The Office Jungle: Exploring Unusual Ways of Working through Bodily Experimentations

in DIS 2021 - Proceedings of the 2021 ACM Designing Interactive Systems Conference: Nowhere and Everywhere (2021)

Modern office environments foster sitting, a major public health risk, with physical inactivity being the fourth cause of death worldwide. This provocative pictorial presents the design explorations and ... [more ▼]

Modern office environments foster sitting, a major public health risk, with physical inactivity being the fourth cause of death worldwide. This provocative pictorial presents the design explorations and bodily experimentations culminating in The Office Jungle, a critical and speculative redesign of the office environment that encourages physical activity by embracing wildness. The Office Jungle is a design exemplar of a "wild"office space presented as a suspended geodesic structure. It is built to experienc e how our office environment and our behaviour at work affect each other. We advocate that bringing wildness into office spaces will create more durable office environments that foster movement. With this pictorial, we aim to spark discussion amongst designers to think in new ways and to consider new opportunities to design for workplaces that integrate physical activity with work. © 2021 Owner/Author. [less ▲]

The Hubs: Design Insights for Walking Meeting Technology

in Lecture Notes in Computer Science (2021), 12935 LNCS

As an active form of meeting, walking meetings can be beneficial for office workers who often have a sedentary work routine. Despite their substantial benefits in terms of health, social interactions, and ... [more ▼]

As an active form of meeting, walking meetings can be beneficial for office workers who often have a sedentary work routine. Despite their substantial benefits in terms of health, social interactions, and creativity, walking meetings are not yet widely adopted. Some key barriers limiting their social acceptance and wider adoption, for instance, the difficulty to present files or take notes, might be addressed by technology. Using the Hubs - a network of stand-up meeting stations - as a design exemplar, we conducted a scenario-based survey (N = 186) to provide insights into how technological solutions can support the practice of walking meetings. Focusing on the size of the group and type of meetings, we identify scenarios of use and discuss design implications for the development of future technologies and service design components to support walking meetings. © 2021, IFIP International Federation for Information Processing. [less ▲]

Enhanced second-harmonic generation by single metal–insulator multilayered nanocavities with axial symmetry resonating in the near-infrared

in Proceedings of SPIE: The International Society for Optical Engineering (2021), 11770

We report efficient second-harmonic emission by single multilayer metal–dielectric nanocavities. Engineering the intrinsic interface-induced symmetry breaking by resonant optical absorption design, allows ... [more ▼]

We report efficient second-harmonic emission by single multilayer metal–dielectric nanocavities. Engineering the intrinsic interface-induced symmetry breaking by resonant optical absorption design, allows to achieve almost two orders of magnitude higher second-harmonic generation efficiency compared to gold nanostructures with the same geometry. We estimate a second-order nonlinear susceptibility of the order of 1 pm/V, which is comparable to widely used nonlinear crystals. We envision that our system, which combines the advantages of both plasmonic and dielectric materials, might enable the realization of composite nano-systems for an efficient multi-purpose manipulation of nonlinear optical processes at the nanoscale. [less ▲]

Modeling Object’s Affordances via Reward Functions

in IEEE International Conference on Systems, Man, and Cybernetics (2021)

SPACECRAFT RECOGNITION LEVERAGING KNOWLEDGE OF SPACE ENVIRONMENT: SIMULATOR, DATASET, COMPETITION DESIGN, AND ANALYSIS

in 2021 IEEE International Conference on Image Processing (ICIP) (2021)

The role of altered cognitive processing of bodily sensations in pain: A need for innovative and integrative research Conference Paper

in Canadian Journal of Pain (2021)

Exploring the Design Space of InterActive Urban Environments: Triggering physical activity through embedded technology

in DIS 2021 - Proceedings of the 2021 ACM Designing Interactive Systems Conference: Nowhere and Everywhere (2021)

Promoting healthy lifestyles is an essential endeavor for public health. The design of active urban environments can be an effective medium to nudge people into moving. With technology increasingly ... [more ▼]

Promoting healthy lifestyles is an essential endeavor for public health. The design of active urban environments can be an effective medium to nudge people into moving. With technology increasingly integrated into our daily lives, designers have access to more data than ever. In this pictorial, we explore the design space of interActive environments (contraction of ginteractive' and gactive'); places designed to increase the physical activity of users or passers-by through the use of interactive technology. Through sketches, a benchmark of existing concepts and an analysis of designed artefacts, we map the different intervention levels, interaction modalities, behavior change strategies and technological opportunities to design such interActive environments. With this work, we invite the community to consider how digital technology can help understand and shape human behavior in urban environments, and provide inspiration to designers and practitioners. © 2021 Owner/Author. [less ▲]

Short-Term Fluctuation of Subjective Age and its Correlates: An Ecological Momentary Assessment of Older Adults

in Innovation in Aging (2021), 5(Supplement_1), 287-287

We examined short-term fluctuations of subjective age with data obtained from 123 young-old (Mage = 67.19 years) and 47 old-old adults (Mage = 86.59 years) who reported their momentary subjective age six ... [more ▼]

We examined short-term fluctuations of subjective age with data obtained from 123 young-old (Mage = 67.19 years) and 47 old-old adults (Mage = 86.59 years) who reported their momentary subjective age six times a day over seven consecutive days as they were going about their everyday lives. Participants felt younger on a large majority of occasions, and 25% of the total variability in subjective age could be attributed to within-person variation. Those with younger trait subjective ages exhibited larger moment-to-moment variation, while chronological age did not impact variability. Furthermore, we investigated relationships between within-day fluctuations of subjective age and daily cortisol fluctuations. Our findings extend the literature on subjective age by showing that how old people feel can vary on a momentary basis, that state and trait components of subjective age are related, and that fluctuations in subjective age are related to biomarkers of stress. [less ▲]

What is problematic about binary questions on gender in health surveys – a missing answer analysis

in Cogent Medicine (2020, December 04)

Background: In many studies, participants who do not state their gender are excluded from the analysis. This may be appropriate if they do not answer the questionnaire seriously. However, some ... [more ▼]

Background: In many studies, participants who do not state their gender are excluded from the analysis. This may be appropriate if they do not answer the questionnaire seriously. However, some participants may have understandable reasons for not reporting their gender, e.g. questioning their gender identity. Research question: How many students and which students do not answer the question on gender? Methods: We analyzed data of the Health Behaviour in School-aged Children study from Ireland, France, Hungary, Scotland, Belgium (Flemish) and Luxembourg (n = 40,053). To explore the reasons for non-response, we divided the participants into 3 groups: 1. Responders answered both socio- demographic questions (age and gender) 2. age non-responders did not answer the question on age. 3. Gender non-responders answered the question on age, but not the one on gender. Results: 311 out of 40,053 (0.8%) pupils aged 11–18 did not report their gender. About 40% of them did not answer the age question either. However, the other 60% belong to the group of gender non-responders and this group is disadvantaged compared to responders: they report lower self-rated health, more health complaints, less family support and more substance use (alcohol, tobacco, cannabis). 1.9% of pupils did not answer the question about age. These age non-responders answered the questionnaire more selectively overall and skipped more questions. Conclusion: The data suggest that the reasons for age non-response and gender non-response are different. For age non-responders, the fear of de-anonymization seems to be the reason for not indicating their age. Not answering the question on gender is rare. If the participants answered the question on age, but not the question on gender, then the variable gender is missing not at random. The health problems of gender non-responders correspond to the health problems of gender non-conforming adolescents. Thus, the question arises if the group of gender non-responders should be included in the analysis and if the question on gender should be asked differently in the future [less ▲]

Sensitivity Analysis on Regularity Based Driver Advisory Systems

in 2020 IEEE 23rd International Conference on Intelligent Transportation Systems (ITSC) (2020, December)

A cascading Kalman filtering framework for real-time urban network flow estimation

in 2020 IEEE 23rd International Conference on Intelligent Transportation Systems (ITSC) (2020, December)

Reduction of temperature effects for bridge health monitoring

in Eccomas Proceedia (2020, November 23)

Structural health monitoring of concrete bridges can be achieved by tracking static load-testing results or dynamic properties as for example eigenfrequencies. Deviations from a healthy reference state ... [more ▼]

Structural health monitoring of concrete bridges can be achieved by tracking static load-testing results or dynamic properties as for example eigenfrequencies. Deviations from a healthy reference state can be used as damage indicators and even more, help to localize zones of stiffness reduction, i.e. cracking. However, outdoor temperature effects also lead to changes of monitored physical characteristics in the same order of magnitude as damage. Hence, temperature effects need to be removed prior to any condition analysis. The present paper presents a new two-step approach by applying physical compensation first, before using a statistical method based of Principal Component Analysis (PCA) or more exactly on principal vectors and singular values. This technique is here applied to eigenfrequencies, first of a new bridge without damage, but with extreme temperature variation due to thick asphalt layer and special bearing constraints, thus showing strong sensitivity along seasonal temperatures in the intact state. The second object is the Z24 Bridge in Switzerland, which is well documented in literature and where artificial damage was applied prior to demolition. The proposed techniques allow removing noise and temperature effects in a coherent and efficient way. The corrected measurement data can then be used in subsequent steps for its definite purpose, i.e. detection and localization of damage for instance by updating a numerical finite element model which allows assessing a stiffness loss. [less ▲]

Create Digital Games for Education: Game Design as a Teaching Methodology

in Proceedings of ICERI 2020 (2020, November 09)

Besides the pure application of serious games as tools for knowledge transfer, a further trend has been observed in the last few years: The creation of games as an opportunity to gain practical experience ... [more ▼]

Besides the pure application of serious games as tools for knowledge transfer, a further trend has been observed in the last few years: The creation of games as an opportunity to gain practical experience and thereby also build up valuable knowledge. In this context several approaches are possible, such as using paper prototyping, applying Game-Maker tools like Scratch, RPG-Maker, Construct 3 or Game Maker Studio 2, next to the option to use actual game engines like Unity. This contribution aims to discuss the possibility of creating games in a very specific, predefined genre using Game Maker tools that have been especially developed for use in an educational context and therefore offer didactic guidance. The Game Creator tool which was developed as part of the Erasmus+ project Create Digital Games for Education (CDG4E) is presented in more depth. With this tool you can create decision card games inspired by the mobile game bestseller "Reigns". Within the project, the consortium created educational games in different areas such as fake news prevention and STEM education. In addition to these ready-made games, another focus was placed on using the tool itself as a teaching technique, for example to create games on a specific topic with school classes or within youth work, but also as an instrument for setting up dedicated "game jams". This contribution reports on the advantages and drawbacks of creating the tool itself by analyzing qualitative and quantitative data gathered during the iterative design process of the Game Creator. [less ▲]

Locust: Highly Concurrent DHT Experimentation Framework for Security Evaluations

in Proceedings of ICPS ICCNS 2020 (2020, November)

Distributed Hash Table (DHT) protocols, such as Kademlia, provide a decentralized key-value lookup which is nowadays integrated into a wide variety of applications, such as Ethereum, InterPlanetary File ... [more ▼]

Distributed Hash Table (DHT) protocols, such as Kademlia, provide a decentralized key-value lookup which is nowadays integrated into a wide variety of applications, such as Ethereum, InterPlanetary File System (IPFS), and BitTorrent. However, many security issues in DHT protocols have not been solved yet. DHT networks are typically evaluated using mathematical models or simulations, often abstracting away from artefacts that can be relevant for security and/or performance. Experiments capturing these artefacts are typically run with too few nodes. In this paper, we provide Locust, a novel highly concurrent DHT experimentation framework written in Elixir, which is designed for security evaluations. This framework allows running experiments with a full DHT implementation and around 4,000 nodes on a single machine including an adjustable churn rate; thus yielding a favourable trade-off between the number of analysed nodes and being realistic. We evaluate our framework in terms of memory consumption, processing power, and network traffic. [less ▲]

International Law and the European Court of Justice: The Politics of Avoiding History

in Journal of the History of International Law (2020, October 21), 22(2-3), 446-472

Using the example of the European Court of Justice (ECJ), this article addresses the lack of historical contextualization which is prevalent in most general accounts of EU law and EU institutions. It ... [more ▼]

Using the example of the European Court of Justice (ECJ), this article addresses the lack of historical contextualization which is prevalent in most general accounts of EU law and EU institutions. It argues that this narrative is the result of a tradition established by the founders of the discipline. For these early ‘Euro-lawyers’, distinguishing the practice of European institutions from earlier international institutions had important political implications. This was especially true with regard to the ECJ. By providing a selective and partly decontextualized narrative of this court and describing it as largely unprecedented in international law, early Euro-lawyers were not only able to bolster the ‘supranational’ and ‘sui generis’ character of their nascent discipline. They were also able to avoid comparisons between the ECJ and prior international courts and tribunals whose similarly wide-ranging powers and integrated nature had been considered as politically problematic. [less ▲]

Measuring the Contextual Dimension of User Experience: Development of the User Experience Context Scale (UXCS)

in Proceedings of the 11th Nordic Conference on Human-Computer Interaction: Shaping Experiences, Shaping Society (2020, October)

The context of use has been highlighted for a long time as being a key factor impacting User Experience (UX). Yet current UX evaluation tools, especially questionnaires, rarely encompass an explicit ... [more ▼]

The context of use has been highlighted for a long time as being a key factor impacting User Experience (UX). Yet current UX evaluation tools, especially questionnaires, rarely encompass an explicit investigation of the context. With the ever-growing trend for mobile products and ubiquitous computing, the absence of a dedicated measurement tool becomes critical. Based on a review of relevant literature and a fine-grained categorization of contextual factors, we developed the UX Context Scale (UXCS), a 30-items instrument allowing for a measure of context properties, as perceived by the user. We report on the development of the scale and present a first validation study (N = 137). A principal component analysis on the subjective items reveals a 6-components structure: Physical Context, Social Context, Internal Context, Perceived Resources, Task Context, and Temporal Context. Reliability of each subscale is high and further analyses confirm the relevance of this tool for UX evaluation. [less ▲]

SDR IMPLEMENTATION OF A TESTBED FOR SYNCHRONIZATION OF COHERENT DISTRIBUTED REMOTE SENSING SYSTEMS

in Proceedings of IEEE International Geoscience and Remote Sensing Symposium 2020 (2020, September 26)

Remote Sensing from distributed platforms has become attractive for the community in the last years. Phase, frequency, and time synchronization are a crucial requirement for many such applications as ... [more ▼]

Remote Sensing from distributed platforms has become attractive for the community in the last years. Phase, frequency, and time synchronization are a crucial requirement for many such applications as multi-static remote sensing and also for distributed beamforming for communications. The literature on the field is extensive, and in some cases, the requirements an complexity of the proposed synchronization solution may surpass the ones set by the application itself. Moreover, the synchronization solution becomes even more challenging when the nodes are flying or hovering on aerial or space platforms. In this work, we discuss the synchronization considerations for the implementation of distributed remote sensing applications. The general framework considered is based on a distributed collection of autonomous nodes that synchronize their clocks with a common reference using inter-satellite links. For this purpose, we implement a synchronization link between two nodes operating in a full-duplex fashion. The experimental testbed uses commercially available SDR platforms to emulate two satellites, two targets, and the communication channel. The proposal is evaluated considering phase and frequency errors for different system parameters. [less ▲]

Automatic Detection of Nigrosome Degeneration in Susceptibility-Weighted MRI for Computer-Aided Diagnosis of Parkinson’s Disease Using Machine Learning

in Movement Disorders (2020, September 12)

Objective: Automatize the detection of ‘swallow-tail’ appearance in substantia nigra dopaminergic neurons using MRI for more robust tests on Parkinson’s disease (PD) diagnosis. Background: Differential ... [more ▼]

Objective: Automatize the detection of ‘swallow-tail’ appearance in substantia nigra dopaminergic neurons using MRI for more robust tests on Parkinson’s disease (PD) diagnosis. Background: Differential diagnosis of PD is challenging even in specialized centers. The use of imaging techniques can be bene cial for the diagnosis. Although DaTSCAN has been proven to be clinically useful, it is not widely available and has radiation risk and high-cost associated. Therefore, MRI scans for PD diagnosis offer several advantages over DaTSCAN [1]. Recent literature shows strong evidence of high diagnostic accuracy using the ‘swallow-tail’ shape of the dorsolateral substantia nigra in 3T – SWI [2]. Nevertheless, the majority of such studies rely on the subjective opinion of experts and manual methods for the analysis to assess the accuracy of these features. Alternatively, we propose a fully automated solution to evaluate the absence or presence of this feature for computer-aided diagnosis (CAD) of PD. Method: Restrospective study of 27 PD and 18 non-PD was conducted, including standard high-resolution 3D MRI – T1 & SWI sequences (additionally, T2 scans were used to increase the registration references). Firstly, spatial registration and normalization of the images were performed. Then, the ROI was extracted using atlas references. Finally, a supervised machine learning model was built using 5-fold-within-5-fold nested cross-validation. Results: Preliminary results show signi cant sensitivity (0.92) and ROC AUC (0.82), allowing for automated classi cation of patients based on swallow-tail biomarker from MRI. Conclusion: Detection of nigrosome degeneration (swallow-tail biomarker) in accessible brain imaging techniques can be automatized with signi cant accuracy, allowing for computer-aided PD diagnosis. References: [1] Schwarz, S. T., Xing, Y., Naidu, S., Birchall, J., Skelly, R., Perkins, A., ... & Gowland, P. (2017). Protocol of a single group prospective observational study on the diagnostic value of 3T susceptibility weighted MRI of nigrosome-1 in patients with parkinsonian symptoms: the N3iPD study (nigrosomal iron imaging in Parkinson’s disease). BMJ open, 7(12), e016904. [2] – Schwarz, S. T., Afzal, M., Morgan, P. S., Bajaj, N., Gowland, P. A., & Auer, D. P. (2014). The ‘swallow tail’ appearance of the healthy nigrosome –a new accurate test of Parkinson’s disease: a case-control and retrospective cross-sectional MRI study at 3T. PloS one, 9(4). [less ▲]

Knowledgezooclient: Constructing knowledge graph for android

in The 3rd International Workshop on Advances in Mobile App Analysis (2020, September)

In this work, we describe the design and implementation of a reusable tool named KnowledgeZooClient targeting the construction, as a crowd-sourced effort, of a knowledge graph for Android apps ... [more ▼]

In this work, we describe the design and implementation of a reusable tool named KnowledgeZooClient targeting the construction, as a crowd-sourced effort, of a knowledge graph for Android apps. KnowledgeZooClient is made up of two modules: (1) the Metadata Extraction Module (MEM), which aims at extracting metadata from Android apps and (2) the Metadata Integration Module (MIM) for importing and integrating extracted metadata into a graph database. The usefulness of KnowledgeZooClient is demonstrated via an exclusive knowledge graph called KnowledgeZoo, which contains information on over 500,000 apps already and still keeps growing. Interested users can already benefit from KnowledgeZoo by writing advanced search queries so as to collect targeted app samples. [less ▲]

RIVER MORPHOLOGY MONITORING OF A SMALL-SCALE ALPINE RIVERBED USING DRONE PHOTOGRAMMETRY AND LIDAR

in The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences (2020, August 12), XLIII-B2-2020 Article Metrics Related articles(1017), 1024

An efficient alternative to labour-intensive terrestrial and costly airborne surveys is the use of small, inexpensive Unmanned Aerial Vehicles (UAVs) or Remotely Piloted Aerial Systems (RPAS). These low ... [more ▼]

An efficient alternative to labour-intensive terrestrial and costly airborne surveys is the use of small, inexpensive Unmanned Aerial Vehicles (UAVs) or Remotely Piloted Aerial Systems (RPAS). These low-altitude remote sensing platforms, commonly known as drones, can carry lightweight optical and LiDAR sensors. Even though UAV systems still have limited endurance, they can provide a flexible and relatively inexpensive monitoring solution for a limited area of interest. This study investigated the applicability of monitoring the morphology of a frequently changing glacial stream using high-resolution topographic surface models derived from low-altitude UAV-based photogrammetry and LiDAR. An understanding of river-channel morphology and its response to anthropogenic and natural disturbances is imperative for effective watershed management and conservation. We focus on the data acquisition, processing workflow and highlight identified challenges and shortcomings. Additionally, we demonstrate how LiDAR data acquisition simulations can help decide which laser scanning approach to use and help optimise data collection to ensure full coverage with desired level of detail. Lastly, we showcase a case study of 3D surface change analysis in an alpine stream environment with UAV-based photogrammetry. The datasets used in this study were collected as part of the ISPRS Summer School of Alpine Research, which will continue to add new data layers on a biyearly basis. This growing data repository is freely available for research. [less ▲]

Reservoir Computing with Random Chemical Systems

in ALIFE 2020: The 2020 Conference on Artificial Life (2020, July 14)

Top-down engineering of biomolecular circuits to perform specific computational tasks is notoriously hard and time-consuming. Current circuits have limited complexity and are brittle and application ... [more ▼]

Top-down engineering of biomolecular circuits to perform specific computational tasks is notoriously hard and time-consuming. Current circuits have limited complexity and are brittle and application-specific. Here we propose an alternative: we design and test a bottom-up constructed Reservoir Computer (RC) that uses random chemical circuits inspired by DNA strand displacement reactions. This RC has the potential to be implemented easily and trained for various tasks. We describe and simulate it by means of a Chemical Reaction Network (CRN) and evaluate its performance on three computational tasks: the Hamming distance and a short- as well as a long-term memory. Compared with the deoxyribozyme oscillator RC model simulated by Yahiro et al., our random chemical RC performs 75.5% better for the short-term and 67.2% better for the long-term memory task. Our model requires an 88.5% larger variety of chemical species, but it relies on random chemical circuits, which can be more easily realized and scaled up. Thus, our novel random chemical RC has the potential to simplify the way we build adaptive biomolecular circuits. [less ▲]

The Unsecure Side of (Meta)Data in IoT Systems

in Ambient Intelligence and Smart Environments (2020, July), 28

The exponential spreading and deployment of emerging digital technologies such as the Internet of Things (IoT) has been remarkable: the IoT market is expected to triple, at least, from USD 170.57 billion ... [more ▼]

The exponential spreading and deployment of emerging digital technologies such as the Internet of Things (IoT) has been remarkable: the IoT market is expected to triple, at least, from USD 170.57 billion in 2017 to USD 561.04 billion by 2022. IoT technologies collect, generate and communicate a huge amount of different data and metadata, through an increasing number of interconnected devices and sensors. Current EU legislation on data protection classifies data into personal and non-personal. The paper aims at charting the resulting entanglements from an interdisciplinary perspective. The legal analysis, integrated with a technical perspective, will address firstly the content of IoT communications, i.e. “data”, and the underlying distinction between personal and non-personal. Secondly, the focus will shift on the metadata related to communications. Through a technical analysis of the highly sensitive nature of metadata, even when the content is encrypted, I will argue that metadata are likely to undermine even more the ontological and sharp division between personal and non-personal data upon which the European legal frameworks for privacy and data protection have been built. The incoming ePrivacy Regulation shall provide metadata, which should be considered always personal data, the same level of protection of “content” data. This interpretation might broaden the scope of application of GDPR and the connected obligations and responsibilities of data controllers and data processors too much. [less ▲]

Connecting the real world to mathematical models in elementary schools in Luxemburg

in Proceedings of the British Society for Research into Learning Mathematics (2020, July), 40(2), 1-6

In the Luxemburgish national curriculum for elementary schools (MENFP, 2011) experimentations and discoveries of mathematics concepts in courses are strongly recommended. Elementary school teachers should ... [more ▼]

In the Luxemburgish national curriculum for elementary schools (MENFP, 2011) experimentations and discoveries of mathematics concepts in courses are strongly recommended. Elementary school teachers should engage students in active mathematical modelling approaches, where they can develop processes and content skills through discoveries. Moreover, learned skills should be connected to real-world problems and situations to foster a better understanding of students’ living environments. Nevertheless, this teaching culture in mathematics is unusual in elementary schools and teachers tend to teach based on textbooks. Students mostly learn mathematics by imitation and repetition rather than through modelling mathematics with real-world problems and situations. Thus, to develop new methodologies in teaching mathematics and to meet the requirements of the national curriculum, we designed different technology-enhanced teaching and learning methods to engage students in experimental approaches within and outside classrooms. Moreover, we conducted three studies with digital and physical modelling, augmented reality, and a tutoring system in elementary school mathematics courses. Based on our collected data, we identified settings and tasks likely to support active mathematical modelling approaches. [less ▲]

Decision Triggered Data Transmission and Collection in Industrial Internet of Things

in 2020 IEEE Wireless Communications and Networking Conference (WCNC) (2020, June 19)

We propose a decision triggered data transmission and collection (DTDTC) protocol for condition monitoring and anomaly detection in the industrial Internet of things (IIoT). In the IIoT, the collection ... [more ▼]

We propose a decision triggered data transmission and collection (DTDTC) protocol for condition monitoring and anomaly detection in the industrial Internet of things (IIoT). In the IIoT, the collection, processing, encoding, and transmission of the sensor readings are usually not for the reconstruction of the original data but for decision making at the fusion center. By moving the decision making process to the local end devices, the amount of data transmission can be significantly reduced, especially when normal signals with positive decisions dominate in the whole life cycle and the fusion center is only interested in collecting the abnormal data. The proposed concept combines compressive sensing, machine learning, data transmission, and joint decision making. The sensor readings are encoded and transmitted to the fusion center only when abnormal signals with negative decisions are detected. All the abnormal signals from the end devices are gathered at the fusion center for a joint decision with feedback messages forwarded to the local actuators. The advantage of such an approach lies in that it can significantly reduce the volume of data to be transmitted through wireless links. Moreover, the introduction of compressive sensing can further reduce the dimension of data tremendously. An exemplary case, i.e., diesel engine condition monitoring, is provided to validate the effectiveness and efficiency of the proposed scheme compared to the conventional ones. [less ▲]

Validated Variational Inference via Practical Posterior Error Bounds

in Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics (AISTATS) (2020, June)

Evolving a Deep Neural Network Training Time Estimator

in Communications in Computer and Information Science (2020, February)

We present a procedure for the design of a Deep Neural Net- work (DNN) that estimates the execution time for training a deep neural network per batch on GPU accelerators. The estimator is destined to be ... [more ▼]

We present a procedure for the design of a Deep Neural Net- work (DNN) that estimates the execution time for training a deep neural network per batch on GPU accelerators. The estimator is destined to be embedded in the scheduler of a shared GPU infrastructure, capable of providing estimated training times for a wide range of network architectures, when the user submits a training job. To this end, a very short and simple representation for a given DNN is chosen. In order to compensate for the limited degree of description of the basic network representation, a novel co-evolutionary approach is taken to fit the estimator. The training set for the estimator, i.e. DNNs, is evolved by an evolutionary algorithm that optimizes the accuracy of the estimator. In the process, the genetic algorithm evolves DNNs, generates Python-Keras programs and projects them onto the simple representation. The genetic operators are dynamic, they change with the estimator’s accuracy in order to balance accuracy with generalization. Results show that despite the low degree of information in the representation and the simple initial design for the predictor, co-evolving the training set performs better than near random generated population of DNNs. [less ▲]

Inferring Urban Mobility and Habits from User Location History

in Transportation Research Procedia (2020, January), 47

The influence of well-being, social support, media use and sociodemographic factors on problematic social media sue among Luxembourgish adolescents

in Cogent Medicine (2020), 7(1),

Background: Adolescents spend an increasing amount of time communicating online. Previous research has indicated that electronic media communication has been associated with positive outcomes on ... [more ▼]

Background: Adolescents spend an increasing amount of time communicating online. Previous research has indicated that electronic media communication has been associated with positive outcomes on adolescent well-being and development, however, problematic social media use is on the rise. This study investigates factors that influence problematic social media use (PSMU), based on previous empirical research and the Differential Susceptibility to Media Effects Model by Valkenburg and Peter (2013). Methods: The data used in this study stems from the 2018 Health Behaviour for School-aged Children (HBSC) study in Luxembourg. Data from elementary and secondary school students aged 11 to 18 was used (N = 6164), which was collected through a written survey. A four-stage hierarchical multiple regression analysis was conducted using SPSS, with problematic social media use as the dependent variable. 14 independent variables were included in the model, added in four blocks: sociodemographic factors, social support factors, well-being factors and media use factors.Results: The results indicate that in stage one of the hierarchical regression, the sociodemographic predictors accounted for 3% of the variation in problematic social media use. The addition of the social support factors to the model in stage two explained an additional 7% of the variation in problematic social media use, and the addition of the well-being factors in stage three an additional 5.3%. In stage four of the hierarchical regression media use factors were added to the model, and the four blocks of predictors accounted for 22.2% of the variation in problematic social media use (Adjusted R2 = 0.222). The most important predictors for problematic social media use were preference for online social interaction (β = 0.205, p < .001), the intensity of electronic media communication (β = 0.155, p < .001), psychosomatic complaints (β = 0.136, p < .001), perceived stress (β = 0.122, p < .001) and cyberbullying perpetration (β = 0.117, p < .001). Conclusions: The block of sociodemographic factors contributed minimally to the explanation of the variance in problematic social media use in the model. The most important predictors for problematic social media use were preference for online social interaction, the intensity of electronic media communication, psychosomatic complaints, perceived stress and cyberbullying perpetration. This suggests that there are several starting points for the prevention of problematic social media use among adolescents. [less ▲]

Security and Privacy in Resource-Constrained Devices

in CEUR Workshop Proceedings (2020), 2598

Recent adversarial attacks have been shown IoT devices weaknesses due to their limited computing power. Given also their ubiquitous presence, lower costs and limitations in keeping security measures up ... [more ▼]

Recent adversarial attacks have been shown IoT devices weaknesses due to their limited computing power. Given also their ubiquitous presence, lower costs and limitations in keeping security measures up-todate, resource-constrained devices represent a growing risk for the security of IT infrastructure. The scope of the research is to investigate the weaknesses of resource-constrained IoT devices. The methodology for the investigation is the legal analysis of existing legal frameworks regulating IoT cybersecurity and data security; afterwards it will be carried out a critical evaluation of the existing best practices. This critical analysis should face the twofold challenge of increasing transparency and trust in resource-constrained systems. Users and companies are two faces of the same coin: accountability of data collectors and user awareness are crucial in the security and data protection debate. Thus, a comprehensive overview of the relevant legal frameworks and guidelines would increase the understanding of risks of the users, whilst data controllers (especially of small and medium enterprises) may have an instrument to implement properly security measures. [less ▲]

Mental health impact of the confinement measures during the COVID-19 pandemic

in Innovation in Aging (2020), 4(S1), 952

Role of Ion-Assisted Recombination and Grain Boundaries in Perovskite Solar Cell Hysteresis and Efficiency

in IEEE NANO (2020)

Kummer theory for number fields

in Proceedings of the Roman Number Theory Association (2020)

Federated Learning For Cyber Security: SOC Collaboration For Malicious URL Detection

in IEEE International Conference on Distributed Computing Systems (ICDCS) (2020)

Managed security service providers increasingly rely on machine-learning methods to exceed traditional, signature- based threat detection and classification methods. As machine- learning often improves ... [more ▼]

Managed security service providers increasingly rely on machine-learning methods to exceed traditional, signature- based threat detection and classification methods. As machine- learning often improves with more data available, smaller orga- nizations and clients find themselves at a disadvantage: Without the ability to share their data and others willing to collaborate, their machine-learned threat detection will perform worse than the same model in a larger organization. We show that Feder- ated Learning, i.e. collaborative learning without data sharing, successfully helps to overcome this problem. Our experiments focus on a common task in cyber security, the detection of unwanted URLs in network traffic seen by security-as-a-service providers. Our experiments show that i) Smaller participants benefit from larger participants ii) Participants seeing different types of malicious traffic can generalize better to unseen types of attacks, increasing performance by 8% to 15% on average, and up to 27% in the extreme case. iii) Participating in Federated training never harms the performance of the locally trained model. In our experiment modeling a security-as-a service setting, Federated Learning increased detection up to 30% for some participants in the scheme. This clearly shows that Federated Learning is a viable approach to address issues of data sharing in common cyber security settings. [less ▲]

Examining the Interplay of Generalized and Personal Views on Aging on Physical and Mental Health Across 2.5 Years

in Innovation in Aging (2020), 4(Supplement_1), 588-588

It remains unknown how distinct types of views on aging (VoA) are related to one another, and to aging outcomes. We used a latent-variable structural equation model to test the hypothesis that generalized ... [more ▼]

It remains unknown how distinct types of views on aging (VoA) are related to one another, and to aging outcomes. We used a latent-variable structural equation model to test the hypothesis that generalized views on aging (assessed as Age Stereotypes (AS)) would influence personal views on aging (assessed as Self-Perceptions of Aging (SPA)), which in-turn would influence later physical and mental health. Data came from a longitudinal survey on VoA (N= 537, MageT1 = 64.13, age rangeT1 = 40-98). As expected, SPA mediated the effect of AS on physical (loss-SPA: β = .23, p< .001; gain-SPA: β = .06, p< .001; R2 = .62) and mental health (loss-SPA: β = .13, p< .001; gain-SPA: β = .03, p< .01, ; R2 = .31). Congruent with theoretical assumptions, our findings provide empirical support for a directional pathway by which generalized views on aging affect health outcomes via personal views of aging. [less ▲]

Social Roles, Subjective Age, and Gender: Exploring the Links in Later Life

in Innovation in Aging (2020), 4(Supplement_1), 556-556

Subjective age (SA) is strongly linked to positive developmental outcomes and successful aging. The social roles people assume are supposed to impact SA, since they incorporate age-graded social ... [more ▼]

Subjective age (SA) is strongly linked to positive developmental outcomes and successful aging. The social roles people assume are supposed to impact SA, since they incorporate age-graded social experiences and age-stereotypic role expectations. Social roles are also strongly gendered, providing the opportunity to understand gender-specific processes of SA. This study investigates a broad range of social roles and their relation to older men and women’s SA in later life. N = 285 participants aged 50 to 86 years (Mage = 65.04, SD = 8.88) reported on 19 social roles and their SA. Higher commitment to social roles of continued development and engagement was related to a younger subjective age, above and beyond sociodemographic variables, physical and mental health, but only for younger men. Commitment to family roles was related to a younger subjective age only for older men. Implications for the gender-specific understanding of antecedents of SA are discussed. [less ▲]

Amplification of Magneto-Optical Activity via Hybridization with Dark Plasmons

in Conference on Lasers and Electro-Optics (2020) (2020)

Views on Aging and Well-Being in the Covid Crisis – A Longitudinal Study in Luxembourg

in Innovation in Aging (2020), 4(Supplement_1), 961-961

During the Covid-Crisis, stereotypes of older adults as helpless and vulnerable were spread, and intergenerational conflict was stirred more or less openly. We thus focused on perceived ageism during the ... [more ▼]

During the Covid-Crisis, stereotypes of older adults as helpless and vulnerable were spread, and intergenerational conflict was stirred more or less openly. We thus focused on perceived ageism during the crisis and its effects on well-being and health of older adults. Since views on aging are multifaceted and can be both, risk and resource for individual development, we assessed people’s self-perceptions of aging (SPA) as social loss, continued growth and physical decline and subjective age (SA). We hypothesized that people with SPA of social loss and physical decline would be more susceptible to negative effects of perceived ageism, whereas those with SPA of continued growth and younger SA would be less affected. NT1 = 611 community-dwelling adults aged 60 – 98 (Mage = 69.92 years) were recruited in June 2020 online and via phone in Luxembourg. In September 2020, participants will be contacted again for a follow-up. Analyses with cross-sectional data show that participants who felt more discriminated reported lower life satisfaction after the onset of the crisis (r = -.35) and worse subjective health (r = -.14). SPA of social loss and higher SA increased the negative effect of ageism on well-being (beta = -.57) and subjective health (beta = -.53), respectively. Our results point to mid- and long-term consequences of age discriminatory and stereotype-based crisis communication for the well-being of older adults and the importance of individual SPA in critical situations. [less ▲]

Examining the Relation Among Subjective Age and Working Memory in Old Age on a High-Frequency Basis Across 7 Days

in Innovation in Aging (2020), 4(Supplement_1), 598-598

While increasing longitudinal evidence suggests that negative age views accelerate cognitive decline and increase dementia risk, we know little about such co-variance dynamics on a daily basis. We make ... [more ▼]

While increasing longitudinal evidence suggests that negative age views accelerate cognitive decline and increase dementia risk, we know little about such co-variance dynamics on a daily basis. We make use of subjective age and working memory performance data obtained six times a day over seven consecutive days as people went about their daily routines from 123 young-old (aged 66-69 years, 47.2% women) and 42 old-old (aged 86-90 years, 55.8% women) adults. Notably, multilevel models revealed considerably-sized short-term intra-individual variation of subjective age and working memory within days and these short-term within-day fluctuations in subjective age and working memory were coupled as expected. Hence, increased subjective age went along with lowered working memory confirming previous research. However, the respective between-day associations appeared reversed. Given this evidence of correlated short-term variability, we also discuss implications of different change dynamics that might explain moment-to-moment versus day-to-day associations between subjective age and working memory. [less ▲]

Changes in neighborhood-level socioeconomic disadvantage and older Americans’ cognitive functioning

in Innovation in Aging (2020), 4(S1), 483

Prevalence of Mild Cognitive Impairment in Latin America and the Caribbean: A Systematic Review

in Innovation in Aging (2020), 4(S1), 897898

Attitude control algorithms in a swarm of cubesats: Kriging interpolation and coordinated data exchange

in Advances in the Astronautical Sciences (2020), 173

This study is a part of the Skoltech University project to deploy a swarm of four identical 3U CubeSats in LEO. The CubeSats are to be equipped with gamma-ray sensors and their collective behavior will be ... [more ▼]

This study is a part of the Skoltech University project to deploy a swarm of four identical 3U CubeSats in LEO. The CubeSats are to be equipped with gamma-ray sensors and their collective behavior will be exhibited in detecting gamma-ray bursts and coordinated attitude control. We consider a fully magnetic attitude control system, comprising a magnetometer as a part of attitude determination routine and three orthogonal magnetorquers as actuators. Having implemented and tested the conventional three-axis magnetic attitude determination and control algorithms, we proceed to study how the performance of such ADCS may be enhanced by using measurements and state vectors exchange. We interpolate the exchanged data, using the Kriging algorithm in conjunction with Extended Kalman filter and Lyapunov-based controller, since it provides the auto correlation and variance information about the environment of the magnetic field, which is of utmost importance for heterogeneous and noisy fields. In our simulations we compare the performance of the controller for a single satellite to that of the satellite in the swarm of CubeSats, which maintains the form of a regular tetrahedron and carries out distributed measurements with interpolation. Improved attitude stabilization for the latter scenario is demonstrated by mean squared errors. [less ▲]

The hub: Facilitating walking meetings through a network of interactive devices

in DIS 2020 Companion - Companion Publication of the 2020 ACM Designing Interactive Systems Conference (2020)

Walking meetings are a promising means to improve healthy behavior at work. By providing a physically active way of working, walking meetings can reduce our sitting time. Several obstacles that limit the ... [more ▼]

Walking meetings are a promising means to improve healthy behavior at work. By providing a physically active way of working, walking meetings can reduce our sitting time. Several obstacles that limit the social acceptance and wider adoption of walking meeting practice have been highlighted in previous research. Amongst these, the difficulty to take notes or present files is a recurring concern for office workers. To address these barriers, we designed the Hub, a network of stand-up meeting stations that accommodate different work-related tasks during walking meetings. We report on two pilot user tests investigating users' experiences and ideas for improvement, and present future research steps. We discuss the usefulness and relevance of the Hub concept to overcome the obstacles associated with walking meetings. © 2020 Owner/Author. [less ▲]

Linear system identification from ensemble snapshot observations

in Proceedings of the IEEE Conference on Decision and Control (2019, December)

Developments in transcriptomics techniques have caused a large demand in tailored computational methods for modelling gene expression dynamics from experimental data. Recently, so-called single-cell ... [more ▼]

Developments in transcriptomics techniques have caused a large demand in tailored computational methods for modelling gene expression dynamics from experimental data. Recently, so-called single-cell experiments have revolutionised genetic studies. These experiments yield gene expression data in single cell resolution for a large number of cells at a time. However, the cells are destroyed in the measurement process, and so the data consist of snapshots of an ensemble evolving over time, instead of time series. The problem studied in this article is how such data can be used in modelling gene regulatory dynamics. Two different paradigms are studied for linear system identification. The first is based on tracking the evolution of the distribution of cells over time. The second is based on the so-called pseudotime concept, identifying a common trajectory through the state space, along which cells propagate with different rates. Therefore, at any given time, the population contains cells in different stages of the trajectory. Resulting methods are compared in numerical experiments. [less ▲]

Performance and Complexity Tradeoffs of Several Constellations for Non Coherent Massive MIMO

in 22nd International Symposium on Wireless Personal Multimedia Communications (WPMC) (2019, November)

MQLV: Optimal Policy of Money Management in Retail Banking with Q-Learning

in Proceedings of the Fourth Workshop on MIning DAta for financial applicationS (MIDAS 2019) co-located with the 2019 European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD 2019) (2019, September)

Reinforcement learning has become one of the best approach to train a computer game emulator capable of human level performance. In a reinforcement learning approach, an optimal value function is learned ... [more ▼]

Reinforcement learning has become one of the best approach to train a computer game emulator capable of human level performance. In a reinforcement learning approach, an optimal value function is learned across a set of actions, or decisions, that leads to a set of states giving different rewards, with the objective to maximize the overall reward. A policy assigns to each state-action pairs an expected return. We call an optimal policy a policy for which the value function is optimal. QLBS, Q-Learner in the Black-Scholes(-Merton) Worlds, applies the reinforcement learning concepts, and noticeably, the popular Q-learning algorithm, to the financial stochastic model of Black, Scholes and Merton. It is, however, specifically optimized for the geometric Brownian motion and the vanilla options. Its range of application is, therefore, limited to vanilla option pricing within the financial markets. We propose MQLV, Modified Q-Learner for the Vasicek model, a new reinforcement learning approach that determines the optimal policy of money management based on the aggregated financial transactions of the clients. It unlocks new frontiers to establish personalized credit card limits or bank loan applications, targeting the retail banking industry. MQLV extends the simulation to mean reverting stochastic diffusion processes and it uses a digital function, a Heaviside step function expressed in its discrete form, to estimate the probability of a future event such as a payment default. In our experiments, we first show the similarities between a set of historical financial transactions and Vasicek generated transactions and, then, we underline the potential of MQLV on generated Monte Carlo simulations. Finally, MQLV is the first Q-learning Vasicek-based methodology addressing transparent decision making processes in retail banking. [less ▲]

Visualization of AE's Training on Credit Card Transactions with Persistent Homology

in Proceedings of the International Workshop on Applications of Topological Data Analysis In conjunction with ECML PKDD 2019 (2019, September)

Auto-encoders are among the most popular neural network architecture for dimension reduction. They are composed of two parts: the encoder which maps the model distribution to a latent manifold and the ... [more ▼]

Auto-encoders are among the most popular neural network architecture for dimension reduction. They are composed of two parts: the encoder which maps the model distribution to a latent manifold and the decoder which maps the latent manifold to a reconstructed distribution. However, auto-encoders are known to provoke chaotically scattered data distribution in the latent manifold resulting in an incomplete reconstructed distribution. Current distance measures fail to detect this problem because they are not able to acknowledge the shape of the data manifolds, i.e. their topological features, and the scale at which the manifolds should be analyzed. We propose Persistent Homology for Wasserstein Auto-Encoders, called PHom-WAE, a new methodology to assess and measure the data distribution of a generative model. PHom-WAE minimizes the Wasserstein distance between the true distribution and the reconstructed distribution and uses persistent homology, the study of the topological features of a space at different spatial resolutions, to compare the nature of the latent manifold and the reconstructed distribution. Our experiments underline the potential of persistent homology for Wasserstein Auto-Encoders in comparison to Variational Auto-Encoders, another type of generative model. The experiments are conducted on a real-world data set particularly challenging for traditional distance measures and auto-encoders. PHom-WAE is the first methodology to propose a topological distance measure, the bottleneck distance, for Wasserstein Auto-Encoders used to compare decoded samples of high quality in the context of credit card transactions. [less ▲]

ARCHITECTURES AND SYNCHRONIZATION TECHNIQUES FOR COHERENT DISTRIBUTED REMOTE SENSING SYSTEMS

in 2019 IEEE International Geoscience and Remote Sensing Symposium (IGARSS) (2019, August 31)

Phase, frequency and time synchronization is a crucial requirement for many applications as such as multi-static remote sensing and distributed beamforming for communications. The literature on the field ... [more ▼]

Phase, frequency and time synchronization is a crucial requirement for many applications as such as multi-static remote sensing and distributed beamforming for communications. The literature on the field is very wide, and in some cases, the requirements of the proposed synchronization solution may surpass the ones set by the application itself. Moreover, the synchronization solution becomes even more challenging when the nodes are flying or hovering on aerial or space platforms. In this work, we compare and classify the synchronization technologies available in the literature according to a common proposed framework, and we discuss the considerations of an implementation for distributed remote sensing applications. The general framework considered is based on a distributed collection of autonomous nodes that try to synchronize their clocks with a common reference. Moreover, they can be classified in non-overlapping, adjacent and overlapping frequency band scenarios [less ▲]

DISPUTool -- A tool for the Argumentative Analysis of Political Debates

in Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, {IJCAI-19} (2019, August 14)

Political debates are the means used by political candidates to put forward and justify their positions in front of the electors with respect to the issues at stake. Argument mining is a novel research ... [more ▼]

Political debates are the means used by political candidates to put forward and justify their positions in front of the electors with respect to the issues at stake. Argument mining is a novel research area in Artificial Intelligence, aiming at analyzing dis-course on the pragmatics level and applying a certain argumentation theory to model and automatically analyze textual data. In this paper, we present DISPUTool, a tool designed to ease the work of historians and social science scholars in analyzing the argumentative content of political speeches. More precisely, DISPUTool allows to explore and automatically identify argumentative components over the 39 political debates from the last 50 years of US presidential campaigns (1960-2016). [less ▲]

Surface characterization of epitaxial Cu-rich CuInSe2 absorbers

in IEEE Photovoltaic Specialists Conference. Conference Record (2019, July)

We investigated the electrical properties of epitaxial Cu-rich CuInSe 2 by Kelvin probe force microscopy (KPFM) under ambient and ultra-high vacuum conditions. We first measured the sample under ambient ... [more ▼]

We investigated the electrical properties of epitaxial Cu-rich CuInSe 2 by Kelvin probe force microscopy (KPFM) under ambient and ultra-high vacuum conditions. We first measured the sample under ambient conditions before and after potassium cyanide (KCN) etching. In both cases, we do not see any substantial contrast in the surface potential data; furthermore, after the KCN etching we observed outgrowths with a height around 2nm over the sample surface. On the other hand, the KPFM measurements under ultra-high vacuum conditions show a work function dependence according to the surface orientation of the Cu-rich CuInSe 2 crystal. Our results show the possibility to increase the efficiency of epitaxial Cu-rich CuInSe 2 by growing the materials in the appropriated surface orientation where the variations in work function are reduced. [less ▲]

Together or Alone: The Price of Privacy in Collaborative Learinig

in Proceedings on Privacy Enhancing Technologies (2019, July)

Machine learning algorithms have reached mainstream status and are widely deployed in many applications. The accuracy of such algorithms depends significantly on the size of the underlying training ... [more ▼]

Machine learning algorithms have reached mainstream status and are widely deployed in many applications. The accuracy of such algorithms depends significantly on the size of the underlying training dataset; in reality a small or medium sized organization often does not have the necessary data to train a reasonably accurate model. For such organizations, a realistic solution is to train their machine learning models based on their joint dataset (which is a union of the individual ones). Unfortunately, privacy concerns prevent them from straightforwardly doing so. While a number of privacy-preserving solutions exist for collaborating organizations to securely aggregate the parameters in the process of training the models, we are not aware of any work that provides a rational framework for the participants to precisely balance the privacy loss and accuracy gain in their collaboration. In this paper, by focusing on a two-player setting, we model the collaborative training process as a two-player game where each player aims to achieve higher accuracy while preserving the privacy of its own dataset. We introduce the notion of Price of Privacy, a novel approach for measuring the impact of privacy protection on the accuracy in the proposed framework. Furthermore, we develop a game-theoretical model for different player types, and then either find or prove the existence of a Nash Equilibrium with regard to the strength of privacy protection for each player. Using recommendation systems as our main use case, we demonstrate how two players can make practical use of the proposed theoretical framework, including setting up the parameters and approximating the non-trivial Nash Equilibrium. [less ▲]