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Part 1: The International Cross Domain Conference (CD-ARES 2016); International audience; Peer review is widely viewed as an essential step for ensuring scientific quality of a work and is a cornerstone of scholarly publishing. On the other hand, the actors involved in the publishing process are often driven by incentives which may, and increasingly do, undermine the quality of published work, especially in the presence of unethical conduits. In this work we investigate the feasibility of a tool capable of generating fake reviews for a given scientific paper automatically. While a tool of this kind cannot possibly deceive any rigorous editorial procedure, it could nevertheless find a role in several questionable scenarios and magnify the scale of scholarly frauds.A key feature of our tool is that it is built upon a small knowledge base, which is very important in our context due to the difficulty of finding large amounts of scientific reviews. We experimentally assessed our method 16 human subjects. We presented to these subjects a mix of genuine and machine generated reviews and we measured the ability of our proposal to actually deceive subjects judgment. The results highlight the ability of our method to produce reviews that often look credible and may subvert the decision.

The efficacy of leveraging telehealth services on clinical outcomes remains scarcely documented. We conducted a rapid review to explore the effectiveness of telehealth interventions for the diagnosis, contact tracing and care of the corona virus disease of 2019 in sub Saharan Africa. Using MEDLINE, Science Direct and Cochrane Library databases, a review was conducted during the month of July 2020 of peer reviewed articles reporting on the use of telehealth interventions in sub-Saharan Africa. All the studies were assessed against the inclusion criteria by two independent reviewers. The 7 studies included in the synthesis were conducted in 2 countries [Nigeria (× 1), Zimbabwe (× 1)], and commentaries covering the entire sub Saharan Africa in general (× 4) and to Uganda (× 1). All the included articles and commentaries were published in 2020. We established that mobile applications are effective in providing information for referrals of potential patients infected by COVID 19 and provides convenient access to routine care without the risk of exposure through close contact. In countries such as Nigeria, mobile positioning data significantly improved decision making, capacity and scope of contact tracing and surveillance of known contacts of confirmed cases. We noted that collaborations between the government, mobile network operators and technology companies were utilised for successful mobile positioning data tracing interventions for COVID patients. Mobile applications such as the Vula platform in South Africa were also noted as effective in providing psychological support to health care workers attending to patients.

Background Patients who suffer from different diseases may use different electronic health (eHealth) resources. Thus, those who plan eHealth interventions should take into account which eHealth resources are used most frequently by patients that suffer from different diseases. Objective The aim of this study was to understand the associations between different groups of chronic diseases and the use of different eHealth resources. Methods Data from the seventh survey of the Tromsø Study (Tromsø 7) were analyzed to determine how different diseases influence the use of different eHealth resources. Specifically, the eHealth resources considered were use of apps, search engines, video services, and social media. The analysis contained data from 21,083 participants in the age group older than 40 years. A total of 15,585 (15,585/21,083; 73.92%) participants reported to have suffered some disease, 10,604 (10,604/21,083; 50.29%) participants reported to have used some kind of eHealth resource in the last year, and 7854 (7854/21,083; 37.25%) participants reported to have used some kind of eHealth resource in the last year and suffered (or had suffered) from some kind of specified disease. Logistic regression was used to determine which diseases significantly predicted the use of each eHealth resource. Results The use of apps was increased among those individuals that (had) suffered from psychological problems (odds ratio [OR] 1.39, 95% CI 1.23-1.56) and cardiovascular diseases (OR 1.12, 95% CI 1.01-1.24) and those part-time workers that (had) suffered from any of the diseases classified as others (OR 2.08, 95% CI 1.35-3.32). The use of search engines for accessing health information increased among individuals who suffered from psychological problems (OR 1.39, 95% CI 1.25-1.55), cancer (OR 1.26, 95% CI 1.11-1.44), or any of the diseases classified as other diseases (OR 1.27, 95% CI 1.13-1.42). Regarding video services, their use for accessing health information was more likely when the participant was a man (OR 1.31, 95% CI 1.13-1.53), (had) suffered from psychological problems (OR 1.70, 95% CI 1.43-2.01), or (had) suffered from other diseases (OR 1.43, 95% CI 1.20-1.71). The factors associated with an increase in the use of social media for accessing health information were as follows: (had) suffered from psychological problems (OR 1.65, 95% CI 1.42-1.91), working part time (OR 1.35, 95% CI 0.62-2.63), receiving disability benefits (OR 1.42, 95% CI 1.14-1.76), having received an upper secondary school education (OR 1.20, 95% CI 1.03-1.38), being a man with a high household income (OR 1.67, 95% CI 1.07-2.60), suffering from cardiovascular diseases and having a high household income (OR 3.39, 95% CI 1.62-8.16), and suffering from respiratory diseases while being retired (OR 1.95, 95% CI 1.28-2.97). Conclusions Our findings show that different diseases are currently associated with the use of different eHealth resources. This knowledge is useful for those who plan eHealth interventions as they can take into account which type of eHealth resource may be used for gaining the attention of the different user groups.

Background Type 1 diabetes is a chronic condition of blood glucose metabolic disorder caused by a lack of insulin secretion from pancreas cells. In people with type 1 diabetes, hyperglycemia often occurs upon infection incidences. Despite the fact that patients increasingly gather data about themselves, there are no solid findings that uncover the effect of infection incidences on key parameters of blood glucose dynamics to support the effort toward developing a digital infectious disease detection system. Objective The study aims to retrospectively analyze the effect of infection incidence and pinpoint optimal parameters that can effectively be used as input variables for developing an infection detection algorithm and to provide a general framework regarding how a digital infectious disease detection system can be designed and developed using self-recorded data from people with type 1 diabetes as a secondary source of information. Methods We retrospectively analyzed high precision self-recorded data of 10 patient-years captured within the longitudinal records of three people with type 1 diabetes. Obtaining such a rich and large data set from a large number of participants is extremely expensive and difficult to acquire, if not impossible. The data set incorporates blood glucose, insulin, carbohydrate, and self-reported events of infections. We investigated the temporal evolution and probability distribution of the key blood glucose parameters within a specified timeframe (weekly, daily, and hourly). Results Our analysis demonstrated that upon infection incidence, there is a dramatic shift in the operating point of the individual blood glucose dynamics in all the timeframes (weekly, daily, and hourly), which clearly violates the usual norm of blood glucose dynamics. During regular or normal situations, higher insulin and reduced carbohydrate intake usually results in lower blood glucose levels. However, in all infection cases as opposed to the regular or normal days, blood glucose levels were elevated for a prolonged period despite higher insulin and reduced carbohydrates intake. For instance, compared with the preinfection and postinfection weeks, on average, blood glucose levels were elevated by 6.1% and 16%, insulin (bolus) was increased by 42% and 39.3%, and carbohydrate consumption was reduced by 19% and 28.1%, respectively. Conclusions We presented the effect of infection incidence on key parameters of blood glucose dynamics along with the necessary framework to exploit the information for realizing a digital infectious disease detection system. The results demonstrated that compared with regular or normal days, infection incidence substantially alters the norm of blood glucose dynamics, which are quite significant changes that could possibly be detected through personalized modeling, for example, prediction models and anomaly detection algorithms. Generally, we foresee that these findings can benefit the efforts toward building next generation digital infectious disease detection systems and provoke further thoughts in this challenging field.

Background Parents seek trustworthy information online to promote healthy eating for their toddlers. Such information must be perceived as relevant and easy to implement and use. Objective The objectives of this study were to conduct a process evaluation of the electronic health (eHealth) intervention (Food4toddlers) targeting food environment, parental feeding practices, and toddlers’ diet and to examine possible differences in these areas according to education and family composition. Methods A 2-armed randomized controlled trial, including 298 parent–toddler dyads from Norway, was conducted in 2017. In total, 148 parents in the intervention group received access to an intervention website for 6 months. Data on website usage were retrieved from the learning management platform used (NEO). Participants’ satisfaction with the intervention was asked for in a postintervention questionnaire. Chi-square and t tests were used to examine differences in usage and satisfaction between education and family composition groups. Results Most participants were mothers (144/148, 97.2%), lived in two-adult households (148/148, 100%), and were born in Norway (132/148, 89.1%). Mean parental age was 31.5 years (SD 4.2). More than 87.8% (129/147) had a university education degree and 56.5% (83/147) had over 4 years of university education. Most (128/148, 86.5%) intervention participants entered the website at least once (mean days of access 7.4 [SD 7.1]). Most parents reported the website as appropriate to the child’s age (71/83, 86%) and self-explanatory (79/83, 95%) and appreciated the interface (52/83, 63%) and layout (46/83, 55%). In total, 61% (51/83) stated that they learned something new from the intervention. Parents with over 4 years of university education and in 1-child households used the intervention website more than those with 4 years or less of university education (8.4 vs 5.9 days in total, P=.04) and households with more than 1 child (8.3 vs 5.8 days in total, P=.04), respectively. Conclusions The Food4toddlers intervention website was found to be relevant by most participants in the intervention group, although usage of the website differed according to educational level and family composition. For eHealth interventions to be effective, intervention materials such as websites must be used by the target group. Our results highlight the need to include users from different groups when developing interventions. Trial Registration ISRCTN Registry ISRCTN92980420; http://www.isrctn.com/ISRCTN92980420

Source at https://doi.org/10.2196/13678. Background: Despite the increasing prevalence of diabetes and increasing use of electronic health (eHealth) among people with diabetes, little is known about the association between the use of eHealth and the use of provider-based health services. Objective: The objective of this study was to investigate whether the use of eHealth might change patients’ decisions regarding doctor-seeking behavior and whether information acquired from the internet was discussed with a doctor. Methods: We used email survey data collected in 2018 from members of the Norwegian Diabetes Association (aged 18 to 89 years) diagnosed with diabetes. Using logistic regressions, we studied patients’ internet-triggered changes in decisions regarding doctor visits; whether they discussed information from the internet with a doctor; and whether these topics were associated with gender, age, education, self-rated health, and self-reported anxiety/depression. Results: Among the 895 informants, 75.4% (645/856) had never made an internet-triggered change of decision in any direction regarding visiting a doctor, whereas 16.4% (41/859) had decided to visit and 17.3% (148/856) had decided not to visit. The probability of changing decisions decreased with higher age and increased with the severity of self-reported anxiety/depression. Around half of the study participants (448/858, 52.2%) had never discussed information from the internet with a doctor. The probability of discussing internet information with a doctor was higher for those in bad/very bad self-rated health (odds ratio 2.12, CI 1.15-3.90) and for those with moderate self-reported anxiety/depression (odds ratio 2.30, CI 1.30-4.10). Conclusions: Our findings suggest that using eHealth has a significant impact on doctor-visiting decisions among people with diabetes, especially among people aged 18 to 39 years and among those reporting anxiety/depression. It is of great importance that the information posted is of high quality and that the large differences between internet-users regarding age as well as mental and somatic health status are taken into account. More research is needed to confirm and further explore the findings of this study.

The following article, Hansen, A.H., Brož, J., Claudi, T. & Årsand, E. (2018). Relations between the use of electronic health and the use of general practitioner and somatic specialist visits in patients with type 1 diabetes: Cross-sectional study. Journal of Medical Internet Research, 20(11), can be accessed at https://doi.org/10.2196/11322. Background: The prevalence of diabetes and the use of electronic health (eHealth) are increasing. People with diabetes need frequent monitoring and follow-up of health parameters, and eHealth services can be of great value. However, little is known about the association between the use of eHealth and provider-based health care services among people with diabetes. Objective: The objective of this study was to investigate the use of 4 different eHealth platforms (apps, search engines, video services, and social media sites) and associations with the use of provider-based health care visits among people diagnosed with type 1 diabetes mellitus (T1DM). Methods: We used email survey data collected from 1250 members of the Norwegian Diabetes Association (aged 18 to 89 years) in 2018. Eligible for analyses were the 523 respondents with T1DM. Using descriptive statistics, we estimated the use of eHealth and the use of general practitioners (GPs) and somatic specialist outpatient services. By logistic regressions, we studied the associations between the use of these provider-based health services and the use of eHealth, adjusted for gender, age, education, and self-rated health. Results: Of the sample of 523 people with T1DM, 90.7% (441/486) had visited a GP once or more, and 61.0% (289/474) had visited specialist services during the previous year. Internet search engines (such as Google) were used for health purposes sometimes or often by 84.0% (431/513), apps by 55.4% (285/514), social media (such as Facebook) by 45.2% (232/513), and video services (such as YouTube) by 23.3% (118/506). Participants aged from 18 to 39 years used all forms of eHealth more than people aged 40 years and older, with the exception of social media. The use of search engines was positively associated with the use of somatic specialist services (odds ratio 2.43, 95% CI 1.33-4.45). GP visits were not associated with any kind of eHealth use. Conclusions: eHealth services are now widely used for health support and health information by people with T1DM, primarily in the form of search engines but often in the form of apps and social media as well. We found a positive association between the use of search engines and specialist visits and that people with T1DM are frequent users of eHealth, GPs, and specialist services. We found no evidence that eHealth reduces the use of provider-based health care; these services seem to be additional rather than alternative. Future research should focus on how health care services can meet and adapt to the high prevalence of eHealth use. Our results also indicate that many patients with T1DM do not visit specialist clinics once a year as recommended. This raises questions about collaboration in health care services and needs to be followed up in future research.

Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 30.05.2017. This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/). Background: Adequate self-management is the cornerstone of type 2 diabetes treatment, as people make the majority of daily treatment measures and health decisions. The increasing prevalence of type 2 diabetes mellitus (T2DM) and the complexity of diabetes self-management demonstrate the need for innovative and effective ways to deliver self-management support. eHealth interventions are promoted worldwide and hold a great potential in future health care for people with chronic diseases such as T2DM. However, many eHealth interventions face high dropout rates. This led to our interest in the experiences of participants who dropped out of an eHealth intervention for adults with T2DM, based on the Guided Self-Determination (GSD) counseling method. Objective: In this study, we aimed to explore experiences with an eHealth intervention based on GSD in general practice from the perspective of those who dropped out and to understand their reasons for dropping out. To the best of our knowledge, no previous qualitative study has focused on participants who withdrew from an eHealth self-management support intervention for adults with T2DM. Methods: A qualitative design based on telephone interviews was used to collect data. The sample comprised 12 adults with type 2 diabetes who dropped out of an eHealth intervention. Data were collected in 2016 and subjected to qualitative content analysis. Results: We identified one overall theme: “Losing motivation for intervention participation.” This theme was illustrated by four categories related to the participants’ experiences of the eHealth intervention: (1) frustrating technology, (2) perceiving the content as irrelevant and incomprehensible, (3) choosing other activities and perspectives, and (4) lacking face-to-face encounters. Conclusions: Our findings indicate that the eHealth intervention based on GSD without face-to-face encounters with nurses reduced participants’ motivation for engagement in the intervention. To maintain motivation, our study points to the importance of combining eHealth with regular face-to-face consultations. Our study also shows that the perceived benefit of the GSD eHealth intervention intertwined with choosing to focus on other matters in complex daily lives are critical aspects in motivation for such interventions. This indicates the importance of giving potential participants tailored information about the aim, the content, and the effort needed to remain engaged in complex interventions so that eligible participants are recruited. Finally, motivation for engagement in the eHealth intervention was influenced by the technology used in this study. It seems important to facilitate more user-friendly but high-security eHealth technology. Our findings have implications for improving the eHealth intervention and to inform researchers and health care providers who are organizing eHealth interventions focusing on self-management support in order to reduce dropout rates.

الملخص: عادة ما تكون المقالات ما قبل الطباعة بمثابة مقدمة أولية لأوراق تمت مراجعتها من قِبل النظراء ويتم وضعها على الفور تقريبا، باستثناء بعض الفحص السطحي، في مستودع وصول مفتوح للجمهور للسماح للمعلومات بالوصول إلى القراء بسرعة، والتغلب على الخمول المرتبط عادة بالمعالجة بطريقة المجلات التي تعتمد على مراجعة الأقران. بالنسبة للباحثين في بداية حياتهم المهنية الذين قد يكونون متحمسين للحصول على بعض التقدير لجهودهم، أو الرغبة في الحصول على مدخلات مفتوحة وعلنية حول عملهم، فإن النشر قبل الطباعة هو بالتأكيد خيار نشر مفيد. ومع ذلك، إذا لم يتم فحص البيانات والمعلومات المتعلقة بالصحة بعناية، فقد تشكل خطرا، وقد تعمل أيضا كمصدر لمعلومات مضللة عن الصحة العامة. تشير زيادة النمو والمنافسة بين خوادم ما قبل الطباعة، إلى جانب حجم هائل من المطبوعات المسبقة المتعلقة بـ كوفيد-١٩، وخاصة على خادم ما قبل الطباعة لعلم الأحياء، وخادم ما قبل الطباعة للعلوم الطبية، بالإضافة إلى تحديد الفهرسة التي يتم اختبارها الآن على موقع بوب ميد، إلى أن المطبوعات المسبقة يتم استخدامها بشكل متزايد في العلوم الطبية الحيوية. وهناك حاجة إلى سياسات أخلاقية أقوى وأكثر قوة لفحص المطبوعات المسبقة قبل نشرها للجمهور، وحتى إذا كان هذا يعني تأخيرا طفيفا في النشر، فقد يؤدي ذلك إلى زيادة ثقة الأكاديميين في هذا الشكل من المعلومات العلمية والتواصل. يجب تقديم سياسات أخلاقية واضحة وصارمة بشكل عاجل من قبل مجموعات الأخلاقيات مثل لجنة أخلاقيات النشر، واللجنة الدولية لمحرري المجلات الطبية للمجلات الأعضاء التي تسمح بنشر مقالات ما قبل الطباعة قبل مراجعة النظراء التقليدية. ستفيد الإرشادات الأخلاقية الصارمة التي تتعامل مع سوء السلوك على قدم المساواة في مقالات ما قبل الطباعة والأبحاث التي راجعها النظراء، ستفيد نزاهة النشر الأكاديمي. Abstract: Preprints are typically crude precursors of peer-reviewed papers that are placed almost immediately, save for some superficial screening, on an open-access repository to allow the information to reach readers quickly, circumventing the long-drawn process typically associated with processing in peer-reviewed journals. For early-career researchers who might be enthusiastic about obtaining some recognition for their efforts, or wanting open and public input about their work, preprints are certainly a useful publication choice. However, if health-related data and information have not been carefully scrutinised, they may pose a risk and may even serve as a source of public health misinformation. Surging growth and competition among preprint servers, coupled with a massive volume of COVID-19-related preprints, mainly on bioRxiv and medRxiv, as well as select indexing now being tested on PubMed, suggests that preprints are being increasingly used in the biomedical sciences. Stronger and more robust ethical policies are needed to screen preprints before they are released to the public, and even if this implies a slight delay in publication, it may increase academics' trust in this form of scientific information and communication. Clear and stringent ethical policies need to be urgently introduced by ethics groups such as COPE and the ICMJE, whose many member journals allow preprints to be posted before traditional peer review. Stringent ethical guidelines that treat misconduct equally in preprints and peer-reviewed papers will boost the integrity of academic publishing.

Computer Science researchers rely on peer-reviewed conferences to publish their work and to receive feedback. The impact of these peer-reviewed papers on researchers’ careers can hardly be overstated. Yet conference organizers can make inconsistent choices for their review process, even in the same subfield. These choices are rarely reviewed critically, and when they are, the emphasis centers on the effects on the technical program, not the authors. In particular, the effects of conference policies on author experience and diversity are still not well understood. To help address this knowledge gap, this paper presents a cross-sectional study of 56 conferences from one large subfield of computer science, namely computer systems. We introduce a large author survey (n = 918), representing 809 unique papers. The goal of this paper is to expose this data and present an initial analysis of its findings. We primarily focus on quantitative comparisons between different survey questions and comparisons to external information we collected on author demographics, conference policies, and paper statistics. Another focal point of this study is author diversity. We found poor balance in the gender and geographical distributions of authors, but a more balanced spread across sector, experience, and English proficiency. For the most part, women and nonnative English speakers exhibit no differences in their experience of the peer-review process, suggesting no specific evidence of bias against these accepted authors. We also found strong support for author rebuttal to reviewers’ comments, especially among students and less experienced researchers.

Advances in technologies (e.g. smartphones, wearables) have resulted in the concept of ‘self-tracking’, and the use of self-tracking technologies in physical activity (i.e. fitness tracking) is on the rise. For example, many people track and monitor their fitness-related metrics (e.g. steps walked, distance ran, and calories burned) to change their behaviours or keep themselves active. Despite the widespread application of self-tracking in fitness, relatively little is known about its drivers and outcomes. To address this gap, the current paper provides an overview of the literature (empirical papers) on self-tracking with a focus on the drivers and outcomes of fitness tracking behaviour and offers four important contributions. First, it identifies 19 drivers of fitness tracking technology usage. Second, it discusses four main outcomes of fitness tracking behaviour. Third, by drawing on the existing studies conducted across various fitness tracking technologies (e.g. fitness trackers, apps) and user groups (e.g. patients, seniors, and females), it provides valuable insights that can be generalisable to other settings (e.g. other types of users and fitness tracking products). Finally, the current paper provides important practical implications and addresses avenues for future research.

The development of navigation tools for people who are visually impaired had become an important concern in the research area of assistive technologies. This paper gives a comprehensive review of different articles published in the area of navigation solutions for people who are visually impaired. Unlike other review papers, this review considers major solutions that work in both the indoor or/and outdoor environments which are based on different technology. From the review, it became clear that the navigation systems proposed for the target users lack some core features that are quite important for independent navigation. Also, there can be instances in which humanitarian conditions also have to be considered in the navigation system design. Based on these findings, a set of recommendations are also given which can be considered in the future design of navigation systems for blind and visually impaired people.

Using peer assessment in the classroom to increase student engagement by actively involving the pupils in the assessment process has been practiced and researched for decades. In general, the literature suggests using peer review for project-based exercises. This paper analyzes the applicability of peer assessment to smaller exercises at secondary school level and makes recommendations for its use in computer science courses. Furthermore, a school pilot project introducing student-centered classrooms, called “learning office”, is described. Additionally, a concept for the implementation of peer assessment in such student-centered classrooms is outlined. We introduced two traditional secondary school classes consisting of a total of 57 students to the peer assessment method within the scope of the same software engineering course. The peer students assessed two of 13 exercises using the Moodle workshop activity. The students evaluated these two exercises using an anonymous online questionnaire. At the end of the course, they rated each of the 13 exercises regarding their learning motivation. Overall, the anonymous feedback on the peer review exercises was very positive. The students not only obtained more feedback, but also received it in a timelier manner compared to regular teacher assessment. The results of the overall rating of all 13 exercises revealed that the two peer reviewed exercises have been rated significantly better than the other eleven exercises assessed by the teacher. Evidence therefore suggests that peer review is a viable option for small- and medium-sized exercises in the context of computer science education at secondary school level under certain conditions, which we discuss in this paper.

With a tremendous growth in the number of scientific papers, researchers have to spend too much time and struggle to find the appropriate papers they are looking for. Local citation recommendation that provides a list of references based on a text segment could alleviate the problem. Most existing local citation recommendation approaches concentrate on how to narrow the semantic difference between the scientific papers’ and citation context’s text content, completely neglecting other information. Inspired by the successful use of the encoder-decoder framework in machine translation, we develop an attention-based encoder-decoder (AED) model for local citation recommendation. The proposed AED model integrates venue information and author information in attention mechanism and learns relations between variable-length texts of the two text objects, i.e., citation contexts and scientific papers. Specifically, we first construct an encoder to represent a citation context as a vector in a low-dimensional space; after that, we construct an attention mechanism integrating venue information and author information and use RNN to construct a decoder, then we map the decoder’s output into a softmax layer, and score the scientific papers. Finally, we select papers which have high scores and generate a recommended reference paper list. We conduct experiments on the DBLP and ACL Anthology Network (AAN) datasets, and the results illustrate that the performance of the proposed approach is better than the other three state-of-the-art approaches.

The recent academic literature contains a number of hypotheses, drivers, or explanations to reveal why electricity infrastructure isn't being developed within sub-Saharan Africa (SSA) in the 21st century. In this paper, we argue that this literature is misdirected, or at least incomplete, in how it approaches risk. We hypothesise that this lack of infrastructure development in the region reflects a dearth of investment due to the existence of excessive negative uncertainties or risks – as investment is a function of uncertainty and reward – but that the recent academic literature appears to not appreciate this. To make this argument, we chose a manageable sample of three African countries, which already had a notable body of academic literature concerning them: Kenya, Mozambique and Tanzania. Focusing on these countries, we then undertook a systematic review of 815 ‘peer reviewed’ papers published on the academic libraries of Scopus and/or the Web of Science on the topic of electricity, infrastructure, and risk over a five-year period to see how this literature evaluated the problem. Drawing from the most relevant 101 studies within that sample, we critically examine the methodological, conceptual, and empirical aspects of this literature.

Carnivores-livestock interactions cause human-wildlife conflicts worldwide. These interactions are present under a wide range of ecological and economic circumstances. This paper studies the relationship between predation mortality and natural mortality, when food availability affects natural mortality of the livestock. Semi-domestic Saami reindeer (Rangifer t. tarandus) herding in Norway is used as a case study. When predation affects reindeer density, food competition among reindeer changes, which changes weights and natural mortality in the reindeer population. An age-structured bio-economic model is presented, where this relationship is taken into account. While predation mortality may be additional to natural mortality in absence of food limitation, it can compensate for natural mortality in situations of food scarcity. Furthermore, due to density dependency in livestock weights, predation may increase the meat value of livestock. The paper analyzes how predation affects livestock production and economic performance under an optimized management scheme. One main result is that predation shifts the optimal harvesting composition towards calf harvesting and, therefore, the optimal stock composition among the different categories of animals. This contrasts findings in the existing bioeconomic literature. Furthermore, a changing harvesting pattern towards calf harvest is an important adjustment that highly limits the negative impact on profit of predation.

Peer-to-peer approaches refer to a participatory style of teaching and learning, which increasingly gain popularity as inclusive and participatory interventions to encourage changes towards more sustainable energy practices. However, this prominence has not been matched by evidence on the effectiveness of such approaches. By investigating the design and implementation of the peer-to-peer project useITsmartly, which centred on the topic of energy efficient and sustainable ICT use, this paper focuses on the effectiveness of this peer-to-peer approach as inclusive participatory intervention. Drawing on the environmental justice literature, it addresses particularly the second-level effectiveness, that is the impact peer-to-peer exercises have on the peer educators themselves in terms of capacity building and empowerment. The paper evaluates the preparation, recruitment, training and multiplication phases of the approach and concludes that it is essential to invest enough time and resources to truly recognize the peer educators and their lifestyles and practices, and enable them to participate in the peer education on their own terms. If not, lack of motivation and skills of the peer educators as well as too much focus on quantitative targets may compromise the actual purpose of the peer-to-peer approach and turn it into a top-down exercise.

Initial internet-based cognitive behavioral therapy (iCBT) programs for anxiety disorders in children and young people (CYP) have been developed and evaluated, however these have not yet been widely adopted in routine practice. The lack of guidance and formalized approaches to the development and dissemination of iCBT has arguably contributed to the difficulty in developing iCBT that is scalable and sustainable beyond academic evaluation and that can ultimately be adopted by healthcare providers. This paper presents a consensus statement and recommendations from a workshop of international experts in CYP anxiety and iCBT (#iCBTLorentz Workshop Group) on the development, evaluation, engagement and dissemination of iCBT for anxiety in CYP., Highlights • This paper gives a consensus statement and recommendations for research on iCBT for anxiety in youth • We discuss considerations regarding the development, evaluation, engagement and dissemination of iCBT for anxiety in youth • ICBT for youth anxiety should be initially evaluated with a RCT, while further iterations could use other research designs • Consistent measures relating to youth anxiety and iCBT usage should be employed, as well as precise reporting of iCBT programs • Dissemination of iCBT for youth anxiety into routine clinical practice should be considered from the start of development

It is a non‐trivial task for research‐centric courses in the software engineering curriculum to compete and engage students on the same level as the practical, software development courses. Practical software development courses and projects are inherently motivating to students, as they provide necessary elements such as agency, relatedness, and the strong sense of competence upon completing software engineering tasks. In contrast, reading research articles and technical white papers feels dry and non‐engaging. Nevertheless, a well‐balanced MSc programme curriculum covers both, learning through construction and practical courses as well as research courses. The main motivation for the development of game‐centric approaches to the research aspects of curriculum is to improve students’ interest and engagement with those courses. In this paper, we present the methodology and initial evaluations from three gamification strategies used in the Master's degree programme. These are: the game of reading and discussing research articles (GoRaD), the game of arguing and counter‐arguing, and combining research and practice. The paper presents our experimentation and initial evaluations of the use of those strategies, as well as plans for future development and enhancements. © 2018 The Authors. Computer Applications in Engineering Education Published by Wiley Periodicals Inc. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

Software startups have long been a significant driver in economic growth and innovation. The on-going failure of the major number of startups calls for a better understanding of state-of-the-practice of startup activities. Objective With a focus on engineering perspective, this study aims at identifying the change in focus of research area and thematic concepts operating startup research. A systematic mapping study on 74 primary papers (in which 27 papers are newly selected) from 1994 to 2017 was conducted with a comparison with findings from previous mapping studies. A classification schema was developed, and the primary studies were ranked according to their rigour. We discovered that most research has been conducted within the SWEBOK knowledge areas software engineering process, management, construction, design, and requirements, with the shift of focus towards process and management areas. We also provide an alternative classification for future startup research. We find that the rigour of the primary papers was assessed to be higher between 2013–2017 than that of 1994–2013. We also find an inconsistency of characterizing startups. Future work can focus on certain research themes, such as startup evolution models and human aspects, and consolidate the thematic concepts describing software startups. © 2018. This is the authors’ accepted and refereed manuscript to the article. Locked until 19.6.2020 due to copyright restrictions. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/

Peer review of scholarly papers is seen to be a critical step in the publication of high quality outputs in reputable journals. However, it appears that there are few incentives for researchers to agree to conduct suitable reviews in a timely fashion and in some cases unscrupulous practices are occurring as part of the production of academic research output. Innovations in internet-based technologies mean that there are ways in which some of the challenges can be addressed. In particular, this paper proposes a new currency system using the BlockChain as its basis that provides a number of solutions. Potential benefits and problems of using the technology are discussed in the paper and these will need further investigation should the idea develop further. Ultimately, the currency could be used as an alternative publication metric for authors, institutions and journals.

The peer review process is central to the scientific method, the advancement and spread of research, as well as crucial for individual careers. However, the single-blind review mode currently used in most Software Engineering (SE) venues is susceptible to apparent and hidden biases, since reviewers know the identity of authors. We perform a study on the benefits and costs that are associated with introducing double- blind review in SE venues. We surveyed the SE community’s opinion and interviewed experts on double-blind reviewing. Our results indicate that the costs, mostly logistic challenges and side effects, outnumber its benefits and mostly regard difficulty for authors in blinding papers, for reviewers in understanding the increment with respect to previous work from the same authors, and for organizers to manage a complex transition. While the surveyed community largely consents on the costs of DBR, only less than one-third disagree with a switch to DBR for SE journals, all SE conferences, and, in particular, ICSE; the analysis of a survey with authors of submitted papers at ICSE 2016 run by the program chairs of that edition corroborates our result.

In recent years however, more re-identification attacks have been attempted by researchers elsewhere in the world.Further findings are that most research in this area has been conducted on Global datasets by American researchers. The publication of increasing amounts of anonymised open source data has resulted in a worryingly rising number of successful re-identification attacks. This has a number of privacy and security implications both on an individual and corporate level.This paper uses a systematic literature review to investigate the depth and extent of this problem as reported in peer reviewed literature. Using a detailed protocol,seven research portals were explored, 10,873 database entries were searched, from which a subset of 220 papers were selected for further review. From this total, 55 papers were selected as being within scope and to be included in the final review.The main review findings are that 72.7% of all successful re-identification attacks have taken place since 2009. Most attacks use multiple datasets. The majority of them have taken place on global datasets such as social networking data, and have been conducted by US based researchers. Furthermore, the number of datasets can be used as an attribute.Because privacy breaches have security, policy and legal implications (e.g. data protection, Safe Harbor etc.), the work highlights the need for new and improved anonymisation techniques or indeed, a fresh approach to open source publishing.

Published version. Source at http://dx.doi.org/10.1016/j.procs.2016.09.039 The implementation of Electronic Health Records (EHRs) in developing countries is considered a means for improving data quality and high quality care. However, existing research, indicate that EHRs have recorded greater quantity of bad data instead of improving the quality of data. The reasons for this is not exactly clear. Accordingly, this paper takes a broader socio-technical approach to explore the issues in more detail. The paper explores the relationship between EHRs and quality at the Pentecost Hospital Madina-Ghana by using an interpretative research approach. The result of our study indicates that the EHRs introduced at the hospital have so far had limited effect on data quality and that context-related challenges are the major pitfalls identified in the study. Based on a socio- technical approach the paper discusses the need to; consider users and technology as intertwined, how technology changes practice and how it formalizes roles and responsibilities in the process, why it requires collaborative work and why realistic goals as opposed to exaggerated expectation

Source: doi: 10.1109/ACCESS.2016.2599851 Collecting data via a questionnaire and analyzing them while preserving respondents' privacy may increase the number of respondents and the truthfulness of their responses. It may also reduce the systematic differences between respondents and non-respondents. In this paper, we propose a privacy- preserving method for collecting and analyzing survey responses using secure multi-party computation. The method is secure under the semi-honest adversarial model. The proposed method computes a wide variety of statistics. Total and stratified statistical counts are computed using the secure protocols developed in this paper. Then, additional statistics, such as a contingency table, a chi-square test, an odds ratio, and logistic regression, are computed within the R statistical environment using the statistical counts as building blocks. The method was evaluated on a questionnaire data set of 3158 respondents sampled for a medical study and simulated questionnaire data sets of up to 50 000 respondents. The computation time for the statistical analyses linearly scales as the number of respondents increases. The results show that the method is efficient and scalable for practical use. It can also be used for other applications in which categorical data are collected.

In this paper, we investigated how internationally mobile students from Norway diverge from students in Norway regarding social background, grades obtained at upper secondary school, and motivation to study. Data from two comparable surveys were used, one relating to students abroad and one relating to domestic students. Results showed that, on average, mobile students were of higher social origin than domestic students, but this did not apply across all fields. In some subject fields, mobile students had higher grades than domestic students, while they were lower in others. Mobile students clearly demonstrated higher motivation than domestic students, even when controlling for subject field and background variables. In sum, we found that mobile students constitute a select group in several ways, most prominently regarding study motivation. This suggests that mobile students potentially represent a positive contribution to the learning environment in more ways than bringing diversity in cultural background.

The objective of exposing girls to Computer Science as a career option has led to research directed towards gaming activities for girls. These activities include both game play and game design. Research about gaming activities for increasing girls’ interest in computer science has gained much attention over the past few years and has resulted in a number of contributions. We follow up with an overview of the status of research through a Systematic Literature Review. We investigate the relation between the various game playing or designing activities and their impact on girls’ perception of Computer Science as a career choice. We further present the design consideration for the games and related activities to potentially improve the perception of girls towards a Computer Science career. The applied method is a Systematic Literature Review through which we investigate which contributions were made, which knowledge areas were most explored, and which research facets have been used. We identify 25 papers to distill a common understanding of the state-of-the-art. Specifically, we investigate the effects that the game play/design activities had on girls’ perception about Computer Science; and what are the key design factors to be kept in mind while designing a serious game to improve girls’ perception about Computer Science. The results of this systematic literature review show that game playing or designing could indeed improve how girls perceive having a career in CS. The key aspects that such activities require are personalizing, opportunity for collaboration and the presence of a female lead character, This work has been done during the tenure of an ERCIM Alain Bensoussan fellowship

This paper explores whether efficacy beliefs can alter the relationship between worry about climate change and personal energy-saving behaviors, controlling for climate change beliefs and socio-demographics. For this purpose, we used data from 23 countries that participated in the European Social Survey Round 8 (N = 44 387). Worry about climate change, personal efficacy, personal outcome expectancy, and collective outcome expectancy were each associated with personal energy-saving behaviors concerning either energy curtailment or energy efficiency. The results further show that outcome expectancies moderate the association between worry about climate change and both types of energy behaviors. Worry was more strongly related to energy curtailment behaviors among those with high levels of personal and collective outcome expectancy. A similar pattern was found for energy efficiency behaviors, which were more strongly predicted by worry about climate change when combined with high levels of collective outcome expectancy. These findings are relevant for climate change communication, especially informational campaigns aiming to lower overall household energy use. publishedVersion

Scientific peer review is pivotal to maintain quality standards for academic publication. The effectiveness of the reviewing process is currently being challenged by the rapid increase of paper submissions in various conferences. Those venues need to recruit a large number of reviewers of different levels of expertise and background. The submitted reviews often do not meet the conformity standards of the conferences. Such a situation poses an ever-bigger burden on the meta-reviewers when trying to reach a final decision. In this work, we propose a human-AI approach that estimates the conformity of reviews to the conference standards. Specifically, we ask peers to grade each other’s reviews anonymously with respect to important criteria of review conformity such as sufficient justification and objectivity. We introduce a Bayesian framework that learns the conformity of reviews from both the peer grading process, historical reviews and decisions of a conference, while taking into account grading reliability. Our approach helps meta-reviewers easily identify reviews that require clarification and detect submissions requiring discussions while not inducing additional overhead from reviewers. Through a large-scale crowdsourced study where crowd workers are recruited as graders, we show that the proposed approach outperforms machine learning or review grades alone and that it can be easily integrated into existing peer review systems.

© 2020, Springer-Verlag London Ltd., part of Springer Nature. Among the variety of the available requirements elicitation techniques, interviews are the most commonly used. Performing effective interviews is challenging, especially for students and novice analysts, since interviews’ success depends largely on soft skills and experience. Despite their diffusion and their challenging nature, when it comes to requirements engineering education and training (REET), limited resources and few well-founded pedagogical approaches are available to allow students to acquire and improve their skills as interviewers. To overcome this limitation, this paper presents two pedagogical approaches, namely SaPeer and ReverseSaPeer. SaPeer uses role-playing, peer review and self-assessment to enable students to experience first-hand the difficulties related to the interviewing process, reflect on their mistakes, and improve their interview skills by practice and analysis. ReverseSaPeer builds on the first approach and includes a role reversal activity in which participants play the role of a customer interviewed by a competent interviewer. We evaluate the effectiveness of SaPeer through a controlled quasi-experiment, which shows that the proposed approach significantly reduces the amount of mistakes made by the participants and that it is perceived as useful and easy by the participants. ReverseSaPeer and the impact of role reversal are analyzed through a thematic analysis of the participant’s reflections. The analysis shows that not only the students perceive the analysis as beneficial, but also that they have emotional involvement in learning. This work contributes to the body of knowledge of REET with two methods, quantitative and qualitative evaluated, respectively. Furthermore, we share the pedagogical material used, to enable other educators to apply and possibly tailor the approach.

The coronavirus disease 2019 (COVID-19) pandemic has brought changes to the way medical care is delivered to keep health workers safe while simultaneously managing available resources. The well-being of patients and healthcare workers is crucial and has become a topic of debate as the world faces adjusts to the COVID-19 pandemic. Therefore, there is need to consider innovative methods of delivering medical care. Telehealth and digital health care which is the provision of medical care via Information Communication Technology (ICT) with highspeed telecommunications systems, has increasingly becoming popular in providing medical care services can be adopted to reduce infections during quarantine and social distancing practices. Specifically, by means of document and literature review this paper discusses the role of telehealth and digital care solutions, types and application of telehealth, and current policies for COVID-19. More importantly, findings from the article present the human, infrastructure, and institutional determinants that influence the adoption of telehealth and digital care solutions during the pandemic. The findings discuss how telehealth and digital care technologies can benefit the society. This study provides implications to informs medical staffs on the potential of digital technologies to provide support during and after the pandemic.

[Excerpt] By March 2020, while the entire planet Earth was entering a dark time of pandemia, we communicated in this editorial the trends of J Optom in different bibliometric indices including Impact Factor, SCImago Journal Rank ing, H-index, CiteScore and Source Normalized Impact per Paper. (1) More recently the CiteScore has been reviewed by Else vier to mitigate some short-term trends and J Optom raised even further in its score from 1.65 to 2.3.2 Accord ing to Scoups, this new calculation enforces credibility of the score by only considering peer-review publications, considering a longer window of 4 years instead of 3 and considering the more recent citations in the year of calculation.3 This is only an aspect of the impact of the journal that has increased steadily as it continues to con solidate through different milestones achieved over the last years (4). [...], (undefined)

In this paper, the passing ability of football players is determined by building three generalized additive mixed models that each explains a different aspect of a pass’ success: difficulty, risk and potential. The models are built on data from the 2014–2016 seasons of the Norwegian top division Eliteserien, and their predictive power is tested on the 2017 season. The results provide insight into the factors affecting the success of a pass in Eliteserien. These include the location of the pass, the relationship to previous passes and to situations such as throw-ins, corners, free kicks or tackles, as well as conditions specific to the Eliteserien, such as the time of season and the ground surface type. Finally, the key pass makers in the league are identified.

Personalization of the e-learning systems according to the learner’s needs and knowledge level presents the key element in a learning process. E-learning systems with personalized recommendations should adapt the learning experience according to the goals of the individual learner. Aiming to facilitate personalization of a learning content, various kinds of techniques can be applied. Collaborative and social tagging techniques could be useful for enhancing recommendation of learning resources. In this paper, we analyze the suitability of different techniques for applying tag-based recommendations in e-learning environments. The most appropriate model ranking, based on tensor factorization technique, has been modified to gain the most efficient recommendation results. We propose reducing tag space with clustering technique based on learning style model, in order to improve execution time and decrease memory requirements, while preserving the quality of the recommendations. Such reduced model for providing tag-based recommendations has been used and evaluated in a programming tutoring system. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Serious and fatal accidents happen on construction sites every year. However, earlier research indicate that the root of the accidents can often be found in the early phases of the project process. In this paper, we examine what occurs in the early phases of project management in construction that can be harmful to health and safety in the construction phase. The investigation focuses on two main research questions: 1) can health and safety in the construction phase be improved during the early phases of project management, and, if so, 2) what are the main challenges of health and safety in the early phases of project management that need to be addressed in order to do so? The data presented is collected by interviewing regional safety representatives in Norway. They point to three main challenges to health and safety in the early phases of construction projects: 1) lack of competence, 2) lack of prioritization, and 3) lack of consequence. In conclusion, we suggest that educational institutions, construction clients and public authorities all need to play their part to improve the situation.

Coordinating research objectives concurrently with product development and engineering is a challenge in student-run CubeSat projects. The literature review from several universities and the International Council of Systems Engineering (INCOSE) Space Systems Working Group (SSWG) all acknowledge the need for a better methodology. This paper describes findings from a university CubeSat exploratory case study related to team management, reviews and design. Introducing Systems Engineering (SE) tools such as formalized reviews, A3 reports, systemigrams and N2 dependency maps have aided the development process. This was evident through faster development iterations and fewer design confusions. Results show that relocation into a common space based on recommendations from Concurrent Engineering (CE) has improved overall communication and team work. © 2019 The Authors. Published by Elsevier B.V.This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/)

This is the peer reviewed version which has been published in final form at [DOI]. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions., Software testing is crucial in continuous integration (CI). Ideally, at every commit, all the test cases should be executed, and moreover, new test cases should be generated for the new source code. This is especially true in a Continuous Test Generation (CTG) environment, where the automatic generation of test cases is integrated into the continuous integration pipeline. In this context, developers want to achieve a certain minimum level of coverage for every software build. However, executing all the test cases and, moreover, generating new ones for all the classes at every commit is not feasible. As a consequence, developers have to select which subset of classes has to be tested and/or targeted by test‐case generation. We argue that knowing a priori the branch coverage that can be achieved with test‐data generation tools can help developers into taking informed decision about those issues. In this paper, we investigate the possibility to use source‐code metrics to predict the coverage achieved by test‐data generation tools. We use four different categories of source‐code features and assess the prediction on a large data set involving more than 3'000 Java classes. We compare different machine learning algorithms and conduct a fine‐grained feature analysis aimed at investigating the factors that most impact the prediction accuracy. Moreover, we extend our investigation to four different search budgets. Our evaluation shows that the best model achieves an average 0.15 and 0.21 MAE on nested cross‐validation over the different budgets, respectively, on EVOSUITE and RANDOOP. Finally, the discussion of the results demonstrate the relevance of coupling‐related features for the prediction accuracy.

This paper describes Readersourcing 2.0, an ecosystem providing an implementation of the Readersourcing approach. Readersourcing is proposed as an alternative to the standard peer review activity that aims to exploit the otherwise lost opinions of readers. To achieve this, Readersourcing 2.0 implements two different models based on the so-called codetermination algorithms. We describe the requirements, present the overall architecture, and show how the end-user can interact with the system. Readersourcing 2.0 will be used in the future to study also other topics, like the idea of sheperding the users to achieve a better quality of the reviews and the differences between a review activity carried out with a single-blind or a double-blind approach., Preprint for the IRCDL 2019 conference

Enterprise software needs to be customizable, and the customization needs from a customer are often beyond what the software vendor can predict in advance. In the on-premises era, customers do deep customizations beyond vendor's prediction by directly modifying the vendor's source code and then build and operate it on their own premises. When enterprise software is moving to cloud-based multi-tenant SaaS (Software as a Service), it is no longer possible for customers to directly modify the vendor's source code, because the same instance of code is shared by multiple customers at runtime. Therefore, the question is whether it is still possible to do deep customization on multi-tenant SaaS. In this paper, we give an answer to this question with a novel architecture style to realize deep customization of SaaS using intrusive microservices. We evaluate the approach on an open source online commercial system, and discuss the further research questions to make deep customization applicable in practice. Deep customization of multi-tenant SaaS using intrusive microservices

The subject of this study was the product development project creating a new innovative proof-of-concept (POC) prototype device that could control a connected industrial overhead crane in order to perform automatic or semi-automatic high precision lifts within a limited time frame. The development work focused on innovating a new measuring concept, which was parallel to finding suitable sensors for the application. Furthermore, the project resulted in a closed loop control system with Industrial Internet connected sensors and a user interface for factory workers. The prototyping journey is depicted to illustrate the decisions made during the product development project to contribute to both the pragmatic and the process discussion in the field of Industrial Internet. The purpose of this research was to explore and generate hypotheses for how new applications should be developed for heavy industry connected devices. The research question is: what are the implications of applying agile product development methods, such as Wayfaring, to heavy industrial machinery and Industrial Internet -based problems? The methodologies used in this paper, in addition to developing the device, are case study research and hypotheses generated from case studies. The hypotheses generated include that it is also possible to prototype large size connected machinery with low-cost and in a short time, and investment decisions for heavy Industrial Internet products become easier with concrete data from proof-of-concept prototypes by creating knowledge about the investment risk and the value proposition.

This is the peer reviewed version of the following article: “ Domènech, B., Ferrer, L. and Pastor, R. (201o) Comparison of various approaches to design wind-PV rural electrification projects in remote areas of developing countries. Wiley Interdisciplinary Reviews-Energy and Environment, Desember which has been published in final form at [doi: 10.1002/wene.332]. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving." Nowadays, around 1.1 billion people in rural and remote areas of developing countries remain without electricity. Stand-alone projects that combine the wind and photovoltaic generation technologies as well as microgrids and individual supplies for the distribution network are an adequate strategy to reach such isolated regions. However, the design of electrification projects is complex, having to define the best combination of generation and distribution technologies, under a challenging social context and tight technoeconomic resources. In order to ease decision-making, several tools have been developed in the literature and are here reviewed, grouped into three main categories: optimization processes, aiming to minimize project costs subject to technical constraints, through exact or heuristic algorithms; multicriteria processes, using different methods to select the best among a set of predefined scenarios according to economic, technical, social, and environmental criteria; and systematized tools, that have been developed to provide user-friendly interface for their larger dissemination in different regions and contexts. Hence, this paper aims to provide researchers and practitioners an analysis of the advantages and limitations of approaches used over the last decade when addressing the designing of wind and/or photovoltaic electrification projects for extremely poor and isolated areas in developing countries, as well as some areas for further research.

This is a report on the ninth edition of the Conference and Labs of the Evaluation Forum (CLEF 2018), held in early September 2018, in Avignon, France. CLEF was a four day event combining a Conference and an Evaluation Forum. The Conference featured keynotes by Nicholas Belkin, Julio Gonzalo, and Gabriella Pasi, and presentation of 29 peer reviewed research papers covering a wide range of topics in addition to many posters. The Evaluation Forum consisted to ten Labs: CENTRE, CheckThat, DynSe, eRisk, eHealth, ImageCLEF, LifeCLEF, Cultural Microblog Contextualization, PAN, and PIR-CLEF, addressing a wide range of tasks, media, languages, and ways to go beyond standard test collections.

This paper engages with social justice in engineering education based on pedagogical tools aimed at improving analytical reading, writing and critical reflection in course activities. The authors conceptualizes analytical thinking, critical reflection, and web-based peer review as tools for transformation of student learning, and apply these tools as instructions to engineering students studying city planning in Stockholm, Sweden. Students were asked to use the tools to critically analyze the role of national identities, social vis-à-vis technological engineering, and what politics have shaped Swedish society. In studying these aspects of city planning, the authors argue for a shift in attention toward the practices of engineers’ work around issues of social justice, an argument reinforced by the results of textual analysis of student essay reflections on social justice in city planning. The results are a wide range of themes of critical reflection made by students arising from course activities. These included balancing social and environmental justice, like suburban segregation, planning ideals and, in some cases, challenges for the planning profession. We argue that these are valuable lessons for engineers, which can be achieved by combining practical experiences of planning practices with tools for advancing critical and analytical skills of engineering students. By analyzing engineering students’ views on solutions and challenges of addressing social justice in practice, we can improve our understanding of the engineering skills required to work with social justice. In this way, the study complements discussion and critiques of the relationships between society and engineering outlined in the rhetoric of engineering grand challenges, and contributes by discussing new roles for engineers in facing day-to-day challenges working with social justice.

The Wireless Body Area Network (WBAN) has gained popularity as a new technology for e-Health, and is considered as one of the key research areas in computer science and healthcare applications. WBAN collects patients’ data, monitors constantly their physiological parameters, using small implantable or wearable sensors, and communicates these data using wireless communication techniques in short range. WBAN is playing a huge role in improving the quality of healthcare. Still, due to sensitive and concurrent nature of e-Heath systems, current research has showed that designers must take into considerations the security and privacy protection of the data collected by a WBAN to safeguard patients from different exploits or malicious attacks, since e-Health technologies are increasingly connected to the Internet via wireless communications. In this paper we outline the most important security requirements for WBANs. Furthermore, we discuss key security threats to avoid. Finally, we conclude with a summary of security mechanisms to follow that address security and privacy concerns of WBANs, and need to be explored in an increasingly connected healthcare world. This Article is brought to you for free and open access by the Publication and Journals at UBT Knowledge Center.