Enterprise Agility: Why Is Transformation so Hard?

Enterprise agility requires capabilities to transform, sense and seize new business opportunities more quickly than competitors. However, acquiring those capabilities, such as continuous delivery and scaling agility to product programmes, portfolios and business models, is challenging in many organisations. This paper introduces definitions of enterprise agility involving business management and cultural lenses for analysing large-scale agile transformation. The case organisation, in the higher education domain, leverages collaborative discovery sprints and an experimental programme to enable a bottom-up approach to transformation. Meanwhile the prevalence of bureaucracy and organisational silos are often contradictory to agile principles and values. The case study results identify transformation challenges based on observations from a five-month research period. Initial findings indicate that increased focus on organisational culture and leveraging of both bottom-up innovation and supportive top-down leadership activities, could enhance the likelihood of a successful transformation

DevOps in practice : A multiple case study of five companies

Context: DevOps is considered important in the ability to frequently and reliably update a system in operational state. DevOps presumes cross-functional collaboration and automation between software development and operations. DevOps adoption and implementation in companies is non-trivial due to required changes in technical, organisational and cultural aspects. Objectives: This exploratory study presents detailed descriptions of how DevOps is implemented in practice. The context of our empirical investigation is web application and service development in small and medium sized companies. Method: A multiple-case study was conducted in five different development contexts with successful DevOps implementations since its benefits, such as quick releases and minimum deployment errors, were achieved. Data was mainly collected through interviews with 26 practitioners and observations made at the companies. Data was analysed by first coding each case individually using a set of predefined themes and thereafter perform a cross-case synthesis. Results: Our analysis yielded some of the following results: (I) software development team attaining ownership and responsibility to deploy software changes in production is crucial in DevOps. (ii) toolchain usage and support in deployment pipeline activities accelerates the delivery of software changes, bug fixes and handling of production incidents. (ii) the delivery speed to production is affected by context factors, such as manual approvals by the product owner (iii) steep learning curve for new skills is experienced by both software developers and operations staff, who also have to cope with working under pressure. Conclusion: Our findings contributes to the overall understanding of DevOps concept, practices and its perceived impacts, particularly in small and medium sized companies. We discuss two practical implications of the results.Peer reviewe

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

The Many Faces of Edge Intelligence

Edge Intelligence (EI) is an emerging computing and communication paradigm that enables Artificial Intelligence (AI) functionality at the network edge. In this article, we highlight EI as an emerging and important field of research, discuss the state of research, analyze research gaps and highlight important research challenges with the objective of serving as a catalyst for research and innovation in this emerging area. We take a multidisciplinary view to reflect on the current research in AI, edge computing, and communication technologies, and we analyze how EI reflects on existing research in these fields. We also introduce representative examples of application areas that benefit from, or even demand the use of EI.Peer reviewe

The Many Faces of Edge Intelligence

Peer reviewe

6G White Paper on Machine Learning in Wireless Communication Networks

The focus of this white paper is on machine learning (ML) in wireless communications. 6G wireless communication networks will be the backbone of the digital transformation of societies by providing ubiquitous, reliable, and near-instant wireless connectivity for humans and machines. Recent advances in ML research has led enable a wide range of novel technologies such as self-driving vehicles and voice assistants. Such innovation is possible as a result of the availability of advanced ML models, large datasets, and high computational power. On the other hand, the ever-increasing demand for connectivity will require a lot of innovation in 6G wireless networks, and ML tools will play a major role in solving problems in the wireless domain. In this paper, we provide an overview of the vision of how ML will impact the wireless communication systems. We first give an overview of the ML methods that have the highest potential to be used in wireless networks. Then, we discuss the problems that can be solved by using ML in various layers of the network such as the physical layer, medium access layer, and application layer. Zero-touch optimization of wireless networks using ML is another interesting aspect that is discussed in this paper. Finally, at the end of each section, important research questions that the section aims to answer are presented

Vesiruton energia ja ravinteet talteen – Elodea II -hankkeen loppuraportti

Kanadanvesirutto (Elodea canadensis) on haitalliseksi vieraslajiksi luokiteltu uposkasvi, joka on levinnyt satoihin järviin Suomessa. Vesirutto voi kasvattaa laajoja, jopa koko järven laajuisia massakasvustoja, syrjäyttää muita alkuperäisiä lajeja, aiheuttaa hajotessaan happikatoa sekä heikentää järvien virkistyskäyttömahdollisuuksia. Vuosina 2019–2021 toteutetun Elodea II -hankkeen tavoitteena oli kehittää kustannustehokkaita keinoja vesiruton poistamiseksi sekä biomassan ja sen sisältämien ravinteiden hyödyntämiseksi. Vesiruton biomassan poistoon kehitettiin tätä kohdetta varten optimoitu raivausnuotta, jolla biomassan poisto onnistui hankkeen tarpeita varten. Raivausnuottaus on kuitenkin työlästä ja hidasta monine työvaiheineen, joten menetelmä vaatii vielä jatkokehitystä. Vesiruton poiston haitalliset vaikutukset veden laatuun jäivät vähäisiksi, mutta raivausnuottauksen mukana poistetut harvinaiset vesikasvit näyttivät palautuvan nopeasti. Biomassan sisältämien ravinteiden hyödyntämismahdollisuutta selvitettiin käyttämällä sitä viherlannoitteena peruna- ja kokoviljasäilörehukasvustoille. Biomassan käsittely ja peltolevitys onnistuivat maatalouskoneilla hyvin. Biomassan lisäyksestä viherlannoitteena ei kuitenkaan saatu odotettuja lannoitevaikutuksia peltokokeissa. Toisaalta siitä ei ollut haittaa testikohteina käytetyille viljelykasveille, minkä perusteella peltolevitys voisi tarjota toimivan ja kustannustehokkaan ratkaisun vesiruton loppusijoitukseen. Laboratoriokokeissa vesiruton pinnalta eristettiin yli 200 erilaista mikrobia. Alustavien tulosten perusteella muutamat bakteeri-isolaatit estivät tehokkaasti perunarupea aiheuttavien Streptomyces-bakteerien ja kohtalaisesti perunaseittiä aiheuttavan Rhizoctonia solani -sienen kasvua. Perunaseitin osalta sama vaikutus oli havaittavissa myös peltokokeissa. Vesiruton soveltuvuutta biokaasuntuotannon lisäsyötteeksi sekä biomassan säilöntämahdollisuuksia selvitettiin laboratorio- ja maatilamittakaavan kokeissa. Tavanomaiset nurmirehun korjuu- ja varastointimenetelmät soveltuvat biomassan käsittelyyn, mutta työ on hitaampaa pieneksi silppuuntuvan ja märän materiaalin vuoksi. Biomassan paalaus biokaasulaitokselle kuljetettavaksi oli mahdollista, kun biomassa seostettiin nurmen kanssa. Pelkän biomassan säilöntä minisiiloissa käymiseen perustuvalla menetelmällä onnistui varsin heikosti aistittavan laadun, happamuuden ja mikrobien määrän perusteella. Käymistä rajoittivat biomassan varsin vähäinen kuiva-ainepitoisuus ja todennäköisesti myös niukka liukoisten hiilihydraattien pitoisuus. Nurmirehun lisäys kuitenkin edisti säilönnän onnistumista. Vesiruton biomassa parantaa biokaasutuksen metaanisaantoa ja sen käyttö on tietyin reunaehdoin jopa kannattavaa. Toimenpiteiden kannattavuutta arvioitiin ja kehiteltiin toimintamalleja, joiden avulla voidaan luoda vesiruton poistamiseen liittyviä liiketoimintamahdollisuuksia paikallisille yrittäjille

WDR12, a Member of Nucleolar PeBoW-Complex, Is Up-Regulated in Failing Hearts and Causes Deterioration of Cardiac Function

Aims In a recent genome-wide association study, WD-repeat domain 12 (WDR12) was associated with early-onset myocardial infarction (MI). However, the function of WDR12 in the heart is unknown. Methods and Results We characterized cardiac expression of WDR12, used adenovirus-mediated WDR12 gene delivery to examine effects of WDR12 on left ventricular (LV) remodeling, and analyzed relationship between MI associated WDR12 allele and cardiac function in human subjects. LV WDR12 protein levels were increased in patients with dilated cardiomyopathy and rats post-infarction. In normal adult rat hearts, WDR12 gene delivery into the anterior wall of the LV decreased interventricular septum diastolic and systolic thickness and increased the diastolic and systolic diameters of the LV. Moreover, LV ejection fraction (9.1%, P Conclusions WDR12 triggers distinct deterioration of cardiac function in adult rat heart and the MI associated WDR12 variant is associated with diastolic dysfunction in human subjects.Peer reviewe