standardized tests, like college admission, require a great deal of forethought and effort on the part of students. If a student is hoping to get into the institution of their dreams, MCAT prep, GMAT prep, GRE prep, or LSAT prep is a crucial part of the process.

Importance of Test Prep Books 

Even though there are several advantages to standardized test preparation, many families cannot afford to pay huge amounts of money for tutoring or preparatory classes. However, test prep books are available in a significant budget range, just as college degrees are. There is a multitude of ways to prepare for a test, from personal instructors and huge courses to low-cost guides and free internet resources. It is worth your time and money to prepare for the MCAT, GMAT, GRE, and LSAT if you use test prep books. Here’s why:

Helps you Keep Track of Your Progress 

Keeping track of one’s progress might assist students narrow down their selection of potential colleges. It is critical to establish a list of goals, reach, and probable schools as a part of MCAT prep, GMAT prep, GRE prep, or LSAT prep. There is a multitude of elements that go into compiling this list, one of which is the likelihood of an applicant getting admitted based on their grades and test results.

In order to compete in the admissions process, a high GPA is required. While a perfect MCAT prep, GMAT prep, GRE prep, or LSAT prep does not certain admission, a poor score may swiftly push a candidate to the “no” list, standardized exams are a means to an end in college applications. Standardized test scores, as well as grades and course quality, are often acknowledged by universities as one of the top three variables in admissions choices. That’s why parents and students alike put a lot of emphasis on improving their exam scores.

Assists to Learn Strategies 

Not only do students study material, but they also learn strategies. The assumption that a person’s ability to do well on a standardized exam is completely dependent on their aptitude is a myth. The test-taking technique is just as essential as a solid understanding of the material for students to perform well. Students may get the most out of their study time and performance by working with a great test prep book. MCAT, GMAT, GRE, and LSAT demand a wide range of abilities, including the ability to evaluate question complexity, the process of reasoning, and speed.

Improves Test Scores 

Exam marks may be improved with even a little amount of study. How important is it for a student’s prospects of admission to raise their test scores? A slight rise in standardized test scores might play an important role in an admissions decision, as per a NACAC study of prestigious universities. No matter how high or low a student’s test score is, an increase of only 10-20 points might be the difference between a “yes” and a “no.”

Students may increase their MCAT, GMAT, GRE, or LSAT score by 30 points by completing only one or two guided practice sessions. Many students have seen their test scores rise by four points or more after only one or two hours of studying test prep books. Increasing one’s test score by one point, from 27 to 31, might open up previously out-of-reach opportunities for a student.

Summing Up!

Students might expect to see benefits, however, they will have to put in the effort. Test preparation is often ridiculed because of the perception that students get little benefit from it. Students that study hard for their scores may see big changes even if they only gain a few points, despite what some opponents say. It takes a lot of time, work, and determination to Improve your results, just like any other exam. Only those pupils who are willing to put in the effort will benefit from test prep books.

Thu, 04 Aug 2022 17:12:00 -0500 en-US text/html https://www.thestreet.com/review/choose-a-test-prep-book/
Killexams : Interview: Frank Cohen on FastSOA

InfoQ today publishes a one-chapter excerpt from Frank Cohen's book  "FastSOA". On this occasion, InfoQ had a chance to talk to Frank Cohen, creator of the FastSOA methodology, about the issues when trying to process XML messages, scalability, using XQuery in the middle tier, and document-object-relational-mapping.

InfoQ:
Can you briefly explain the ideas behind "FastSOA"?

Frank Cohen: For the past 5-6 years I have been investigating the impact an average Java developer's choice of technology, protocols, and patterns for building services has on the scalability and performance of the resulting application. For example, Java developers today have a choice of 21 different XML parsers! Each one has its own scalability, performance, and developer productivity profile. So a developer's choice on technology makes a big impact at runtime.

I looked at distributed systems that used message oriented middleware to make remote procedure calls. Then I looked at SOAP-based Web Services. And most recently at REST and AJAX. These experiences led me to look at SOA scalability and performance built using application server, enterprise service bus (ESB,) business process execution (BPEL,) and business integration (BI) tools. Across all of these technologies I found a consistent theme: At the intersection of XML and SOA are significant scalability and performance problems.

FastSOA is a test methodology and set of architectural patterns to find and solve scalability and performance problems. The patterns teach Java developers that there are native XML technologies, such as XQuery and native XML persistence engines, that should be considered in addition to Java-only solutions.

InfoQ: What's "Fast" about it? ;-)

FC: First off, let me describe the extent of the problem. Java developers building Web enabled software today have a lot of choices. We've all heard about Service Oriented Architecture (SOA), Web Services, REST, and AJAX techniques. While there are a LOT of different and competing definitions for these, most Java developers I speak to expect that they will be working with objects that message to other objects - locally or on some remote server - using encoded data, and often the encoded data is in XML format.

The nature of these interconnected services we're building means our software needs to handle messages that can be small to large and simple to complex. Consider the performance penalty of using a SOAP interface and streams XML parser (StAX) to handle a simple message schema where the message size grows. A modern and expensive multi-processor server that easily serves 40 to 80 Web pages per second serves as little as 1.5 to 2 XML requests per second.

Scalability Index

Without some sort of remediation Java software often slows to a crawl when handling XML data because of a mismatch between the XML schema and the XML parser. For instance, we checked one SOAP stack that instantiated 14,385 Java objects to handle a request message of 7000 bytes that contains 200 XML elements.

Of course, titling my work SlowSOA didn't sound as good. FastSOA offers a way to solve many of the scalability and performance problems. FastSOA uses native XML technology to provide service acceleration, transformation, and federation services in the mid-tier. For instance, an XQuery engine provides a SOAP interface for a service to handle decoding the request, transform the request data into something more useful, and routes the request to a Java object or another service.

InfoQ: One alternative to XML databinding in Java is the use of XML technologies, such as XPath or XQuery. Why muddy the water with XQuery? Why not just use Java technology?

FC:We're all after the same basic goals:

  1. Good scalability and performance in SOA and XML environments.
  2. Rapid development of software code.
  3. Flexible and easy maintenance of software code as the environment and needs change.

In SOA, Web Service, and XML domains I find the usual Java choices don't get me to all three goals.

Chris Richardson explains the Domain Model Pattern in his book POJOs in Action. The Domain Model is a popular pattern to build Web applications and is being used by many developers to build SOA composite applications and data services.

Platform

The Domain Model divides into three portions: A presentation tier, an application tier, and a data tier. The presentation tier uses a Web browser with AJAX and RSS capabilities to create a rich user interface. The browser makes a combination of HTML and XML requests to the application tier. Also at the presentation tier is a SOAP-based Web Service interface to allow a customer system to access functions directly, such as a parts ordering function for a manufacturer's service.

At the application tier, an Enterprise Java Bean (EJB) or plain-old Java object (Pojo) implements the business logic to respond to the request. The EJB uses a model, view, controller (MVC) framework - for instance, Spring MVC, Struts or Tapestry - to respond to the request by generating a response Web page. The MVC framework uses an object/relational (O/R) mapping framework - for instance Hibernate or Spring - to store and retrieve data in a relational database.

I see problem areas that cause scalability and performance problems when using the Domain Model in XML environments:

  • XML-Java Mapping requires increasingly more processor time as XML message size and complexity grows.
  • Each request operates the entire service. For instance, many times the user will check order status sooner than any status change is realistic. If the system kept track of the most latest response's time-to-live duration then it would not have to operate all of the service to determine the most previously cached response.
  • The vendor application requires the request message to be in XML form. The data the EJB previously processed from XML into Java objects now needs to be transformed back into XML elements as part of the request message. Many Java to XML frameworks - for instance, JAXB, XMLBeans, and Xerces ? require processor intensive transformations. Also, I find these frameworks challenging me to write difficult and needlessly complex code to perform the transformation.
  • The service persists order information in a relational database using an object-relational mapping framework. The framework transforms Java objects into relational rowsets and performs joins among multiple tables. As object complexity and size grows my research shows many developers need to debug the O/R mapping to Improve speed and performance.

In no way am I advocating a move away from your existing Java tools and systems. There is a lot we can do to resolve these problems without throwing anything out. For instance, we could introduce a mid-tier service cache using XQuery and a native XML database to mitigate and accelerate many of the XML domain specific requests.

Architecture

The advantage to using the FastSOA architecture as a mid-tier service cache is in its ability to store any general type of data, and its strength in quickly matching services with sets of complex parameters to efficiently determine when a service request can be serviced from the cache. The FastSOA mid-tier service cache architectures accomplishes this by maintaining two databases:

  • Service Database. Holds the cached message payloads. For instance, the service database holds a SOAP message in XML form, an HTML Web page, text from a short message, and binary from a JPEG or GIF image.
  • Policy Database. Holds units of business logic that look into the service database contents and make decisions on servicing requests with data from the service database or passing through the request to the application tier. For instance, a policy that receives a SOAP request validates security information in the SOAP header to validate that a user may receive previously cached response data. In another instance a policy checks the time-to-live value from a stock market price quote to see if it can respond to a request from the stock value stored in the service database.

FastSOA uses the XQuery data model to implement policies. The XQuery data model supports any general type of document and any general dynamic parameter used to fetch and construct the document. Used to implement policies the XQuery engine allows FastSOA to efficiently assess common criteria of the data in the service cache and the flexibility of XQuery allows for user-driven fuzzy pattern matches to efficiently represent the cache.

FastSOA uses native XML database technology for the service and policy databases for performance and scalability reasons. Relational database technology delivers satisfactory performance to persist policy and service data in a mid-tier cache provided the XML message schemas being stored are consistent and the message sizes are small.

InfoQ: What kinds of performance advantages does this deliver?

FC: I implemented a scalability test to contrast native XML technology and Java technology to implement a service that receives SOAP requests.

TPS for Service Interface

The test varies the size of the request message among three levels: 68 K, 202 K, 403 K bytes. The test measures the roundtrip time to respond to the request at the consumer. The test results are from a server with dual CPU Intel Xeon 3.0 Ghz processors running on a gigabit switched Ethernet network. I implemented the code in two ways:

  • FastSOA technique. Uses native XML technology to provide a SOAP service interface. I used a commercial XQuery engine to expose a socket interface that receives the SOAP message, parses its content, and assembles a response SOAP message.
  • Java technique. Uses the SOAP binding proxy interface generator from a popular commercial Java application server. A simple Java object receives the SOAP request from the binding, parses its content using JAXB created bindings, and assembles a response SOAP message using the binding.

The results show a 2 to 2.5 times performance improvement when using the FastSOA technique to expose service interfaces. The FastSOA method is faster because it avoids many of the mappings and transformations that are performed in the Java binding approach to work with XML data. The greater the complexity and size of the XML data the greater will be the performance improvement.

InfoQ: Won't these problems get easier with newer Java tools?

FC: I remember hearing Tim Bray, co-inventor of XML, extolling a large group of software developers in 2005 to go out and write whatever XML formats they needed for their applications. Look at all of the different REST and AJAX related schemas that exist today. They are all different and many of them are moving targets over time. Consequently, when working with Java and XML the average application or service needs to contend with three facts of life:

  1. There's no gatekeeper to the XML schemas. So a message in any schema can arrive at your object at any time.
  2. The messages may be of any size. For instance, some messages will be very short (less than 200 bytes) while some messages may be giant (greater than 10 Mbytes.)
  3. The messages use simple to complex schemas. For instance, the message schema may have very few levels of hierarchy (less than 5 children for each element) while other messages will have multiple levels of hierarchy (greater than 30 children.)

What's needed is an easy way to consume any size and complexity of XML data and to easily maintain it over time as the XML changes. This kind of changing landscape is what XQuery was created to address.

InfoQ: Is FastSOA only about improving service interface performance?

FC: FastSOA addresses these problems:

  • Solves SOAP binding performance problems by reducing the need for Java objects and increasing the use of native XML environments to provide SOAP bindings.
  • Introduces a mid-tier service cache to provide SOA service acceleration, transformation, and federation.
  • Uses native XML persistence to solve XML, object, and relational incompatibility.

FastSOA Pattern

FastSOA is an architecture that provides a mid-tier service binding, XQuery processor, and native XML database. The binding is a native and streams-based XML data processor. The XQuery processor is the real mid-tier that parses incoming documents, determines the transaction, communicates with the ?local? service to obtain the stored data, serializes the data to XML and stores the data into a cache while recording a time-to-live duration. While this is an XML oriented design XQuery and native XML databases handle non-XML data, including images, binary files, and attachments. An equally important benefit to the XQuery processor is the ability to define policies that operate on the data at runtime in the mid-tier.

Transformation

FastSOA provides mid-tier transformation between a consumer that requires one schema and a service that only provides responses using a different and incompatible schema. The XQuery in the FastSOA tier transforms the requests and responses between incompatible schema types.

Federation

Lastly, when a service commonly needs to aggregate the responses from multiple services into one response, FastSOA provides service federation. For instance, many content publishers such as the New York Times provide new articles using the Rich Site Syndication (RSS) protocol. FastSOA may federate news analysis articles published on a Web site with late breaking news stories from several RSS feeds. This can be done in your application but is better done in FastSOA because the content (news stores and RSS feeds) usually include time-to-live values that are ideal for FastSOA's mid-tier caching.

InfoQ: Can you elaborate on the problems you see in combining XML with objects and relational databases?

FC: While I recommend using a native XML database for XML persistence it is possible to be successful using a relational database. Careful attention to the quality and nature of your application's XML is needed. For instance, XML is already widely used to express documents, document formats, interoperability standards, and service orchestrations. There are even arguments put forward in the software development community to represent service governance in XML form and operated upon with XQuery methods. In a world full of XML, we software developers have to ask if it makes sense to use relational persistence engines for XML data. Consider these common questions:

  • How difficult is it to get XML data into a relational database?
  • How difficult is it to get relational data to a service or object that needs XML data? Can my database retrieve the XML data with lossless fidelity to the original XML data? Will my database deliver acceptable performance and scalability for operations on XML data stored in the database? Which database operations (queries, changes, complex joins) are most costs in terms of performance and required resources (cpus, network, memory, storage)?

Your answers to these questions forms a criteria by which it will make sense to use a relational database, or perhaps not. The alternative to relational engines are native XML persistence engines such as eXist, Mark Logic, IBM DB2 V9, TigerLogic, and others.

InfoQ: What are the core ideas behind the PushToTest methodology, and what is its relation to SOA?

FC: It frequently surprises me how few enterprises, institutions, and organizations have a method to test services for scalability and performance. One fortune 50 company asked a summer intern they wound up hiring to run a few performance tests when he had time between other assignments to check and identify scalability problems in their SOA application. That was their entire approach to scalability and performance testing.

The business value of running scalability and performance tests comes once a business formalizes a test method that includes the following:

  1. Choose the right set of test cases. For instance, the test of a multiple-interface and high volume service will be different than a service that handles periodic requests with huge message sizes. The test needs to be oriented to address the end-user goals in using the service and deliver actionable knowledge.
  2. Accurate test runs. Understanding the scalability and performance of a service requires dozens to hundreds of test case runs. Ad-hoc recording of test results is unsatisfactory. Test automation tools are plentiful and often free.
  3. Make the right conclusions when analyzing the results. Understanding the scalability and performance of a service requires understanding how the throughput measured as Transactions Per Second (TPS) at the service consumer changes with increased message size and complexity and increased concurrent requests.

All of this requires much more than an ad-hoc approach to reach useful and actionable knowledge. So I built and published the PushToTest SOA test methodology to help software architects, developers, and testers. The method is described on the PushToTest.com Web site and I maintain an open-source test automation tool called PushToTest TestMaker to automate and operate SOA tests.

PushToTest provides Global Services to its customers to use our method and tools to deliver SOA scalability knowledge. Often we are successful convincing an enterprise or vendor that contracts with PushToTest for primary research to let us publish the research under an open source license. For example, the SOA Performance kit comes with the encoding style, XML parser, and use cases. The kit is available for free download at: http://www.pushtotest.com/Downloads/kits/soakit.html and older kits are at http://www.pushtotest.com/Downloads/kits.

InfoQ: Thanks a lot for your time.


Frank Cohen is the leading authority for testing and optimizing software developed with Service Oriented Architecture (SOA) and Web Service designs. Frank is CEO and Founder of PushToTest and inventor of TestMaker, the open-source SOA test automation tool, that helps software developers, QA technicians and IT managers understand and optimize the scalability, performance, and reliability of their systems. Frank is author of several books on optimizing information systems (Java Testing and Design from Prentice Hall in 2004 and FastSOA from Morgan Kaufmann in 2006.) For the past 25 years he led some of the software industry's most successful products, including Norton Utilities for the Macintosh, Stacker, and SoftWindows. He began by writing operating systems for microcomputers, helping establish video games as an industry, helping establish the Norton Utilities franchise, leading Apple's efforts into middleware and Internet technologies, and was principal architect for the Sun Community Server. He cofounded Inclusion.net (OTC: IINC), and TuneUp.com (now Symantec Web Services.) Contact Frank at fcohen@pushtotest.com and http://www.pushtotest.com.

Sun, 05 Jun 2022 15:49:00 -0500 en text/html https://www.infoq.com/articles/fastsoa-cohen/
Killexams : Navigating the Ins and Outs of a Microservice Architecture (MSA)

Key takeaways

  • MSA is not a completely new concept, it is about doing SOA correct by utilizing modern technology advancements.
  • Microservices only address a small portion of the bigger picture - architects need to look at MSA as an architecture practice and implement it to make it enterprise-ready.
  • Micro is not only about the size, it is primarily about the scope.
  • Integration is a key aspect of MSA that can implement as micro-integrations when applicable.
  • An iterative approach helps an organization to move from its current state to a complete MSA.

Enterprises today contain a mix of services, legacy applications, and data, which are topped by a range of consumer channels, including desktop, web and mobile applications. But too often, there is a disconnect due to the absence of a properly created and systematically governed integration layer, which is required to enable business functions via these consumer channels. The majority of enterprises are battling this challenge by implementing a service-oriented architecture (SOA) where application components provide loosely-coupled services to other components via a communication protocol over a network. Eventually, the intention is to embrace a microservice architecture (MSA) to be more agile and scalable. While not fully ready to adopt an MSA just yet, these organizations are architecting and implementing enterprise application and service platforms that will enable them to progressively move toward an MSA.

In fact, Gartner predicts that by 2017 over 20% of large organizations will deploy self-contained microservices to increase agility and scalability, and it's happening already. MSA is increasingly becoming an important way to deliver efficient functionality. It serves to untangle the complications that arise with the creation services; incorporation of legacy applications and databases; and development of web apps, mobile apps, or any consumer-based applications.

Today, enterprises are moving toward a clean SOA and embracing the concept of an MSA within a SOA. Possibly the biggest draws are the componentization and single function offered by these microservices that make it possible to deploy the component rapidly as well as scale it as needed. It isn't a novel concept though.

For instance, in 2011, a service platform in the healthcare space started a new strategy where whenever it wrote a new service, it would spin up a new application server to support the service deployment. So, it's a practice that came from the DevOps side that created an environment with less dependencies between services and ensured a minimum impact to the rest of the systems in the event of some sort of maintenance. As a result, the services were running over 80 servers. It was, in fact, very basic since there were no proper DevOps tools available as there are today; instead, they were using Shell scripts and Maven-type tools to build servers.

While microservices are important, it's just one aspect of the bigger picture. It's clear that an organization cannot leverage the full benefits of microservices on their own. The inclusion of MSA and incorporation of best practices when designing microservices is key to building an environment that fosters innovation and enables the rapid creation of business capabilities. That's the real value add.

Addressing Implementation Challenges

The generally accepted practice when building your MSA is to focus on how you would scope out a service that provides a single-function rather than the size. The inner architecture typically addresses the implementation of the microservices themselves. The outer architecture covers the platform capabilities that are required to ensure connectivity, flexibility and scalability when developing and deploying your microservices. To this end, enterprise middleware plays a key role when crafting both your inner and outer architectures of the MSA.

First, middleware technology should be DevOps-friendly, contain high-performance functionality, and support key service standards. Moreover, it must support a few design fundamentals, such as an iterative architecture, and be easily pluggable, which in turn will provide rapid application development with continuous release. On top of these, a comprehensive data analytics layer is critical for supporting a design for failure.

The biggest mistake enterprises often make when implementing an MSA is to completely throw away established SOA approaches and replace them with the theory behind microservices. This results in an incomplete architecture and introduces redundancies. The smarter approach is to consider an MSA as a layered system that includes an enterprise service bus (ESB) like functionality to handle all integration-related functions. This will also act as a mediation layer that enables changes to occur at this level, which can then be applied to all relevant microservices. In other words, an ESB or similar mediation engine enables a gradual move toward an MSA by providing the required connectivity to merge legacy data and services into microservices. This approach is also important for incorporating some fundamental rules by launching the microservice first and then exposing it via an API.

Scoping Out and Designing the 'Inner Architecture'

Significantly, the inner architecture needs to be simple, so it can be easily and independently deployable and independently disposable. Disposability is required in the event that the microservice fails or a better service emerges; in either case, there is a requirement for the respective microservice to be easily disposed. The microservice also needs to be well supported by the deployment architecture and the operational environment in which the microservice is built, deployed, and executed. Therefore, it needs to be simple enough to be independently deployable. An ideal example of this would be releasing a new version of the same service to introduce bug fixes, include new features or enhancements to existing features, and to remove deprecated services.

The key requirements of an MSA inner architecture are determined by the framework on which the MSA is built. Throughput, latency, and low resource usage (memory and CPU cycles) are among the key requirements that need to be taken into consideration. A good microservice framework typically will build on lightweight, fast runtime, and modern programming models, such as an annotated meta-configuration that's independent from the core business logic. Additionally, it should offer the ability to secure microservices using desired industry leading security standards, as well as some metrics to monitor the behavior of microservices.

With the inner architecture, the implementation of each microservice is relatively simple compared to the outer architecture. A good service design will ensure that six factors have been considered when scoping out and designing the inner architecture:

First, the microservice should have a single purpose and single responsibility, and the service itself should be delivered as a self-contained unit of deployment that can create multiple instances at the runtime for scale.

Second, the microservice should have the ability to adopt an architecture that's best suited for the capabilities it delivers and one that uses the appropriate technology.

Third, once the monolithic services are broken down into microservices, each microservice or set of microservices should have the ability to be exposed as APIs. However, within the internal implementation, the service could adopt any suitable technology to deliver that respective business capability by implementing the business requirement. To do this, the enterprise may want to consider something like Swagger to define the API specification or API definition of a particular microservice, and the microservice can use this as the point of interaction. This is referred to as an API-first approach in microservice development.

Fourth, with units of deployment, there may be options, such as self-contained deployable artifacts bundled in hypervisor-based images, or container images, which are generally the more popular option.

Fifth, the enterprise needs to leverage analytics to refine the microservice, as well as to provision for recovery in the event the service fails. To this end, the enterprise can incorporate the use of metrics and monitoring to support this evolutionary aspect of the microservice.

Sixth, even though the microservice paradigm itself enables the enterprise to have multiple or polyglot implementations for its microservices, the use of best practices and standards is essential for maintaining consistency and ensuring that the solution follows common enterprise architecture principles. This is not to say that polyglot opportunities should not be completely vetoed; rather they need to be governed when used.

Addressing Platform Capabilities with the 'Outer Architecture'

Once the inner architecture has been set up, architects need to focus on the functionality that makes up the outer architecture of their MSA. A key component of the outer architecture is the introduction of an enterprise service bus (ESB) or similar mediation engine that will aide with the connecting legacy data and services into MSA. A mediation layer will also enable the enterprise to maintain its own standards while others in the ecosystem manage theirs.

The use of a service registry will support dependency management, impact analysis, and discovery of the microservices and APIs. It also will enable streamlining of service/API composition and wire microservices into a service broker or hub. Any MSA should also support the creation of RESTful APIs that will help the enterprise to customize resource models and application logic when developing apps.

By sticking to the basics of designing the API first, implementing the microservice, and then exposing it via the API, the API rather than the microservice becomes consumable. Another common requirement enterprises need to address is securing microservices. In a typical monolithic application, an enterprise would use an underlying repository or user store to populate the required information from the security layer of the old architecture. In an MSA, an enterprise can leverage widely-adopted API security standards, such as OAuth2 and OpenID Connect, to implement a security layer for edge components, including APIs within the MSA.

On top of all these capabilities, what really helps to untangle MSA complexities is the use of an underlying enterprise-class platform that provides rich functionality while managing scalability, availability, and performance. That is because the breaking down of a monolithic application into microservices doesn't necessarily amount to a simplified environment or service. To be sure, at the application level, an enterprise essentially is dealing with several microservices that are far more simple than a single monolithic, complicated application. Yet, the architecture as a whole may not necessarily be less arduous.

In fact, the complexity of an MSA can be even greater given the need to consider the other aspects that come into play when microservices need to talk to each other versus simply making a direct call within a single process. What this essentially means is that the complexity of the system moves to what is referred to as the "outer architecture", which typically consists of an API gateway, service routing, discovery, message channel, and dependency management.

With the inner architecture now extremely simplified--containing only the foundation and execution runtime that would be used to build a microservice--architects will find that the MSA now has a clean services layer. More focus then needs to be directed toward the outer architecture to address the prevailing complexities that have arisen. There are some common pragmatic scenarios that need to be addressed as explained in the diagram below.

The outer architecture will require an API gateway to help it expose business APIs internally and externally. Typically, an API management platform will be used for this aspect of the outer architecture. This is essential for exposing MSA-based services to consumers who are building end-user applications, such as web apps, mobile apps, and IoT solutions.

Once the microservices are in place, there will be some sort of service routing that takes place in which the request that comes via APIs will be routed to the relevant service cluster or service pod. Within microservices themselves, there will be multiple instances to scale based on the load. Therefore, there's a requirement to carry out some form of load balancing as well.

Additionally, there will be dependencies between microservices--for instance, if microservice A has a dependency on microservice B, it will need to invoke microservice B at runtime. A service registry addresses this need by enabling services to discover the endpoints. The service registry will also manage the API and service dependencies as well as other assets, including policies.

Next, the MSA outer architecture needs some messaging channels, which essentially form the layer that enables interactions within services and links the MSA to the legacy world. In addition, this layer helps to build a communication (micro-integration) channel between microservices, and these channels should be lightweight protocols, such as HTTP, MQTT, among others.

When microservices talk to each other, there needs to be some form of authentication and authorization. With monolithic apps, this wasn't necessary because there was a direct in-process call. By contrast, with microservices, these translate to network calls. Finally, diagnostics and monitoring are key aspects that need to be considered to figure out the load type handled by each microservice. This will help the enterprise to scale up microservices separately.

Reviewing MSA Scenarios

To put things into perspective, let's analyze some real scenarios that demonstrate how the inner and outer architecture of an MSA work together. We'll assume an organization has implemented its services using Microsoft Windows Communication Foundation or the Java JEE/J2EE service framework, and developers there are writing new services using a new microservices framework by applying the fundamentals of MSA.

In such a case, the existing services that expose the data and business functionality cannot be ignored. As a result, new microservices will need to communicate with the existing service platforms. In most cases, these existing services will use the standards adhered to by the framework. For instance, old services might use service bindings, such as SOAP over HTTP, Java Message Service (JMS) or IBM MQ, and secured using Kerberos or WS-Security. In this example, messaging channels too will play a big role in protocol conversions, message mediation, and security bridging from the old world to the new MSA.

Another aspect the organization would need to consider is any impact to its scalability efforts in terms of business growth given the prevalent limitations posed by a monolithic application, whereas an MSA is horizontally scalable. Among some obvious limitations are possible errors as it's cumbersome to test new features in a monolithic environment and delays to implement these changes, hampering the need to meet immediate requirements. Another challenge would be supporting this monolithic code base given the absence of a clear owner; in the case of microservices, individual or single functions can be managed on their own and each of these can be expanded as required quickly without impacting other functions.

In conclusion, while microservices offer significant benefits to an organization, adopting an MSA in a phased out or iterative manner may be the best way to move forward to ensure a smooth transition. Key aspects that make MSA the preferred service-oriented approach is clear ownership and the fact that it fosters failure isolation, thereby enabling these owners to make services within their domains more stable and efficient.

About the Author

Asanka Abeysinghe is vice president of solutions architecture at WSO2. He has over 15 years of industry experience, which include implementing projects ranging from desktop and web applications through to highly scalable distributed systems and SOAs in the financial domain, mobile platforms, and business integration solutions. His areas of specialization include application architecture and development using Java technologies, C/C++ on Linux and Windows platforms. He is also a committer of the Apache Software Foundation.

Mon, 26 Dec 2016 20:00:00 -0600 en text/html https://www.infoq.com/articles/navigating-microservices-architecture/
Killexams : Severity of Asthma Score Predicts Clinical Outcomes in Patients With Moderate to Severe Persistent Asthma

Abstract and Introduction

Abstract

Background: The severity of asthma (SOA) score is based on a validated disease-specific questionnaire that addresses frequency of asthma symptoms, use of systemic corticosteroids, use of other asthma medications, and history of hospitalization/intubation for asthma. SOA does not require measurements of pulmonary function. This study compared the ability of SOA to predict clinical outcomes in the EXCELS (Epidemiological Study of Xolair [omalizumab]: Evaluating Clinical Effectiveness and Long-term Safety in Patients with Moderate to Severe Asthma) patient population vs three other asthma assessment tools. EXCELS is a large, ongoing, observational study of patients with moderate to severe persistent asthma and reactivity to perennial aeroallergens.
Methods: Baseline scores for SOA, asthma control test (ACT), work productivity and impairment index-asthma (WPAI-A), and FEV1 % predicted were compared for their ability to predict five prespecified adverse clinical outcomes in asthma: serious adverse events (SAEs) reported as exacerbations, SAEs leading to hospitalizations, the incidence of unscheduled office visits, ED visits, and po or IV corticosteroid bursts related to asthma. Logistic regression analysis, area under receiver operating characteristic curves (AUCROCs), and classification and regression tree (CART) analysis were used to evaluate the ability of the four tools to predict adverse clinical outcomes using baseline and 1-year data from 2,878 patients enrolled in the non-omalizumab cohort of EXCELS.
Results: SOA was the only assessment tool contributing significantly in all five statistical models of adverse clinical outcomes by logistic regression analysis (full model AUCROC range, 0.689–0.783). SOA appeared to be a stand-alone predictor for four of five outcomes (reduced model AUCROC range, 0.689–0.773). CART analysis showed that SOA had the greatest variable importance for all five outcomes.
Conclusions: SOA score was a powerful predictor of adverse clinical outcomes in moderate to severe asthma, as evaluated by either logistic regression analysis or CART analysis.

Introduction

Asthma remains a major public health concern and is associated with significant loss of productivity, increased health-care use, and substantial costs.[1] From 2002 to 2007, the annual US economic cost of asthma totaled $56.0 billion, including $50.1 billion for direct health care.[1] Patients with severe or difficult-to-treat asthma have been shown to account for a large percentage of the morbidity, mortality, and costs.[2,3] Preventing asthma-specific morbidity and mortality depends on properly identifying and treating high-risk patients.[4,5]

Asthma severity and asthma control are related but separate clinical constructs.[6] Asthma control includes the domains of impairment (measured by the asthma control test [ACT] and FEV1) and risk of future adverse health outcomes (measured by the frequency of exacerbations). Poorer levels of asthma control have been associated with increased risk of severe asthma-related events;[6–9] however, assessment of individual components of asthma control may not accurately predict adverse asthma outcomes.[10] Although severe exacerbations are more common in patients with poorly controlled asthma, exacerbations also occur in patients with well-controlled asthma or asthma that is mild in severity. Moreover, certain asthma medications provide short-term control of symptoms and lung function without apparent effects on inflammation or airway hyperreactivity.[11]

The severity of asthma (SOA) score was developed as a tool to identify asthma patients at risk for adverse clinical outcomes. Previous efforts have established the reliability,[8] concurrent validity,[5,6,8] and predictive validity[7,8] of the 13-item disease-specific SOA score that was designed for use in survey research. A notable feature of the SOA instrument is that it does not require measurement of pulmonary function. The score is based on the frequency of current asthma symptoms (daytime or nocturnal), use of systemic corticosteroids, use of other asthma medications (besides systemic corticosteroids), and history of hospitalization and intubation for asthma.[7,8] The SOA score has been designed as a composite score and does not have statistically validated subscales based on the individual score components. Although the SOA instrument has been validated in patient populations treated by both pulmonary and allergy specialists[12,13] as well as family practice physicians,[14] current lung function data were not available for many of the patients examined in these prior validation studies.

The Epidemiologic Study of Xolair (omalizumab): Evaluating Clinical Effectiveness and Long-term Safety in Patients with Moderate to Severe Asthma (EXCELS) is a large, ongoing prospective observational study in patients with moderate to severe asthma and reactivity to a perennial aeroallergen.[15] It was initiated to primarily monitor the safety of omalizumab over a 5-year period and included a large referent group of patients who had not been treated with omalizumab. EXCELS provides an opportunity to longitudinally validate the SOA score in a cohort of patients with severe asthma in whom spirometry was performed concurrently with the ACT[16] and the asthma-specific adaptation of the work productivity and activity impairment-asthma instrument (WPAI-A).[17,18]

The objective of the current analysis was to validate the SOA score in EXCELS and compare it with the ACT, WPAI-A, and FEV1 percent predicted for the ability to predict five prespecified adverse clinical outcomes during a 1-year follow-up. These validated, clinically relevant assessment tools were chosen for comparison in order to broadly characterize the current impact of asthma on symptoms, lung function, activity limitation, and disability related to asthma.[16,19,20] Two distinct statistical methods were applied in modeling the data: logistic regression analysis and a classification and regression tree (CART) analysis. CART,[21,22] also known as binary recursive partitioning, has been used in clinical studies to efficiently identify the major factors associated with a clinical outcome.[23,24] CART analysis is complementary to logistic regression analysis, but identifies interactions among clinical variables without making assumptions about the data distribution; it is also capable of producing an intuitive visual representation of clinical interactions.

Sat, 23 Jul 2022 12:00:00 -0500 en text/html https://www.medscape.com/viewarticle/757328_1
Killexams : SOA RANKED TOP DEEMED UNIVERSITY IN STATE BY OUTLOOK-ICARE SURVEY

Bhubaneswar, July 22: The Siksha ‘O’ Anusandhan Deemed to be University (SOA) here has been ranked 15th among the top 50 Deemed to be Universities in the country in the latest Outlook-ICARE India University rankings for 2019, making it the highest ranked such university in Odisha.

Bhubaneswar, July 22: The Siksha ‘O’ Anusandhan Deemed to be University (SOA) here has been ranked 15th among the top 50 Deemed to be Universities in the country in the latest Outlook-ICARE India University rankings for 2019, making it the highest ranked such university in Odisha.

As per the Outlook-ICARE survey methodology, the evaluation of institutions was based on parameters such as Faculty Student Ratio (FSR), Faculty with Ph.D (FWP), Papers Per Faculty (PPF), Citations Per Paper (CPP) and Inclusiveness and Diversity (ID).

Institutions were awarded an overall rank depending on the number of points achieved through the evaluation and their key strengths in specific parameters.

Siksha ‘O’ Anusandhan (SOA) Deemed to be University’s achievements in a nutshell

Siksha ‘O’ Anusandhan Deemed to be University here retained the 24th position it had obtained in 2018 to occupy the top spot in the university category in Odisha as the rankings for institutions of higher education for 2019 were announced by the Ministry of Human Resource Development in New Delhi on Monday.

In the rankings conducted through the National Institutional Ranking Framework (NIRF) and released by the President, Mr. Ramnath Kovind, SOA was placed 24th in the university category--- the place it held in 2018--- and 41st among overall institutions of higher education in the country.

With this, SOA, which was conferred with the status of a Deemed to be University by the UGC in 2007 (repeat 2007), has remained the top institution in the university category in Odisha for the fourth consecutive year. Against the score of 49.59 it had registered in 2018, SOA continued to shine by securing 50.31 this year.

The Institute of Medical Sciences and SUM Hospital, faculty of medical sciences of SOA, was ranked 21st in the country to be the top ranked medical college in the state.

SOA’s faculty of engineering and technology, Institute of Technical Education and Research (ITER), which entered the ranking process for the first time this year was ranked 32nd in the country behind National Institute of Technology, Rourkela (16th) and IIT, Bhubaneswar (17th).

SOA is proud to be associated with 9 degree granting institutes, which has a whopping strength of 10,000 students. The institute leaves no stone unturned in providing quality education in the field of medicine, engineering & technology, dental sciences, management sciences, pharmaceutical sciences, law, nursing, hospitality, tourism management and agriculture. SOA keeps on updating its curriculum from time to time as per the latest industry trends and believes in providing education to students with a holistic approach.

The department of Institute of Technical Education and Research (ITER), faculty of engineering and technology of SOA, has now become the 4th institute in the country to get 3 of its programs accredited by the reputed Accreditation Board for Engineering and Technology (ABET), USA.

Adding yet another feather to its glowing cap, SOA has been ranked third in the country in the Swachh Campus Ranking for 2018 conducted by the HRD ministry. This shows the commitment and dedication of Siksha ‘O’ Anusandhan’s vision to work towards the skill development of students and betterment of the society.

SALIENT FEATURES

127 Acres campus

4, 47,395 sqm. Built-up Area

13 Research Centres

38 Research Labs

197 e-Enabled Classrooms

State-of-the-art 1400-seat auditorium alongside four other auditoria

10 Student Activity Centres

Multiple ISP Connectivity (more than 2 Gbps)

Fully Wi-Fi Campus

37 National Collaborations

127 International Collaborations

High-end Multi-disciplinary Research in Emerging Areas

Fully Automated Libraries with Ample Print Learning Resources

Adequate e-Resources with e-Databases

Fellowship for Doctoral & Post-Doctoral Programmes

Scholarship for Meritorious Students

This shows the capability and willingness of Siksha ‘O’ Anusandhan to provide quality education to students and conduct ground-breaking research work in various fields. SOA has been expanding and new disciplines are on the anvil. But the principal objective remains to ensure that students, while training to be professionals, value their own lives as that of others.

Disclaimer: The information provided in this Notification is solely by SOA Deemed to be University., Jagranjosh.com bears no representations or warranties of any kind, express or implied, about the completeness, accuracy, reliability, suitability or availability with respect to the information. Individuals are therefore suggested to check the authenticity of the information.

Thu, 21 Jul 2022 12:00:00 -0500 text/html https://www.jagranjosh.com/articles/soa-ranked-top-deemed-university-in-state-by-outlook-icare-survey-1564564898-1
Killexams : ZTE Security Standards Gain Recognition from the Telecommunication Industry No result found, try new keyword!ZTE receives outstanding marks for its 5G Flexhaul products in the BSIMM12 assessment. The BSIMM is a descriptive model that offers a baseline of observed actions for software security initiatives and ... Tue, 26 Jul 2022 03:33:00 -0500 https://finance.dailyherald.com/dailyherald/article/getnews-2022-7-26-zte-security-standards-gain-recognition-from-the-telecommunication-industry Killexams : How we test and review products

Popular Science started writing about technology more than 150 years ago. There was no such thing as “gadget writing” when we published our first issue in 1872, but if there was, our mission to demystify the world of innovation for everyday readers means we would have been all over it. Here in the present, PopSci is fully committed to helping readers navigate the increasingly intimidating array of devices on the market right now. 

Our writers and editors have combined decades of experience covering and reviewing consumer electronics. We each have our own obsessive specialties—from high-end audio, to video games, to cameras, and beyond—but when we’re reviewing devices outside of our immediate wheelhouses, we do our best to seek out trustworthy voices and opinions to help guide people to the very best recommendations. We know we don’t know everything, but we’re excited to live through the analysis paralysis that internet shopping can spur so readers don’t have to. 

What we test

Considering that every product that makes it to the marketplace has some underpinnings in science and technology, Popular Science can cover pretty much any device under the sun. That kind of freedom has its positives and negatives. We may spend one week evaluating the best solar generators, then quickly pivot to the pursuit of the best dog toys. At any given time, a gear editor’s desk might be littered with a new GoPro, a Sonos speaker, a MagSafe battery charger, some electrolyte drink mix, a steel water bottle, and an unopened doggie DNA test kit. 

How we test and review products

While we cover a wide array of subjects, we always strive to treat every product and category with the same rigor that makes PopSci stories worth memorizing in the first place.

We typically get the gear we test on loan directly from the companies. Brands understand that sending us products to test doesn’t ensure that we’re going to cover them positively. We’re committed to offering honest, and complete (as much as possible) assessments because we know people are paying ever-increasing prices for this stuff. We take that responsibility seriously. 

In some instances, we’ll check out gear as part of a pre-release media event or demo day, which companies hold to supply media a chance to evaluate multiple products on the same day. We like these showcases because they supply us a chance to see the products, without having to inflict the ecological damage that comes with shipping large, heavy items all over the country in order to put together a review. 

Obviously, we can’t test everything. As a general interest publication, we would have to put our hands on a literal mountain of stuff each month. Some of our recommendations draw their inspiration from extensive research. We rely on knowledgeable writers to mix their hands-on experience with data from trustworthy editorial reviews, reliable user feedback, and straight-up spec sheet comparisons. 

We typically start evaluating a product category with the widest possible net. We survey everything from the tried-and-true heavy hitter companies that rarely miss to the more obscure Amazon products offered by shadowy companies with names that appear like nothing more than six random letters. Then we narrow down our selections, attempting to try as many top picks as timing and availability allow, before finalizing the list. 

Every review process is slightly different because the products all vary. Reviewing a TV is leagues apart from evaluating an air fryer. Though, it is lucky when we get to review both at once because then we can count watching Mad Max: Fury Road and eating Impossible plant-based “chicken” nuggets as work. 

For some evaluations, we use tools designed specifically to make quantitative evaluations. For example, we’ll sometimes run color accuracy tests on monitors. And our audio reviewers have specific tracks they play to test out the response and performance in speakers and headphones. It’s a process made of a million processes, and we take all of them seriously. 

When we decide something truly deserves special recognition after hands-on testing and hardcore vetting, we’ll supply it our Editor’s Choice badge. We’ve interacted with, trust, and genuinely like those products. In many cases, we probably own them ourselves. 

Affiliate disclosure

If you see a link in our reviews content, it’s likely an affiliate link. When you click those and buy something, our partner sites may supply us a small commission on the sale. It helps support our journalism. 

While those relationships do involve money, they in no way influence our opinions about products. If something stinks, we’re going to tell you about it. Then we’ll tell you about several other better options and you can buy one of those through our affiliate links. Yes, this does lead to the occasional awkward email with a company, but that’s part of the gig. 

Our experts

PopSci’s Executive Editor, Gear & Reviews, Stan Horaczek has been writing about and reviewing consumer electronics for long enough that some of his earliest bylines are Engadget posts about the Motorola RAZR (great phone, by the way!). Reviews Editor Mike Epstein has been a prolific video game and accessory reviewer for years, and Associate Managing Editor Tony Ware knows so much about high-end audio that we threaten to mute him in meetings before he starts in about open-ear versus closed-back headphones for lossless audio playback. Suffice it to say: We’re nerds, and we seek out other nerds to help us on our noble nerd pursuit to pick the best stuff and recommend it to you. Here’s who we are:

Tue, 26 Jul 2022 04:54:00 -0500 en-US text/html https://www.popsci.com/product-testing-and-review-guidelines
Killexams : Genotype–phenotype databases: challenges and solutions for the post-genomic era
  • Wheeler, D. L. et al. Database resources of the National Center for Biotechnology Information. Nucleic Acids Res. 35, D5–D12 (2007).

    CAS  Article  Google Scholar 

  • Hubbard, T. et al. The Ensembl genome database project. Nucleic Acids Res. 30, 38–41 (2002).

    CAS  Article  Google Scholar 

  • Kent, W. J. et al. The Human Genome Browser at UCSC. Genome Res. 12, 996–1006 (2002).

    CAS  Article  Google Scholar 

  • Stein, L. Creating a bioinformatics nation. Nature 417, 119–120 (2002).

    CAS  Article  Google Scholar 

  • Miyazaki, S. et al. DDBJ in the stream of various biological data. Nucleic Acids Res. 32, D31–D34 (2004).

    CAS  Article  Google Scholar 

  • Benson, D. A. et al. GenBank. Nucleic Acids Res. 36, D25–D30 (2008).

    CAS  Article  Google Scholar 

  • Kanz, C. et al. The EMBL Nucleotide Sequence Database. Nucleic Acids Res. 33, D29–D33 (2005).

    CAS  Article  Google Scholar 

  • Chen, N. et al. WormBase: a comprehensive data resource for Caenorhabditis biology and genomics. Nucleic Acids Res. 33, D383–D389 (2005).

    CAS  Article  Google Scholar 

  • Twigger, S. N. et al. The Rat Genome Database, update 2007 — easing the path from disease to data and back again. Nucleic Acids Res. 35, D658–D662 (2007).

    CAS  Article  Google Scholar 

  • Bult, C. J. et al. The Mouse Genome Database (MGD): mouse biology and model systems. Nucleic Acids Res. 36, D724–D728 (2008).

    CAS  Article  Google Scholar 

  • Hamosh, A. et al. Online Mendelian Inheritance in Man (OMIM), a knowledgebase of human genes and genetic disorders. Nucleic Acids Res. 33, D514–D517 (2005).

    CAS  Article  Google Scholar 

  • McKusick, V. A. Mendelian Inheritance in Man. A Catalog of Human Genes and Genetic Disorders (Johns Hopkins Univ. Press, 1966).

    Google Scholar 

  • Ball, E. V. et al. Microdeletions and microinsertions causing human genetic disease: common mechanisms of mutagenesis and the role of local DNA sequence complexity. Hum. Mutat. 26, 205–213 (2005).

    CAS  Article  Google Scholar 

  • Altman, R. B. PharmGKB: a logical home for knowledge relating genotype to drug response phenotype. Nature Genet. 39, 426–426 (2007).

    CAS  Article  Google Scholar 

  • Lehmann, H. & Kynoch, P. A. M. Human Haemoglobin Variants and Their Characteristics (North-Holland Publishing, Amsterdam, 1976).

    Google Scholar 

  • Horaitis, O. et al. A database of locus-specific databases. Nature Genet. 39, 425 (2007).

    CAS  Article  Google Scholar 

  • Mailman, M. D. et al. The NCBI dbGaP database of genotypes and phenotypes. Nature Genet. 39, 1181–1186 (2007).

    CAS  Article  Google Scholar 

  • Becker, K. G. et al. The Genetic Association Database. Nature Genet. 36, 431–432 (2004).

    CAS  Article  Google Scholar 

  • Bertram, L. et al. Systematic meta-analyses of Alzheimer disease genetic association studies: the AlzGene database. Nature Genet. 39, 17–23 (2007).

    CAS  Article  Google Scholar 

  • Allen, N. C. et al. Systematic meta-analyses and field synopsis of genetic association studies in schizophrenia: the SzGene database. Nature Genet. 40, 827–834 (2008).

    CAS  Article  Google Scholar 

  • Mardis, E. R. The impact of next-generation sequencing technology on genetics. Trends Genet. 24, 133–141 (2008).

    CAS  Article  Google Scholar 

  • Howe, D. et al. Big data: the future of biocuration. Nature 455, 47–50 (2008).

    CAS  Article  Google Scholar 

  • Goble, C. & Stevens, R. State of the nation in data integration for bioinformatics. J. Biomed. Inform. 41, 687–693 (2008). This paper describes many of the technologies and challenges in data integration; in particular, different methods ranging from 'heavyweight' data warehousing approaches to loose-touch data 'mashups'.

    Article  Google Scholar 

  • Knoppers, B. et al. Population Genomics: The Public Population Project in Genomics (P3G): a proof of concept? Eur. J. Hum. Genet. 16, 664–665 (2008).

    CAS  Article  Google Scholar 

  • Ioannidis, J. P. A. et al. A road map for efficient and reliable human genome epidemiology. Nature Genet. 38, 3–5 (2006).

    CAS  Article  Google Scholar 

  • Elnitski, L. L. et al. The ENCODEdb portal: simplified access to ENCODE Consortium data. Genome Res. 17, 954–959 (2007).

    CAS  Article  Google Scholar 

  • Hoyweghen, I. V. & Horstman, K. European practices of genetic information and insurance: lessons for the Genetic Information Nondiscrimination Act. JAMA 300, 326–327 (2008).

    Article  Google Scholar 

  • Diergaarde, B. et al. Genetic information: special or not? Responses from focus groups with members of a health maintenance organization. Am. J. Med. Genet. A 143, 564–569 (2007).

    Article  Google Scholar 

  • Gilbar, R. Patient autonomy and relatives' right to know genetic information. Med. Law 26, 677–697 (2007).

    PubMed  Google Scholar 

  • Knoppers, B. M. et al. The emergence of an ethical duty to disclose genetic research results: international perspectives. Eur. J. Hum. Genet. 14, 1170–1178 (2006).

    Article  Google Scholar 

  • Godard, B. et al. Data storage and DNA banking for biomedical research: informed consent, confidentiality, quality issues, ownership, return of benefits. A professional perspective. Eur. J. Hum. Genet. 11 (Suppl. 2), S88–S122 (2003).

    Article  Google Scholar 

  • Homer, N. et al. Resolving individuals contributing trace amounts of DNA to highly complex mixtures using high-density SNP genotyping microarrays. PLoS Genet. 4, e1000167 (2008).

    Article  Google Scholar 

  • Cambon-Thomsen, A., Rial-Sebbag, E. & Knoppers, B. M. Trends in ethical and legal frameworks for the use of human biobanks. Eur. Respir. J. 30, 373–382 (2007).

    CAS  Article  Google Scholar 

  • Zerhouni, E. A. & Nabel, E. G. Protecting aggregate genomic data. Science 322, 44 (2008).

    CAS  Article  Google Scholar 

  • Giardine, B. et al. PhenCode: connecting ENCODE data with mutations and phenotype. Hum. Mutat. 28, 554–562 (2007).

    CAS  Article  Google Scholar 

  • Stein, L. D. Integrating biological databases. Nature Rev. Genet. 4, 337–345 (2003).

    CAS  Article  Google Scholar 

  • Stevens, R., Goble, C. A. & Bechhofer, S. Ontology-based knowledge representation for bioinformatics. Brief. Bioinform. 1, 398–414 (2000).

    CAS  Article  Google Scholar 

  • Quackenbush, J. Standardizing the standards. Mol. Syst. Biol. 2, 2006.0010 (2006).

  • Smith, B. et al. The OBO Foundry: coordinated evolution of ontologies to support biomedical data integration. Nature Biotechnol. 25, 1251–1255 (2007).

    CAS  Article  Google Scholar 

  • Dowell, R. D. et al. The Distributed Annotation System. BMC Bioinformatics 2, 7 (2001).

    CAS  Article  Google Scholar 

  • Berners-Lee, T., Hendler, J. & Lassila, O. The Semantic Web — a new form of web content that is meaningful to computers will unleash a revolution of new possibilities. Sci. Am. 284, 34–43 (2001).

    Article  Google Scholar 

  • Compete, collaborate, compel [Editorial]. Nature Genet. 39, 931 (2007).

  • Kauffmann, F. & Cambon-Thomsen, A. Tracing biological collections: between books and clinical trials. JAMA 299, 2316–2318 (2008).

    CAS  Article  Google Scholar 

  • Merali, Z. & Giles, J. Databases in peril. Nature 435, 1010–1011 (2005).

    CAS  Article  Google Scholar 

  • Stein, L. D. Towards a cyberinfrastructure for the biological sciences: progress, visions and challenges. Nature Rev. Genet. 9, 678–688 (2008). This is a latest comprehensive review of current and emerging components of informatics infrastructure for modern biological research.

    CAS  Article  Google Scholar 

  • Spellman, P. T. et al. Design and implementation of microarray gene expression markup language (MAGE-ML). Genome Biol. 3, research0046.1–00469 (2002).

    Article  Google Scholar 

  • The Gene Ontology Consortium. Gene Ontology: tool for the unification of biology. Nature Genet. 25, 25–29 (2000).

  • Jones, A. R. et al. The Functional Genomics Experiment model (FuGE): an extensible framework for standards in functional genomics. Nature Biotechnol. 25, 1127–1133 (2007).

    CAS  Article  Google Scholar 

  • Clark, T., Martin, S. & Liefeld, T. Globally distributed object identification for biological knowledgebases. Brief. Bioinform. 5, 59–70 (2004).

    CAS  Article  Google Scholar 

  • Saltz, J. et al. caGrid: design and implementation of the core architecture of the cancer biomedical informatics grid. Bioinformatics 22, 1910–1916 (2006).

    CAS  Article  Google Scholar 

  • Wang, X., Gorlitsky, R. & Almeida, J. S. From XML to RDF: how semantic web technologies will change the design of 'omic' standards. Nature Biotechnol. 23, 1099–1103 (2005). This paper describes the potential of semantic web standards and technologies for describing and integrating biological data.

    CAS  Article  Google Scholar 

  • Taylor, C. F. et al. Promoting coherent minimum reporting guidelines for biological and biomedical investigations: the MIBBI project. Nature Biotechnol. 26, 889–896 (2008).

    CAS  Article  Google Scholar 

  • Sun, 10 Jul 2022 12:23:00 -0500 en text/html https://www.nature.com/articles/nrg2483
    Killexams : ZTE Security Standards Gain Recognition from the Telecommunication Industry

    ZTE Corporation, a significant global supplier of telecommunications, enterprise, and consumer technology solutions for the mobile internet, recently announced that it has completed the Building Security In Maturity Model 12 (BSIMM12) assessment of its 5G Flexhaul products published by Synopsys, outperforming 128 competitors globally with a top score of 100. It isn’t the first time that ZTE security has achieved an excellent performance in the third party’s assessment. Indeed, ZTE security standards have already gained recognition from the telecommunication industry. Let’s review how ZTE’s past achievements reaped industry recognition.

    ZTE receives outstanding marks for its 5G Flexhaul products in the BSIMM12 assessment.

    The BSIMM is a descriptive model that offers a baseline of observed actions for software security initiatives and is one of the top security practice models in the market. It was created by Synopsys and the BSIMM community in collaboration in 2008 to assist businesses in organizing, carrying out, assessing, and enhancing their software security initiatives (SSIs).

    The 2021 edition of the BSIMM report, BSIMM12, examines information from the software security activities of 128 companies from a variety of industries, including financial services, FinTech, independent software vendors (ISVs), Internet of Things (IoT), healthcare, cloud, and technology organizations. ZTE works hard to properly manage and control all security vulnerabilities throughout the lifecycle of its products through architecture analysis, security features & design, automatic static analysis, and penetration testing. ZTE performs regression testing, automatic security hardening, and quantitative scenario evaluation during the O&M phase in the current networks to continuously assure product security.

    ZTE has participated in the BSIMM assessment as one of the first echelon members for a number of years. ZTE’s ranking at the top of the first echelon in the BSIMM12 evaluation at the end of 2021 marked a transition in product security from excellence to leadership.

    For its 5G RAN solution, ZTE received a CC EAL3+ certification.

    Last year, ZTE corporation successfully gained the Common Criteria (CC) EAL3+ certification for its 5G RAN solution.

    This certification marks that ZTE is now the first telecoms vendor in the world to have a comprehensive system solution comprised of a number of 5G RAN components that receive the CC EAL3+ certificate. The certificate also attests to the fact that ZTE 5G RAN equipment accomplishes industry-leading levels of security.

    Based on IEC/ISO15408, the Common Criteria for Information Technology Security Evaluation is an authoritative, widely accepted international standard. Currently, 31 countries participate in the CC certification’s mutual recognition program. Major worldwide telecom operators appreciate the CC certification in their procurement initiatives due to its high caliber and objectivity.

    About the target of evaluation (TOE), the CC certification specifies seven evaluation assurance levels (EAL), of which EAL3 (methodically tested and checked) is the highest level thus far attained by a system-level product in the telecommunications industry. The TOE has achieved EAL3+ status, which indicates that it satisfies both the EAL3 and other upgraded requirements for the evaluated security capability.

    ZTE’s certificate, which includes 15 5G RAN products such AAU/RRU, BBU, Unified Management Expert (UME), and others, is the first CC EAL3+ certified in the industry for a complete solution. User plane data routing, data scheduling and transmission, mobility management, and data stream IP header compression and encryption are just a small part of the features that the solution provides and interfaces with User Equipment (UE). Through a web interface, the UME is used to manage the system.

    The evaluation, which includes security throughout the whole product lifecycle, including product design, development, testing, manufacture, and delivery, was carried out by the accredited CC evaluation lab SGS Brightsight from the Netherlands. The Netherlands Scheme for Certifying in the Area of IT Security (NSCIB), administered by the certification company TüV Rheinland Nederland B.V., gave the certificate to ZTE and proclaimed that the evaluation met all requirements for the CC Certificate’s international recognition.

    ZTE’s 5G network equipment passes NESAS security assessments against SCAS as mandated by 3GPP.

    According to the official announcement on GSMA website, ZTE’s 5G NR gNodeB and seven 5GC network equipment passed the GSMA’s Network Equipment Security Assurance Scheme (NESAS) security assessment.

    In March 2021, ZTE completed the NESAS security evaluation of its 5G network products in accordance with the security specifications outlined in Security Assurance Specifications (SCAS) by 3GPP.

    All relevant SCAS test cases have been executed by SGS Brightsight, a NESAS Security Test Laboratory recognized by GSMA. Air interface security, service-oriented architecture (SOA) security, access security, control/user plane security, general network product security, transmission security, operation and maintenance security, vulnerability and robustness testing are all covered by the tests. The test report, which presents the security levels of ZTE’s 5G products objectively, states that ZTE has passed all of the tests.

    As a comprehensive and effective cybersecurity assessment framework, NESAS has been taking into account the feedback from various stakeholders and continuously improving its capacity to meet the security requirements of network operators, equipment vendors, regulators, and national security authorities.

    Conclusion

    Security has been in the spotlight with the development of telecommunication technologies. Improving industrial security standards requires all telecommunication companies to make efforts together. ZTE, obviously, sets an example for other market players.

    Media Contact
    Company Name: ZTE Corporation
    Contact Person: Lunitta LU
    Email: Send Email
    Country: China
    Website: https://policy.zte.com.cn/

    Tue, 26 Jul 2022 03:35:00 -0500 GetNews en-US text/html https://www.digitaljournal.com/pr/zte-security-standards-gain-recognition-from-the-telecommunication-industry
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