TY - JOUR A1 - Wang, Cheng A1 - Yang, Haojin A1 - Meinel, Christoph T1 - A deep semantic framework for multimodal representation learning JF - Multimedia tools and applications : an international journal N2 - Multimodal representation learning has gained increasing importance in various real-world multimedia applications. Most previous approaches focused on exploring inter-modal correlation by learning a common or intermediate space in a conventional way, e.g. Canonical Correlation Analysis (CCA). These works neglected the exploration of fusing multiple modalities at higher semantic level. In this paper, inspired by the success of deep networks in multimedia computing, we propose a novel unified deep neural framework for multimodal representation learning. To capture the high-level semantic correlations across modalities, we adopted deep learning feature as image representation and topic feature as text representation respectively. In joint model learning, a 5-layer neural network is designed and enforced with a supervised pre-training in the first 3 layers for intra-modal regularization. The extensive experiments on benchmark Wikipedia and MIR Flickr 25K datasets show that our approach achieves state-of-the-art results compare to both shallow and deep models in multimodal and cross-modal retrieval. KW - Multimodal representation KW - Deep neural networks KW - Semantic feature KW - Cross-modal retrieval Y1 - 2016 U6 - https://doi.org/10.1007/s11042-016-3380-8 SN - 1380-7501 SN - 1573-7721 VL - 75 SP - 9255 EP - 9276 PB - Springer CY - Dordrecht ER - TY - JOUR A1 - Emuoyibofarhe, Justice O. A1 - Akindele, Akinyinka Tosin A1 - Ronke, Babatunde Seyi A1 - Omotosho, Adebayo A1 - Meinel, Christoph T1 - A Fuzzy Rule-Based Model for Remote Monitoring of Preterm in the Intensive Care Unit of Hospitals JF - International Journal of Medical Research & Health Sciences N2 - The use of Remote patient monitoring (RPM) systems to monitor critically ill patients in the Intensive Care Unit (ICU) has enabled quality and real-time healthcare management. Fuzzy logic as an approach to designing RPM systems provides a means for encapsulating the subjective decision-making process of medical experts in an algorithm suitable for computer implementation. In this paper, a remote monitoring system for preterm in neonatal ICU incubators is modeled and simulated. The model was designed with 4 input variables (body temperature, heart rate, respiratory rate, and oxygen level saturation), and 1 output variable (action performed represented as ACT). ACT decides whether-an alert is generated or not and also determines the message displayed when a notification is required. ACT classifies the clinical priority of the monitored preterm into 5 different fields: code blue, code red, code yellow, code green, and-code black. The model was simulated using a fuzzy logic toolbox of MATLAB R2015A. About 216 IF_THEN rules were formulated to monitor the inputs data fed into the model. The performance of the model was evaluated using-the confusion matrix to determine the model’s accuracy, precision, sensitivity, specificity, and false alarm rate. The-experimental results obtained shows that the fuzzy-based system is capable of producing satisfactory results when used for monitoring and classifying the clinical statuses of neonates in ICU incubators. KW - Remote patient monitoring KW - Fuzzy logic KW - Preterm KW - Incubator KW - Confusion matrix Y1 - 2019 SN - 2319-5886 VL - 8 IS - 5 SP - 33 EP - 44 PB - Sumathi CY - Trichy ER - TY - JOUR A1 - Kayem, Anne Voluntas dei Massah A1 - Meinel, Christoph A1 - Wolthusen, Stephen D. T1 - A resilient smart micro-grid architecture for resource constrained environments JF - Smart Micro-Grid Systems Security and Privacy N2 - Resource constrained smart micro-grid architectures describe a class of smart micro-grid architectures that handle communications operations over a lossy network and depend on a distributed collection of power generation and storage units. Disadvantaged communities with no or intermittent access to national power networks can benefit from such a micro-grid model by using low cost communication devices to coordinate the power generation, consumption, and storage. Furthermore, this solution is both cost-effective and environmentally-friendly. One model for such micro-grids, is for users to agree to coordinate a power sharing scheme in which individual generator owners sell excess unused power to users wanting access to power. Since the micro-grid relies on distributed renewable energy generation sources which are variable and only partly predictable, coordinating micro-grid operations with distributed algorithms is necessity for grid stability. Grid stability is crucial in retaining user trust in the dependability of the micro-grid, and user participation in the power sharing scheme, because user withdrawals can cause the grid to breakdown which is undesirable. In this chapter, we present a distributed architecture for fair power distribution and billing on microgrids. The architecture is designed to operate efficiently over a lossy communication network, which is an advantage for disadvantaged communities. We build on the architecture to discuss grid coordination notably how tasks such as metering, power resource allocation, forecasting, and scheduling can be handled. All four tasks are managed by a feedback control loop that monitors the performance and behaviour of the micro-grid, and based on historical data makes decisions to ensure the smooth operation of the grid. Finally, since lossy networks are undependable, differentiating system failures from adversarial manipulations is an important consideration for grid stability. We therefore provide a characterisation of potential adversarial models and discuss possible mitigation measures. KW - Resource constrained smart micro-grids KW - Architectures KW - Disadvantaged communities KW - Energy KW - Grid stability KW - Forecasting KW - Feedback control loop Y1 - 2018 SN - 978-3-319-91427-5 SN - 978-3-319-91426-8 U6 - https://doi.org/10.1007/978-3-319-91427-5_5 VL - 71 SP - 71 EP - 101 PB - Springer CY - Dordrecht ER - TY - JOUR A1 - Roschke, Sebastian A1 - Cheng, Feng A1 - Meinel, Christoph T1 - An alert correlation platform for memory-supported techniques JF - Concurrency and computation : practice & experience N2 - Intrusion Detection Systems (IDS) have been widely deployed in practice for detecting malicious behavior on network communication and hosts. False-positive alerts are a popular problem for most IDS approaches. The solution to address this problem is to enhance the detection process by correlation and clustering of alerts. To meet the practical requirements, this process needs to be finished fast, which is a challenging task as the amount of alerts in large-scale IDS deployments is significantly high. We identifytextitdata storage and processing algorithms to be the most important factors influencing the performance of clustering and correlation. We propose and implement a highly efficient alert correlation platform. For storage, a column-based database, an In-Memory alert storage, and memory-based index tables lead to significant improvements of the performance. For processing, algorithms are designed and implemented which are optimized for In-Memory databases, e.g. an attack graph-based correlation algorithm. The platform can be distributed over multiple processing units to share memory and processing power. A standardized interface is designed to provide a unified view of result reports for end users. The efficiency of the platform is tested by practical experiments with several alert storage approaches, multiple algorithms, as well as a local and a distributed deployment. KW - memory-based correlation KW - memory-based clustering KW - memory-based databases KW - IDS management Y1 - 2012 U6 - https://doi.org/10.1002/cpe.1750 SN - 1532-0626 VL - 24 IS - 10 SP - 1123 EP - 1136 PB - Wiley-Blackwell CY - Hoboken ER - TY - JOUR A1 - Grüner, Andreas A1 - Mühle, Alexander A1 - Meinel, Christoph T1 - ATIB BT - Design and evaluation of an architecture for brokered self-sovereign identity integration and trust-enhancing attribute aggregation for service provider JF - IEEE access : practical research, open solutions / Institute of Electrical and Electronics Engineers N2 - Identity management is a principle component of securing online services. In the advancement of traditional identity management patterns, the identity provider remained a Trusted Third Party (TTP). The service provider and the user need to trust a particular identity provider for correct attributes amongst other demands. This paradigm changed with the invention of blockchain-based Self-Sovereign Identity (SSI) solutions that primarily focus on the users. SSI reduces the functional scope of the identity provider to an attribute provider while enabling attribute aggregation. Besides that, the development of new protocols, disregarding established protocols and a significantly fragmented landscape of SSI solutions pose considerable challenges for an adoption by service providers. We propose an Attribute Trust-enhancing Identity Broker (ATIB) to leverage the potential of SSI for trust-enhancing attribute aggregation. Furthermore, ATIB abstracts from a dedicated SSI solution and offers standard protocols. Therefore, it facilitates the adoption by service providers. Despite the brokered integration approach, we show that ATIB provides a high security posture. Additionally, ATIB does not compromise the ten foundational SSI principles for the users. KW - Blockchains KW - Protocols KW - Authentication KW - Licenses KW - Security KW - Privacy KW - Identity management systems KW - Attribute aggregation KW - attribute assurance KW - digital identity KW - identity broker KW - self-sovereign identity KW - trust model Y1 - 2021 U6 - https://doi.org/10.1109/ACCESS.2021.3116095 SN - 2169-3536 VL - 9 SP - 138553 EP - 138570 PB - Institute of Electrical and Electronics Engineers CY - New York, NY ER - TY - JOUR A1 - Meinel, Christoph A1 - Wang, Long T1 - Building content clusters based on modelling page pairs N2 - We give a new view on building content clusters from page pair models. We measure the heuristic importance within every two pages by computing the distance of their accessed positions in usage sessions. We also compare our page pair models with the classical pair models used in information theories and natural language processing, and give different evaluation methods to build the reasonable content communities. And we finally interpret the advantages and disadvantages of our models from detailed experiment results Y1 - 2006 UR - http://www.springerlink.com/content/105633/ U6 - https://doi.org/10.1007/11610113_85 ER - TY - JOUR A1 - Torkura, Kennedy A. A1 - Sukmana, Muhammad Ihsan Haikal A1 - Cheng, Feng A1 - Meinel, Christoph T1 - CloudStrike BT - chaos engineering for security and resiliency in cloud infrastructure JF - IEEE access : practical research, open solutions N2 - Most cyber-attacks and data breaches in cloud infrastructure are due to human errors and misconfiguration vulnerabilities. Cloud customer-centric tools are imperative for mitigating these issues, however existing cloud security models are largely unable to tackle these security challenges. Therefore, novel security mechanisms are imperative, we propose Risk-driven Fault Injection (RDFI) techniques to address these challenges. RDFI applies the principles of chaos engineering to cloud security and leverages feedback loops to execute, monitor, analyze and plan security fault injection campaigns, based on a knowledge-base. The knowledge-base consists of fault models designed from secure baselines, cloud security best practices and observations derived during iterative fault injection campaigns. These observations are helpful for identifying vulnerabilities while verifying the correctness of security attributes (integrity, confidentiality and availability). Furthermore, RDFI proactively supports risk analysis and security hardening efforts by sharing security information with security mechanisms. We have designed and implemented the RDFI strategies including various chaos engineering algorithms as a software tool: CloudStrike. Several evaluations have been conducted with CloudStrike against infrastructure deployed on two major public cloud infrastructure: Amazon Web Services and Google Cloud Platform. The time performance linearly increases, proportional to increasing attack rates. Also, the analysis of vulnerabilities detected via security fault injection has been used to harden the security of cloud resources to demonstrate the effectiveness of the security information provided by CloudStrike. Therefore, we opine that our approaches are suitable for overcoming contemporary cloud security issues. KW - cloud security KW - security chaos engineering KW - resilient architectures KW - security risk assessment Y1 - 2020 U6 - https://doi.org/10.1109/ACCESS.2020.3007338 SN - 2169-3536 VL - 8 SP - 123044 EP - 123060 PB - Institute of Electrical and Electronics Engineers  CY - Piscataway ER - TY - JOUR A1 - Thienen, Julia von A1 - Weinstein, Theresa Julia A1 - Meinel, Christoph T1 - Creative metacognition in design thinking BT - exploring theories, educational practices, and their implications for measurement JF - Frontiers in psychology N2 - Design thinking is a well-established practical and educational approach to fostering high-level creativity and innovation, which has been refined since the 1950s with the participation of experts like Joy Paul Guilford and Abraham Maslow. Through real-world projects, trainees learn to optimize their creative outcomes by developing and practicing creative cognition and metacognition. This paper provides a holistic perspective on creativity, enabling the formulation of a comprehensive theoretical framework of creative metacognition. It focuses on the design thinking approach to creativity and explores the role of metacognition in four areas of creativity expertise: Products, Processes, People, and Places. The analysis includes task-outcome relationships (product metacognition), the monitoring of strategy effectiveness (process metacognition), an understanding of individual or group strengths and weaknesses (people metacognition), and an examination of the mutual impact between environments and creativity (place metacognition). It also reviews measures taken in design thinking education, including a distribution of cognition and metacognition, to support students in their development of creative mastery. On these grounds, we propose extended methods for measuring creative metacognition with the goal of enhancing comprehensive assessments of the phenomenon. Proposed methodological advancements include accuracy sub-scales, experimental tasks where examinees explore problem and solution spaces, combinations of naturalistic observations with capability testing, as well as physiological assessments as indirect measures of creative metacognition. KW - accuracy KW - creativity KW - design thinking KW - education KW - measurement KW - metacognition KW - innovation KW - framework Y1 - 2023 U6 - https://doi.org/10.3389/fpsyg.2023.1157001 SN - 1664-1078 VL - 14 PB - Frontiers Research Foundation CY - Lausanne ER - TY - JOUR A1 - Bin Tareaf, Raad A1 - Berger, Philipp A1 - Hennig, Patrick A1 - Meinel, Christoph T1 - Cross-platform personality exploration system for online social networks BT - Facebook vs. Twitter JF - Web intelligence N2 - Social networking sites (SNS) are a rich source of latent information about individual characteristics. Crawling and analyzing this content provides a new approach for enterprises to personalize services and put forward product recommendations. In the past few years, commercial brands made a gradual appearance on social media platforms for advertisement, customers support and public relation purposes and by now it became a necessity throughout all branches. This online identity can be represented as a brand personality that reflects how a brand is perceived by its customers. We exploited recent research in text analysis and personality detection to build an automatic brand personality prediction model on top of the (Five-Factor Model) and (Linguistic Inquiry and Word Count) features extracted from publicly available benchmarks. Predictive evaluation on brands' accounts reveals that Facebook platform provides a slight advantage over Twitter platform in offering more self-disclosure for users' to express their emotions especially their demographic and psychological traits. Results also confirm the wider perspective that the same social media account carry a quite similar and comparable personality scores over different social media platforms. For evaluating our prediction results on actual brands' accounts, we crawled the Facebook API and Twitter API respectively for 100k posts from the most valuable brands' pages in the USA and we visualize exemplars of comparison results and present suggestions for future directions. KW - Big Five model KW - personality prediction KW - brand personality KW - machine KW - learning KW - social media analysis Y1 - 2020 U6 - https://doi.org/10.3233/WEB-200427 SN - 2405-6456 SN - 2405-6464 VL - 18 IS - 1 SP - 35 EP - 51 PB - IOS Press CY - Amsterdam ER - TY - JOUR A1 - Omotosho, Adebayo A1 - Ayegba, Peace A1 - Emuoyibofarhe, Justice A1 - Meinel, Christoph T1 - Current State of ICT in Healthcare Delivery in Developing Countries JF - International Journal of Online and Biomedical Engineering N2 - Electronic health is one of the most popular applications of information and communication technologies and it has contributed immensely to health delivery through the provision of quality health service and ubiquitous access at a lower cost. Even though this mode of health service is increasingly becoming known or used in developing nations, these countries are faced with a myriad of challenges when implementing and deploying e-health services on both small and large scale. It is estimated that the Africa population alone carries the highest percentage of the world’s global diseases despite its certain level of e-health adoption. This paper aims at analyzing the progress so far and the current state of e-health in developing countries particularly Africa and propose a framework for further improvement. KW - E-health KW - developing countries KW - framework KW - ICT KW - healthcare Y1 - 2019 U6 - https://doi.org/10.3991/ijoe.v15i08.10294 SN - 2626-8493 VL - 15 IS - 8 SP - 91 EP - 107 PB - Kassel University Press CY - Kassel ER - TY - JOUR A1 - Krentz, Konrad-Felix A1 - Meinel, Christoph T1 - Denial-of-sleep defenses for IEEE 802.15.4 coordinated sampled listening (CSL) JF - Computer Networks N2 - Coordinated sampled listening (CSL) is a standardized medium access control protocol for IEEE 80215.4 networks. Unfortunately, CSL comes without any protection against so-called denial-of-sleep attacks. Such attacks deprive energy-constrained devices of entering low-power sleep modes, thereby draining their charge. Repercussions of denial-of-sleep attacks include long outages, violated quality-of-service guarantees, and reduced customer satisfaction. However, while CSL has no built-in denial-of-sleep defenses, there already exist denial-of-sleep defenses for a predecessor of CSL, namely ContikiMAC. In this paper, we make two main contributions. First, motivated by the fact that CSL has many advantages over ContikiMAC, we tailor the existing denial-of-sleep defenses for ContikiMAC to CSL. Second, we propose several security enhancements to these existing denial-of-sleep defenses. In effect, our denial-of-sleep defenses for CSL mitigate denial-of-sleep attacks significantly better, as well as protect against a larger range of denial-of-sleep attacks than the existing denial-of-sleep defenses for ContikiMAC. We show the soundness of our denial-of-sleep defenses for CSL both analytically, as well as empirically using a whole new implementation of CSL. (C) 2018 Elsevier B.V. All rights reserved. KW - Internet of things KW - Link layer security KW - MAC security KW - Denial of sleep Y1 - 2018 U6 - https://doi.org/10.1016/j.comnet.2018.10.021 SN - 1389-1286 SN - 1872-7069 VL - 148 SP - 60 EP - 71 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Lindberg, Tilmann A1 - Meinel, Christoph A1 - Wagner, Ralf T1 - Design thinking : a fruitful concept for IT development? Y1 - 2011 SN - 978-3-642-13756-3 ER - TY - JOUR A1 - Meinel, Christoph A1 - Leifer, Larry T1 - Design thinking research Y1 - 2012 SN - 978-3-642-31990-7 ER - TY - JOUR A1 - Meinel, Christoph A1 - Leifer, Larry T1 - Design thinking research Y1 - 2011 SN - 978-3-642-13756-3 ER - TY - JOUR A1 - Meinel, Christoph A1 - Leifer, Larry T1 - Design thinking research Y1 - 2012 ER - TY - JOUR A1 - Meinel, Christoph A1 - Gayvoronskaya, Tatiana A1 - Mühle, Alexander T1 - Die Zukunftspotenziale der Blockchain-Technologie JF - Die Zukunft der Medizin : disruptive Innovationen revolutionieren Medizin und Gesundheit Y1 - 2019 SN - 978-3-95466-398-9 SN - 978-3-95466-448-1 SP - 259 EP - 280 PB - Medizinisch Wissenschaftliche Verlagsgesellschaft CY - Berlin ER - TY - JOUR A1 - Azodi, Amir A1 - Cheng, Feng A1 - Meinel, Christoph T1 - Event Driven Network Topology Discovery and Inventory Listing Using REAMS JF - Wireless personal communications : an international journal N2 - Network Topology Discovery and Inventory Listing are two of the primary features of modern network monitoring systems (NMS). Current NMSs rely heavily on active scanning techniques for discovering and mapping network information. Although this approach works, it introduces some major drawbacks such as the performance impact it can exact, specially in larger network environments. As a consequence, scans are often run less frequently which can result in stale information being presented and used by the network monitoring system. Alternatively, some NMSs rely on their agents being deployed on the hosts they monitor. In this article, we present a new approach to Network Topology Discovery and Network Inventory Listing using only passive monitoring and scanning techniques. The proposed techniques rely solely on the event logs produced by the hosts and network devices present within a network. Finally, we discuss some of the advantages and disadvantages of our approach. KW - Network topology KW - Inventory systems KW - Network monitoring KW - Network graph KW - Service detection KW - Event processing KW - Event normalization Y1 - 2015 U6 - https://doi.org/10.1007/s11277-015-3061-3 SN - 0929-6212 SN - 1572-834X VL - 94 SP - 415 EP - 430 PB - Springer CY - New York ER - TY - JOUR A1 - Jaeger, David A1 - Graupner, Hendrik A1 - Pelchen, Chris A1 - Cheng, Feng A1 - Meinel, Christoph T1 - Fast Automated Processing and Evaluation of Identity Leaks JF - International journal of parallel programming N2 - The relevance of identity data leaks on the Internet is more present than ever. Almost every week we read about leakage of databases with more than a million users in the news. Smaller but not less dangerous leaks happen even multiple times a day. The public availability of such leaked data is a major threat to the victims, but also creates the opportunity to learn not only about security of service providers but also the behavior of users when choosing passwords. Our goal is to analyze this data and generate knowledge that can be used to increase security awareness and security, respectively. This paper presents a novel approach to the processing and analysis of a vast majority of bigger and smaller leaks. We evolved from a semi-manual to a fully automated process that requires a minimum of human interaction. Our contribution is the concept and a prototype implementation of a leak processing workflow that includes the extraction of digital identities from structured and unstructured leak-files, the identification of hash routines and a quality control to ensure leak authenticity. By making use of parallel and distributed programming, we are able to make leaks almost immediately available for analysis and notification after they have been published. Based on the data collected, this paper reveals how easy it is for criminals to collect lots of passwords, which are plain text or only weakly hashed. We publish those results and hope to increase not only security awareness of Internet users but also security on a technical level on the service provider side. KW - Identity leak KW - Data breach KW - Automated parsing KW - Parallel processing Y1 - 2018 U6 - https://doi.org/10.1007/s10766-016-0478-6 SN - 0885-7458 SN - 1573-7640 VL - 46 IS - 2 SP - 441 EP - 470 PB - Springer CY - New York ER - TY - JOUR A1 - Rezaei, Mina A1 - Näppi, Janne J. A1 - Lippert, Christoph A1 - Meinel, Christoph A1 - Yoshida, Hiroyuki T1 - Generative multi-adversarial network for striking the right balance in abdominal image segmentation JF - International journal of computer assisted radiology and surgery N2 - Purpose: The identification of abnormalities that are relatively rare within otherwise normal anatomy is a major challenge for deep learning in the semantic segmentation of medical images. The small number of samples of the minority classes in the training data makes the learning of optimal classification challenging, while the more frequently occurring samples of the majority class hamper the generalization of the classification boundary between infrequently occurring target objects and classes. In this paper, we developed a novel generative multi-adversarial network, called Ensemble-GAN, for mitigating this class imbalance problem in the semantic segmentation of abdominal images. Method: The Ensemble-GAN framework is composed of a single-generator and a multi-discriminator variant for handling the class imbalance problem to provide a better generalization than existing approaches. The ensemble model aggregates the estimates of multiple models by training from different initializations and losses from various subsets of the training data. The single generator network analyzes the input image as a condition to predict a corresponding semantic segmentation image by use of feedback from the ensemble of discriminator networks. To evaluate the framework, we trained our framework on two public datasets, with different imbalance ratios and imaging modalities: the Chaos 2019 and the LiTS 2017. Result: In terms of the F1 score, the accuracies of the semantic segmentation of healthy spleen, liver, and left and right kidneys were 0.93, 0.96, 0.90 and 0.94, respectively. The overall F1 scores for simultaneous segmentation of the lesions and liver were 0.83 and 0.94, respectively. Conclusion: The proposed Ensemble-GAN framework demonstrated outstanding performance in the semantic segmentation of medical images in comparison with other approaches on popular abdominal imaging benchmarks. The Ensemble-GAN has the potential to segment abdominal images more accurately than human experts. KW - imbalanced learning KW - generative multi-discriminative networks KW - semantic KW - segmentation KW - abdominal imaging Y1 - 2020 U6 - https://doi.org/10.1007/s11548-020-02254-4 SN - 1861-6410 SN - 1861-6429 VL - 15 IS - 11 SP - 1847 EP - 1858 PB - Springer CY - Berlin ER - TY - JOUR A1 - Roschke, Sebastian A1 - Cheng, Feng A1 - Meinel, Christoph T1 - High-quality attack graph-based IDS correlation JF - Logic journal of the IGPL N2 - Intrusion Detection Systems are widely deployed in computer networks. As modern attacks are getting more sophisticated and the number of sensors and network nodes grow, the problem of false positives and alert analysis becomes more difficult to solve. Alert correlation was proposed to analyse alerts and to decrease false positives. Knowledge about the target system or environment is usually necessary for efficient alert correlation. For representing the environment information as well as potential exploits, the existing vulnerabilities and their Attack Graph (AG) is used. It is useful for networks to generate an AG and to organize certain vulnerabilities in a reasonable way. In this article, a correlation algorithm based on AGs is designed that is capable of detecting multiple attack scenarios for forensic analysis. It can be parameterized to adjust the robustness and accuracy. A formal model of the algorithm is presented and an implementation is tested to analyse the different parameters on a real set of alerts from a local network. To improve the speed of the algorithm, a multi-core version is proposed and a HMM-supported version can be used to further improve the quality. The parallel implementation is tested on a multi-core correlation platform, using CPUs and GPUs. KW - Correlation KW - attack graph KW - HMM KW - multi-core KW - IDS Y1 - 2013 U6 - https://doi.org/10.1093/jigpal/jzs034 SN - 1367-0751 VL - 21 IS - 4 SP - 571 EP - 591 PB - Oxford Univ. Press CY - Oxford ER - TY - JOUR A1 - Thienen, Julia von A1 - Noweski, Christine A1 - Rauth, Ingo A1 - Meinel, Christoph A1 - Lange, Sabine T1 - If you want to know who are, tell me where you are : the importance of places Y1 - 2012 ER - TY - JOUR A1 - Wang, Cheng A1 - Yang, Haojin A1 - Meinel, Christoph T1 - Image Captioning with Deep Bidirectional LSTMs and Multi-Task Learning JF - ACM transactions on multimedia computing, communications, and applications N2 - Generating a novel and descriptive caption of an image is drawing increasing interests in computer vision, natural language processing, and multimedia communities. In this work, we propose an end-to-end trainable deep bidirectional LSTM (Bi-LSTM (Long Short-Term Memory)) model to address the problem. By combining a deep convolutional neural network (CNN) and two separate LSTM networks, our model is capable of learning long-term visual-language interactions by making use of history and future context information at high-level semantic space. We also explore deep multimodal bidirectional models, in which we increase the depth of nonlinearity transition in different ways to learn hierarchical visual-language embeddings. Data augmentation techniques such as multi-crop, multi-scale, and vertical mirror are proposed to prevent over-fitting in training deep models. To understand how our models "translate" image to sentence, we visualize and qualitatively analyze the evolution of Bi-LSTM internal states over time. The effectiveness and generality of proposed models are evaluated on four benchmark datasets: Flickr8K, Flickr30K, MSCOCO, and Pascal1K datasets. We demonstrate that Bi-LSTM models achieve highly competitive performance on both caption generation and image-sentence retrieval even without integrating an additional mechanism (e.g., object detection, attention model). Our experiments also prove that multi-task learning is beneficial to increase model generality and gain performance. We also demonstrate the performance of transfer learning of the Bi-LSTM model significantly outperforms previous methods on the Pascal1K dataset. KW - Deep learning KW - LSTM KW - multimodal representations KW - image captioning KW - mutli-task learning Y1 - 2018 U6 - https://doi.org/10.1145/3115432 SN - 1551-6857 SN - 1551-6865 VL - 14 IS - 2 PB - Association for Computing Machinery CY - New York ER - TY - JOUR A1 - Grünewald, Franka A1 - Meinel, Christoph T1 - Implementation and Evaluation of Digital E-Lecture Annotation in Learning Groups to Foster Active Learning JF - IEEE transactions on learning technologies N2 - The use of video lectures in distance learning involves the two major problems of searchability and active user participation. In this paper, we promote the implementation and usage of a collaborative educational video annotation functionality to overcome these two challenges. Different use cases and requirements, as well as details of the implementation, are explained. Furthermore, we suggest more improvements to foster a culture of participation and an algorithm for the extraction of semantic data. Finally, evaluations in the form of user tests and questionnaires in a MOOC setting are presented. The results of the evaluation are promising, as they indicate not only that students perceive it as useful, but also that the learning effectiveness increases. The combination of personal lecture video annotations with a semantic topic map was also evaluated positively and will thus be investigated further, as will the implementation in a MOOC context. KW - eLectures KW - tele-teaching KW - video annotation KW - collaborative learning Y1 - 2015 U6 - https://doi.org/10.1109/TLT.2015.2396042 SN - 1939-1382 VL - 8 IS - 3 SP - 286 EP - 298 PB - Inst. of Electr. and Electronics Engineers CY - Los Alamitos ER - TY - JOUR A1 - Ambassa, Pacome L. A1 - Kayem, Anne Voluntas dei Massah A1 - Wolthusen, Stephen D. A1 - Meinel, Christoph T1 - Inferring private user behaviour based on information leakage JF - Smart Micro-Grid Systems Security and Privacy N2 - In rural/remote areas, resource constrained smart micro-grid (RCSMG) architectures can provide a cost-effective power supply alternative in cases when connectivity to the national power grid is impeded by factors such as load shedding. RCSMG architectures can be designed to handle communications over a distributed lossy network in order to minimise operation costs. However, due to the unreliable nature of lossy networks communication data can be distorted by noise additions that alter the veracity of the data. In this chapter, we consider cases in which an adversary who is internal to the RCSMG, deliberately distorts communicated data to gain an unfair advantage over the RCSMG’s users. The adversary’s goal is to mask malicious data manipulations as distortions due to additive noise due to communication channel unreliability. Distinguishing malicious data distortions from benign distortions is important in ensuring trustworthiness of the RCSMG. Perturbation data anonymisation algorithms can be used to alter transmitted data to ensure that adversarial manipulation of the data reveals no information that the adversary can take advantage of. However, because existing data perturbation anonymisation algorithms operate by using additive noise to anonymise data, using these algorithms in the RCSMG context is challenging. This is due to the fact that distinguishing benign noise additions from malicious noise additions is a difficult problem. In this chapter, we present a brief survey of cases of privacy violations due to inferences drawn from observed power consumption patterns in RCSMGs centred on inference, and propose a method of mitigating these risks. The lesson here is that while RCSMGs give users more control over power management and distribution, good anonymisation is essential to protecting personal information on RCSMGs. KW - Approximation algorithms KW - Electrical products KW - Home appliances KW - Load modeling KW - Monitoring KW - Power demand KW - Wireless sensor networks KW - Distributed snapshot algorithm KW - Micro-grid networks KW - Power consumption characterization KW - Sensor networks Y1 - 2018 SN - 978-3-319-91427-5 SN - 978-3-319-91426-8 U6 - https://doi.org/10.1007/978-3-319-91427-5_7 VL - 71 SP - 145 EP - 159 PB - Springer CY - Dordrecht ER - TY - JOUR A1 - Rafiee, Hosnieh A1 - von Loewis, Martin A1 - Meinel, Christoph T1 - IPv6 Deployment and Spam Challenges JF - IEEE Internet computing N2 - Spam has posed a serious problem for users of email since its infancy. Today, automated strategies are required to deal with the massive amount of spam traffic. IPv4 networks offer a variety of solutions to reduce spam, but IPv6 networks' large address space and use of temporary addresses - both of which are particularly vulnerable to spam attacks - makes dealing with spam and the use of automated approaches much more difficult. IPv6 thus poses a unique security issue for ISPs because it's more difficult for them to differentiate between good IP addresses and those that are known to originate spam messages. Y1 - 2012 SN - 1089-7801 VL - 16 IS - 6 SP - 22 EP - 29 PB - Inst. of Electr. and Electronics Engineers CY - Los Alamitos ER - TY - JOUR A1 - Chujfi-La-Roche, Salim A1 - Meinel, Christoph T1 - Matching cognitively sympathetic individual styles to develop collective intelligence in digital communities JF - AI & society : the journal of human-centred systems and machine intelligence N2 - Creation, collection and retention of knowledge in digital communities is an activity that currently requires being explicitly targeted as a secure method of keeping intellectual capital growing in the digital era. In particular, we consider it relevant to analyze and evaluate the empathetic cognitive personalities and behaviors that individuals now have with the change from face-to-face communication (F2F) to computer-mediated communication (CMC) online. This document proposes a cyber-humanistic approach to enhance the traditional SECI knowledge management model. A cognitive perception is added to its cyclical process following design thinking interaction, exemplary for improvement of the method in which knowledge is continuously created, converted and shared. In building a cognitive-centered model, we specifically focus on the effective identification and response to cognitive stimulation of individuals, as they are the intellectual generators and multiplicators of knowledge in the online environment. Our target is to identify how geographically distributed-digital-organizations should align the individual's cognitive abilities to promote iteration and improve interaction as a reliable stimulant of collective intelligence. The new model focuses on analyzing the four different stages of knowledge processing, where individuals with sympathetic cognitive personalities can significantly boost knowledge creation in a virtual social system. For organizations, this means that multidisciplinary individuals can maximize their extensive potential, by externalizing their knowledge in the correct stage of the knowledge creation process, and by collaborating with their appropriate sympathetically cognitive remote peers. KW - argumentation research KW - cyber humanistic KW - cognition KW - collaboration KW - knowledge building KW - knowledge management KW - teamwork KW - virtual groups Y1 - 2017 U6 - https://doi.org/10.1007/s00146-017-0780-x SN - 0951-5666 SN - 1435-5655 VL - 35 IS - 1 SP - 5 EP - 15 PB - Springer CY - New York ER - TY - JOUR A1 - Serth, Sebastian A1 - Staubitz, Thomas A1 - van Elten, Martin A1 - Meinel, Christoph ED - Gamage, Dilrukshi T1 - Measuring the effects of course modularizations in online courses for life-long learners JF - Frontiers in Education N2 - Many participants in Massive Open Online Courses are full-time employees seeking greater flexibility in their time commitment and the available learning paths. We recently addressed these requirements by splitting up our 6-week courses into three 2-week modules followed by a separate exam. Modularizing courses offers many advantages: Shorter modules are more sustainable and can be combined, reused, and incorporated into learning paths more easily. Time flexibility for learners is also improved as exams can now be offered multiple times per year, while the learning content is available independently. In this article, we answer the question of which impact this modularization has on key learning metrics, such as course completion rates, learning success, and no-show rates. Furthermore, we investigate the influence of longer breaks between modules on these metrics. According to our analysis, course modules facilitate more selective learning behaviors that encourage learners to focus on topics they are the most interested in. At the same time, participation in overarching exams across all modules seems to be less appealing compared to an integrated exam of a 6-week course. While breaks between the modules increase the distinctive appearance of individual modules, a break before the final exam further reduces initial interest in the exams. We further reveal that participation in self-paced courses as a preparation for the final exam is unlikely to attract new learners to the course offerings, even though learners' performance is comparable to instructor-paced courses. The results of our long-term study on course modularization provide a solid foundation for future research and enable educators to make informed decisions about the design of their courses. KW - Massive Open Online Course (MOOC) KW - course design KW - modularization KW - learning path KW - flexibility KW - e-learning KW - assignments KW - self-paced learning Y1 - 2022 U6 - https://doi.org/10.3389/feduc.2022.1008545 SN - 2504-284X VL - 7 PB - Frontiers CY - Lausanne, Schweiz ER - TY - JOUR A1 - Takouna, Ibrahim A1 - Sachs, Kai A1 - Meinel, Christoph T1 - Multiperiod robust optimization for proactive resource provisioning in virtualized data centers JF - The journal of supercomputing : an internat. journal of supercomputer design, analysis and use KW - Energy-aware KW - Virtualization KW - Resource management KW - Robust optimization KW - Prediction Y1 - 2014 U6 - https://doi.org/10.1007/s11227-014-1246-2 SN - 0920-8542 SN - 1573-0484 VL - 70 IS - 3 SP - 1514 EP - 1536 PB - Springer CY - Dordrecht ER - TY - JOUR A1 - Lindberg, Tilmann A1 - Köppen, Eva A1 - Rauth, Ingo A1 - Meinel, Christoph T1 - On the perection, adoption and Implementation of design thinking in the IT industry Y1 - 2012 ER - TY - JOUR A1 - Kayem, Anne Voluntas dei Massah A1 - Wolthusen, Stephen D. A1 - Meinel, Christoph T1 - Power Systems BT - a matter of security and privacy JF - Smart Micro-Grid Systems Security and Privacy N2 - Studies indicate that reliable access to power is an important enabler for economic growth. To this end, modern energy management systems have seen a shift from reliance on time-consuming manual procedures, to highly automated management, with current energy provisioning systems being run as cyber-physical systems. Operating energy grids as a cyber-physical system offers the advantage of increased reliability and dependability, but also raises issues of security and privacy. In this chapter, we provide an overview of the contents of this book showing the interrelation between the topics of the chapters in terms of smart energy provisioning. We begin by discussing the concept of smart-grids in general, proceeding to narrow our focus to smart micro-grids in particular. Lossy networks also provide an interesting framework for enabling the implementation of smart micro-grids in remote/rural areas, where deploying standard smart grids is economically and structurally infeasible. To this end, we consider an architectural design for a smart micro-grid suited to low-processing capable devices. We model malicious behaviour, and propose mitigation measures based properties to distinguish normal from malicious behaviour. KW - Lossy networks KW - Low-processing capable devices KW - Smart micro-grids KW - Security KW - Privacy KW - Energy Y1 - 2018 SN - 978-3-319-91427-5 SN - 978-3-319-91426-8 U6 - https://doi.org/10.1007/978-3-319-91427-5_1 VL - 71 SP - 1 EP - 8 PB - Springer CY - Dordrecht ER - TY - JOUR A1 - Thomas, Max A1 - Staubitz, Thomas A1 - Meinel, Christoph ED - Meinel, Christoph ED - Schweiger, Stefanie ED - Staubitz, Thomas ED - Conrad, Robert ED - Alario Hoyos, Carlos ED - Ebner, Martin ED - Sancassani, Susanna ED - Żur, Agnieszka ED - Friedl, Christian ED - Halawa, Sherif ED - Gamage, Dilrukshi ED - Scott, Jeffrey ED - Kristine Jonson Carlon, May ED - Deville, Yves ED - Gaebel, Michael ED - Delgado Kloos, Carlos ED - von Schmieden, Karen T1 - Preparing MOOChub metadata for the future of online learning BT - optimizing for AI recommendation services JF - EMOOCs 2023 : Post-Covid Prospects for Massive Open Online Courses - Boost or Backlash? N2 - With the growing number of online learning resources, it becomes increasingly difficult and overwhelming to keep track of the latest developments and to find orientation in the plethora of offers. AI-driven services to recommend standalone learning resources or even complete learning paths are discussed as a possible solution for this challenge. To function properly, such services require a well-defined set of metadata provided by the learning resource. During the last few years, the so-called MOOChub metadata format has been established as a de-facto standard by a group of MOOC providers in German-speaking countries. This format, which is based on schema.org, already delivers a quite comprehensive set of metadata. So far, this set has been sufficient to list, display, sort, filter, and search for courses on several MOOC and open educational resources (OER) aggregators. AI recommendation services and further automated integration, beyond a plain listing, have special requirements, however. To optimize the format for proper support of such systems, several extensions and modifications have to be applied. We herein report on a set of suggested changes to prepare the format for this task. KW - Digitale Bildung KW - Kursdesign KW - MOOC KW - Micro Degree KW - Online-Lehre KW - Onlinekurs KW - Onlinekurs-Produktion KW - digital education KW - e-learning KW - micro degree KW - micro-credential KW - online course creation KW - online course design KW - online teaching Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-624830 SP - 329 EP - 338 PB - Universitätsverlag Potsdam CY - Potsdam ER - TY - JOUR A1 - Rezaei, Mina A1 - Yang, Haojin A1 - Meinel, Christoph T1 - Recurrent generative adversarial network for learning imbalanced medical image semantic segmentation JF - Multimedia tools and applications : an international journal N2 - We propose a new recurrent generative adversarial architecture named RNN-GAN to mitigate imbalance data problem in medical image semantic segmentation where the number of pixels belongs to the desired object are significantly lower than those belonging to the background. A model trained with imbalanced data tends to bias towards healthy data which is not desired in clinical applications and predicted outputs by these networks have high precision and low recall. To mitigate imbalanced training data impact, we train RNN-GAN with proposed complementary segmentation mask, in addition, ordinary segmentation masks. The RNN-GAN consists of two components: a generator and a discriminator. The generator is trained on the sequence of medical images to learn corresponding segmentation label map plus proposed complementary label both at a pixel level, while the discriminator is trained to distinguish a segmentation image coming from the ground truth or from the generator network. Both generator and discriminator substituted with bidirectional LSTM units to enhance temporal consistency and get inter and intra-slice representation of the features. We show evidence that the proposed framework is applicable to different types of medical images of varied sizes. In our experiments on ACDC-2017, HVSMR-2016, and LiTS-2017 benchmarks we find consistently improved results, demonstrating the efficacy of our approach. KW - Imbalanced medical image semantic segmentation KW - Recurrent generative KW - adversarial network Y1 - 2019 U6 - https://doi.org/10.1007/s11042-019-7305-1 SN - 1380-7501 SN - 1573-7721 VL - 79 IS - 21-22 SP - 15329 EP - 15348 PB - Springer CY - Dordrecht ER - TY - JOUR A1 - AlSa'deh, Ahmad A1 - Meinel, Christoph T1 - Secure neighbor discovery Review, challenges, perspectives, and recommendations JF - IEEE security & privacy : building confidence in a networked world N2 - Secure Neighbor Discovery is designed as a countermeasure to Neighbor Discovery Protocol threats. The authors discuss Secure Neighbor Discovery implementation and deployment challenges and review proposals to optimize it. Y1 - 2012 SN - 1540-7993 VL - 10 IS - 4 SP - 26 EP - 34 PB - Inst. of Electr. and Electronics Engineers CY - Los Alamitos ER - TY - JOUR A1 - Omotosho, Adebayo A1 - Emuoyibofarhe, Justice A1 - Meinel, Christoph T1 - Securing e-prescription from medical identity theft using steganography and antiphishing techniques JF - Journal of applied security research N2 - Drug prescription is among the health care process that usually makes references to the patients’ medical and insurance information among other personal data, because this information is very vital and delicate, it should be adequately protected from identity thieves. This article aims at securing Electronic Prescription (EP) in order to minimize patient’s data theft and foster patients’ trust of EP system. This paper presents a steganography and antiphishing technique for preventing medical identity theft in EP. The proposed EP system design focused on the security features in the prescriber and dispensers’ modules of EP by ensuring the prescriber sends the prescription of the patient in a safe manner and to the right dispenser without the interference of fake third parties. Hexadecimal steganography image system is used to cover and secure the sent prescription details. Malicious electronic dispensing system is prevented through an authentication technique where a dispenser uses a captcha together with a one-time password, and the web server encrypted token for prescriber’s device authentication. The steganography system is evaluated using Peak Signal to Noise Ratio (PSNR). The system implementation results showed that steganography and antiphishing techniques are capable of providing a secure EP systems. KW - Electronic prescription KW - one-time password KW - steganography KW - phishing KW - medical identity theft Y1 - 2017 U6 - https://doi.org/10.1080/19361610.2017.1315788 SN - 1936-1610 SN - 1936-1629 VL - 12 SP - 447 EP - 461 PB - Routledge, Taylor & Francis Group CY - Philadelphia ER - TY - JOUR A1 - Yeung, Ching-man Au A1 - Noll, Michael G. A1 - Gibbins, Nicholas A1 - Meinel, Christoph A1 - Shadbolt, Nigel T1 - Spear spamming-resistant expertise analysis and ranking incollaborative tagging systems JF - Computational intelligence N2 - In this article, we discuss the notions of experts and expertise in resource discovery in the context of collaborative tagging systems. We propose that the level of expertise of a user with respect to a particular topic is mainly determined by two factors. First, an expert should possess a high-quality collection of resources, while the quality of a Web resource in turn depends on the expertise of the users who have assigned tags to it, forming a mutual reinforcement relationship. Second, an expert should be one who tends to identify interesting or useful resources before other users discover them, thus bringing these resources to the attention of the community of users. We propose a graph-based algorithm, SPEAR (spamming-resistant expertise analysis and ranking), which implements the above ideas for ranking users in a folksonomy. Our experiments show that our assumptions on expertise in resource discovery, and SPEAR as an implementation of these ideas, allow us to promote experts and demote spammers at the same time, with performance significantly better than the original hypertext-induced topic search algorithm and simple statistical measures currently used in most collaborative tagging systems. KW - collaborative tagging KW - expertise KW - folksonomy KW - HITS KW - ranking KW - spamming Y1 - 2011 U6 - https://doi.org/10.1111/j.1467-8640.2011.00384.x SN - 0824-7935 SN - 1467-8640 VL - 27 IS - 3 SP - 458 EP - 488 PB - Wiley-Blackwell CY - Hoboken ER - TY - JOUR A1 - Phiri, Lighton A1 - Meinel, Christoph A1 - Suleman, Hussein T1 - Streamlined orchestration: An orchestration workbench framework for effective teaching JF - Current opinion in plant biology N2 - Effective classroom management is considered a key criterion to making classrooms effective learning environments. Supporting classroom orchestration—the teacher-centric real-time management of classroom activities—is central to achieving effective classroom management. However, the multi-faceted nature of classroom orchestration, its complexity, and general classroom constraints such as time, present challenges for the effective management of the modern-day classroom environment. Though effective, most existing approaches for overcoming orchestration challenges, such as Google Classroom, are arguably ad hoc. We argue that streamlined technology-driven orchestration can be attained through the use of an orchestration workbench, potentially making educators more effective within formal learning environments. Early supporting evidence, from a study involving the use of a prototype orchestration tool, demonstrates the feasibility of organised orchestration and its potential to improve students' learning experience. KW - Computer-assisted instruction KW - Orchestration KW - Technology enhanced learning Y1 - 2016 U6 - https://doi.org/10.1016/j.compedu.2016.01.011 SN - 0360-1315 SN - 1873-782X VL - 95 SP - 231 EP - 238 PB - Elsevier CY - Oxford ER - TY - JOUR A1 - Quasthoff, Matthias A1 - Meinel, Christoph T1 - Supporting object-oriented programming of semantic-web software JF - IEEE transactions on systems, man, and cybernetics : Part C, Applications and reviews N2 - This paper presents the state of the art in the development of Semantic-Web-enabled software using object-oriented programming languages. Object triple mapping (OTM) is a frequently used method to simplify the development of such software. A case study that is based on interviews with developers of OTM frameworks is presented at the core of this paper. Following the results of the case study, the formalization of OTM is kept separate from optional but desirable extensions of OTM with regard to metadata, schema matching, and integration into the Semantic-Web infrastructure. The material that is presented is expected to not only explain the development of Semantic-Web software by the usage of OTM, but also explain what properties of Semantic-Web software made developers come up with OTM. Understanding the latter will be essential to get nonexpert software developers to use Semantic-Web technologies in their software. KW - Resource description framework KW - Software KW - Java KW - Data models KW - Programming KW - Interviews Y1 - 2012 U6 - https://doi.org/10.1109/TSMCC.2011.2151282 SN - 1094-6977 VL - 42 IS - 1 SP - 15 EP - 24 PB - Inst. of Electr. and Electronics Engineers CY - Piscataway ER - TY - JOUR A1 - Gumienny, Raja A1 - Meinel, Christoph A1 - Gericke, Lutz A1 - Quasthoff, Matthias A1 - LoBue, Peter A1 - Willems, Christian T1 - Tele-board : enabling efficient collaboration in digital design spaces across time and distance Y1 - 2011 SN - 978-3-642-13756-3 ER - TY - JOUR A1 - Gericke, Lutz A1 - Gumienny, Raja A1 - Meinel, Christoph T1 - Tele-board : folow the traces of your design process history Y1 - 2012 ER - TY - JOUR A1 - Gumienny, Raja A1 - Gericke, Lutz A1 - Wenzel, Matthias A1 - Meinel, Christoph T1 - Tele-board in use : applying aq digital whiteboard system in different situations and setups Y1 - 2012 SN - 978-3-642-31990-7 ER - TY - JOUR A1 - Thienen, Julia von A1 - Noweski, Christine A1 - Meinel, Christoph A1 - Rauth, Ingo T1 - The co-evolution of theory and practice in design thinking - or - "Mind the oddness trap!" Y1 - 2011 SN - 978-3-642-13756-3 ER - TY - JOUR A1 - Jobst, Birgit A1 - Köppen, Eva A1 - Lindberg, Tilmann A1 - Moritz, Josephine A1 - Rhinow, Holger A1 - Meinel, Christoph T1 - The faith-factor in design thinking : creative confidence through education at the design thinking schools Potsdam and Standford? Y1 - 2012 SN - 978-3-642-31990-7 ER - TY - JOUR A1 - Meinel, Christoph A1 - Klotz, Volker T1 - The first 10 years of the ECCC digital library Y1 - 2006 UR - http://portal.acm.org/cacm U6 - https://doi.org/10.1145/1107458.1107484 ER - TY - JOUR A1 - Hagedorn, Christiane A1 - Serth, Sebastian A1 - Meinel, Christoph T1 - The mysterious adventures of Detective Duke BT - how storified programming MOOCs support learners in achieving their learning goals JF - Frontiers in education N2 - About 15 years ago, the first Massive Open Online Courses (MOOCs) appeared and revolutionized online education with more interactive and engaging course designs. Yet, keeping learners motivated and ensuring high satisfaction is one of the challenges today's course designers face. Therefore, many MOOC providers employed gamification elements that only boost extrinsic motivation briefly and are limited to platform support. In this article, we introduce and evaluate a gameful learning design we used in several iterations on computer science education courses. For each of the courses on the fundamentals of the Java programming language, we developed a self-contained, continuous story that accompanies learners through their learning journey and helps visualize key concepts. Furthermore, we share our approach to creating the surrounding story in our MOOCs and provide a guideline for educators to develop their own stories. Our data and the long-term evaluation spanning over four Java courses between 2017 and 2021 indicates the openness of learners toward storified programming courses in general and highlights those elements that had the highest impact. While only a few learners did not like the story at all, most learners consumed the additional story elements we provided. However, learners' interest in influencing the story through majority voting was negligible and did not show a considerable positive impact, so we continued with a fixed story instead. We did not find evidence that learners just participated in the narrative because they worked on all materials. Instead, for 10-16% of learners, the story was their main course motivation. We also investigated differences in the presentation format and concluded that several longer audio-book style videos were most preferred by learners in comparison to animated videos or different textual formats. Surprisingly, the availability of a coherent story embedding examples and providing a context for the practical programming exercises also led to a slightly higher ranking in the perceived quality of the learning material (by 4%). With our research in the context of storified MOOCs, we advance gameful learning designs, foster learner engagement and satisfaction in online courses, and help educators ease knowledge transfer for their learners. KW - gameful learning KW - storytelling KW - programming KW - learner engagement KW - course design KW - MOOCs KW - content gamification KW - narrative Y1 - 2023 U6 - https://doi.org/10.3389/feduc.2022.1016401 SN - 2504-284X VL - 7 PB - Frontiers Media CY - Lausanne ER - TY - JOUR A1 - Thienen, Julia von A1 - Clancey, William J. A1 - Corazza, Giovanni Emanuele A1 - Meinel, Christoph T1 - Theoretical foundations of design thinking creative thinking theories JF - Design Thinking Research: Making Distinctions: Collaboration versus Cooperation N2 - Design thinking is acknowledged as a thriving innovation practice plus something more, something in the line of a deep understanding of innovation processes. At the same time, quite how and why design thinking works-in scientific terms-appeared an open question at first. Over recent years, empirical research has achieved great progress in illuminating the principles that make design thinking successful. Lately, the community began to explore an additional approach. Rather than setting up novel studies, investigations into the history of design thinking hold the promise of adding systematically to our comprehension of basic principles. This chapter makes a start in revisiting design thinking history with the aim of explicating scientific understandings that inform design thinking practices today. It offers a summary of creative thinking theories that were brought to Stanford Engineering in the 1950s by John E. Arnold. Y1 - 2018 SN - 978-3-319-60967-6 SN - 978-3-319-60966-9 U6 - https://doi.org/10.1007/978-3-319-60967-6_2 SP - 13 EP - 40 PB - Springer CY - New York ER - TY - JOUR A1 - Noweski, Christine A1 - Scheer, Andrea A1 - Büttner, Nadja A1 - Thienen, Julia von A1 - Erdmann, Johannes A1 - Meinel, Christoph T1 - Towards a paradigm shift in education practice : developing twenty-first century skills with design thinking Y1 - 2012 SN - 978-3-642-31990-7 ER - TY - JOUR A1 - Sapegin, Andrey A1 - Jaeger, David A1 - Cheng, Feng A1 - Meinel, Christoph T1 - Towards a system for complex analysis of security events in large-scale networks JF - Computers & security : the international journal devoted to the study of the technical and managerial aspects of computer security N2 - After almost two decades of development, modern Security Information and Event Management (SIEM) systems still face issues with normalisation of heterogeneous data sources, high number of false positive alerts and long analysis times, especially in large-scale networks with high volumes of security events. In this paper, we present our own prototype of SIEM system, which is capable of dealing with these issues. For efficient data processing, our system employs in-memory data storage (SAP HANA) and our own technologies from the previous work, such as the Object Log Format (OLF) and high-speed event normalisation. We analyse normalised data using a combination of three different approaches for security analysis: misuse detection, query-based analytics, and anomaly detection. Compared to the previous work, we have significantly improved our unsupervised anomaly detection algorithms. Most importantly, we have developed a novel hybrid outlier detection algorithm that returns ranked clusters of anomalies. It lets an operator of a SIEM system to concentrate on the several top-ranked anomalies, instead of digging through an unsorted bundle of suspicious events. We propose to use anomaly detection in a combination with signatures and queries, applied on the same data, rather than as a full replacement for misuse detection. In this case, the majority of attacks will be captured with misuse detection, whereas anomaly detection will highlight previously unknown behaviour or attacks. We also propose that only the most suspicious event clusters need to be checked by an operator, whereas other anomalies, including false positive alerts, do not need to be explicitly checked if they have a lower ranking. We have proved our concepts and algorithms on a dataset of 160 million events from a network segment of a big multinational company and suggest that our approach and methods are highly relevant for modern SIEM systems. KW - Intrusion detection KW - SAP HANA KW - In-memory KW - Security KW - Machine learning KW - Anomaly detection KW - Outlier detection Y1 - 2017 U6 - https://doi.org/10.1016/j.cose.2017.02.001 SN - 0167-4048 SN - 1872-6208 VL - 67 SP - 16 EP - 34 PB - Elsevier Science CY - Oxford ER - TY - JOUR A1 - Bethge, Joseph A1 - Serth, Sebastian A1 - Staubitz, Thomas A1 - Wuttke, Tobias A1 - Nordemann, Oliver A1 - Das, Partha-Pratim A1 - Meinel, Christoph T1 - TransPipe BT - A Pipeline for Automated Transcription and Translation of Videos JF - EMOOCs 2021 N2 - Online learning environments, such as Massive Open Online Courses (MOOCs), often rely on videos as a major component to convey knowledge. However, these videos exclude potential participants who do not understand the lecturer’s language, regardless of whether that is due to language unfamiliarity or aural handicaps. Subtitles and/or interactive transcripts solve this issue, ease navigation based on the content, and enable indexing and retrieval by search engines. Although there are several automated speech-to-text converters and translation tools, their quality varies and the process of integrating them can be quite tedious. Thus, in practice, many videos on MOOC platforms only receive subtitles after the course is already finished (if at all) due to a lack of resources. This work describes an approach to tackle this issue by providing a dedicated tool, which is closing this gap between MOOC platforms and transcription and translation tools and offering a simple workflow that can easily be handled by users with a less technical background. The proposed method is designed and evaluated by qualitative interviews with three major MOOC providers. Y1 - 2021 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-516943 VL - 2021 SP - 79 EP - 94 PB - Universitätsverlag Potsdam CY - Potsdam ER - TY - JOUR A1 - Thienen, Julia von A1 - Noweski, Christine A1 - Meinel, Christoph A1 - Lang, Sabine A1 - Nicolai, Claudia A1 - Bartz, Andreas T1 - What can design thinking learn from behavior group theraphy? Y1 - 2012 SN - 978-3-642-31990-7 ER - TY - JOUR A1 - Steinbeck, Hendrik A1 - Meinel, Christoph ED - Meinel, Christoph ED - Schweiger, Stefanie ED - Staubitz, Thomas ED - Conrad, Robert ED - Alario Hoyos, Carlos ED - Ebner, Martin ED - Sancassani, Susanna ED - Żur, Agnieszka ED - Friedl, Christian ED - Halawa, Sherif ED - Gamage, Dilrukshi ED - Scott, Jeffrey ED - Kristine Jonson Carlon, May ED - Deville, Yves ED - Gaebel, Michael ED - Delgado Kloos, Carlos ED - von Schmieden, Karen T1 - What makes an educational video? BT - deconstructing characteristics of video production styles for MOOCs JF - EMOOCs 2023 : Post-Covid Prospects for Massive Open Online Courses - Boost or Backlash? N2 - In an effort to describe and produce different formats for video instruction, the research community in technology-enhanced learning, and MOOC scholars in particular, have focused on the general style of video production: whether it is a digitally scripted “talk-and-chalk” or a “talking head” version of a learning unit. Since these production styles include various sub-elements, this paper deconstructs the inherited elements of video production in the context of educational live-streams. Using over 700 videos – both from synchronous and asynchronous modalities of large video-based platforms (YouTube and Twitch), 92 features were found in eight categories of video production. These include commonly analyzed features such as the use of green screen and a visible instructor, but also less studied features such as social media connections and changing camera perspective depending on the topic being covered. Overall, the research results enable an analysis of common video production styles and a toolbox for categorizing new formats – independent of their final (a)synchronous use in MOOCs. Keywords: video production, MOOC video styles, live-streaming. KW - Digitale Bildung KW - Kursdesign KW - MOOC KW - Micro Degree KW - Online-Lehre KW - Onlinekurs KW - Onlinekurs-Produktion KW - digital education KW - e-learning KW - micro degree KW - micro-credential KW - online course creation KW - online course design KW - online teaching Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-622086 SP - 47 EP - 58 PB - Universitätsverlag Potsdam CY - Potsdam ER - TY - JOUR A1 - Weinstein, Theresa Julia A1 - Ceh, Simon Majed A1 - Meinel, Christoph A1 - Benedek, Mathias T1 - What's creative about sentences? BT - a computational approach to assessing creativity in a sentence generation task JF - Creativity Research Journal N2 - Evaluating creativity of verbal responses or texts is a challenging task due to psychometric issues associated with subjective ratings and the peculiarities of textual data. We explore an approach to objectively assess the creativity of responses in a sentence generation task to 1) better understand what language-related aspects are valued by human raters and 2) further advance the developments toward automating creativity evaluations. Over the course of two prior studies, participants generated 989 four-word sentences based on a four-letter prompt with the instruction to be creative. We developed an algorithm that scores each sentence on eight different metrics including 1) general word infrequency, 2) word combination infrequency, 3) context-specific word uniqueness, 4) syntax uniqueness, 5) rhyme, 6) phonetic similarity, and similarity of 7) sequence spelling and 8) semantic meaning to the cue. The text metrics were then used to explain the averaged creativity ratings of eight human raters. We found six metrics to be significantly correlated with the human ratings, explaining a total of 16% of their variance. We conclude that the creative impression of sentences is partly driven by different aspects of novelty in word choice and syntax, as well as rhythm and sound, which are amenable to objective assessment. Y1 - 2022 U6 - https://doi.org/10.1080/10400419.2022.2124777 SN - 1040-0419 SN - 1532-6934 VL - 34 IS - 4 SP - 419 EP - 430 PB - Routledge, Taylor & Francis Group CY - Abingdon ER -