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Tech

Statista features promising statistics on the Enterprise Software market value worldwide from 2013 to 2019, reflecting the current situation in this field. Considering how Gartner estimated that “the market will reach $521.8 billion in 2021” in one of his updates, it may be that the reality would even surpass the initial forecasts.


LASTING Software holds a 22+ year experience in Enterprise Software solutions. As we implemented and built computer software systems for various clients across industries, we have seen this market experience a solid growth. New technologies empowered the business activities, and the companies adopted them into their ERPs.

We delivered innovative add-on extensions, as well as stand-alone components and integrated solutions. Our team provided solutions for our clients in the manufacturing, process control and materials planning areas (and not only).

 

In summary…

More than 10000 users on all continents use our solutions in any one day. The reports we have created increase speed 30fold for users across the globe. They have become their software of choice. We understand ERP systems and we customized them as requested, for a positive impact on the daily activities of those using it.

 

Takeaway

LASTING Software always adapts to your requests. Our teams feature experienced software engineers, innovators, and hands-on leaders.


We build the enhanced, flexible software that allows for efficient, sustainable business growth. Our customized solutions are being used on all continents by over 50 000 users.


Our business model is simple. It enables investors to control the cash flow and changing skill sets required at different phases of the investment cycle. For SMEs, for example, we provide end to end coverage of projects or components which have been unable to be delivered because of resourcing constraints.

 

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Tech

Deep learning aims to make computers mimic the human brain. It is “inspired by and based on the model of the human brain to create artificial neural networks for machines”. The aim is to make machines express themselves and act in a similar way to us.

There is no degree of passion about this topic that equals the one met with the professionals that develop intelligent machines. Therefore, we want to recommend you a specific article this week.

 

Working in deep learning goes beyond tasks, into enthusiasm

The article pointed out by one of our team members is co-authored by Ronald van Loon and Rodrigo Agundez. The latter is “very enthusiastic about the improvements that deep learning can offer”.

The focus here is on the importance of the technological progress we are witnessing in real time. The post presents as well the huge work involved in the back-end algorithms. As the author says:


Creating machines that are capable of understanding minute differences in words embedded in a context may seem like a very small thing, but requires a very large set of data and complex algorithms to execute.


The accuracy is extremely important in differentiating complex and successful algorithms from the rest. You will see how and why deep learning is superior to AI (Artificial Intelligence), by going through the original post.


Our take


Both the authors benefit from hands-on experience in the field, and share the same passion for advanced technology. This is specific to our team members, too. We can easily relate to their enthusiasm by replaying our own experiences.

 

The article we recommend also mentions how the ubiquitous connectivity that now links software engineers around the globe makes it easier for the cutting edge companies to hire talented developers. Having access to research and open source data, as well as enriching one’s experience continuously through each new project, really opens up the horizon.

 

Once again we feel elated about our field of work – and this is the basic premise for great things!

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Tech

Before seeing what IoMT stands for, we’ll ask you a question. Do you know that LASTING Software developed solutions underpinning 93% percent of the pharmaceutical companies’ trials?

Our company provides fast prototyping, and links your business intelligence to the real world, via connected systems and the cloud. Healthcare solutions are a field we are experienced in. Our solutions are greatly appreciated. They place us right in the middle of the digitization movement that takes place in this industry as we speak.


What is IoMT?

IoMT translates as the Internet of Medical Things, a specialized branch of IoT. It comprises all web-connected medical devices.

Expected to reach $136.8 billion worldwide by 2021, according to this report by Allied Market Research, the IoMT is expanding, with the patient monitoring application segment in lead position.

With scientific & technological advances, such as these smart pills that notify an app whether the patient took them as prescribed or not, the healthcare devices are set for a spectacular growth rate in the short to medium future. Subsequently, so are the apps and software solutions that will collect, process and analyze the resulting big data.

As Forbes put it, “the IoMT can help monitor, inform and notify not only care-givers, but provide healthcare providers with actual data to identify issues before they become critical or to allow for earlier invention”.

A sub-segment of the IoMT consists of pharma IoMT – involving drug development & treatment processes digitization.


The reason for IoMT’s slower evolution

It is well known that the healthcare industry adopts the Internet of Things technologies at a slower pace, compared to other industries. As the certification/approval procedures prove it, each device, software solution, innovation and generally each new piece of technology needs to undergo a thorough process of verification and validation in this industry.

The reason is in fact simple – people’s lives may depend on it. By consequence, there is no place for faulty hardware or software in an industry such as healthcare. Of course, the question of trusting someone’s life entirely to AI is still in its theoretical debate phase. Nevertheless, all products that officially form the IoMT have to successfully pass the trial and certification phases.

Combining the fact that software engineering is now a global activity, with the lower prices-better quality phenomenon, allows for skilled engineers to program efficient hardware in this field. As mentioned above, we are looking forward to a vast increase in the number of medical devices in the next few years.

 

Turning healthcare data into powerful insights

Once collected, the IoMT data holds a vast potential. It’s also Forbes that mentions the “healthcare’s cultural metamorphosis”, in the article we quoted above.  Turning this data into useful insights medical professionals can act upon is the next big step.

Here enter the efficient software solutions. Bringing AI algorithms together with cyber-security features, the healthcare software solutions make sure to link patterns and interpretations with the initial raw information.

It’s a wonderful world of possibilities.

Also, it is a field where discipline, data privacy, efficient work procedures and compliance are all of highest importance. Cost-efficiency in the healthcare software solutions field means working with the best professionals. Providing experience, a customer-minded work style and respecting the commonly agreed procedures are important during the development stage. Going with the cheapest partners may prove costly over time, endangering the solution’s approval or being a potential liability.

Having a rock-solid digital technology foundation lists as one of the best ways of to combat security risks within medical devices.

 

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Tech

by Ecaterina Ganenco, Business Intelligence Developer, LASTING Software
(Presentation held during Codecamp Timisoara, April 2018)

The story of how developing a consumer mindset testing software influenced my way of thinking


Have you ever wondered why movies in Cineplex’s are scheduled? Why are they not always starting at the same time, or how managers show more comedies in a country, whereas a continent prefers romance better?

Before being part of the development team I used to go the movies rarely and mostly to Russian movies, which were more popular in my area.

The Movie Scheduling Problem and its data resolution

When people come to see a movie, they are following through a previous decision.

Decision-making is the process of identifying and choosing alternatives. It is based on the values and preferences of the decision maker. It also is a cognitive process.

Reverse engineering this cognitive process resulted in a smart software. A software capable of anticipating the selection of movie shows that would gather the most spectators. Among several alternative possibilities, the software aimed at pointing out the most suited scheduling formula.

The factors computed into such software are:

  • Decisional balance
  • Simple prioritization
  • Consulting with a person in authority
  • Anti-authoritarianism traits
  • Automated decision support (rule based)
  • Decision support systems (decision-making software)

The difficulty consisted in overcoming the decision-making paradox. Sometimes people decide predictably, while other times their choices may seem random. Yet, there are a few steps that would sift out the random factors as much as possible:

Formal analysis ->Covered problems -> Generalized set partitioning problem

Remember how historical data works magic? Inputting the historical data related to moviegoers serves in establishing patterns. We may not be able to eliminate the random element in decision making. But we can find the patterns in the outcome of the decisions, taken as historical data.

The app aimed to plan the best strategy. Finding out the optimal movie program for a single day given meant that it required a lot of details. The capacities of the screening rooms, the technical capabilities of this rooms, the list of movies to be shown or the set of theatre specific constraints are all important.

The formula is not unusual in big data apps. The users generate data – data is collected and packaged – the software processes the data – the software returns the data. Based on the returned results (predictive analysis), those who use the software can now make their own efficient decisions.

While working in software development, my focus is on the technology. However, my personal experience is that my mindset can also change due to the value and impact of the solutions I’m working on.

When I worked on a tool serving in understanding the consumer mindset, I had the opportunity of figuring out its impact on more than one levels. Such tools use big data. Finding out how my work, how the efforts of my team turn into structured data and facts, was important for me.

Products and services need to reach the people who enjoy them. In other words, the consumers need the right offer at the right time. Determining these key parameters may be a software matter.

 

How it is started:

 

How do you help consumers to consume more?

It is very simple – you provide quality and the right services/products.  Companies achieve product uniqueness through an elaborate process. But in this process they must answer two main questions:

–  What do consumers want?

–  What do (their) customers want?

Answers vary, of course. Factors such as culture may trigger different answers. I asked myself “So what determines if culture matters?” There are subjective areas of culture, for example religion, education or history. These stand the chance of being extremely personal. Their effect is seen in choice variations between different background people. Other factors are unifying. Patterns or globalization will ensure similar choices for example

 

We are consumers of our (own) applications

Any developer may answer the questions above when imagining it is she/he who uses that precise software solution. I thought about what I like and dislike as an app user.

What I like

– The application should solve a problem
– Easiness to navigate between pages
– Design

What I dislike

– If the application doesn’t resolve the problem
– If the application is not user friendly
– Performance issues

If the result of my work falls into the first category, I feel motivated.

Don’t ignore the word of mouth

Word of mouth or viva voce is organic marketing in itself. It can boost a product. It can also point out what goes wrong with it, before it’s too late. So just think:

– What sort of conversations are people having about the product?
– When people share information about our program, does it tend to be positive or negative, emotionally charged or indifferent?

Defining consumer groups

My story is about putting my work into perspective. I made the exercise of thinking as an app user, to objectively review the outcome of my activity. Then I became fascinated by the functionality of the software product I worked on.

To gather the right data, a big data software program needs guiding. Putting data sources into groups serves as guidance, for example. Half of the work is done if you can define the consumers groups.

Since the app I worked on targeted people, we had to define consumer groups. In the case of movie scheduling, I noticed this was achieved in 2 ways. I then thought of how this applies to a software product, to an app. One needs to test & define consumers as a prerequisite to grouping.

Test

–  A/B Testing
– Set the time of research
– Ask the question which you want answered
– Try to find and granulate all the things you need

Define

– Apply statistic tests to data
– Identify the vulnerable people
– People that don’t like the application – Who are they? Why don’t they like it?
– People that like the application – What are the main reasons?

What we should also take into account when we apply the test to a specific group is hidden features.
– Look at the details
– Run emotional ideas
– Test the nonverbal language

Also, historical data can do wonders.


My story

As a member of the public, I felt that any movie theatre chain that would use such tools to accommodate me better won my vote of confidence.

I started to go to the movies more. Especially English-speaking movies. I changed my decisions, in appreciation of the software-supported work that movie theatres put in, to meet the consumers.

The consumers are just clients, in higher numbers. And clients are always the masters. Accepting to be served gracefully is an art. In the current times we are often served by algorithms and software programs. Benefitting from this modern services is also a wise step, as well as an art.

So, the next time you go see a movie that is perfect for a rainy evening in the city, send out a good thought for the people behind the algorithms. We salute you through the software that just translated your preferences into reality.

 

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