arXiv subjects

Tommi Mikkonen

Publications and source records attributed to Tommi Mikkonen.

80 records · Page 5Linked to original sources

arXiv2021

On Medical Device Software CE Compliance and Conformity Assessment

Manufacturing of medical devices is strictly controlled by authorities, and manufacturers must conform to the regulatory requirements of the region in which a medical device is being marketed for use. In general, these requirements make no difference between the physical device, embedded software running inside a physical device, or software that constitutes the device in itself. As a result, standalone software with intended medical use is considered to be a medical device. Consequently, its development must meet the same requirements as the physical medical device manufacturing. This practice creates a unique challenge for organizations developing medical software. In this paper, we pinpoint a number of regulatory requirement mismatches between physical medical devices and standalone medical device software. The view is based on experiences from industry, from the development of all-software medical devices as well as from defining the manufacturing process so that it meets the regulatory requirements.

cs.CY↗

arXiv2021

Amidst Uncertainty -- or Not? Decision-Making in Early-Stage Software Startups

It is commonly claimed that the initial stages of any startup business are dominated by continuous, extended uncertainty, in an environment that has even been described as chaotic. Consequently, decisions are made in uncertain circumstances, so making the right decision is crucial to successful business. However, little currently exists in the way of empirical studies into this supposed uncertainty. In this paper, we study decision-making in early-stage software startups by means of a single, in-depth case study. Based on our data, we argue that software startups do not work in a chaotic environment, nor are they characterized by unique uncertainty unlike that experienced by other firms.

cs.SE↗

arXiv2021

Time for AI (Ethics) Maturity Model Is Now

There appears to be a common agreement that ethical concerns are of high importance when it comes to systems equipped with some sort of Artificial Intelligence (AI). Demands for ethical AI are declared from all directions. As a response, in recent years, public bodies, governments, and universities have rushed in to provide a set of principles to be considered when AI based systems are designed and used. We have learned, however, that high-level principles do not turn easily into actionable advice for practitioners. Hence, also companies are publishing their own ethical guidelines to guide their AI development. This paper argues that AI software is still software and needs to be approached from the software development perspective. The software engineering paradigm has introduced maturity model thinking, which provides a roadmap for companies to improve their performance from the selected viewpoints known as the key capabilities. We want to voice out a call for action for the development of a maturity model for AI software. We wish to discuss whether the focus should be on AI ethics or, more broadly, the quality of an AI system, called a maturity model for the development of AI systems.

cs.CY↗

arXiv2020

Testing the Robustness of AutoML Systems

Automated machine learning (AutoML) systems aim at finding the best machine learning (ML) pipeline that automatically matches the task and data at hand. We investigate the robustness of machine learning pipelines generated with three AutoML systems, TPOT, H2O, and AutoKeras. In particular, we study the influence of dirty data on accuracy, and consider how using dirty training data may help create more robust solutions. Furthermore, we also analyze how the structure of the generated pipelines differs in different cases.

cs.LG↗

arXiv2020

Validation Frameworks for Self-Driving Vehicles: A Survey

As a part of the digital transformation, we interact with more and more intelligent gadgets. Today, these gadgets are often mobile devices, but in the advent of smart cities, more and more infrastructure---such as traffic and buildings---in our surroundings becomes intelligent. The intelligence, however, does not emerge by itself. Instead, we need both design techniques to create intelligent systems, as well as approaches to validate their correct behavior. An example of intelligent systems that could benefit smart cities are self-driving vehicles. Self-driving vehicles are continuously becoming both commercially available and common on roads. Accidents involving self-driving vehicles, however, have raised concerns about their reliability. Due to these concerns, the safety of self-driving vehicles should be thoroughly tested before they can be released into traffic. To ensure that self-driving vehicles encounter all possible scenarios, several millions of hours of testing must be carried out; therefore, testing self-driving vehicles in the real world is impractical. There is also the issue that testing self-driving vehicles directly in the traffic poses a potential safety hazard to human drivers. To tackle this challenge, validation frameworks for testing self-driving vehicles in simulated scenarios are being developed by academia and industry. In this chapter, we briefly introduce self-driving vehicles and give an overview of validation frameworks for testing them in a simulated environment. We conclude by discussing what an ideal validation framework at the state of the art should be and what could benefit validation frameworks for self-driving vehicles in the future.

cs.SE↗

arXiv2020

6G White Paper on Edge Intelligence

In this white paper we provide a vision for 6G Edge Intelligence. Moving towards 5G and beyond the future 6G networks, intelligent solutions utilizing data-driven machine learning and artificial intelligence become crucial for several real-world applications including but not limited to, more efficient manufacturing, novel personal smart device environments and experiences, urban computing and autonomous traffic settings. We present edge computing along with other 6G enablers as a key component to establish the future 2030 intelligent Internet technologies as shown in this series of 6G White Papers. In this white paper, we focus in the domains of edge computing infrastructure and platforms, data and edge network management, software development for edge, and real-time and distributed training of ML/AI algorithms, along with security, privacy, pricing, and end-user aspects. We discuss the key enablers and challenges and identify the key research questions for the development of the Intelligent Edge services. As a main outcome of this white paper, we envision a transition from Internet of Things to Intelligent Internet of Intelligent Things and provide a roadmap for development of 6G Intelligent Edge.

cs.DC↗

arXiv2018

Optical frequency comb photoacoustic spectroscopy

We report the first photoacoustic detection scheme using an optical frequency comb - the optical frequency comb photoacoustic spectroscopy (OFC-PAS). OFC-PAS combines the broad spectral coverage and the high resolution of OFCs with the small sample volume of cantilever-enhanced PA detection. In OFC-PAS, a Fourier transform spectrometer (FTS) is used to modulate the intensity of the exciting comb source at a frequency determined by its scanning speed. One of the FTS outputs is directed to the PA cell and the other is measured simultaneously with a photodiode and used to normalize the PA signal. The cantilever-enhanced PA detector operates in a non-resonant mode, enabling detection of broadband frequency response. The broadband and the high-resolution capabilities of OFC-PAS are demonstrated by measuring the rovibrational spectra of the fundamental C-H stretch band of CH${_4}$, with no instrumental line shape distortions, at total pressures of 1000 mbar, 650 mbar, and 400 mbar. In this first demonstration, a spectral resolution two orders of magnitude higher than previously reported with broadband PAS is obtained, limited by the pressure broadening. A limit of detection of 0.8 ppm of methane in N${_2}$ is accomplished in a single interferogram measurement (200 s measurement time, 1000 MHz resolution, 1000 mbar total pressure) for an exciting power spectral density of 42 μW/cm${^{-1}}$. A normalized noise equivalent absorption of 8x10${^{-10}}$ W cm${^{-1}}$ Hz${^{-1/2}}$ is obtained, which is only a factor of three higher than the best reported with PAS based on continuous wave lasers. A wide dynamic range of up to four orders of magnitude and a very good linearity (limited by the Beer-Lambert law) over two orders of magnitude are realized. OFC-PAS extends the capability of optical sensors for multispecies trace gas analysis in small sample volume with high resolution and selectivity.

physics.optics↗

arXiv2018

Broadband cantilever-enhanced photoacoustic spectroscopy in the mid-IR using supercontinuum

We demonstrate cantilever-enhanced photoacoustic spectroscopy in the mid-infrared using a supercontinuum source. The approach is broadband, compact, and allows for higher photoacoustic signal intensity and enhanced signal-to-noise ratio as compared to systems employing conventional back body radiation sources. Using this technique, we perform spectroscopic measurements of the full ro-vibrational band structure of water vapor at 1900 nm and methane at 3300 nm with relative signal enhancement factors of 70 and 19, respectively, when compared to measurements that use a black body radiation source. Our results offer novel perspective for photoacoustic detection opening the door to compact and sensitive broadband analyzers in the mid-infrared spectral region.

physics.ins-det↗