Mikko Ahonen

Motivating and supporting collaboration in open innovation

Purpose – The purpose of this paper is to explore collaboration in open innovation (OI) communities. The paper focuses on the following two research problems: how can users be motivated to collaborate in OI communities and what kind of tools and methods can support collaboration in OI communities?Design/methodology/approach – The exploratory case study includes three innovation intermediaries originated in three different countries: France, The Netherlands and Finland. The primary data source consists of the open‐ended questions posted to the maintainers and users by e‐mail. The data include five responses from the maintainers and 12 responses from the users. The secondary source is the internet document review. The classification of the factors in the preliminary framework is derived from reading and rereading the answers of the respondents until the themes started emerging from the data. Thereafter, the data are coded according to the chosen themes.Findings – Results suggest that monetary rewards are no...

Supporting pervasive learning environments: adaptability and context awareness in mobile learning

In the mobile learning context, it is helpful to consider context awareness and adaptivity as two sides of the same coin. The purpose of the adaptivity and context awareness is to better support a variety of learners, given that they may have very different skills and motivations to learn in varying contexts. The recent research on adaptivity and context awareness has turned towards supporting pervasive environments and this is coupled with the increasing trend in seeing learning environments from an informal learning perspective. In this paper are presented experiences of developing an adaptive and context aware mobile learning system, with examples of other systems underlining the development towards supporting pervasive learning environments. We then consider approaches for the future development of systems supporting pervasive learning environments.

Epidemiological Evidence for a Health Risk from Mobile Phone Base Stations

Abstract Human populations are increasingly exposed to microwave/radiofrequency (RF) emissions from wireless communication technology, including mobile phones and their base stations. By searching PubMed, we identified a total of 10 epidemiological studies that assessed for putative health effects of mobile phone base stations. Seven of these studies explored the association between base station proximity and neurobehavioral effects and three investigated cancer. We found that eight of the 10 studies reported increased prevalence of adverse neurobehavioral symptoms or cancer in populations living at distances < 500 meters from base stations. None of the studies reported exposure above accepted international guidelines, suggesting that current guidelines may be inadequate in protecting the health of human populations. We believe that comprehensive epidemiological studies of longterm mobile phone base station exposure are urgently required to more definitively understand its health impact.

Accessibility and Mobile Learning

During the Digital Learning and MOBIlearn projects, the authors have acknowledged a new gap in defining accessibility in the context of mobile learning. This document describes this gap and seeks a broader definition of accessibility. Accessibility is discussed in terms of 1) usability, 2) a digital divide and 3) evaluation. First they describe how accessibility is traditionally understood in usability design and what issues mobility brings to accessibility. Secondly, equality issues are discussed in the context of a digital divide. Then the mobile learning evaluation framework is introduced and the implications of accessibility on evaluation are discussed. Finally, these perspectives are integrated and future research topics are proposed.

Radiofrequency radiation at Stockholm Central Railway Station in Sweden and some medical aspects on public exposure to RF fields

The Stockholm Central Railway Station in Sweden was investigated for public radiofrequency (RF) radiation exposure. The exposimeter EME Spy 200 was used to collect the RF exposure data across the railway station. The exposimeter covers 20 different radiofrequency bands from 88 to 5,850 MHz. In total 1,669 data points were recorded. The median value for total exposure was 921 μW/m2 (or 0.092 μW/cm2; 1 μW/m2=0.0001 μW/cm2) with some outliers over 95,544 μW/m2 (6 V/m, upper detection limit). The mean total RF radiation level varied between 2,817 to 4,891 μW/m2 for each walking round. High mean measurements were obtained for GSM + UMTS 900 downlink varying between 1,165 and 2,075 μW/m2. High levels were also obtained for UMTS 2100 downlink; 442 to 1,632 μW/m2. Also LTE 800 downlink, GSM 1800 downlink, and LTE 2600 downlink were in the higher range of measurements. Hot spots were identified, for example close to a wall mounted base station yielding over 95,544 μW/m2 and thus exceeding the exposimeters detection limit. Almost all of the total measured levels were above the precautionary target level of 3–6 μW/m2 as proposed by the BioInitiative Working Group in 2012. That target level was one-tenth of the scientific benchmark providing a safety margin either for children, or chronic exposure conditions. We compare the levels of RF radiation exposures identified in the present study to published scientific results reporting adverse biological effects and health harm at levels equivalent to, or below those measured in this Stockholm Central Railway Station project. It should be noted that these RF radiation levels give transient exposure, since people are generally passing through the areas tested, except for subsets of people who are there for hours each day of work.

Case-control study on occupational exposure to extremely low-frequency electromagnetic fields and glioma risk

BACKGROUND Exposure to extremely low-frequency electromagnetic fields (ELF-EMF) was in 2002 classified as a possible human carcinogen, Group 2B, by the International Agency for Research on Cancer at WHO. METHODS Life time occupations were assessed in case-control studies during 1997-2003 and 2007-2009. An ELF-EMF Job-Exposure Matrix was used for associating occupations with ELF exposure (μT). Cumulative exposure (μT-years), average exposure (μT), and maximum exposed job (μT) were calculated. RESULTS Cumulative exposure gave for astrocytoma grade IV (glioblastoma multiforme) in the time window 1-14 years odds ratio (OR) = 1.9, 95% confidence interval (CI) = 1.4-2.6, p linear trend <0.001, and in the time window 15+ years OR = 0.9, 95%CI = 0.6-1.3, p linear trend = 0.44 in the highest exposure categories 2.75+ and 6.59+ μT years, respectively. CONCLUSION An increased risk in late stage (promotion/progression) of astrocytoma grade IV for occupational ELF-EMF exposure was found.

Case-Control Study on Occupational Exposure to Extremely Low-Frequency Electromagnetic Fields and the Association with Meningioma

Objective Exposure to extremely low-frequency electromagnetic fields (ELF-EMF) was in 2002 classified as a possible human carcinogen, Group 2B, by the International Agency for Research on Cancer at WHO based on an increased risk for childhood leukemia. In case-control studies on brain tumors during 1997–2003 and 2007–2009 we assessed lifetime occupations in addition to exposure to different agents. The INTEROCC ELF-EMF Job-Exposure Matrix was used for associating occupations with ELF-EMF exposure (μT) with meningioma. Cumulative exposure (μT-years), average exposure (μT), and maximum exposed job (μT) were calculated. Results No increased risk for meningioma was found in any category. For cumulative exposure in the highest exposure category 8.52+ μT years odds ratio (OR) = 0.9, 95% confidence interval (CI) = 0.7–1.2, and p linear trend = 0.45 were calculated. No statistically significant risks were found in different time windows. Conclusion In conclusion occupational ELF-EMF was not associated with an increased risk for meningioma.

Electromagnetic Radiation and Health: Human Indicators

Manmade electromagnetic radiation increases in the environment as new applications are frequently adopted. Humans serve as receiving antennas for electromagnetic waves. Thus various new responses can be expected. In addition to radio and television programs, mobile telephony, distant reading of electricity and water consumption and many other technologies load us electrically and magnetically both out- and indoors. Most exposures are active all the time, day and night, continuously or in regular pulses. Personal devices are also important sources, since they touch the skin and are held near the brain and heart. Humans are good bioindicators, as their physiological parameters, such as heart function and blood biochemistry, are frequently recorded. Data storage and analysis are getting better. Humans also report symptoms that cannot be directly measured, and carry valuable information on bioeffects. Studies from recent decades have shown that exposure to electromagnetic waves can break DNA chains, damage proteins, even increase the blood brain barrier permeability, disturb sleep, and cause fatigue, memory and concentration problems. Neural, hormonal and psychosocial development is affected. An increase in human brain tumours has been described in correlation with mobile phone use on the exposed side of the head. The symptoms of electrohypersensitivity cause morbidity, but the interaction between multiple radiation frequencies and the mechanisms leading to frequency sensitivity are still poorly understood. Producers of mobile communication devices continuously warn users not to keep personal devices in skin contact. The Precautionary Principle that has been signed by many nations applies to all environmental risk factors, including exposure to electromagnetic waves.

Building a Ubiquitous Artifact That Integrates Problem-Solving and Learning Processes to Support Creativity

This ongoing Ph.D. research work started with observations of shortcomings in the innovation and knowledge management processes in two companies, one Finnish and the other American. An extensive creativity and innovation literature survey was conducted. Problems were identified in three areas: idea evaluation (Amabile 1998), systematic idea development to the innovation phase (Drucker 1985), and community participation in individual idea suggestions (Hargadon 2003). A specific model, the technology brokering model (Hargadon and Sutton 1997) was chosen. From this starting point, a mobile prototype was built, evaluated, and gradually improved using a design science research framework (Hevner et al. 2004; Jarvinen 2004) and action research methods. The utility of the prototype is evaluated in three case organizations. This paper focuses on describing the mobile and ubiquitous computing related challenges in this prototype building process. Earlier work relates to the research of mobility, mobile architectures, user interfaces, and mobile learning (Ahonen et al. 2004; Syvanen et al. 2003), most recently in the global MOBIleam project.^ Within this research work, a mobile artifact is built to support learning, problem-solving, and creativity processes. According to Goodyear (2000), such an artifact and related tools should support individual construction of meaning and personal learnplace creation. From the perspective of the current research, the notion of leamplaces points, first, to ubiquitous computing environments and, second, to the informal learning area. However, due to the constantly changing context

Voltage transients measurements and power line communication

Power line communication (PLC) connects energy producers with energy consumers. In the European Union stricter guidelines are under development to limit disturbances in the 2-150 kHz frequency range, because devices utilising PLC do not work. This study measured voltage transients in 22 locations and identified sources for noise. Home environments and public buildings were measured. Measurements were conducted in the frequency range of 150 kHz-500 kHz (according to EN 55011 to EN 55022) and in the lower frequency range of 3 kHz to 95 kHz. Results indicate that voltage transients are generated mostly by switching mode power supplies, pumps, rectifiers, inverters and even low quality smart meters. Several of these devices exceeded PLC standard level, 122 dBμV. Additionally we demonstrate that basic power quality recordings do not provide enough information to mitigate PLC problems occurring within microseconds and frequency specific voltage transient measurements are needed.